m.tech computer engineering code: mtce-16-101 …€¦ · m.tech computer engineering code:...

M.TECH COMPUTER ENGINEERING

CODE: MTCE-16-101

SUBJECT NAME: COMPUTER SYSTEM SOFTWARE

NO OF CREDITS: 4

M.TECH SEMESTER I SESSIONAL: 40

L P THEORY EXAM: 60

4 0 TOTAL: 100

NOTE: Question paper has two parts. Part-1 has 10 questions each of 2 marks. It covers the

entire syllabus. Attempt any four questions out of six from Part-2.

Course Objectives

1. To apprise students of various programming techniques along with respective merits and

demerits of each technique.

2. To introduce basics terminology and design principles associated with OOPs and

constructs in C++ to support those.

3. To discuss the principles of abstraction and encapsulation with emphasis on silent

functions written by compiler, const-pass-by-reference, issues with friend functions,

handling of pointer-type-variables , static data members and similar c++ constructs.

4. To discuss the principles of inheritance and polymorphism with emphasis on virtual and

non-virtual functions, open and close principle, Liskcov’s substitution principle, virtual

dotr, private inheritance, virtual base classes and similar c++ constructs.

5. To familiarize students with compile time polymorphism and code sharing with c++

templates.

6. To make students understand the difference between error and exception handling with

proper language constructs for the same.

7. To introduce basic UML design notations, static and dynamic models elements for object

oriented system design.

8. To familiarize students with importance of system software with specific emphasis on

language translators.

9. To make students understand the basics of assembly language and design issues of two

pass and single pass assembler.

10. To apprise student of basic compiler, Linker and Loader design issues with data

structures used by these.

Introduction to Object oriented Programming and Design:

Unit I : Programming Techniques- A Survey

Introduction to programming paradigms – unstructured programming, structured,

procedural, and modular programming; drawbacks of structured programming; Object

Oriented programming.

Classes and Objects : Introduction to objects; classes – declaration in C++, abstraction

and encapsulation, creating objects; array of objects; objects as function arguments, scope

resolution operator, static data members; properties of classes and objects.

Unit II : Functions : Advanced concepts

Polymorphism, Function overloading; inline functions; friend functions- Member

functions of a class as friends of another class, Friend Function as a bridge between two

classes; friend classes; recursion – types of recursion: linear, binary, tail recursion

Constructors – types of constructors: default, user defined, parameterized, copy

constructors, and constructors with default arguments; rules for constructor definition and

usage; destructors -rules for destructor definition and usage.

Unit III : Inheritance: Extending classes

Introduction to code reuse; containership-aggregation; inheritance – visibility modes,

‘Open Close Principle’(OCP) types of inheritance: multilevel, multiple inheritance;

function overriding – virtual functions, ‘Liskov’s Substitution Principle’ (LSP), pure

virtual functions; roles of constructors and destructors in inheritance; virtual base class –

graph inheritance.

Introduction to code sharing; templates; generic classes; templates with more than one

generic parameter

Unit IV :Exception handling

Introduction – traditional error handling; exception handling in C++ - ‘try, throw, and

catch blocks’, multiple throw and multiple catch blocks, throwing objects; situations of

usage of exception handling.

Introduction to UML :Introduction – static model, dynamic model; class diagrams –

relationship among classes: composition – association & aggregation, multiplicity,

generalization – inheritance, hierarchy of classes, dependency; use case diagrams;

behaviour diagrams: interaction diagrams – sequence and collaboration diagrams, state

chart diagrams, activity diagrams; implementation diagrams: component and deployment

diagrams.

System Programming:

Unit V :Types of software: system software and application software; introduction to

system software: assembler, compiler, interpreter, macro processor, linker, loader,

operating system etc.

Assemblers : Elements of assembly language, assembly process, forward reference

problem, design of a two pass assembler, concept of back patching ; introduction to

macros and design of a macro processor.

Compilers

Introduction to compilation process, programming language grammers, scanning,

parsing, introduction to code optimization.

Unit VI :Loaders and Linkers:

Introduction to loading, linking, and relocation; program relocatability; absolute loaders,

relative loaders, static and dynamic linking – data structures used by loaders and linkers;

link load and go scheme, load link and go scheme of linkage editor.

Course Outcomes

a. The students will be able to decide which programming technique to use in a given

design situation based on the respective merits and demerits.

b. The students will be able to design clean interfaces for the classes using the abstraction

design principle.

c. The students will be able to separate out the interfaces from the implementation during

the class design by applying the abstraction and encapsulation principles.

d. The students will be able to understand the design cost involved for using c++ constructs

like passing parameters by value or by reference, deep copy cotr, silent function writing

by compiler and friend functions.

e. The students will be able to use inheritance correctly for writing “is-a” kind of

relationships based programs and not mere for code reuse.

f. The students will be able to write polymorphic programs with clear understanding of

inheritance of interfaces v/s inheritance of default implementation v/s inheritance of static

implementation.

g. The students will be able to handle issues with multiple inheritance, memory leak issue

for not using virtual dotr, issue with inheritance of non-virtual function.

h. The students will be able to write generic program using c++ templates and handle

runtime issues using exception handling.

i. The student will be able to design software systems using UML notation and models.

j. The students will be able to understand the difference between application software and

system software and importance of language translators.

k. The students will be able to design a two pass assembler for a given ISA architecture.

l. The students will be able to understand the various phases involved in a complier design

and would be able to do lexical, syntactical and semantic analysis of simple programming

instructions.

m. The students will be able to understand program relocatability and c++ linking model.

n. The students will be also understand absolute and relative loaders for loading and running

c++ programs.

MAPPING OF COURSE OBJECTIVES AND COURSE OUTCOMES

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REFERENCES

1. A.K.Sharma, Kavita Kapur, “ Introductory Computer Science with C++, Vol. II”, Dhanpat Rai

Publications

2. E. Balagurusamy, “Object Oriented Programming with C++”, TMH.

3. Herbert Schield “The Complete Reference in C++” TMH.

4. Donovan ,”Systems Programming”, Tata McGraw Hill.

5. Dhamdhere,” System Software” Tata McGraw Hill.


CODE: MTCE-16-103

SUBJECT NAME: MATHEMATICAL FOUNDATIONS OF COMPUTER SCIENCE

NO OF CREDITS: 4


L P THEORY EXAM: 60

4 0 TOTAL: 100



Course Objectives

1. Need for formal communication with the computing machines and requirement for

creation of formal languages

2. Various components of grammars relating to design of meaningful sentences in formal

languages

3. Classification & hierarchy of grammars on the basis of their production systems

4. Tools associated with various types of grammars ( 0, 1, 2 and 3) and their usage for

recognition of corresponding types of languages

5. Ambiguities and possible defects in Context free grammars and their removal

6. Need for standard (normal) forms of grammar

7. Concept of algorithm and its association with Turing Machine

8. Designing Turing machines for various languages and integer computing

9. Various extensions of Turing machines

10. Decidable and non decidable properties of various types of languages

11. Concept of recursive and recursively enumerable languages

12. Computability and its association with primitive recursive and µ recursive functions

Unit 1: Finite Automata and Regular Languages

Deterministic and non-deterministic Finite Automata, Equivalence of Finite Automata (FA),

Equivalence of NDFA and DFA, Myhill-Nerode Theorem and minimization of FA, FA with null

moves, FA with outputs: Moore and mealy Machines, Equivalence of Moore and Mealy

machines, Regular Expressions, Regular languages and FA, Arden theorem: Equivalence of FA

and Regular Expressions, Closure properties of regular sets, Pumping Lemma for Regular Sets,

Applications of the pumping lemma.

Unit 2: Chomsky classification of Grammars

Unrestricted languages, Context sensitive languages, Context free languages and regular

languages, Relation between classes of languages, Parse trees, Ambiguity in CFG, Reduced

forms, Removal of useless Symbols and unit production, Chomsky Normal Form (CNF),

Griebach Normal Form (GNF), Closure properties of CFL, Pumping lemma for CFG,

Applications of CFG.

Unit 3: Pushdown Automata and Turing machines

Basic Structure of PDA, Acceptance by PDA, PDA and Context Free Languages, Design of

PDA corresponding to a grammar, LL(k) parsing, bottom up and top down parser design, LBA,

Basic structure and working of Turing Machine, Nondeterministic and deterministic Turing

Machine, Role of TM as language recognizer, computer for integers and enumerator and

associated design problems, Space and time complexity of TM, binary coding of TM, Universal

Turing Machine, halting problem of TM, Decision problems and Rice’s Theorem.

Unit 4: Undecidability

Recursive and recursive enumerable languages, Post Correspondence Problem, Primitive

recursive functions.

Unit 5: Advancements in Automata Theory

Multitrack and Multitape TM, Post machine, Design of Post machine, Cellular Automata.

Course Outcomes

a. Discuss the requirement for formal language to communicate with the computing

machine

b. Understand the concept of Terminals, Non terminals, production system and starting

sentential form in relation to formal grammars

c. Classify the languages on the basis of their production system

d. Design the grammar and machines for Regular and context free grammars

e. Remove the defects and ambiguity in Type 2 grammar and convert the grammar to

standard normal forms

f. Design the Turing machines for various languages, integer computing and enumeration

g. Discuss the check the decidability issue relating to various aspects of formal language

h. Check if a given language is recursive/ recursively enumerable/ neither

i. Check if a given function is computable or not

Mapping of Course Objectives and Course Outcomes


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REFERENCES

1. Formal languages and Automata Theory- C. K. Nagpal, Oxford University Press 2011.

2. “Introduction to automata theory Language and Computation”, J.E. Hopcroft, R. Motwani, J.D.

Ullman, Pearson education.

3. “Theory of computer Science: Automata Language and Computation”, K.L.P Mishra and

Chandrasekaran, Prentice Hall of India.

4. “Introduction to Computer Theory”, D.I.A Cohen, Willey India.

5. “Introduction to Languages and the Theory of Computation”,John C. Martin, Tata McGraw Hill


CODE: MTCE-16-105

SUBJECT NAME: SOFTWARE TESTING

NO OF CREDITS: 4


L P THEORY EXAM: 60

4 0 TOTAL: 100



Course Objectives

1. To get familiar the students about basic concepts of software testing and its techniques.

2. To study the concepts of Verification and validation activities.

3. To study in detail the process of performing the black box and white box testing

approaches with examples.

4. To get familiar the students the concept of regression testing.

5. To study about the various testing automation and debugging tools and case studies.

6. To study the basuc and advanced concepts of object oriented testing

Unit 1 Testing terminology and Methodology Definition of testing, goals, psychology, model for testing, effective testing, limitations of

testing, Importance of Testing, Definition of Failure, faults or bug, error, incident, test case, test

ware, life cycle of bug, bug effects, bug classification, test case design, testing methodology,

development of test strategy, verification, validation, Static testing: Inspection ,Review and

Walkthrough, dynamic testing, testing life cycle model, testing techniques, testing principles,

Testing Metrices.

Unit 2 Verification and validation

Verification activities, verification of requirements, verification of HL design, verification of

data design, verification of architectural design, verification of UI design, verification of LL

design, introduction to validation activities

Unit 3 Dynamic testing White Box testing: Boundary value analysis, equivalence class portioning, state table based

testing, decision table based, error guessing.

Black Box Testing: Logic coverage criteria, basic path testing, graph matrices.

Unit 4 Validation Testing

Unit testing, drivers , stubs, integration testing, methods, functional testing, system testing,

recovery testing, security testing, stress testing, performance testing, usability testing

Unit 5 Regression Testing Objective of regression testing, Regression test process, Regression testing techniques.

Unit 6 Test Automation and debugging

S/w measurement and testing, testing metrics and tools

Case Study: Testing for Object-oriented and web-based systems

Unit 7 Object-Oriented Testing Use-case based testing; Class testing, Testing Exception handling

Course Outcomes

a. The students will be able to understand the concepts of software testing and its

techniques.

b. Knowledge of verification and validation activities.

c. Study of black box and white box testing techniques.

d. Study the concept of regression testing and its techniques.

e. Study of object oriented testing techniques.

f. Study of case studies and various testing automation and debugging tools.

g. Study of various testing metrics.



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REFERENCES

1. G.J Myers, The Art of Software Testing, John Wiley & Sons, 1979

2. Naresh Chauhan, Software Testing Principles and Practices,OXFORD University Press.


CODE: MTIT-16-103

SUBJECT NAME: INFORMATION RETRIEVAL SYSTEMS (ELECTIVE –I)

NO OF CREDITS: 4


L P THEORY EXAM: 60

4 0 TOTAL: 100



Course Objectives

1. To build an understanding of the fundamental concepts of Information Retrieval

2. To familiarize students with the basic taxonomy and terminology of Indices

3. To understand Heap’s Law for estimation and Zipf’s law for modeling distribution of

terms

4. To understand dictionary compression and posting list compression

5. To introduce the scoring , tf-idf weighting and vector space model for scoring

6. To understand cluster pruning and tiered indices

7. To learn the elements of Web Search basics

8. To learn various language models for information retrieval and their types

Unit 1 Introduction to Information Retrieval

Information retrieval problem, an inverted index, Processing Boolean queries, The extended

Boolean model versus ranked retrieval, an inverted index, Bi-word indexes, Positional indexes,

Combination schemes

Unit 2 Index construction

Hardware basics, Blocked sort-based indexing, Single-pass in-memory indexing, Distributed

indexing, Dynamic indexing, Other types of indexes

Index compression: Statistical properties of terms in information retrieval, Heaps’ law:

Estimating the number of terms, Zipf’s law: Modeling the distribution of terms, Dictionary

compression, Dictionary as a string, Blocked storage, Postings file compression.

Unit 3 Scoring, term weighting and the vector space model

Parametric and zone indexes, Weighted zone scoring, Learning weights, The optimal weight,

Term frequency and weighting, Inverse document frequency, Tf-idf weighting, The vector space

model for scoring, Variant tf-idf functions.

Unit 4 Computing scores in a complete search system

Efficient scoring and ranking, Inexact top K document retrieval, Index elimination, Champion

lists, Static quality scores and ordering, Impact ordering, Cluster pruning, Components of an

information retrieval system, Tiered indexes

Unit 5 Web search basics

Background and history, Web characteristics, The web graph, Spam, Advertising as the

economic model, The search user experience, User query needs

Crawling, Crawler architecture, DNS resolution, The URL frontier, Link analysis, The Web as a

graph, Anchor text and the web graph, PageRank, Markov chains, The PageRank computation,

Topic-specific PageRank

Unit 6 Language models for information retrieval

Language models, Finite automata and language models, Types of language models,

Multinomial distributions over words, The query likelihood model, Using query likelihood

language models in IR, Estimating the query generation probability, Language modelling versus

other approaches in IR

Course Outcomes

a. The students will be able to understand basic Inforamation Retrieval Systems.

b. The students will be able to lean how Boolean queries are processed.

c. The students will be able to identify the different types of indices: inverted index,

positional index, bi-word index etc

d. The student will be able to make estimations and model distribution of terms and

compressions

e. The students will be able to enumerate various types of indices. And also understand the

concept of efficient storage of indices.

f. The students will be able to learn tf-idf scoring and vector space model scoring for

ranking

g. The students will be able to understand Static quality ordering, cluster pruning and tiered

indices

h. The students will be able to understand the basic concept of Search Engines their

architecture and various functional components.

i. The students will be able to understand the basic concept of Web crawlers and their

architecture

j. The students will be able to understand various language models related to information

retrieval



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REFERENCES

1. An Introduction to Information Retrieval Christopher D. Manning, Prabhakar

Raghavan, Hinrich Schütze Cambridge University Press

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CODE: MTCE-16-113

SUBJECT NAME: AGILE SOFTWARE DEVELOPMENT (ELECTIVE –I)

NO OF CREDITS: 4


L P THEORY EXAM: 60

4 0 TOTAL: 100



Course Objectives

1. To learn the fundamental principles and practices associated with each of the agile

development methods, evolutionary development and delivery.

2. To learn from fun hands-on activities in the classroom (or in collaborative groups online)

and also on a course project where students will apply the principles and practices of

agile software development and to understand various agile methodologies.

3. To learn how agile methods are planned and prioritized.

4. To perform estimation in agile by using various methods of estimation.

5. To learn how agile methods scrum is used, including the role of scrum software

development life cycle.

6. To perform in-depth testing into aspects of agile development that are particularly

relevant to each student through detailed discussion sessions.

Unit-1 Iterative and Evolutionary Development

Key motivations for iterative development, meeting the requirements and challenges iteratively,

Risk driven & client-driven iterative planning, time-box iterative development, Evolutionary &

adaptive development, Evolutionary requirement analysis, incremental & evolutionary delivery.

Unit-2 Adapting to Agile

Background, overview & definitions, Agile manifesto, Agile principles, Agile Methods-

Extreme Programming, Scrum Development methodology, Crystal family of methodologies,

Rational Unified Process (RUP).

Unit-3 Agile Planning & Prioritization

Agile application to planning, Success features for Agile planning, velocity, prioritizing story &

themes, Kano model for prioritization, Relative weighing model for prioritization.

Unit-4 Agile Estimation

Estimation, estimating size with story points, estimating with ideal days & ideal time, ideal day

as a measure of time, techniques for estimating, re-estimation, choosing between story points &

ideal days, Splitting user-stories, estimating user-stories, release plan, updating the release plan.

Unit-5 Agile Software Development using Scrum

Adaptive scrum, Product backlog, Sprint, Scrum life cycle, Scrum estimation, Scrum Planning,

Working with scrum.

Unit-6 Agile Testing

Introduction to Agile testing quadrants, test-driven development, unit testing, component

testing, functional testing, story testing, exploratory testing, scenario testing, usability testing,

acceptance testing, performance and load testing, security testing, ility testing, pair testing.

Course outcomes

a. Student will understand fundamental principles and practices associated with each of the

agile development methods, evolutionary development and delivery.

b. Students will understand various agile methodologies and techniques to plan and

prioritize various tasks.

c. Students can perform estimation in agile by using various methods of estimation.

d. Students will understand scrum method of agile, including the role of scrum software

development life cycle.

e. Students will become familiar with various testing concepts.


Course Outcomes

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REFERENCES

1. S/w development using Scrum, Succeeding with Agile by Mike Cohn

2. Agile & iterative development- A manager’s Guide Craig Larman.

3. Agile Testing, A Practical Guide for Testers and Agile Teams,Lisa Crispin, Janet Gregory


CODE: MTCN-16-101

SUBJECT NAME: DATA COMMUNICATION NETWORK (ELECTIVE –I)

NO OF CREDITS: 4


L P THEORY EXAM: 60

4 0 TOTAL: 100



Course Objectives

1. To make students familiar with concepts of Data Communication, Line Encoding

Schemes, Multiplexing techniques, Modulation methods.

2. To introduce B-ISDN and ATM, Optical Transmission, Network techniques, Signaling

principles

3. To make students familiar with concept of broadband network performance, traffic

management aspects

4. To make students familiar with ATM traffic parameters and transfer capabilities, Quality

of service

5. To make students familiar with ATM ATM switching: matrix type, central memory, ring

type switching element.

6. To make students familiar with Switching networks

Unit I :Introduction:

Data Communication: Data transmission, Parallel Transmission, Serial Transmission, Line Encoding

Schemes: Unipolar, Polar, Bipolar, Multiplexing techniques: TDM, FDM, Modulation methods:

AM, FM, PM, Pulse Code Modulation. Spread spectrum, Concepts of layering, TCP/IP and ISO’s

OSI reference model. Transmission media.

Unit II : Data Link Layer

Error detection and correction, Data link control - Flow and Error control - Sliding

window protocol - ARQ schemes, HDLC protocol - Point to Point Protocol, Multiple Access

Techniques - Random Access, Controlled Access, Logical Link Control (LLC) and Medium

Access Sub-layer functions - LAN standards - IEEE 802.3 (CSMA/CD) - Fast Ethernet - Giga

Bit Ethernet, IEEE 802.4 (Token Bus), IEEE 802.5 (Token Ring), IEEE 802.11 (Wireless LAN).

Unit III : Network Layer

Inter-networking- Subnetting, Supernetting and Masking , Class full and Classless addressing.

Routing - Link state and Distance Vector Routing - Congestion control algorithms - Network

Layer Protocols - ARP, RARP, IPv4, ICMP and IPv6. Unicast Routing and Multicast Routing

techniques.

Unit IV : Transport Layer

Processes to Processes Delivery - Transmission Control Protocol (TCP) - User Datagram

Protocol, Stream Control Transmission Protocol (SCTP) - Data Traffic - Congestion Control and

Quality of Service - Techniques to improve QOS - Integrated Services - Differentiated Services,

QoS in switched networks.

Unit V : Session, Presentation And Application Layers

Services, Network security - Security Cryptography, Message confidentiality, message integrity,

message authentication, Digital Signature, Entity Authentication, Key Management, Application

layer- DNS, E-mail (SMTP), FTP, HTTP, Voice over IP.

Course Outcomes

a. The students will be able to understand basic terminology used in database systems.

b. The students will be familiar with the basic concepts and the applications of database

systems.

c. The students will be able to understand role of Database administrator in DBMS.

d. The students will be able to understand various data model like Hierarchical model,

Network Model, Relational model, E-R model.

e. The students will be familiar with relational database theory and be able to write

relational algebra expressions for query.

f. The students will be able to understand the logical design guidelines for databases,

including the E-R method and normalization approach.

g. The students will be familiar with database storage structure and access techniques like

file and page organization, indexing methods like B-tree and hashing.

h. The students will be familiar with basic issues of transaction processing and concurrency

control.

i. The students will be able to understand serializability and also its various protocols to

maintain it.

j. The students will be able to choose the database management system suitable for a

specific project and knows its structure and functions.

k. The students will be able to know the SQL language clauses and functions and can write

optimal queries in SQL.

l. The students will be able to understand various storage mechanisms.

m. The students will be also understand how to retrieve data manipulate data using SQL.



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REFERENCES

1. Forouzan, Data Communications and Networking, TMH, 4 th Edition, 2006.

2. William Stallings, Data and Computer Communications, PHI, 7 th Edition, 2003.

3. S.Tanenbaum, Computer Networks, 4 th Edition, Pearson Education Asia Inc., 2004.

4. Leon-Garcia, Widjaja, Communication Networks, Fundamental Concepts and Key

Architecture, TMH, 2 nd Edition, 2004.


CODE: MTCE-16-115

SUBJECT NAME: ADVANCED COMPUTER ARCHITECTURE (ELECTIVE –I)

NO OF CREDITS: 4


L P THEORY EXAM: 60

4 0 TOTAL: 100



Course Objectives

1. Describe the principles of processor design and Classify instruction set architectures.

2. The course focuses on about uni-processor implementation alternatives (single cycle,

multiple-cycle, and pipelined implementations)

3. Special emphasis will be on quantifying design decisions in terms of performance and

cost.

4. It helps to understand the memory hierarchy, the caches, virtual memory, storage

systems.

5. Architectures exploiting instruction-level parallelism (ILP), data-level parallelism (DLP),

thread-level and task-level parallelisms are treated.

6. Furthermore new code generation techniques needed for exploiting ILP will be treated.

7. Investigating modern design structures of Pipelined and Multiprocessors systems.

8. To acquaint with recent computer architectures and I/O devices, as well as driving or

managing these types of advanced hardware. The course focuses on processor design,

pipelining, superscalar, out-of-order execution

Unit-I Introduction and Advanced concepts:

Introduction: Evaluation of computers generations of computers – basics of computer

architecture – stored program organization (Von Neumann architecture) – instruction formats

and types – addressing modes –register organization and stack organization.

Advanced concepts: Horizontal and vertical instruction format, microprogramming,

microinstruction sequencing and control; instruction pipeline; parallel processing; problems in

parallel processing; data hazard, control hazard.

Unit II Parallel Processing :

Parallelism in uni processor system – parallel computer structures – architectural classification

schemes, parallel processing applications

Unit III Memory and I/O systems :

Hierarchical Memory structure , Virtual memory systems caches – design methods –

associativememories – input / output system – programmed I/O – DMA and interrupts – I/O

processors.

Unit IV Principles of pipelining and vector processing

Pipelining: an overlapped parallelism ,instruction and arithmetic pipelines, principles of

designing pipelined processors, vector processing requirements.

Unit V array processors and multi processors:

SIMD array processors, SIMD interconnection networks - static vd dynamic networks, Mesh-

connected network, Cube connected Network

Functional structures for multi processors , interconnection networks and multiprocessor

operating systems.

Unit VI Data Flow Computers:

Data driven computing, control flow vs data flow, data flow computer architectures- static data

flow computers and dynamic data flow computers.

Course Outcomes

a. Understand the classes of computers, the change in technology and the quantitative

principles of computer design

b. Understand the advanced concepts of computer architecture.

c. Expose the major differentials of RISC and CISC architectural characteristics

d. Comprehend operation of instruction level parallelism in pipelines and the challenges of

ILP.

e. Will know about computer performance, instruction set architecture design and

implementation.

f. Understand the components and operation of a memory hierarchy and the range of

performance issues influencing its design.

g. Design Scheduling and Structuring Code for Parallelism and study of issues related to

VLIW

h. Discuss the large scale multiprocessors and their relevance to the scientific applications

i. Be able to understand an existing software& hardware system and extend the system to

meet evolving requirements.


REFERENCES

1. John P Hayes, Computer architecture and organization, III edition McGraw Hill, 1998.

2. Pipelined and Parallel processor design by Michael J. Fiynn – 1995, Narosa

3. Computer Architecture and parallel Processing” Kai Hwang and A. Briggs International

edition McGraw-Hill.

4. Computer Architecture A quantitative approach 3rd edition John L. Hannessy & David A.

Patteson Morgan Kufmann (An Imprint of Elsevier)


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CODE: MTCE-16-102

SUBJECT NAME: RESOURCE MANAGEMENT IN COMPUTER SYSTEMS

NO OF CREDITS: 4

M.TECH SEMESTER II SESSIONAL: 40

L P THEORY EXAM: 60

4 0 TOTAL: 100



Course Objectives

1. To get familiar the students about basic as well as advanced concepts in operating

systems

2. To introduce all the types of operating system, architectures and basic operation.

3. To study the detail of various components of operating systems viz. process management,

memory management, file management, disk management, I/O management

Unit-I Operating System Introduction: Need of OS, Evolution of OS, Types of OS - Simple Batch,

Multi programmed, multiuser, multitasking, multiprocessing, Distributed Systems, Real-Time

Systems, Embedded OS. Functions, Resource types, nature of resources, components of resource

management. Interrupt-driven operations for OS, Hardware protection to implement

multiprogramming/multitasking.

Unit-II

OS Architecture: General operations, system calls, system program, system generation

program, general structure: monolithic, layered architecture, Virtual Machines, Microkernel,

ExoKernel, Hybrid.

Unit-III Process management: Process Lifecycle, Implementation of process, Context switching,

process switching, schedulers, processes operations, introduction to multithreading.

Process Scheduling: Scheduling levels, scheduling types, scheduling goals, scheduling

algorithms: FCFS, Priority, Round Robin, HRRN, Virtual RR, Multi-level Queue, multi-level

feedback, fare share, lottery.

Unit-IV

Process Synchronization: Concurrent process, Critical Section Problem, Semaphores, Critical

regions, Monitors, message passing system.

Deadlocks: Deadlock Prevention, Deadlock Avoidance, Deadlock Detection and Recovery.

Unit-V

Memory Management: Basic concepts, Contiguous Allocation, Buddy system, Non-

contiguous, Paging, page table structure, Segmentation.

Virtual Memory Management: need of VM, principal of locality, Demand Paging, VM system

with TLB, Page Replacement Algorithm: FIFO, Optimal, LRU, Second Chance, Clock, NRU,

and NFU. Thrashing.

Unit-VI File System Interface– Types of files, Access methods, Directory Structure, Protection, File

System Structure, Allocation methods, Free-space Management.

Disk management: Need of disk scheduling, disk scheduling criteria, disk scheduling algorithm.

Unit-VII I/O Management - I/O Systems: I/O Hardware, I/O software, types of I/O, kernel I/O

subsystems.

Course Outcomes

a. The students will be able to understand the need and evolution of operating systems

b. Knowledge of batch systems, multiprogrammed systems, multiuser systems, multitasking

systems, multiprocessing systems, distributed systems, real-time systems

c. General operation of operating systems

d. Study of process life cycle, process scheduling, process synchronization, deadlocks

e. Study of memory allocation schemes, virtual memory

f. Study of file allocation methods and implementation of file systems

g. Study of implementation of I/O systems



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REFERENCES

1. William Stallings: Operating Systems, PHI, Latest Edition.

2. A.S. Tanenbaum: Modern Operating Systems, Latest edition Pearson/PHI.

3. Dhamdhere: Operating System Concepts, TMH.


CODE: MTCE-16-104

SUBJECT NAME: SOFT COMPUTING

NO OF CREDITS: 4


L P THEORY EXAM: 60

4 0 TOTAL: 100



Course Objectives

1. Need of soft computing in the context of real life scenarios.

2. Various constituent methodologies underlying in the domain of soft computing.

3. Fundamentals of fuzzy sets and logic

4. Fuzzy logic based control/ expert systems.

5. Inductive logic and need for training in the context of machine learning.

6. Neuron models relating to supervised and unsupervised learning.

7. Training the neurons on given input/output class information.

8. Combining neural and fuzzy paradigms

9. Genetic modeling of a problem

10. Solving a problem with huge state space using genetic modeling and operators

11. Applying soft computing in common domains like IR, Drug design etc.

Unit-I

Neural Networks: History, overview of biological Neuro-system, Mathematical Models of

Neurons, ANN architecture, Learning rules, Learning Paradigms-Supervised, Unsupervised and

reinforcement Learning, ANN training Algorithms-perceptions, Training rules, Delta, Back

Propagation Algorithm, Multilayer Perception Model, Hopfield Networks, Associative

Memories, Applications of Artificial Neural Networks.

Unit-II

Fuzzy Logic: Introduction to Fuzzy Logic, Classical and Fuzzy Sets: Overview of Classical

Sets, Membership Function, Fuzzy rule generation.

Unit-III

Operations on Fuzzy Sets: Compliment, Intersections, Unions, Combinations of Operations,

Aggregation Operations.

Unit-IV

Fuzzy Arithmetic: Fuzzy Numbers, Linguistic Variables, Arithmetic Operations on Intervals &

Numbers, Lattice of Fuzzy Numbers, Fuzzy Equations.

Unit-V

Fuzzy Logic: Classical Logic, Multivalued Logics, Fuzzy Propositions, Fuzzy Qualifiers,

Linguistic Hedges.

Uncertainty based Information: Information & Uncertainty, Nonspecificity of Fuzzy & Crisp

Sets, Fuzziness of Fuzzy Sets.

Genetic Algorithms, Scope & application areas, solution of 0-1Knapsack problem using GA

Course Outcomes

a. Discuss the various aspects of uncertainty in real life and inability of conventional

computing to handle them.

b. Relate real life problem contexts to soft computing paradigms tools

c. Design and use fuzzy sets and numbers in the context of various domains.

d. Design fuzzy rule based system for a control application like washing machine.

e. Identify the problems suitable for solution using neural networks

f. Train a perceptron network over a given input/output pattern information.

g. Design a genetic model for a given problem with huge state space.

h. Apply GA tools and solution to a problem to find an amicable solution for the same.

i. Design soft computing models to solve real life problems


Course Outcomes

Course

Objectives

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REFERENCES

1. “Fuzzy sets and Fuzzy Logic: Theory and applications”,G.J. Klir,B.Yuan, PHI

2. “Introduction to Fuzzy sets and Fuzzy Logic”, M.Ganesh , PHI

3. “An Introduction to Fuzzy Control”, D Driankov, H Hellendoorn, M Reinfrank,

Narosa Publishing Company

4. “ Neural Networks: A classroom approach”, Satish Kumar , Tata McGraw Hill

5. Haykin S., “Neural Networks-A Comprehensive Foundations”, Prentice-Hall

International, New Jersey, 1999.

6. Anderson J.A., “An Introduction to Neural Networks”, PHI, 1999


CODE: MTCE-16-112

SUBJECT NAME: SOFTWARE PROJECT MANAGEMENT (ELECTIVE II)

NO OF CREDITS: 4


L P THEORY EXAM: 60

4 0 TOTAL: 100



Course Objectives

1. To make the students understand the fundamental principles of Software Project

management & will also have a good knowledge of responsibilities of project manager

and how to handle these.

2. Understand the project planning process.

3. Be familiar with the different methods and techniques used for project management.

4. Be familiar with the techniques of project reporting, defect analysis and prevention.

5. To make the students understand the various quality techniques.

Unit I Project Management Concepts

Management Spectrum, People, Product, Process, Project, W5HH Principle.

Problems with software projects, project management and CMM, project management process:

planning, execution and closure. Stepwise overview of project planning

Unit II Software Project Planning

Programme management and project evaluation, Project planning objectives, project planning

infrastructure, process planning, Selection of an appropriate process model effort estimation

models, estimation techniques: Function Point Analysis, COCOMO, Use case point analysis.

Activity planning & Risk Management: project schedules, projects and activities, network

planning models, activity on node & activity on arrow networks.

Risk Management: identification, assessment and projection, control, RMMM plan,

Measurement and tracking planning, Configuration management: baselines, configuration items,

configuration process, version control, change control, configuration audit, SCM standards

Resource allocation: nature of resources, scheduling resources,

Unit III Project Execution and Closure

Project reporting structures, categories of reporting, collecting the data: partial completion

reporting, risk reporting. Visualizing progress: Gantt chart, Slip chart, Ball charts, Check sheet,

Histogram, parito chart, Run Chart, Control Chart, Scatter plot Timeline charts. Earned value

analysis, prioritizing monitoring, Project tracking, Milestone analysis, Cost impact of software

defects, Defect amplification and removal, Defect analysis and prevention.

Project Closure analysis: role of closure analysis, performing closure analysis, closure analysis

report

Unit IV Software Quality Assurance

Project management vs. quality management, quality concepts, Inspection and Reviews: process,

data collection, monitoring and control. Statistical SQA, SQA plan, techniques to help enhance

software quality ,quality metrics, ISO 9000 standard, BS 6079:1996 standard

Case Study: Software Project Management in CMM level 5 organizations

Course Outcomes

a. The students will have good knowledge of the issues and challenges faced while doing

the Software project Management.

b. Students will also be able to understand why majority of the software projects fails and

how that failure probability can be reduced effectively. They will completely understand

the complete software project planning process.

c. Students will be able to calculate the cost & staff for a particular project at the start.

d. Students will be able to do the project Scheduling, tracking, risk analysis, quality

management and Project Cost estimation using different techniques

e. Students will be able to give quality software by making systematic approach i.e.

Software engineering.


Course Outcomes

Course

Objectives

REFERENCES

1. Software project management by Bob Hughes and Mike Cotterell, TMH

2. Software project management in practice by Pankaj Jalote, Pearson Education

3. Software Project management by Sanjay Mahapatra

4. Software Engineering by R.S. Pressman, McGraw Hill

5. Software Testing: Principles and practices by Naresh Chauhan, Oxford University press,

India

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CODE: MTCE-16-116

SUBJECT NAME: REQUIREMENT ENGINEERING (ELECTIVE II)

NO OF CREDITS: 4


L P THEORY EXAM: 60

4 0 TOTAL: 100



Course Objectives

1. To get familiar the students about the discipline of requirement engg. and its framework

2. To introduce the means for putting the requirements in context

3. To introduce the requirement documentation

4. To introduce the requirement elicitation and negotiation

5. To get familiarity with requirement validation and its management

Unit-1: Fundamentals & Framework:

Motivation, Requirements, Continuous Requirements Engineering, The requirement engineering

framework , system context, System Boundary, Context Boundary.

Unit-2: Scenarios & Documentation:

Fundamentals of Scenarios, Scenario Types, Documenting Scenarios, Solution oriented

requirements ,goals and Scenarios, fundamentals of requirements documentation, Natural

Language Documentation, structuring natural Language requirements, fundamentals of

conceptual modelling

Unit-3: Elicitation & Negotiation:

Fundamentals of requirement elicitation, Elicitation techniques, Assistance techniques for

Elicitation, fundamentals of requirement negotiation, conflict management, negotiation

Unit-4: Management & Validation :

Fundamentals of requirement management ,goals,definition,managing requirement artifacts,

requirement traceability, fundamentals of tracebility,traceability relationship types, project

specific traceability, prioritizing requirements, fundamentals of requirements prioritization,

preparation activities, Techniques for requirement prioritization, change management for

requirements, validation techniques.

Course Outcomes

a. The student will be able to understand the requirement engineering as early development

phase and overview of requirement engg. framework

b. Understand the fundamentals of Scenarios, Scenario Types, Documenting Scenarios,

Solution oriented requirements ,goals and Scenarios, fundamentals of requirements

documentation

c. Understand the conceptual modeling

d. Study of Elicitation techniques

e. Study of requirement traceability, prioritization, change management, validation

techniques



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REFERENCES

1. Requirements Engineering: Fundamentals, Principles and techniques by Klaus Pohl, Springer

International Edition Software.

2. As per the course requirement student may opt for any reference book.


CODE: MTCE-16-118

SUBJECT NAME: AGENT BASED COMPUTING (ELECTIVE II)

NO OF CREDITS: 4


L P THEORY EXAM: 60

4 0 TOTAL: 100



Course Objectives

1. To teach the students fundamental concepts of agents

2. To explain the taxonomy and applications of software agents

3. To provide a detailed understanding of intelligent software agents

4. To explain the student need and approach for implementing Multi Agent Systems

5. To make the student learn various protocols available for communication in MAS

6. To make the students familiar with Agent Communication Languages

7. To provide an in depth knowledge of mobile agents

8. To discuss various security models of agents

9. To discuss and explain various types of attacks on agent based system and their

respective protection mechanisms

10. To learn an agent based framework : aglets

UNIT I : AGENTS – OVERVIEW

Agent Definition, Origin of Agents, Agent Programming Paradigms, Distinguishing features of

Software agents, Taxonomy of Agents, Applications of Agents

UNIT II : INTELLIGENT SOFTWARE AGENTS

Environments, Intelligent Agents, Agents and Objects, Agents and Expert Systems,Agents as

Intentional Systems,Abstract Architecture for Intelligent Agents, Howe to tell an agent what to

do,Synthesizing agents,securing intelligent agents

UNIT III : MULTI AGENT SYSTEM(MAS)

Need of MAS, Utilities and Preferences, Domain Strategies and Nash Equilibria, Competitive

and Zero-Sum Interactions, The Prisonner’s Dilemma, Dependence Relations in MultiAgent

Systems, Agent Communication Languages.

Cooperative Distributed Problem Solving, task sharing and result sharing, contract net protocol

and its extensions.

UNIT IV : MOBILE AGENTS : AGENTS WITH MOBILITY

Need of Mobile Agents, Application areas of Mobile Agents, Mobile Agent migration

process,general framework for agent migration, mobility models, classification of

communication models for mobile agents, taxonomy of attacks and proposed solution for mobile

agent security

UNIT V: SECURITY OF AGENTS & AGENT BASED FRAMEWORKS Agent

Security Issues , Mobile Agents Security , Protecting Agents against Malicious Hosts , Untrusted

Agent , Black Box Security , Authentication for agents.

Study of various agent based frameworks, case study : aglets

Course Outcomes

At the end of the course/session the student would be

a. Acquainted with the basics of software agents

b. Learned the application domain of software agents

c. Have an in depth knowledge of intelligent software agents

d. Learned where and how to use Multi Agent Systems

e. Develop various models for communication between agents using ACLs

f. To apply/ include mobile agents in given distributed systems

g. Become familiar with the various types of attacks in agent systems and their security

mechanisms


Course Outcomes

Course

Objectives

REFERENCES

1. Michael Wooldridge, An introduction to multiagent systems , Wiley Publications, ISBN 0-471-

4969 I-X, (2nd Edition)

2. Intelligent Software Agents by Richard Murch & Tony Johnson

3. Mobile Agents: Basic Concepts, Mobility Models, and the Tracy Toolkit by Peter Braun and

Wilhelm R. Rossak

4. Bigus & Bigus, " Constructing Intelligent agents with Java ", Wiley, 1997.

5. Bradshaw, " Software Agents ", MIT Press, 2000.

6. Russel, Norvig, "Artificial Intelligence: A Modern Approach", Second Edition, Pearson

Education, 2003.

7. Richard Murch, Tony Johnson, "Intelligent Software Agents", Prentice Hall, 2000.

8. Gerhard Weiss, “Multi Agent Systems – A Modern Approach to Distributed Artificial

Intelligence”, MIT Press, 2000.

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http://www.amazon.com/Richard-Murch/e/B001HD1LXO/ref=ntt_athr_dp_pel_1

http://www.amazon.com/Tony-Johnson/e/B001HOIV7W/ref=ntt_athr_dp_pel_2

http://www.amazon.com/Mobile-Agents-Concepts-Mobility-Toolkit/dp/1558608176/ref=sr_1_5?s=books&ie=UTF8&qid=1362831932&sr=1-5&keywords=mobile+agents

http://www.amazon.com/Peter-Braun/e/B001I7VWZ6/ref=sr_ntt_srch_lnk_5?qid=1362831932&sr=1-5


CODE: MTCE-16-122

SUBJECT NAME: ANALYSIS & DESIGN OF ALGORITHMS (ELECTIVE II)

NO OF CREDITS: 4


L P THEORY EXAM: 60

4 0 TOTAL: 100



Course Objectives

1. Introducing students with mathematical preliminaries required to analyze and design

computer algorithms.

2. Introducing to the student advanced data structures required to design efficient computer

algorithms

3. Familiarizing students with specific algorithms for a number of important computational

problems like sorting, searching, and graphs, etc.

4. Use various techniques for efficient algorithm design (divide-and-conquer, greedy,

dynamic programming, backtracking and branch and bound algorithms) and are able to

apply them while designing algorithms.

5. Introducing the concept of NP-complete problems and different techniques to deal with

them. Know the concepts of tractable and intractable problems and the classes P, NP and

NP-complete problems.

Unit 1: Analyzing Algorithms & Problems

Introduction to algorithms, Time and Space Complexity, Basic elements of data structures like

linked lists, stacks and queues, trees, graphs, recursion. Different types of sorting algorithms and

their complexities

Unit 2: Dynamic Sets, Searching and Graphs

Introduction, Array, amortized time analysis, red black trees, hashing, heaps, dynamic

equivalence relations and union-find programs, priority queues with decrease key operations,

traversing graphs, DFS, strongly connected components, biconnected complaints, minimum

spanning tree algo., single source shortest paths, all pair shortest paths

Unit 3: Greedy and Dynamic Methods

Introduction to greedy and dynamic methods, their algorithms, and comparative study

Unit 4: Backtracking and Branch – and – Bound

General backtracking and Branch and Bound Methods, 8 queen, sum of subset, graph coloring,

Hamilton cycles, 0/1 knapsack problem

Unit 5: NP – Hard and NP Complete problems

Basic Concepts, cooks theorem, NP – Hard graph problems, NP hard Scheduling.

Unit 6: Parallel Algorithms

Intro., parallelism, PRAM and other models, some simple PRAM algorithms, handling write

conflicts, Merging and Sorting, Finding Connected Components.

Unit 7: Approximation Algorithms

Intro., Absolute Approximation, e-approximation, polynomial time approximation schemes, fully

polynomial time approximation schemes. String matching algorithms

Course Outcomes

a. Able to analyze and compare complexity for different types of algorithms for different

types of problems.

b. Apply mathematical preliminaries to the analyses and design stages of different types of

algorithms.

c. Choose among different types of data structures the best one for different types of

problems.

d. Recognize the general principles and good algorithm design techniques for developing

efficient computer algorithms.

e. Familiarizing students with specific algorithms for a number of important computational

problems like sorting, searching, and graphs, etc.

f. Decide on the suitability of a specific algorithm design technique for a given problem.

g. Design efficient algorithms for new situations, using as building blocks the techniques

learned.

h. Apply algorithm design techniques to solve certain NP-complete problems.


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REFERENCES

1. Fundamental of Computer algorithms, Ellis Horowitz and Sartaj Sahni, 1978, Galgotia Publ.,

2. Introduction To Algorithms, Thomas H Cormen, Charles E Leiserson And Ronald L Rivest:

1990, TMH

3. The Design and Analysis of Computer Algorithm, Aho A.V. Hopcroft J.E., 1974, Addison

Wesley.

4. Algorithms-The Construction, Proof and Analysis of Programs, Berlion, P.Bizard, P., 1986.

Johan Wiley & Sons, Writing Efficient Programs, Bentley, J.L., PHI

5. Introduction to Design and Analysis of Algorithm, Goodman, S.E. & Hedetnieni, 1997, MGH.

Course Outcome

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CODE: MTCE-16-114

SUBJECT NAME: SOFTWARE ARCHITECTURE & DESIGN PATTERNS

(ELECTIVE III)

NO OF CREDITS: 4


L P THEORY EXAM: 60

4 0 TOTAL: 100



Course Objectives

1. Make the student familiar with the basics of Software Architecture

2. Teach the students basics of Architecture Business Cycle

3. Make the student understand current era software architectures and compare them

4. Make the student understand the basics of a pattern design

5. Make the student study various types of pattern dsigns

6. Make the student learn UML notations for pattern design

UNIT I :

Introduction To Software Architecture, An Engineering Discipline for Software, Status of S/W

Arch, What is Software Architecture? Designing the Architecture, Documenting the architecture,

Reconstructing Software Architecture. Software Processes and the Architecture Business Cycle,

Features of Good Architecture.

UNIT II :

Analyzing Software Architecture Analyzing development qualities at the architectural level,

SAAM, ATAM, CBAM, Architecture Reviews, Creating an Architecture Quality Attributes,

Moving from quality to Architecture, UNIT Operations, Achieving qualities, designing the

Architecture

UNIT III:

Architecture Styles Pipes and Filters, Data Abstraction and Object Oriented organization, Even-

based Implicit Invocation, Layered Systems, Registers, Interpreters, Process Control, Data-

centered, MVC, Message dispatcher, Multi-tier distributed, Other Familiar

Architectures, Heterogeneous Architectures.

UNIT IV:

Patterns What is pattern? Pattern categories, Pattern Description, Patterns and Software

Architecture, Pattern Systems, Classification, Selection

UNIT V:

Design Patterns Catalog Creational Pattern, Structural Pattern, Behavioral Patterns, Pattern

Community, Designing a document editor

UNIT VI:

Architectural Design Guidance Guidance for User Interface Architectures, Formal Models

And Specifications Finalizing the Architectural of a Specific System. Architectural Style.

Architectural Design Space. Case Study of an Industry Standard Computing. Infrastructure:

CORBA, Software architectural notations in UML

Course Outcomes

a. Familiar with the fundamentals of software architure

b. Learned the need and usage of Architecture Business Cycle

c. Compared and contrasted various types of software architectures

d. Learned the basics and types of pattern design

e. Learned UML notations for representing patterns


Course Outcomes

Course

Objectives

REFERENCES

1. Software Architecture in Practice, 2nd Edition by Len Bass, Paul Clements, Rick Kazman,

published by Pearson Edition

2. Design Patterns, by Erich Gamma, Pearson Education

3. Software Architecture Design. Stipes, 2006, Tao, Fu, Qian (required)

4. Eric Braude, Software Design: From Programming to Architecture, Wiley, 2004.

5. Mary Shaw and David Garlan, Software Architecture: Perspectives on an Emerging Discipline,

Prentice Hall, 2003

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CODE: MTCE-16-120

SUBJECT NAME: REAL TIME SYSTEMS (ELECTIVE III)

NO OF CREDITS: 4


L P THEORY EXAM: 60

4 0 TOTAL: 100



Course Objectives

1. The student has an understanding and practical experience with real-time systems.

2. To introduce the students the basic understanding and design of embedded systems.

3. The student has an understanding of embedded software development tools.

4. The students can identify the characteristics and issued in real-time systems design.

5. The student should be able to understand the basic concepts of real time operating systems.

6. The students should be able to choose suitable real time hardware and test algorithms.

7. To introduce the students with fault tolerant systems and issues in real time languages

Unit I : Embedded Systems What is an embedded system? Categories: Stand-alone, Real-time, Networked appliances,

mobile devices. Requirements of Embedded systems, Challenges and issues in Embedded

software development. Embedded Software Development Tools: Host and Target machines,

Linker/ locators for embedded software, Getting embedded software into target system.

Unit II : Real Time Embedded systems Definition, characteristics, classification, release times, deadlines and timing constraints,

temporal parameters of real-time workload, periodic task model, issues involved in real time

system design.

Unit III : Real Time Operating Systems Typical structure of an RTOS, Scheduling strategies, priority structures, task management,

memory management, code sharing, task co-operation and communication, interrupt routines in

an RTOS environment, mutual exclusion, Liveness, Minimum operating system Kernel,

capabilities of commercial RTOS: VxWorks, pSoS, Micro C/OS II.

Unit IV : Task assignment and Scheduling

Allocation / Scheduling problem, offline scheduling, online scheduling, pre-emptive / non-pre-

emptive scheduling, static / dynamic scheduling, Rate-monotonic scheduling algorithm, problem

of priority inversion, priority inheritance protocol, priority ceiling protocol, earliest-deadline-first

scheduling algorithm

Unit V : Real-Time Language Issues

Real-time language requirements, data typing, control structures, facilitating hierarchical

decomposition, synchronization, packages, exception handling, overloading and generics,

multitasking, low-level facilities

Unit VI : Fault-Tolerance Techniques Fault types, fault detection measures, fault detection mechanisms, fault and error containment,

Redundancy: Hardware and software redundancy, time redundancy.

Course Outcomes

a. The students will be able to understand the basics and importance of real-time systems

b. The students will be familiar with the issues and challenges in the embedded system design

c. The students should be able to understand the recent trends in embedded systems design.

d. The students will be able to familiar with the host and target machine.

e. Able to understand the release time, deadline and timing constraints.

f. Understand the issues involved in real time system design.

g. Able to understand the structure of RTOS together with task and memory management.

h. Understand the liveness property of RTOS and minimum operating system kernel.

i. Understand basic multi-task scheduling algorithms for periodic, aperiodic, and sporadic

tasks as well as understand the impact of the latter two on scheduling.

j. Able to familiar with the fault types and error containment zone.

k. The students will be able to understand the concepts of h/w and s/w redundancy.

l. The students will be able to familiar with the characteristics of real time languages.

m. Able to understand the capabilities of commercially available RTOS like VxWorks etc.



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1. Programming for Embedded systems by Dreamtech software team, Wiley Dreamtech India Pvt.

Ltd.

2. Embedded Realtime systems programming, by Sriram V. Iyer and Pankaj Gupta, TMH

3. Realtime computer control by Stuart Bennett, Pearson Education

4. Real time systems by C. M. Krishna, McGraw-Hill

5. Embedded Systems by RajKamal, TMH


CODE: MTIT-16-114

SUBJECT NAME: WEB TECHNOLOGIES (ELECTIVE III)

NO OF CREDITS: 4


L P THEORY EXAM: 60

4 0 TOTAL: 100



Course Objectives

1. To introduce the concept of essentials on web, client – server communication , internet

protocols, markup language.

2. To make the student familiar with XML, DTD and Document Object Model.

3. To make the student familiar with client side programming using HTML, DHTML,

Javascript.

4. To make the student familiar with server side scripting using JSP, Java servlets, EJB.

5. To make the student familiar with the wireless LAN including Bluetooth technology.

6. To introduce the concept of web services and HTML 5.0.

7.

Unit I: Introduction: Web Essentials: Clients, Servers, and Communication. The Internet-Basic Internet Protocols -

The World Wide Web-HTTP request message-response message-Web Clients, Web Servers,

Markup Languages: HTML: list, table, images, frames, forms, CSS.

Unit II:XML

Introduction, Role of XML, Difference between XML and HTML, XML Tree, XML Syntax,

Elements, Attributes, Validation, XML DTD: Introduction, Using DTD in an XML Document,

Element Type Declaration, Attribute Declaration, Entity Declaration, CDATA, DTD validation,

XML schemes: presenting and using XML; XML DOM: DOM Nodes, Document Node,

Element Node, Text Node, Attribute Node, Manipulating DOM Tree, XML Transformation,

XML Application.

Unit III: Client Side Programming

Java script: Introduction, variables, operators, Control structure, Arrays, Functions, documents,

DOM, forms, statements, functions, objects; events and event handling, Accessing and

Manipulating HTML Elements, Data entry and Validations, DHTML.

Unit IV:Server Side Programming

JSP: Creating simple JSP Pages, templating ,Request time expression,Request & Response

objects, Reading parameter values.

Java Servlets- Architecture -Overview-A Servelet-Generating Dynamic Content-Life Cycle-

Parameter Data-Sessions-Cookies- URL Rewriting-Other Capabilities-Data Storage Servelets

and Concurrency

EJB – Basics of EJB – Types of Beans – Development of Session Beans – Steps – Creating &

Implementing Interfaces – Writing Deployment descriptors – Packaging and deploying bean –

using the bean from a client – Development of stateful session bean. Entity beans – Features

(Basics of developing and using entity beans)

Unit V: Web services, Design and modeling of web services, Technologies for Implementing web

services, Current applications of advanced web technologies. HTML 5.0, WebGL, SVG, Social

web and related technologies, - Ontology modeling, Languages for representing ontologies on

the web, Rules and inferences,

Course Outcomes

a. Able to understand the concept of client server communication over web, Internet

protocols, HTTP, and web server.

b. Able to make a web page using HTML, list, tags, forms, CSS.

c. Familiar with XML, role of XML, syntax and attributes of XML.

d. Able to differentiate between XML and HTML and will be familiar with CDATA, DTD

validation, XML schemes, manipulation of DOM tree, XML Transformation.

e. Able to make the application using XML, XML DTD, XML DOM

f. Able to perform client side programming, validation and event handling using Javascript,

DOM, functions, arrays and objects.

g. Able to perform server side scripting, reading and sending the data from and into the

database using JSP.

h. Familiar with Java Servlets, cookies, Java beans, creation and implementation using EJB,

session beans and entity bean.

i. Able to understand the concept of web services, their desing and modelling, HTML 5.0,

WebGL,SVG.



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REFERENCES

1. Uttam K. Roy “Web Technologies”, Oxford Publication.

2. Jeffrey C.Jackson, "Web Technologies--A Computer Science Perspective", Pearson

3. XML by Example: Building Ecommerce applications – Sean McGrath,Pearson Education Asia

4. Java Server pages – Larne Pekowsky – Pearson Education Asia

5. JSP: Java server pages – Barry Burd, IDG Books India

6. EJB Design Patterns – Floyd Marinescu

7. Internet & Web Technologies – Raj Kamal, TMH


CODE: MTCE-16-124

SUBJECT NAME: DATA COMPRESSION TECHNIQUES (ELECTIVE III)

NO OF CREDITS: 4


L P THEORY EXAM: 60

4 0 TOTAL: 100



Course Objectives

1. To introduce the concept of data compression techniques and Mathematical Preliminaries

for compression

2. To make the student familiar with The Huffman coding algorithm: Minimum variance

Huffman codes.

3. To make the student familiar with Coding sequence and dictionary techniques.

4. The students can identify the characteristics and issues file compression and image

compression.

5. To make the student able to understand Distortion criteria , Models , Scalar

Quantization: The Quantization problem

6. Advantages of Vector Quantization over Scalar Quantization, The Linde-Buzo-Gray

Algorithm

Unit - I:

Compression Techniques: Loss less compression , Lossy Compression ,Measures of prefonnance

, Modeling and coding.

Mathematical Preliminaries for Lossless compression: A brief introduction to information

theory.

Models: Physical models, Probability models, Markov models, composite source model,

Coding: uniquely decodable codes, Prefix codes.

Unit – II:

The Huffman coding algorithm: Minimum variance Huffman codes.

Adaptive Huffman coding: Update procedure, Encoding procedure , Decoding procedure.

Golomb codes, Rice codes, Tunstall codes.

Applications of Hoffman coding: Loss less image compression, Text compression, Audio

Compression.

Unit-III:

Coding a sequence , Generating a binary code , Comparison of Binary and Huffman cding ,

Applications: Bi-level image compression-The JBIG standard , JBIG2 , Image compression.

Dictionary Techniques: Introduction , Static Dictionary: Diagram Coding , Adaptive Dictionary.

The LZ77 Approach , The LZ78 Approach ,

Applications: File Compression-UNIX compress , Image Compression: The Graphics

Interchange Format (GIF) , Compression over Modems: V.42 bits , Predictive Coding:

Prediction with Partial match (ppm): The basic algorithm , The ESCAPE SYMBOL , length of

context , The Exclusion Principle , The Burrows-Wheeler Transform: Moveto-front coding ,

CALIC , JPEG-LS , Multi-resolution Approaches , Facsimile Encoding , Dynamic Markoy

Compression.

Unit – IV:

Distortion criteria , Models , Scalar Quantization: The Quantization problem , Uniform

Quantizer , Adaptive Quantization , Non uniform Quantization.

Unit-V:

Advantages of Vector Quantization over Scalar Quantization, The Linde-Buzo-Gray

Algorithm, Tree structured Vector Quantizers, Structured Vector Quantizers.

Course Outcomes

Upon successful completion of the course, the student will be:

a. The student will be able to understand the concept of data compression techniques and

various models associated with compression.

b. The student will be able to perform compression using Huffmann coding algorithm.

c. The students will become familiar Coding sequence and dictionary techniques Static

Dictionary: DiagramCoding, AdaptiveDictionary. The LZ77 Approach , The LZ78

Approach.

d. The students will be able to differentiate between various types of quanitization

techniques.

e. The students will be able to understand the concept of vector Quantization over Scalar

Quantization


Course outcomes

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1. Khalid Sayood, Introduction to Data Compression, Morgan Kaufmann Publishers


CODE: MTCE-16-201

SUBJECT NAME: KNOWLEDGE BASED SYSTEM DESIGN

NO OF CREDITS: 4

M.TECH SEMESTER III SESSIONAL: 40

L P THEORY EXAM: 60

4 0 TOTAL: 100



Course Objectives

1. To introduce the students basic definitions of AI and Agents.

2. To make the students familiar with various Blind and heuristic Search techniques.

3. To make the students familiar about different Knowledge representation schemes.

4. To introduce the students basic types of intelligent systems (rule based, non-rule based

and frame based).

5. To make the students familiar and skilled with the decision making in uncertainty and

ambiguous environment.

6. To make the students familiar with the various kinds of learning and planning techniques.

7. To introduce the students with expert system, fuzzy expert system and expert system

shells

8. To make the students familiar with Natural Language Processing phases and some typical

grammar used NLP.

Basics of AI, Introduction to Agents, Search techniques: Blind and Heuristic, Knowledge

representation, first order predicate logic and resolution, semantic nets, implementation of

semantic nets, Frames, CD’s. Problem solving approaches: forward and backward chaining,

Production System or rule based systems, Non-rule based systems. Frame based systems.

Handling uncertainty and ambiguities using Fuzzy logic etc., Learning and planning,

Applications: Expert system and expert system shells, Fuzzy expert systems, Natural Language

Processing: NTG, ATG, Robotics, Game Playing.

Course Outcomes

a. The student will be familiar with definitions of AI and Agents.

b. The student will be able to perform various Blind and Heuristic Search in problem space.

c. The student will be able to represent knowledge using different Knowledge

representation schemes.

d. The student will be familiar with the difference kind of intelligent systems and difference

among them.

e. The student will be able to design systems for uncertain and ambiguous environment.

f. The student will be familiar with different kinds of learning and planning techniques.

g. The student will be able to design expert system and their shells. They will also be able to

understand the design of fuzzy expert system and nature of their rules.

h. The student will be familiar with Natural Language Processing phases and some typical

grammar used NLP.

i. The student will be familiar with the basics of Robotics and Game playing strategies.


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REFERENCES

1. Artificial Intelligence: A Modern Approach by Stuart Russell and Peter Norvig, Pearson

Publications.

2. Artificial Intelligence: Structures and Strategies for Complex Problem Solving (6th Edition) by

George F Lugar, Pearson Publications.

3. Artificial Intelligence: A New Synthesis by Nils J. Nilsson, Pearson Publication.


CODE: MTCE-16-203

SUBJECT NAME: ADVANCED DATABASE MANAGEMENT SYSTEM

NO OF CREDITS: 4


L P THEORY EXAM: 60

4 0 TOTAL: 100



Course Objectives

1. To make students familiar with DBMS Architecture, Data modeling, Data models,

Normalization and de-normalization.

2. To make students familiar with Query Processing concepts.

3. To make students familiar with Transactions, Concurrency control and Recovery.

4. To make students familiar with Object Oriented Database Development Process.

5. To make students familiar with Parallel and Distributed Databases

6. To make students familiar with databases for advanced applications.

Unit 1: Basic Concepts

DBMS Architecture and Components, Advantages and Disadvantages; Data modelling:

ER, EER, Network, Hierarchical and Relational data models; Normalization and de-

normalization.

Unit 2: Query Processing

General strategies for query processing, query processor, syntax analyzer, Query decomposition,

Heuristic Query optimization.

Unit 3: Transactions, Concurrency control and Recovery

Transaction concept, schedules, serializability, precedence graph meod for serializability, Lock

thrashing, phantom problem; Concurrency control protocols: locking schemes, timestamp based

schemes, optimistic and multi-version techniques; reflecting updates: logging schemes and

checkpoints.

Unit 4: Object Oriented Database Development

Basic concepts of Object oriented Databases, Object identity, Object structure, type constructor,

encapsulation of operations, methods and persistence, Type hierarchies, inheritance, ER Vs

OODM, advantages and disadvantages of OODBMSs, Introduction to Object relational

Database, enhanced SQL (SQL3), design of an ORDBMS, nested relations and collections,

advantages and disadvantages of ORDBMS, Comparison with OODBMS.

Unit 5: Parallel and Distributed Databases

Basic concepts, architectures, parallelization of operations, Methods for data distribution:

fragmentation and replication, catalog management, Distributed query processing: semi-joins

and bloom-joins, Distributed transaction processing.

Unit 6: Databases for Advanced Applications

Data warehousing systems, Data warehouse Vs DBMS, architecture, Data mining systems, KDD

process, temporal database concepts, spatial databases, multimedia databases, Web databases,

Information retrieval and XML.

Course Outcome:

a. The students will be able to understand DBMS Components, Advantages and

Disadvantages.

b. The students will be able to understand Data modeling: ER, EER, Network, Hierarchical

and Relational data models.

c. The students will be able to understand 1NF, 2NF, 3NF, BCNF, 4th

normal form and 5th

normal forms of Normalization and de-normalization.

d. The students will be able to understand general strategies for query processing, query

processor, syntax analyzer, Query decomposition, Heuristic Query optimization.

e. The students will be able to understand transaction concept, schedules, serializability,

precedence graph meod for serializability.

f. The students will be able to understand Lock thrashing, phantom problem.

g. The students will be able to understand Concurrency control protocols: locking schemes,

timestamp based schemes, optimistic and multi-version techniques; reflecting updates:

logging schemes and checkpoints.

h. The students will be able to understand basic concepts of Object oriented Databases,

Object identity, Object structure, type constructor, encapsulation of operations, methods

and persistence, Type hierarchies, inheritance.

i. The students will be able to understand ER Vs OODM, advantages and disadvantages of

OODBMSs,

j. The students will be able to understand Object relational Database, enhanced SQL

(SQL3), design of an ORDBMS, nested relations and collections, advantages and

disadvantages of ORDBMS, Comparison with OODBMS.

k. The students will be able to understand basic concepts, architectures, parallelization of

operations.

l. The students will be able to understand methods for data distribution: fragmentation and

replication, catalog management, Distributed query processing: semi-joins and bloom-

joins, Distributed transaction processing.

m. The students will be able to understand Data warehousing systems, Data warehouse Vs

DBMS, architecture, Data mining systems, KDD process.

n. The students will be able to understand temporal database concepts, spatial databases,

multimedia databases, Web databases, Information retrieval and XML.



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1. Fundamentals of Database systems- Elmasri and Navathe, Pearson Education.

2. Database Management Systems- Raghu Ramakrishnan, Johannes Gehrke, McGraw-Hill.

3. An Introduction to database systems- Bipin C. Desai, Galgolia Publications.

4. Database system concepts- Korth, Silberchatz, Sudarshan, McGraw Hills.

5. Database systems: concepts, design and applications- S.K. Singh, Pearson education.


CODE: MTCN-16-102

SUBJECT NAME: MOBILE & WIRELESS COMMUNICATION (ELECTIVE IV)

NO OF CREDITS: 4


L P THEORY EXAM: 60

4 0 TOTAL: 100



Course Objectives

1. To introduce the concept of wireless communication along with its history, application,

and market.

2. To make the student familiar with basic terminology like frequency, signals, bandwidth,

signals and spread spectrum etc.

3. To introduce the concept of cellular system and design of cellular system. To make the

students familiar with different handoff strategies.

4. To introduce the MAC and Telecommunication system.

5. To make the student familiar with the wireless LAN including Bluetooth technology.

6. To introduce the concept of Mobile Network layer, IP Packet delivery and adhoc network

routing.

7. To make the student familiar with mobile transport layer along with satellite

communication.

8.

Unit-1: Introduction

Applications, history, market, reference model and overview. Wireless Transmission—

Frequencies, signals, antennas, signal propagation, multiplexing, modulation, spread spectrum.

Unit-2: Cellular System- Concept and Design Fundamentals: Introduction. Frequency Reuse. Channel Assignment Strategies. Handoff Strategies. Interference

and System Capacity. Trunking and Grade of Service. Improving Coverage & Capacity in

Cellular Systems.

Unit-3: MAC and Telecommunication system:

Specialized MAC, SDMA, FDMA, TDMA- fixed TDM, classical ALOHA, slotted,

ALOHA, CSMA, DAMA, PKMA, reservation TDMA. Collision avoidance, polling

inhibit sense multiple access.('DM A, comparison, CSM- mobile services, architecture radio

interlace, protocol, localization, calling, handover, security, new data services, Introduction to

W'LL.

Unit-4: Wireless LAN

Wireless LAN: IEEE 802.11-System and protocol architecture, physical layer. MAC

layered management. Bluetooth--- User scenarios, physical layer, MAC layer,

networking, security and link management.

Unit-5: Mobile network Layer:

Mobile IP- goals, assumption, requirement, entities, terminology, IP packet delivery, Agent

advertisement and discovery, registration, tunneling, encapsulation, optimization, reverse

tunnelling. DHCP. Adhoc Networks- routing: destination sequence distance vector,

dynamic source routing, hierarchical algorithm, alternative metric.

Unit-6: Mobile Transport Layer and Satellite Systems:

Transport Layer: Traditional TCP, Indirect 'TCP, Snooping 'TCP, Mobile TCP fast

retransmission recovery, transmission/time out freezing, selective retransmission, Transaction

oriented TCP. Satellite Systems: History, Applications, GLO, LLO, MLO, routing, localization ,

handover in satellite system. .

Course Outcomes

a. Able to understand the concept of wireless communication, its advantages over

traditional wired network communication, different application of wireless

communication system.

b. Familiar with the various terms such as frequencies, signals, multiplexing, modulation

and spread spectrum techniques.

c. Able to understand the concept of cellular system, how cellular systems are designed,

handoff strategies.

d. Able to understand what is system capacity, frequency reuse, requirement of frequency

reuse in wireless networks, improving the coverage and capacity of cellular system.

e. Able to understand and classify different multiplexing strategies.

f. Able to understand and classify different modulation strategies.

g. Differentiate between ALOHA and slotted ALOHA.

h. Familiar with GSM, GSM system architecture, GSM protocol architecture, handover

procedure and security.

i. Familiar to wireless LAN, characteristics and design goals of wireless LAN, architecture

of infrastructure based network.

j. Familiar with IEEE standard 802.11, CSMA/CA access method, fragmentation, MAC

Management, Bluetooth, piconet, scatternet, Bluetooth protocol stack.

k. Able to understand the concept of Mobile IP, its goals and other terminologies. Able to

differentiate between IPV4 and IPV6.

l. Able to understand the concept of adhoc network and differentiate between infrastructure

based and infrastructure less network

m. Familiar with different categories of routing protocols of adhoc network.

n. Familiar with mobile transport layer, TCP, satellite communication, categories, routing

and handover in satellite communication.



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REFERENCES

1. Jochen Schiller," Mobile Communication" , Pcarson Education,2002

2. Lee, " Mobile Cellular Telecommunications" McGRAW- HILL.

3. Wireless Communications : Principles and Practice by Theodore S. Rappaport Prentice Hall India

1996.

4. Wireless Communications : Principles and Practice by Theodore S. Rappaport Pearson 2010.


CODE: MTIT-16-203

SUBJECT NAME: ADVANCED INFORMATION RETRIEVAL SYSTEMS

(ELECTIVE IV)

NO OF CREDITS: 4


L P THEORY EXAM: 60

4 0 TOTAL: 100



Course Objectives

1. To build an understanding of the fundamental concepts of Information Retrieval

2. To familiarize students with the basic taxonomy of Indices and Laws for estimation and

modeling distribution of terms

3. To understand definition of Search, Integration & Web Data Mining

4. To introduce the concept of Semantic Web and related problems

5. To understand RDF : basic elements capabilities and rules

6. To learn the elements of Swoogle, SWDs and indexing

7. To understand the bisics of FOAF, its vocabulary and Semantic Markup

8. To learn Semantic Web Search Engine, Query Processing and Indexing

Unit 1 : Introduction to Advanced Information Retrieval System


Boolean model versus ranked retrieval, Basic Index Construction & Index Compression- an

inverted index, Bi-word indexes, Positional indexes, Combination schemes, Heaps Law & Zipf’s

law, Advanced Indexing & Retrieval Schemes, Better Link Analysis for ranking, Advantages of

Advanced IRS over Basic IRS

Unit-2: The World Of Semantic Web

Introduction to WWW and definition of Search, Integration & Web Data Mining. Semantic Web

and Introduction to metadata, its basic concepts and considerations. Search Engines for

traditional web: Building the index table, conducting the search, Search Engines for Semantic

Web: Building a semantic Web Search Engines, Using the Semantic Web Search Engines

Problems related to Semantic Web Search Engines

Unit-3: The Basic Elements Of Semantic Web

Building block of Semantic Web: RDF, Overview of RDF, Basic elements of RDF, RDF Triples,

Basic syntax, literal values and other RDF capabilities. Fundamental rules of RDF, Aggregation

& Distributed Information

RDFS, Taxanomy and Ontology, Core Elements of RDFS, Syntax & Examples, Concepts of

Ontology & Taxonomy.

Unit-4: The Semantic Web: Real –World Examples

Swoogle: A Search Engine for Semantic Web documents.Swoogle Architecture, Discovery of

SWDs, Collection of Metadata and calculation of rankings using metadata. Indexation and

retrieval of SWDs

FOAF: Friend of a Friend, Basic FOAF Vocabulary & Examples. Creating a FOAF Document

and getting into the Circle. Semantic Markup, Semantic Markup issues.

Unit-5: Semantic Web Search Engines Revisited:

Why Search Engines Again? Why traditional Search /engines fails? The Design of Semantic

Web Search Engine prototype: Query processing, Discovery Strategy, Indexation Strategy,

Using the prototype system.Why this prototype Search Engine provides better performance.

Course Outcomes

a. The students will be able to understand basic Inforamation Retrieval Systems.

b. The students will be able to identify the different types of indices and will be able to

make estimations and model distribution of terms.

c. The students will be able to understand the concept of Semantic Web Search Engine and

related issues.

d. The students will be able to learn RDF, RDF triples , syntax, Aggregation and Distributed

Information.

e. The students will be able to understand the core elements of Swoogle, its architecture and

retrieval of SWDs

f. The students will be able to understand the basic concept of FOAF, creating FOAF

document and Semantic Markup issues

g. The students will be able to understand the design of the Semantic Web Search Engine

h. The students will be able to learn the discovery strategy and indexation strategy.



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CODE: MTCN-16-215

SUBJECT NAME: CLOUD COMPUTING (ELECTIVE IV)

NO OF CREDITS: 4


L P THEORY EXAM: 60

4 0 TOTAL: 100



Course Objectives

1. To introduce the basic concepts of Cloud Computing, service layers involved, deploy

applications over cloud computing platform, Utility Computing and Elastic Computing .

2. To discuss the various Cloud Technologies: AJAX , web services and software for

enterprise applications.

3. To discuss the cloud data in Relational databases and various filesystems: GFS, HDFS,

BigTable, HBase and Dynamo in cloud.

4. To discuss in detail the Map-Reduce concept, Map-Reduce model in parallel computing

and its application.

5. To introduce the fundamentals of cloud security, its tool and cloud computing security

architecture.

6. To familiarize the students with challenges involved in cloud computing security:

Virtualization security management.

7. To discuss the issues involved in cloud computing while implementing real time

application over cloud.

8. To discuss the issues regarding intercloud environments, QOS, Dependability, data

migration, streaming.

9. To make students understand the basics of cloud middleware, Mobile Computing, Grid

Computing, Sky Computing.

10. To discuss research issues to be explored regarding load balancing, resource

optimization, dynamic resource provisioning in cloud computing.

Unit 1:

Introduction to Cloud Computing, Definition, Characteristics, Components, Cloud provider,

SAAS, PAAS, IAAS and Others, Organizational scenarios of clouds, Administering &

Monitoring cloud services, benefits and limitations, Deploy application over cloud, Comparison

among SAAS, PAAS, IAAS, Cloud computing platforms: Infrastructure as service: Amazon

EC2,Platform as Service: Google App Engine, Microsoft Azure, Utility Computing, Elastic

Computing

Unit 2:

Introduction to Cloud Technologies, Study of Hypervisors Compare SOAP and REST

Webservices, AJAX and mashups-Web services: SOAP and REST, SOAP versus REST,

AJAX: asynchronous 'rich' interfaces, Mashups: user interface services Multitenant software:

Multi-entity support, Multi-schema approach, Multi-tenance using cloud data stores, Data access

control for enterprise applications

Unit 3:

Data in the cloud: Relational databases, Cloud file systems: GFS and HDFS, BigTable, HBase

and Dynamo. Map-Reduce and extensions: Parallel computing, The map-Reduce model, Parallel

efficiency of Map-Reduce, Relational operations using Map-Reduce, Enterprise batch processing

using Map-Reduce, Introduction to cloud development, Example/Application of Mapreduce,

Features and comparisons among GFS,HDFS etc, Map-Reduce model

Unit 4:

Cloud security fundamentals, Vulnerability assessment tool for cloud, Privacy and Security in

cloud Cloud computing security architecture: Architectural Considerations- General Issues,

Trusted Cloud computing, Secure Execution Environments and Communications, Micro-

architectures; Identity Management and Access control-Identity management, Access control,

Autonomic Security Cloud computing security challenges: Virtualization security

management- virtual threats, VM Security Recommendations, VM-Specific Security techniques,

Secure Execution Environments and Communications in cloud.

Unit 5:

Issues in cloud computing, Implementing real time application over cloud platform

Issues in Intercloud environments, QOS Issues in Cloud, Dependability, data migration,

streaming in Cloud. Quality of Service (QoS) monitoring in a Cloud computing environment.

Cloud Middleware. Mobile Cloud Computing. Inter Cloud issues. A grid of clouds, Sky

computing, load balancing, resource optimization, resource dynamic reconfiguration, Monitoring

in Cloud

Course Outcomes

a. The students will understand the concept of cloud computing with its service layers and

Utility Computing and Elastic Computing .

b. The students will understand deployment of applications over cloud computing platform.

c. The students will be able to understand various Cloud Technologies, web services and

software involved in cloud computing to design enterprise applications.

d. The students will be able to manage cloud data in relational databases and file systems in

cloud computing.

e. The students will understand the concept of Map-Reduce and how Map-Reduce works in

analysis of data in parallel computing .

f. The students will be able to design cloud based applications using map/reduce paradigm

for handing distributed file system based data.

g. The students will be able to understand concept of cloud security, its tool and architecture

of cloud computing security.

h. The students will be able to understand the challenges involved in cloud computing

security and how VMs can be secured in Virtualization security management

i. The students will be able to understand how real time applications can be implemented

over cloud platform.

j. The students will understand how the various issues arise due to Intercloud environments,

QOS, Dependability, data migration and streaming in cloud

k. The student will be able to understand on-demand utility computing phenomenon known

as cloud computing. How this paradigm is different from Mobile cloud computing, grid

computing, sky computing.

l. The students will be able to understand how computation could be taken to data i.e. in-

situ rather than moving volume of data around.

m. The students will be able to understand many issues involve in cloud computing and

would be able to take up some topics for research activity.



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1. Cloud Computing by Judith Hurwitz, R.Bloor, M.Kanfman, F.Halper (Wiley India Edition)

2. Enterprise Cloud Computing by Gautam Shroff,Cambridge

3. Cloud Security by Ronald Krutz and Russell Dean Vines, Wiley-India

4. Google Apps by Scott Granneman,Pearson

5. Cloud Security & Privacy by Tim Malhar, S.Kumaraswammy, S.Latif (SPD,O’REILLY)

6. Cloud Computing : A Practical Approach, Antohy T Velte, et.al McGraw Hill,

7. Cloud Computing Bible by Barrie Sosinsky, Wiley India


CODE: MTCE-16-211

SUBJECT NAME: NATURAL LANGUAGE PROCESSING (ELECTIVE IV)

NO OF CREDITS: 4


L P THEORY EXAM: 60

4 0 TOTAL: 100



Course Objectives

1. To introduce the students difference levels/stages of natural language processing.

2. To make the students familiar with applications and open problems of/in NLP and NLU.

3. To introduce concept of Formal languages and grammars: Chomsky hierarchy and

problems associated with them.

4. To introduce the top down and the bottom up parsing approaches and their respective

types of parsers.

5. To introduce concept of grammars for Natural Language (like ATN & RTN) and their

problem such as ambiguity.

6. To make the students familiar with the basic techniques of parsing like CKY, Earley &

Tomita’s algorithms.

7. To introduce the students with Morphology of natural languages by taking examples from

Hindi, English.

8. To make the students familiar with Semantics-knowledge and strategies for semantic

understanding.

9. To make the students familiar with speech recognition and issues associated with it.

10. To introduce the HMM model for speech recognition.

UNIT – I

Introcution to NLP and NLU – Applications of NLP & NLU, open problem, Differences

levels of Language Analysis

UNIT – II

Syntatic processing – Linguistic Background – Outline of English Syntax, Top down &

Bottom up processing, Finite state models and morphological processing.

Grammer for Natural language, Ambiguity Resolution.

UNIT – III

Semantic Introduction – Semantic and logical form, Ambiguity, speech acts and embedded

Sentences, other strategies for Sementic Interpretation.

UNIT – IV

Speech Recognition and Spoken language – Issue in Speech Recognition sound structure,

Signal processing, HMM model, NLP, NLU and speech Recognition.

Course Outcomes

a. The student will be familiar with difference levels/stages of natural language processing.

b. The student will be able to understand the familiar with applications and open problems

of/in NLP and NLU.

c. The student will be able to understand types of Formal languages and grammars:

Chomsky hierarchy and problems associated with them. They will also be able to resolve

such problems.

d. The student will be familiar with the top down and the bottom up parsing approaches and

their respective types of parsers.

e. The student will be able to write small grammars for simple English sentences.

f. The student will be familiar with parser like CKY, Earley & Tomita’s.

g. The student will be able to do Morphology of words taken from natural languages like

Hindi, English.

h. The student will be familiar with Semantics-knowledge and its importance in

understanding the language sentence. The student will be also be able to write some

simple semantic structures and will be able to use them for semantic analysis.

i. The student will be familiar with speech recognition and issues associated with it. They

will also be familiar with HMM and will be able to apply that for speech recognition.


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1. James Allen, “Natural Language Understanding”, Pearson education, 2003

2. Rajeev S., Zevarsky, “Speech processing and Recognition , PHI, 2002


CODE: MTIT-16-209

SUBJECT NAME: SEMANTIC WEB (ELECTIVE IV)

NO OF CREDITS: 4


L P THEORY EXAM: 60

4 0 TOTAL: 100



Course Objectives

1. To make the students familiar with Semantic Web technology and its applications.

2. To make the students familiar with origin of semantic web and meta data search engines.

3. To enable students understand Ontology.

4. To give knowledge about role of Ontology, OWL, OWL Stack.

5. To give knowledge about Protégé and make Ontology using protégé.

6. To enable students understand the concept of Semantic search engine .

7. To make the student familiar with semantic web services: UDDI, OWL-S.

8. To make the students understand architecture of Swoogle.

9. To make student familiar with FOAF.

10. To make the students understand sematic markup and semantic web search engine

Unit-1 Semantic Web:

Introduction to semantic web technology, need, problems, applications, it’s relation with

Artificial Intelligence. Traditional web to semantic web – meta data search engines.

Unit-2 Ontology:

XML, RDF, RDFS core, URI and other components of Ontology. Ontology for different

applications, Role of Ontology in intelligent information retrieval on web. OWL, OWL Stack:

define classes- set operators –enumerations- defining properties – Validating OWL ontology,

Mapping Ontology, Writing OWL ontology with Protege.

Unit-3 Semantics:

Kinds of semantics, use of semantics Search Engines: Role of search Engines in intelligent

retrieval of information on web. Semantic web services and applications : Web services – web

services standards – web services to semantic web services- UDDI Concept of OWL-S –

building blocks of OWL-S- mapping OWL-S to UDDI- WSDL-S overview.

Unit-4 Real world examples and applications:

Swoogle- architecture and usage of meta data; FOAF – vocabulary – creating documents –

overview of semantic markup – semantic web search engines.

Course Outcomes

a. The students will be able to understand basics of Semantic Web technology and its

applications.

b. The students will be able to need, problems, applications, semantic web relation with

Artificial Intelligence

c. The students would be able to define Ontology: XML, RDF, RDFS.

d. The students will be able to understand OWL, OWL Stack.

e. The students will be able define classes- set operators –enumerations- defining properties

– Validating OWL ontology.

f. The students will be able to analyze how to map ontology .

g. The students will be able to construct ontology using Protege.

h. The students will be able to understand the concept of Semantic search engines.

i. The students would be able to UDDI,OWL Stack: OWL-S.

j. The students will be familiar with the architecture of SWOOGLE(semantic search

Engine)

k. The students would be able to define FOAF and will be able to create document using

semantic markup.



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REFERENCES

1. Tim Berner’s Lee, “Weaving the web: The original design and ultimate destiny of www”, Harper

Business (imprint of Harper Collins) .

2. Liyang Yu , “Introduction to the Semantic Web and Semantic web services. Chapman & Hall/CRC”,

Taylor & Francis group, 2007.

3. Michael C Daconta, Leo, Kelvin Smith , “The Semantic Web:A guide to the future of XML,Web

services, and knowledge management”, Wiley.

6. Dieter Fensel, James Hendler, Henry Lieberman, Tim Berner’s Lee “Spinning the Semantic Web”,

MIT press

7. Grigoris Antonion, Frank Van Harmalen,“Semantic Web primer”, MIT press Thomas B Passin,

“Explorer’s guide to Semantic Web”, Hanning


CODE: MTCN-16-110

SUBJECT NAME: STENOGRAPHY & DIGITAL WATERMARKING (ELECTIVE V)

NO OF CREDITS: 4


L P THEORY EXAM: 60

4 0 TOTAL: 100



Course Objectives

1. The objective of the course is to make students familiar about security, its various

services and differentiation among various types of security.

2. To make students familiar with basic concepts of steganography, its various techniques

and how is it different from cryptography.

3. To make students familiar with basic concepts of Digital watermarking, its various

classical and modern techniques.

4. To make students familiar about current research areas or topics of stenography and

digital water marking on which research is going on.

Unit-1 : Introduction

What is security?, Need of security, Why is security so hard?, various goals of security,

Difference between Vulnerability, Threats, Attacks and control, Security goals, aspects of

security, security services, security attacks, Kerchoff’s assumption, Difference between

Computer security, Information security, Network Security and Cyber security, security models,

unconditional security, computation security, Computer criminals, Introduction to

steganography, digital water marking.

Unit-2 Steganography

Introduction to Information hiding , Brief history and applications of information hiding,

Principles of Steganography, Steganography vs cryptography, Steganography terms, Type of

steganography, steganography system, Classic Techniques, Modern Steganography techniques :

Masking and Filtering, algorithms and transformations, least bit insertion, Pure , secret key and

public steganography, Steganalysis.

Unit-3 : Digital Watermarking

Introduction, History and terminology, Classification of watermarking, Steganography vs

watermarking, Basic watermarking principle, categories of watermark, Types of watermarking

algorithms, Survey of current watermarking techniques: Spatial domain watermarking,

Transform domain watermarking, Watermarking applications.

Unit- 4 Advance Topics

Discussion of recent research papers on steganography and digital watermarking.

Course Outcome

By the end of the course, students should be able understand importance of security and its

various security models

a. By the end of the course, students should be able understand the concept of stenography,

its importance and application areas and various stenography techniques by which

security can be provided to data.

b. By the end of the course, students should be able understand the concept of Digital water

marking, its application areas, comparative analysis of various techniques to implement it

c. By the end of the course, students should be able to identify research challenges in the

area of stenography and digital water marking.

MAPPING OF CORSE OBJECTIVES WITH COURSE OUTCOMES

Course Outcomes---------------->

Course

Objectives

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REFERENCES

1. Stefan Katzenbelsser and Fabien A. P. Petitcolas, “Information hiding techniques for

Steganography and Digital Watermarking”, ARTECH House Publishers, January 2004.

2. Jessica Fridrich, “Steganography in Digital Media: Principles, Algorithms, and Applications”,

Cambridge university press, 2010.

3. Steganography, Abbas Cheddad, Vdm Verlag and Dr. Muller, “Digital Image” Aktienge sells

chaft & Co. Kg, Dec 2009.

4. Ingemar Cox, Matthew Miller,Jeffrey Bloom,Jessica Fridrich and Ton Kalker, “Digital

Watermarking And Steganography”, Morgan Kaufmann Publishers, Nov 2007.


CODE: MTIT-16-211

SUBJECT NAME: CRYPTOGRAPHY (ELECTIVE V)

NO OF CREDITS: 4


L P THEORY EXAM: 60

4 0 TOTAL: 100



Course Objectives

1. Understand the basic concept of Cryptography, and their mathematical models.

2. To understand various types of ciphers, DES, AES, message Authentication, digital

Signature System.

3. To impart knowledge of major issues in network and computer system security, focusing

mainly on threats from malicious software.

4. To understand common attacks on computer networks and methods to detect and

remediate such attacks.

5. To understand the Public Key Cryptosystems and analyze their security.

6. Evaluating information security procedures and practices.

7. To analyze security vulnerabilities on different network layers.

8. To acquire knowledge about network security tools and authentication applications.

9. To study various key management and key distribution schemes.

10. To study various issues in security of MANETS and study various attacks.

11. To provide the students with the competences required for understanding various issues

in security of Wireless Security Networks and also various attacks against security

mechanism and routing.

Unit-1 : Introduction



security, security services, security attacks, Kerckhoff’s assumption, Difference between

Computer security, Information security, Network Security and Cyber security , security models,

unconditional security, computation security, Computer criminals.

Unit-2 : Encryption Techniques

Terminology of encryption, Requirement of encryption, cryptography, cryptanalysis,

cryptanalytic attacks, symmetric ciphers : Substitutional cipers, Ceasar cipher, Monoalphabetic,

Play fair cipher, ployalphabetic cipher, Vigenère Cipher, Kasiski Method, Autokey Cipher, One-

Time Pad, Transposition ciphers, Rail Fence cipher, Scytale cipher , geometric ciphers, reverse

cipher, Row Transposition Ciphers, Rotor Machines

Unit-3 : Symmetric key Encryption Standards

properties of arithmetic operations, inverse, primes, GCD, modular arithmetic, properties of

modular arithmetic, computing the inverse, Fermat’s theorem, algo for computing inverses,

random number generation. Data Encryption Standard - Simplified DES, Block Cipher

Principles, Data Encryption Standard, Strength of DES, Block Cipher Design Principles,

Block Cipher Modes of operation, RC2, RC4.

Unit-4 : AES and Confidentiality

Advanced Encryption Standard- Evaluation Criteria for AES, AES Cipher;

Contemporary Symmetric Ciphers- Triple DES, Confidentiality using Symmetric

Encryption- Placement of Encryption Function, Traffic Confidentiality, Key Distribution, and

Random Number Generation.

Unit-5 : Public-Key Encryption And Hash Functions

Public Key Cryptography and RSA- Principles of Public Key Cryptosystems, RSA

Algorithm; Key Management, Diffie-Hellman Key Exchange, Elliptic Curve

Cryptography; Message Authentication and Hash Functions- Authentication Requirements,

Authentication Functions, Message Authentication Codes, Hash Functions and MACs; Hash

Algorithms- N-hash, MD4, MD5 Message Digest Algorithm; Secure Hash Algorithm,

Digital Signatures and Authentication Protocols, Digital Signature Standards.

Introduction to Network security: Preety Good Privacy (PGP), S/MIME

Course Outcomes

After the completion of this course the student will able to:

a. Understand theory of fundamental cryptography, encryption and decryption algorithms,

b. Build secure systems by use of block ciphers like AES, DES.

c. Have a detailed knowledge about authentication, hash functions and application level

security mechanisms.

d. Analyze and apply cryptography for secure e-Commerce and other secret transactions.

e. To be familiar with network security designs using available secure solutions and

advanced security issues and technologies.

f. To develop basic security enhancements in MANETS.

g. To know how authentication is implemented in wireless systems and understand

authentication protocols and processes.

h. Become familiar with different types of Attacks and their protection mechanisms.

i. Become familiar with various key management and distribution issues.


Course Outcomes

Course

Objectives

REFERENCES

1. William Stalling, Cryptography and Network Security, 3rd

Edition. PHI New Delhi

2. William Stalling, Network Security Essentials, 2nd


3. Charles P. Pfleeger, Security in computing, 4th Edition Pearson,, New Delhi

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CODE: MTIT-16-213

SUBJECT NAME: NETWORK SECURITY (ELECTIVE V)

NO OF CREDITS: 4


L P THEORY EXAM: 60

4 0 TOTAL: 100



Course Objectives

1. Understand the basic concept of Cryptography and Network Security, their mathematical

models.

2. To understand various types of ciphers, DES, AES, message Authentication, digital

Signature System.

3. To impart knowledge of major issues in network and computer system security, focusing

mainly on threats from malicious software.

4. To understand common attacks on computer networks and methods to detect and

remediate such attacks.

5. To understand the Public Key Cryptosystems and analyze their security.

6. Evaluating information security procedures and practices.

7. To analyze security vulnerabilities on different network layers.

8. To acquire knowledge about network security tools and authentication applications.

9. To study various key management and key distribution schemes.

10. To study various issues in security of MANETS and study various attacks.

11. To provide the students with the competences required for understanding various issues

in security of Wireless Security Networks and also various attacks against security

mechanism and routing.

Unit-1: Introduction



security, security services, security attacks

Encryption Techniques Terminology of encryption, Requirement of encryption, cryptography,

cryptanalysis, cryptanalytic attacks, symmetric ciphers: Substitution ciphers, Transposition

ciphers, Data Encryption Standard (DES, Advanced Encryption Standard (AES), location of

encryption devices, key distribution, Public Key Cryptography and RSA, Diffie-Hellman

Key Exchange, Message Authentication and Hash Functions, MD5, SHA

Unit-2 : Network Security

Security services, Message confidentiality, Message integrity, message authentication, digital

signature, entity authentication. Authentication applications: Kerberose 95, X.509

Authentication service, Public key infrastructure. Electronic mail Security: Preety Good

Privacy (PGP), IP Security: IP security overview, IP security architecture, Authentication

header, Encapsulating security Payload, Combining security associations, Key management.

Unit-3 : Security Attacks in MANET

Security issues in MANET, Attacks in MANET: External Attack, Internal attack, Black hole

attack, warm hole attack, grey hole attack, Byzantine attack, Sleep Deprivation attack, Flooding

attack: RREQ flooding attack, Data flooding Attack.

UNIT-4 : Security Attacks in Wireless Sensor Networks

Security issues in WSN, Attacks in WSN : Attack against Security mechanism, Attack against

basic mechanism like routing: Spoofed, altered, or replayed routing , Information , Selective

forwarding , Sinkhole attacks , Sybil attacks , Wormholes, HELLO flood attacks

Course Outcomes

After the completion of this course the student will able to:

j. Understand theory of fundamental cryptography, encryption and decryption algorithms,

k. Build secure systems by use of block ciphers like AES, DES.

l. Have a detailed knowledge about authentication, hash functions and application level

security mechanisms.

m. Analyze and apply cryptography for secure e-Commerce and other secret transactions.

n. To be familiar with network security designs using available secure solutions and

advanced security issues and technologies.

o. To develop basic security enhancements in MANETS.

p. To know how authentication is implemented in wireless systems and understand

authentication protocols and processes.

q. Become familiar with different types of Attacks and their protection mechanisms.

r. Become familiar with various key management and distribution issues.


Course Outcomes

Course

Objectives

REFERENCES 1. William Stalling, Cryptography and Network Security, 3

rd Edition. PHI New Delhi

2. William Stalling, Network Security Essentials, 2nd


3. Charles P. Pfleeger, Security in computing, 4th Edition Pearson,, New Delhi

4. Kazem Sohrary, Wireless sensor newtroks, Technology, Protocols and applications, Wiley Publishers

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CODE: MTIT-16-215

SUBJECT NAME: WEB MINING (ELECTIVE V)

NO OF CREDITS: 4


L P THEORY EXAM: 60

4 0 TOTAL: 100



Course Objectives

1. To familiarize the students with the basic roadmap of data mining and various data

mining techniques.

2. To introduce the concept of Web mining, types, various measures and techniques

3. To acquaint students with Web content mining and its applications on World Wide Web.

4. To introduce students with Web structure mining and its applications on Web graph and

page ranking algorithms.

5. To understand basics of Web usage mining, usage patterns and its applications on web

logs.

6. To introduce various applications areas of web usage mining like personalized systems

and recommendation systems.

Unit-1: Data Mining Techniques and Algorithms

Data mining, Association Rule Mining, Supervised Learning: Classification & Prediction;

Unsupervised Learning: Cluster Analysis; Markov Models.

Unit-2: Foundation of Web Mining

Data mining and Web mining, Characteristics of Web Data, Web Data Model; Textual, Linkage

and Usage Expressions; Similarity Functions, Information Retrieval Performance Evaluation

Metrics, Web Mining Categories, Techniques and Applications.

Unit-3: Web Content Mining: Vector Space Model, Web Crawling, Web Search, Feature

Enrichment of Short Texts, Automatic Topic Extraction from Web Documents.

Unit-4: Web Structure Mining

Web Search and Hyperlinks, Co-citation and Biographic Coupling, Page Rank and HITS

Algorithm, Weighted Page Rank Algorithm, Web Graph Measurement and Modeling, Using

Link Information for Web Page Classification.

Unit-5: Web Usage Mining

Modeling Web User Interests, Discovery and Analysis of Web Usage Patterns, Bipartite Graph

Model, Clustering user sessions and web pages, Mining Web Logs to Improve Website

Organization, Clustering User Queries from Web Logs for Related Query.

Unit-6: Web Mining and Recommendation Systems

User based and Item based Collaborative Filtering Recommender Systems, Web Query

Recommendations.

Course Outcomes

a. The students will be able to understand basic concepts of data mining, supervised and

unsupervised learning techniques, association rule discovery, clustering, classification

and prediction techniques.

b. The students will be able to understand Web mining in detail and how its different from

data mining.

c. The students will be able to understand Web data models, various similarity functions

and performance measures.

d. The students will be able to understand types of web mining viz. content, structure and

usage mining.

e. The students will be able to understand Web content mining in detail, vector space model

and applications on the web.

f. The students will understand Web structure mining, concept of web graph and

applications in ranking web pages.

g. The students will understand Web usage mining, Bipartite Graph Model and applications

on web Logs to Improve Website Organization.

h. Students will understand applications of web mining to build various web based systems.


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REFERENCES

1. Web Mining and social Networking: Techniques and Applications- Guandong Xu, Yanchung

Zhang, Lin Li, Springer Book Series 2011.

2. Web Data Mining- Bling Liu, Springer Book Series.

M.TECH COMPUTER ENGINEERING (OPEN ELECTIVE)

CODE: OEC-2

SUBJECT NAME: CYBER LAWS AND SECURITY

NO OF CREDITS: 3


L P THEORY EXAM: 60

4 0 TOTAL: 100



UNIT-I History of Information Systems and its Importance, basics, Changing Nature of Information

Systems, Need of Distributed Information Systems, Role of Internet and Web Services,

Information System Threats and attacks, Classification of Threats and Assessing Damages

Security in Mobile and Wireless Computing- Security Challenges in Mobile Devices,

authentication Service Security, Security Implication for organizations, Laptops Security Basic

Principles of Information Security, Confidentiality, Integrity Availability and other terms in

Information Security, Information Classification and their Roles.

UNIT-II

Security Threats to E Commerce, Virtual Organization, Business Transactions on Web, E

Governance and EDI, Concepts in Electronics payment systems, E Cash, Credit/Debit Cards.

Physical Security- Needs, Disaster and Controls, Basic Tenets of Physical Security and Physical

Entry Controls, Access Control- Biometrics, Factors in Biometrics Systems, Benefits, Criteria

for selection of biometrics, Design Issues in Biometric Systems, Interoperability Issues,

Economic and Social Aspects, Legal Challenges

UNIT-III

Model of Cryptographic Systems, Issues in Documents Security, System of Keys, Public Key

Cryptography, Digital Signature, Requirement of Digital Signature System, Finger Prints,

Firewalls, Design and Implementation Issues, Policies Network Security- Basic Concepts,

Dimensions, Perimeter for Network Protection, Network Attacks, Need of Intrusion Monitoring

and Detection, Intrusion Detection Virtual Private Networks- Need, Use of Tunneling with VPN,

Authentication Mechanisms, Types of VPNs and their Usage, Security Concerns in VPN

UNIT-IV

Security metrics- Classification and their benefits Information Security & Law, IPR, Patent

Law, Copyright Law, Legal Issues in Data mIning Security, Building Security into Software Life

Cycle Ethics- Ethical Issues, Issues in Data and Software Privacy Cyber Crime Types &

overview of Cyber Crimes

REFERENCES

1. Godbole,“ Information Systems Security”, Willey

2. Merkov, Breithaupt, “ Information Security”, Pearson Education

3. Yadav, “Foundations of Information Technology”, New Age, Delhi

4. Schou, Shoemaker, “ Information Assurance for the Enterprise”, Tata McGraw Hill

5. Sood,“Cyber Laws Simplified”, Mc Graw Hill

6. Furnell, “Computer Insecurity”, Springer 7. IT Act 2000


OEC-4

SUBJECT NAME: WEB TECHNOLOGY & INFORMATION RETREIVAL

NO OF CREDITS: 3


L P THEORY EXAM: 60

4 0 TOTAL: 100



Unit 1 Web Server Technology

Web’s Robot global access to information, HTML, HTTP, Accessing a web server, publishing

on web server, secure HTTP, Secure Sockets Layer, WWW Proxies, IIS, Case study of apache

web server.

Unit 2 Web search basics

Background and history,Anatomy of WWW, Web characteristics, Spam, The web graph, The

Web Search Users, search engines, architecture of search engines, search tools, DNS resolution,

The URL frontier, Link analysis, PageRank,

UNIT 3 Web Crawlers

Basics of Web crawling, Various crawling techniques , incremental crawler, parallel crawler,

distributed crawlers, focused crawler, agent based crawler, Hidden web Crawler

Unit 4 Introduction to Information Retrieval


Boolean model versus ranked retrieval, an inverted index, Bi-word indexes, Positional indexes,

Combination schemes

Unit 5 Index construction

Hardware basics, Blocked sort-based indexing, Single-pass in-memory indexing, Distributed

indexing, Dynamic indexing, Other types of indexes Index compression: Statistical properties of

terms in information retrieval, Heaps’ law: Estimating the number of terms, Zipf’s law:

Modeling the distribution of terms, Dictionary compression, Dictionary as a string, Blocked

storage, Postings file compression.


CODE: OEC-5

SUBJECT NAME: INTELLECTUAL PROPERTY RIGHTS

NO OF CREDITS: 3


L P THEORY EXAM: 60

4 0 TOTAL: 100



UNIT 1: Introduction to Intellectual Property

Concept of Intellectual Property, Kinds of Intellectual Property, Economic Importance of

Intellectual Property, Indian Theory on Private Property: Constitutional Aspects of Property,

Constitutional Protection of Property and Intellectual Property, Economic Development and

Intellectual Property Rights Protection

UNIT II: Introduction to Patents

Overview, Historical Development, Concepts: Novelty, Utility, Patentable Subject-matter:

Patent Act, 1970- Amendments of 1999, 2000, 2002 and 2005, Pharmaceutical Products and

Process and Patent , Protection, Software Patents, Business Method, Protection of Plant Varieties

and Farmers’ Rights Act, 2001, Patenting of Micro-organism

UNIT III: Procedure of Obtaining of Patents

Concepts of a Patent Application,, Specification: Provisional, Complete, Disclosure Aspects,

Claims: Principal, Dependant, Omnibus, Examination of Application, Opposition of

Application, Sealing of Patents

UNIT IV: Working of Patents – Compulsory License

Commercialization of Inventions: License- Terms of License Agreement, Assignments of

Patents, Revocation of Patents

UNIT V: Infringement

What is Infringement?How is Infringement determined? Who is an Infringer?, Direct,

Contributory and Induced, Defences of Infringement:Research Exemption, Invalidity, Misuse,

Failure to mark, Laches and Estoppel and first sale doctrine

REFERENCES

1. W.R. Cornish, Intellectual Property, Sweet & Maxwell, London (2000)

2. P. Narayana, Patent Law, Wadhwa Publication

3. Merges, Patent Law and Policy: Cases and Materials, 1996

4. Brian C. Reid, A Practical Guide to Patent Law, 2nd Edition, 1993

5. Brinkhof (Edited), Patent Cases, Wolters Kluwer.

6. Prof. Willem Hoyng & Frank Eijsvogels, Global Patent Litigation, Strategy and

Practice, Wolters Kluwer.

7. Gregory Stobbs, Software Patents Worldwide, Wolters Kluwer.

8. Feroz Ali Khader, The Law of Patents- With a special focus on Pharmaceuticals in

India, Lexis Nexis Butterworths Wadhwa, Nagpur.

9. Sookman, Computer Law, 1996

10. N.S. Gopalakrishnan & T.G. Agitha, Principles of Intellectual Property (2009). Eastern Book

Company, Lucknow.