parallel computing

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M. TECH. (PARALLEL COMPUTING)-R13 Regulations

JAWAHARLAL NEHRU TECHNOLOGICAL UNIVERSITY HYDERABAD

(Established by an Act No.30 of 2008 of A.P. State Legislature) Kukatpally, Hyderabad – 500 085, Andhra Pradesh (India)

M. TECH. (PARALLEL COMPUTING)

(R13) COURSE STRUCTURE AND SYLLABUS I Year - I Semester

Code Group Subject L T/P/D C Advanced Data Structures and

Algorithms 3 0 3

Parallel Algorithms 3 0 3 Parallel Computer Architecture 3 0 3 Distributed Systems 3 0 3 Elective -I Web Services

Semantic Web and Social Networks Java & Web Technologies

3 0 3

Elective -II Wireless Networks and Mobile Computing Information Retrieval Systems Neural Networks

3 0 3

Lab Parallel Algorithms Lab 0 3 2 Seminar - - 2 Total 18 3 22

I Year II Semester Code Group Subject L T/P/D C Distributed Databases 3 0 3 Grid and Cloud Computing 3 0 3 Adhoc and Sensor Networks 3 0 3 Information Security 3 0 3 Elective -III Machine Learning

Pattern Recognition Data Mining

3 0 3

Elective -IV Storage Area Networks Advanced Computer Networks Pervasive Computing

3 0 3

Lab Grid Computing Lab 0 3 2 Seminar - - 2 Total 18 3 22

II Year I Semester Code Group Subject L T/P/D C Comprehensive Viva - - 2 Project Seminar 0 3 2 Project Work - - 18 Total - 3 22

II Year II Semester Code Group Subject L T/P/D C Project Work and Seminar - - 22 Total - - 22

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JAWAHARLAL NEHRU TECHNOLOGICAL UNIVERSITY HYDERABAD M. Tech – I Year – I Sem. (Parallel Computing)

ADVANCED DATA STRUCTURES AND ALGORITHMS Objectives:

The fundamental design, analysis, and implementation of basic data structures. Basic concepts in the specification and analysis of programs. Principles for good program design, especially the uses of data abstraction. Significance of algorithms in the computer field Various aspects of algorithm development Qualities of a good solution

UNIT I Algorithms, Performance analysis- time complexity and space complexity, Asymptotic Notation-Big Oh, Omega and Theta notations, Complexity Analysis Examples. Data structures-Linear and non linear data structures, ADT concept, Linear List ADT, Array representation, Linked representation, Vector representation, singly linked lists -insertion, deletion, search operations, doubly linked lists-insertion, deletion operations, circular lists. Representation of single, two dimensional arrays, Sparse matrices and their representation. UNIT II Stack and Queue ADTs, array and linked list representations, infix to postfix conversion using stack, implementation of recursion, Circular queue-insertion and deletion, Dequeue ADT, array and linked list representations, Priority queue ADT, implementation using Heaps, Insertion into a Max Heap, Deletion from a Max Heap, java.util package-ArrayList, LinkedList, Vector classes, .Stacks and Queues in java.util,Iterators in java.util. UNIT III Searching–Linear and binary search methods, Hashing-Hash functions, Collision Resolution methods-Open Addressing, Chaining, Hashing in java.util-HashMap, HashSet, Hashtable . Sorting –Bubble sort, Insertion sort, Quick sort, Merge sort, Heap sort, Radix sort, comparison of sorting methods. UNIT IV Trees- Ordinary and Binary trees terminology, Properties of Binary trees, Binary tree ADT , representations, recursive and non recursive traversals, Java code for traversals, Threaded binary trees. Graphs- Graphs terminology, Graph ADT, representations, graph traversals/search methods-DFS and BFS, Java code for graph traversals, Applications of Graphs-Minimum cost spanning tree using Kruskal’s algorithm, Dijkstra’s algorithm for Single Source Shortest Path Problem. UNIT V Search trees- Binary search tree-Binary search tree ADT ,insertion, deletion and searching operations, Balanced search trees, AVL trees-Definition and examples only, Red Black trees –Definition and examples only, B-Trees-definition, insertion and searching operations, Trees in java.util-TreeSet, TreeMap Classes, Tries(examples only),Comparison of Search trees. Text compression-Huffman coding and decoding, Pattern matching-KMP algorithm. TEXT BOOKS: 1. Data structures, Algorithms and Applications in Java, S.Sahni, Universities Press. 2. Data structures and Algorithms in Java, Adam Drozdek,3rd edition, Cengage learning. 3. Data structures and Algorithm Analysis in Java, M.A. Weiss, 2nd edition, Addison-Wesley

(Pearson Education).

REFERENCE BOOKS: 1 Java for Programmers, Deitel and Deitel, Pearson education. 2. Data structures and Algorithms in Java, R.Lafore, Pearson education. 3 Java: The Complete Reference, 8th editon, Herbert Schildt, TMH.

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4 Data structures and Algorithms in Java, M.T.Goodrich, R.Tomassia, 3rd edition, Wiley India Edition.

5 Data structures and the Java Collection Frame work, W.J.Collins, Mc Graw Hill. 6 Classic Data structures in Java, T.Budd, Addison-Wesley(Pearson Education). 7 Data structures with Java, Ford and Topp, Pearson Education. 8 Data structures using Java, D.S.Malik and P.S.Nair, Cengage learning. 9 Data structures with Java, J.R.Hubbard and A.Huray, PHI Pvt. Ltd. 10 Data structures and Software Development in an Object-Oriented Domain, 11 J.P.Tremblay and G.A.Cheston, Java edition, Pearson Education.

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PARALLEL ALGORITHMS Objectives:

To learn parallel and distributed algorithms development techniques for shared memory and message passing models.

To study the main classes of parallel algorithms. To study the complexity and correctness models for parallel algorithms.

UNIT-I Sequential model, need of alternative model, parallel computational models such as PRAM, LMCC, Hypercube, Cube Connected Cycle, Butterfly, Perfect Shuffle Computers, Tree model, Pyramid model, Fully Connected model, PRAM-CREW, EREW models, simulation of one model from another one. UNIT-II Performance Measures of Parallel Algorithms, speed-up and efficiency of PA, Cost optimality, Example to illustrate Cost-optimal algorithms- such as summation, Min/Max on various models. UNIT-III Parallel Sorting Networks, Parallel Merging Algorithms on CREW/EREW/MCC/, Parallel Sorting Networks on CREW/EREW/MCC/, linear array UNIT-IV Parallel Searching Algorithm, Kth element, Kth element in X+Y on PRAM, Parallel Matrix Transportation and Multiplication Algorithm on PRAM, MCC, Vector-Matrix Multiplication, Solution of Linear Equation, Root finding. UNIT-V Graph Algorithms - Connected Graphs, search and traversal, Combinatorial Algorithms- Permutation, Combinations, Derangements. TEXTBOOK: 1. M.J. Quinn, “Designing Efficient Algorithms for Parallel Computer” by Mc Graw Hill. REFERENCE BOOKS: 1. Algorithms, K.A.Berman and J.L.Paul, Cengage Learning. 2. Distributed Algorithms, N.A.Lynch, Morgan Kaufmann Publishers, Elsevier. 3. Parallel Algorithms, Henri Casanova, A.Legrand, Y.Robert, Chapman &Hall/CRC, Taylor and

Francis Group. 4. Handbook of Parallel Computing, S.Rajasekaran, John Reif, Chapman & Hall/CRC,Taylor and

Francis Group.

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PARALLEL COMPUTER ARCHITECTURE Objectives:

To identify the differences between scalar, superscalar and vector processing and their Architectures.

To explain the meaning of Pipeline processing and describe pipeline processing Architectures.

To describe architectures based on associative memory organizations. To explain the concept of multithreading and its use in parallel computer architecture.

UNIT-I Parallel Computer Architecture: Trends, Convergence of Parallel Architecture, Fundamental Design Issues Programming for Performance: Partitioning for Performance, Data Access and Communication in a Multi memory System, Implications for Programming Models. UNIT-II Shared Memory Multiprocessors: Cache Coherence, Memory Consistency, Design Space for Snooping Protocols, Assessing Protocol Design Trade-offs, Synchronization, Implications for Software. UNIT-III Snoop-Based Multiprocessor Design: Correctness Requirements, Multilevel Cache Hierarchies, Split-Transaction Bus, Case Studies: SGI Challenge and Sun Enterprise 6000, Extending Cache Coherence. Directory – Based Cache Coherence: Scalable Cache Coherence, Overview of Directory Based approaches, Assessing Directory Protocols and Trade-Offs, Design Challenges for Directory Protocols, Memory-Based Directory Protocols: The SGI Origin System, Cache-Based Directory Protocols: The Sequent NUMA-Q, Performance Parameters and Protocol Performance, Synchronization, Implications for Parallel Software, Advanced Topics. UNIT-IV Hardware / Software Trade-Offs: Relaxed Memory Consistency Models, Overcoming Capacity Limitations, Reducing Hardware Cost, Putting It All Together: A Taxonomy and simple COMA, Implications for Parallel Software, Advanced Topics. Interconnection Network Design: Basic Definitions, Basic Communication Performance, Organizational Structure, Interconnection Topologies, Evaluating Design Trade-Offs in Network Topology, Routing, Switch Design, Flow Control, Case Studies. UNIT-V Latency Tolerance: Overview of Latency Tolerance, Latency Tolerance in Explicit Message Passing, Latency Tolerance in a Shared Address Space, Block Data Transfer in a Shared Address Space, Proceeding past Long-Latency Events, Precommunication in a Shared Address Space, Multithreading in a Shared Address Space, Lockup-Free Cache Design. Future Directions: Technology and Architecture, Applications and System Software. TEXT BOOKS: 1. Id E Culler, Jaswinder Pal Singh and Anoop Gupta “ Parallel Computer Architecture”, Mogan

Kaufman, Elsevier Science, India ,2002 2. Kai Hwang, Advanced Computer Architecture, Mc Graw Hill, 1999. 3. John L. Hennessy & David A Patterson, Computer Architecture A Quantitative Approach, Morgan

Kaufmann Publishers, Inc, 1996. REFERENCE BOOK:

1. Parallel Computer Architecture: A Hardware/Software Approach, David E. Culler, Jaswider Pal Singh, Anoop Gupta, Gulf Professional Publishing.

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DISTRIBUTED SYSTEMS Objectives:

To explain what a distributed system is, why you would design a system as a distributed system, and what the desired properties of such systems are;

To list the principles underlying the functioning of distributed systems, describe the problems and challenges associated with these principles, and evaluate the effectiveness and shortcomings of their solutions;

To recognize how the principles are applied in contemporary distributed systems, explain how they affect the software design, and be able to identify features and design decisions that may cause problems;

To design a distributed system that fulfills requirements with regards to key distributed systems properties (such as scalability, transparency, etc.), be able to recognize when this is not possible, and explain why;

To build distributed system software using both basic OS mechanisms as well as higher-level middleware and languages.

UNIT I Characterization of Distributed Systems-Introduction, Examples of Distributed systems, Resource sharing and web, challenges, System models-Introduction, Architectural and Fundamental models, Networking and Internetworking, Interprocess Communication, Distributed objects and Remote Invocation-Introduction, Communication between distributed objects, RPC, Events and notifications, Case study-Java RMI. UNIT II Operating System Support- Introduction, OS layer, Protection, Processes and Threads, Communication and Invocation, Operating system architecture, Distributed File Systems-Introduction, File Service architecture, case study- SUN network file systems. Name Services-Introduction, Name Services and the Domain Name System, Case study of the Global Name Service, Case study of the X.500 Directory Service. UNIT III Peer to Peer Systems–Introduction, Napster and its legacy, Peer to Peer middleware, Routing overlays, Overlay case studies-Pastry, Tapestry, Application case studies-Squirrel, Ocean Store. Time and Global States-Introduction, Clocks, events and Process states, Synchronizing physical clocks, logical time and logical clocks, global states, distributed debugging. Coordination and Agreement-Introduction, Distributed mutual exclusion, Elections, Multicast communication, consensus and related problems. UNIT IV Transactions and Concurrency control-Introduction, Transactions, Nested Transactions, Locks, Optimistic concurrency control, Timestamp ordering, Comparison of methods for concurrency control, Distributed Transactions-Introduction, Flat and Nested Distributed Transactions, Atomic commit protocols, Concurrency control in distributed transactions, Distributed deadlocks, Transaction recovery, Replication-Introduction, System model and group communication, Fault tolerant services, Transactions with replicated data. UNIT V Security-Introduction, Overview of Security techniques, Cryptographic algorithms, Digital signatures, Case studies-Kerberos,TLS,802.11 Wi-Fi. Distributed shared memory, Design and Implementation issues, Sequential consistency and Ivy case study, Release consistency and Munin case study, Other consistency models, CORBA case study-Introduction, CORBA RMI, CORBA Services. TEXT BOOKS: Distributed Systems Concepts and Design, G Coulouris, J Dollimore and T Kindberg, Fourth

Edition, Pearson Education.

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Distributed Systems, S.Ghosh, Chapman &Hall/CRC, Taylor & Francis Group, 2010. REFERENCE BOOKS: Distributed Computing, S.Mahajan and S.Shah, Oxford University Press. Distributed Operating Systems Concepts and Design, Pradeep K.Sinha, PHI. Advanced Concepts in Operating Systems, M Singhal, N G Shivarathri, TMH. Reliable Distributed Systems, K.P.Birman, Springer. Distributed Systems – Principles and Paradigms, A.S. Tanenbaum and M.V. Steen,

Pearson Education. Distributed Operating Systems and Algorithm Analysis, R.Chow, T.Johnson, Pearson. Distributed Operating Systems, A.S.Tanenbaum, Pearson education. Distributed Computing, Principles, Algorithms and Systems, Ajay D.Kshemakalyani

and Mukesh Singhal, Cambridge, rp 2010.

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WEB SERVICES

(ELECTIVE-I) Objectives:

To Understand paradigms needed for testing Web Services To explore different Test Strategies for SOA-based applications To implement functional testing, compliance testing and load testing of Web Services To Identify bug-finding ideas in testing Web Services

UNIT I Evolution and Emergence of Web Services - Evolution of distributed computing, Core distributed computing technologies – client/server, CORBA, JAVA RMI, Micro Soft DCOM, MOM, Challenges in Distributed Computing, role of J2EE and XML in distributed computing, emergence of Web Services and Service Oriented Architecture (SOA). UNIT II Introduction to Web Services – The definition of web services, basic operational model of web services, tools and technologies enabling web services, benefits and challenges of using web services - Web Services Architecture – Web services Architecture and its characteristics, core building blocks of web services, standards and technologies available for implementing web services, web services communication, basic steps of implementing web services, developing web services enabled applications. UNIT III Core fundamentals of SOAP – SOAP Message Structure, SOAP encoding, SOAP message exchange models, SOAP communication and messaging, SOAP security - Developing Web Services using SOAP – Building SOAP Web Services, developing SOAP Web Services using Java, limitations of SOAP. UNIT IV Describing Web Services – WSDL – WSDL in the world of Web Services, Web Services life cycle, anatomy of WSDL definition document, WSDL bindings, WSDL Tools, limitations of WSDL - Discovering Web Services – Service discovery, role of service discovery in a SOA, service discovery mechanisms, UDDI – UDDI Registries, uses of UDDI Registry, Programming with UDDI, UDDI data structures, support for categorization in UDDI Registries, Publishing API, Publishing information to a UDDI Registry, searching information in a UDDI Registry, deleting information in a UDDI Registry, limitations of UDDI. UNIT V Web Services Interoperability – Means of ensuring Interoperability, Overview of .NET and J2EE. Web Services Security – XML security frame work, XML encryption, XML digital signature, XKMS structure, guidelines for signing XML documents. TEXT BOOKS: 1. Developing Java Web Services, R. Nagappan, R. Skoczylas, R.P. Sriganesh, Wiley India, rp –

2008. 2. Developing Enterprise Web Services, S. Chatterjee, J. Webber, Pearson Education, 2008. 3. XML, Web Services, and the Data Revolution, F.P.Coyle, Pearson Education. REFERENCE BOOKS: 1. Building Web Services with Java, 2nd Edition, S. Graham and others, Pearson Edn., 2008. 2. Java Web Services, D.A. Chappell & T. Jewell, O’Reilly,SPD. 3. McGovern, et al., “Java Web Services Architecture”, Morgan Kaufmann Publishers,2005. 4. J2EE Web Services, Richard Monson-Haefel, Pearson Education. 5. Web Services, G. Alonso, F. Casati and others, Springer, 2005.

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SEMANTIC WEB AND SOCIAL NETWORKS (ELECTIVE-I)

Objectives: To learn Web Intelligence To learn Knowledge Representation for the Semantic Web To learn Ontology Engineering To learn Semantic Web Applications, Services and Technology To learn Social Network Analysis and semantic web

UNIT I Web Intelligence Thinking and Intelligent Web Applications, The Information Age ,The World Wide Web, Limitations of Today’s Web, The Next Generation Web, Machine Intelligence, Artificial Intelligence, Ontology, Inference engines, Software Agents, Berners-Lee www, Semantic Road Map, Logic on the semantic Web. UNIT II Knowledge Representation for the Semantic Web Ontologies and their role in the semantic web, Ontologies Languages for the Semantic Web –ResourceDescriptionFramework(RDF)/RDFSchema,OntologyWebLanguage(OWL),UML, XML/XML Schema. UNIT III Ontology Engineering Ontology Engineering, Constructing Ontology, Ontology Development Tools, Ontology Methods, Ontology Sharing and Merging, Ontology Libraries and Ontology Mapping, Logic, Rule and Inference Engines. UNIT IV Semantic Web Applications, Services and Technology Semantic Web applications and services, Semantic Search, e-learning, Semantic Bioinformatics, Knowledge Base ,XML Based Web Services, Creating an OWL-S Ontology for Web Services, Semantic Search Technology, Web Search Agents and Semantic Methods, UNIT V Social Network Analysis and semantic web What is social Networks analysis, development of the social networks analysis, Electronic Sources for Network Analysis – Electronic Discussion networks, Blogs and Online Communities, Web Based Networks. Building Semantic Web Applications with social network features. TEXT BOOKS: 1. Thinking on the Web - Berners Lee, Godel and Turing, Wiley interscience,2008. 2. Social Networks and the Semantic Web ,Peter Mika,Springer,2007. REFERENCE BOOKS: 1. Semantic Web Technologies, Trends and Research in Ontology Based Systems, J.Davies,

R.Studer, P.Warren, John Wiley & Sons. 2. Semantic Web and Semantic Web Services -Liyang Lu Chapman and Hall/CRC Publishers,(Taylor

& Francis Group) 3. Information Sharing on the semantic Web - Heiner Stuckenschmidt; Frank Van Harmelen,

Springer Publications. 4. Programming the Semantic Web,T.Segaran, C.Evans, J.Taylor, O’Reilly,SPD.

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JAVA & WEB TECHNOLOGIES (ELECTIVE-I)

Objectives: To learn the basics of java Console and GUI based programming To introduce XML and processing of XML Data with Java To introduce Server side programming with Java Servlets and JSP To introduce Client side scripting with JavaScript and AJAX. UNIT I HTML Common tags- List, Tables, images, forms, Frames; Cascading Style sheets; Introduction to Java Scripts, Objects in Java Script, Dynamic HTML with Java Script, CSS UNIT II XML: Document type definition, XML Schemas, Document Object model, Presenting XML, Using XML Processors: DOM and SAX Review of Applets, Class, Event Handling, AWT Programming. Introduction to Swing: JApplet, Handling Swing Controls like Icons – Labels – Buttons – Text Boxes – Combo – Boxes – Tabbed Pains – Scroll Pains – Trees – Tables Differences between AWT Controls & Swing Controls Developing a Home page using Applet & Swing. UNIT III Java Beans: Introduction to Java Beans, Advantages of Java Beans, BDK Introspection, Using Bound properties, Bean Info Interface, Constrained properties Persistence, Customizes, Java Beans API. Web servers: Tomcat Server installation & Testing. Introduction to Servelets: Lifecycle of a Serverlet, JSDK The Servelet API, The javax.servelet Package, Reading Servelet parameters, Reading Initialization parameters. UNIT IV More on Servlets: The javax.servelet HTTP package, Handling Http Request & Responses, Using Cookies-Session Tracking, Security Issues. Introduction to JSP: The Problem with Servelet. The Anatomy of a JSP Page, JSP Processing. JSP Application Design with MVC architecture. AJAX. UNIT V JSP Application Development: Generating Dynamic Content, Using Scripting Elements Implicit JSP Objects, Conditional Processing – Displaying Values Using an Expression to Set an Attribute, Declaring Variables and Methods Error Handling and Debugging Sharing Data Between JSP pages, Requests, and Users Passing Control and Date between Pages – Sharing Session and Application Data – Memory Usage Considerations Database Access Database Programming using JDBC Studying Javax.sql.* package Accessing a Database from a JSP Page Application – Specific Database Actions Deploying JAVA Beans in a JSP Page TEXT BOOKS: 1. Web Programming, building internet applications, Chris Bates 2nd edition, WILEY Dreamtech (UNIT

1, 2) 2. The complete Reference Java 2 Fifth Edition, Patrick Naughton and Herbert Schildt., TMH

(Chapters: 25) (UNIT 2,3) 3. Java Server Pages –Hans Bergsten, SPD O’Reilly (UNITs 3,4,5) REFERENCE BOOKS: 1. Programming world wide web-Sebesta, Pearson 2. Core SERVLETS ANDJAVASERVER PAGES VOLUME 1: CORE TECHNOLOGIES, Marty Hall

and Larry Brown Pearson 3. Internet and World Wide Web – How to program, Dietel and Nieto PHI/Pearson.

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4. Jakarta Struts Cookbook, Bill Siggelkow, S P D O’Reilly for chap 8. 5. Murach’s beginning JAVA JDK 5, Murach, SPD 6. An Introduction to web Design and Programming –Wang-Thomson 7. Professional Java Server Programming, S.Allamaraju and others Apress(dreamtech). 8. Java Server Programming ,Ivan Bayross and others, The X Team, SPD 9. Web Warrior Guide to Web Programmming-Bai/Ekedaw-Thomas 10. Beginning Web Programming-Jon Duckett WROX. 11. Java Server Pages, Pekowsky, Pearson. 12. Java Script, D.Flanagan, O’Reilly,SPD.

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WIRELESS NETWORKS AND MOBILE COMPUTING (ELECTIVE – II)

Objectives: To understand GSM and UMTS architectures To have an in-depth knowledge of mobile computing To understand Mobile network layer and transport layer To understand Bluetooth technology

UNIT I WIRELESS NETWORKS: Wireless Network, Wireless Network Architecture, Wireless Switching Technology, Wireless Communication problem, Wireless Network Reference Model, Wireless Networking Issues & Standards. MOBILE COMPUTING: Mobile communication, Mobile computing, Mobile Computing Architecture, Mobile Devices, Mobile System Networks, Mobility Management UNIT II WIRELESS LAN: Infra red Vs radio transmission, Infrastructure and Ad-hoc Network, IEEE 802.11: System Architecture, Protocol Architecture, 802.11b, 802.11a, Newer Developments, HIPERLAN 1, HIPERLAN 2, Bluetooth : User Scenarios, Architecture. UNIT III GLOBAL SYSTEM FOR MOBILE COMMUNICATIONS (GSM): Mobile Services, System Architecture, Protocols, Localization & Calling, Handover, Security. GPRS: GPRS System Architecture, UMTS: UMTS System Architecture. LTE: Long Term Evolution UNIT IV MOBILE NETWORK LAYER: Mobile IP: Goals, Assumptions, Entities and Terminology, IP Packet Delivery, Agent Discovery, Registration, Tunneling and Encapsulation, Optimizations, Dynamic Host Configuration Protocol (DHCP) UNIT V MOBILE TRANSPORT LAYER: Traditional TCP, Indirect TCP, Snooping TCP, Mobile TCP, Fast retransmit/fast recovery, Transmission /time-out freezing, Selective retransmission, Transaction oriented TCP, TCP over 2.5G/3G Wireless Networks. TEXT BOOKS:

1. Jochen Schiller, “Mobile Communications”, Pearson Education, Second Edition, 2008. 2. Dr. Sunilkumar, et al “Wireless and Mobile Networks: Concepts and Protocols”, Wiley India. 3. Raj Kamal, “Mobile Computing”, OXFORD UNIVERSITY PRESS.

REFERENCES BOOKS:

1. Asoke K Talukder, et al, “Mobile Computing”, Tata McGraw Hill, 2008. 2. Matthew S.Gast, “802.11 Wireless Networks”, SPD O’REILLY. 3. Ivan Stojmenovic, “Handbook of Wireless Networks and Mobile Computing”, Wiley, 2007. 4. Kumkum Garg, “Mobile Computing”, Pearson. 5. Handbook of Security of Networks, Yang Xiao, Frank H Li, Hui Chen, World Scientific,

2011.

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INFORMATION RETRIEVAL SYSTEMS (ELECTIVE- II)

Objectives: To use different information retrieval techniques in various application areas To apply IR principles to locate relevant information large collections of data To analyze performance of retrieval systems when dealing with unmanaged data sources To implement retrieval systems for web search tasks.

UNIT I Boolean retrieval. The term vocabulary and postings lists. Dictionaries and tolerant retrieval. Index construction. Index compression. UNIT II Scoring, term weighting and the vector space model. Computing scores in a complete search system. Evaluation in information retrieval. Relevance feedback and query expansion. UNIT III XML retrieval. Probabilistic information retrieval. Language models for information retrieval. Text classification. Vector space classification. UNIT IV Support vector machines and machine learning on documents. Flat clustering. Hierarchical clustering. Matrix decompositions and latent semantic indexing. UNIT V Web search basics. Web crawling and indexes. Link analysis. TEXT BOOK:

1. Introduction to Information Retrieval , Christopher D. Manning and Prabhakar Raghavan and Hinrich Schütze, Cambridge University Press, 2008.

REFERENCE BOOKS:

1. Information Storage and Retrieval Systems: Theory and Implementation, Kowalski, Gerald, Mark T Maybury, Springer.

2. Modern Information Retrieval, Ricardo Baeza-Yates, Pearson Education, 2007. 3. Information Retrieval: Algorithms and Heuristics, David A Grossman and Ophir Frieder, 2nd

Edition, Springer, 2004. 4. Information Retrieval Data Structures and Algorithms, William B Frakes, Ricardo Baeza-

Yates, Pearson Education, 1992. 5. Information Storage & Retrieval, Robert Korfhage , John Wiley & Sons.

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NEURAL NETWORKS

(ELECTIVE- II) Objectives:

To survey of attractive applications of artificial neural networks. To practical approach for using artificial neural networks in various technical, organizational

and economic applications. ‘UNIT I INTRODUCTION - What is a neural network? Human Brain, Models of a Neuron, Neural networks viewed as Directed Graphs, Network Architectures, Knowledge Representation, Artificial Intelligence and Neural Networks (p. no’s 1 –49) LEARNING PROCESS – Error Correction learning, Memory based learning, Hebbian learning UNIT II Competitive, Boltzmann learning, Credit Assignment Problem, Memory, Adaption, Statistical nature of the learning process, (p. no’s 50 –116) SINGLE LAYER PERCEPTRONS – Adaptive filtering problem, Unconstrained Organization Techniques, Linear least square filters, least mean square algorithm, learning curves, Learning rate annealing techniques, perceptron –convergence theorem, Relation between perceptron and Bayes classifier for a Gaussian Environment (p. no’s 117 –155) UNIT III MULTILAYER PERCEPTRON – Back propagation algorithm XOR problem, Heuristics, Output representation and decision rule, Comuter experiment, feature detection, (p. no’s 156 –201) BACK PROPAGATION - back propagation and differentiation, Hessian matrix, Generalization, Cross validation, Network pruning Techniques, Virtues and limitations of back propagation learning, Accelerated convergence, supervised learning. (p. no’s 202 –234) UNIT IV SELF ORGANIZATION MAPS – Two basic feature mapping models, Self organization map, SOM algorithm, properties of feature map, computer simulations, learning vector quantization, Adaptive patter classification, Hierechel Vector quantilizer, contexmel Maps (p. no’s 443 –469, 9.1 –9.8 ) UNIT V NEURO DYNAMICS – Dynamical systems, stavility of equilibrium states, attractors, neurodynamical models, manipulation of attarctors as a recurrent network paradigm (p. no’s 664 –680, 14.1 –14.6) HOPFIELD MODELS – Hopfield models, computer experiment I (p. no’s 680-701, 14.7 –14.8) TEXT BOOK: 1. Neural networks A comprehensive foundations, Simon Haykin, Pearson Education 2nd Edition 2004 REFERENCE BOOKS: 1. Artificial neural networks - B.Yegnanarayana, Prentice Hall, 2005 2. Neural networks in Computer intelligence, Li Min Fu, TMH 2003 3. Neural networks, James A Freeman David M S Kapura, Pearson Education 2004

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PARALLEL ALGORITHMS LAB Objectives:

To implement the various tree structures. To design and implement the parameter study problem. To implement the RPC concepts.

1. Bridge Construction: Develop a program to create two tasks, foundry and bridge, and connects them

with a channel. The channel should be used to communicate stream of integer values 1. .100 from foundry to bridge, followed by the value --I to signal termination.

2. Search (I): Develop a program that uses processor objects and the par construct to implement a prototypical tree-structured computation. The program should explore a binary tree recursively creating a task (processor object + thread) for each tree node and returning the total number of leaf nodes that represent solutions. In the program, the tree is not represented by an explicit data structure; instead, a process's position in the tree is represented by an integer.

3. Extend the above program to allow for non binary trees: that is, trees with an arbitrary number of subtrees rooted at each node.

4. Design and construct a C, C++ implementation of the manager/worker structure used in the parameter study problem.

5. Design and construct a decentralized version of the manager/worker structure, developed above. Design and carry out experiments to determine when each version is more efficient.

6. Channel Communication: Global pointers and sync variables can be used to implement a variety of communication mechanisms. Use these constructs to implement a simple shared queue class. This class can be used to implement channel communication between two concurrently executing producer and consumer tasks: we simply allocate a queue object and provide both tasks with pointers to this object.

7. Design and implement a program that can be used to quantify CC ++ processor object and thread creation costs, both within the same processor and on remote processors. Conduct experiments to measure these costs, and obtain estimates for t1 and t2 .

8. Modify the program developed above to use spawn to implement the RPC used for a send operation, and conduct experiments to compare the performance of the two versions.

9. Search (II): Define a global Mapping object and initialize at the beginning of main to contain the names of the processors on which the program is to execute. These names are read from a file. Provide a constructor for the processor object class Tree that copies the Mapping object to each new processor object as it is created. One of the processor object allocation should call in the search function is augmented with a "call to random_p, which returns a proc_t structure on a randomly selected processor.

10. Coupled Climate Model: Implement a coupled climate modeling system comprising I an ocean model and an atmosphere model which can be structured as ct parallel. Composition of the two component models, in which each model executes on one half of P processors as described in the text book.

II. Finite Difference: We apply the two approaches to the SPMD finite difference .computation used to illustrate sequential composition. This computation may be structured as a sequence of calls to a finite difference routine that performs nearest- neighbor communication and a reduction routine used to detect termination; the latter routine may perform global communication.

12. Implement and instrument the channel library and use this code to measure CC++ .communication costs on various parallel computers.

13. Extend the channel library to allow polling for pending messages. 14. Extend the channel library to provide a merger that allows multiple senders on a channel. 15. Develop a program to provide a 2-D decomposition of principal data structures. 16. Implement a hypercube communication template. Use this template to implement simple reduction,

vector reduction, and broadcast algorithms. 17. Construct a CC++ imp1ementation of the tuple space module. Use this module to implement the

database search problem described in that section. REFERENCE BOOK:

1. Introduction to Parallel algorithms by Jaja from Pearson, 1992.

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JAWAHARLAL NEHRU TECHNOLOGICAL UNIVERSITY HYDERABAD M. Tech – I Year – II Sem. (Parallel Computing)

DISTRIBUTED DATABASES Objectives:

To implement the Distributed databases management system concepts. To enforcing Integrity Constraints to keep the database consistent Normalizing the tables to eliminate redundancies Querying relational data Optimizing and processing the queries Storage Strategies for easy retrieval of data through index

UNIT I Features of Distributed versus Centralized Databases, Principles of Distributed Databases, Levels Of Distribution Transparency, Reference Architecture for Distributed Databases, Types of Data Fragmentation, Integrity Constraints in Distributed Databases, Distributed Database Design. UNIT II Translation of Global Queries to Fragment Queries, Equivalence transformations for Queries, Transforming Global Queries into Fragment Queries, Distributed Grouping and Aggregate Function Evaluation, Parametric Queries. Optimization of Access Strategies, A Framework for Query Optimization, Join Queries, General Queries. UNIT III The Management of Distributed Transactions, A Framework for Transaction Management, Supporting Atomicity of Distributed Transactions, Concurrency Control for Distributed Transactions, Architectural Aspects of Distributed Transactions Concurrency Control, Foundation of Distributed Concurrency Control, Distributed Deadlocks, Concurrency Control based on Timestamps, Optimistic Methods for Distributed Concurrency Control. UNIT IV Reliability, Basic Concepts, Nonblocking Commitment Protocols, Reliability and concurrency Control, Determining a Consistent View of the Network, Detection and Resolution of Inconsistency, Checkpoints and Cold Restart, Distributed Database Administration, Catalog Management in Distributed Databases, Authorization and Protection UNIT V Architectural Issues, Alternative Client/Server Architectures, Cache Consistency, Object Management, Object Identifier Management, Pointer Swizzling, Object Migration, Distributed Object Storage, Object Query Processing, Object Query Processor Architectures, Query Processing Issues, Query Execution, Transaction Management, Transaction Management in Object DBMSs, Transactions as Objects Database Integration, Scheme Translation, Scheme Integration, Query Processing Query Processing Layers in Distributed Multi-DBMSs, Query Optimization Issues Transaction Management Transaction and Computation Model, Multidatabase Concurrency Control, Multidatabase Recovery, Object Orientation and Interoperability, Object Management Architecture CORBA and Database interoperability, Distributed Component Object Model, COM/OLE and Database Interoperability, PUSH-Based Technologies TEXT BOOKS:

1. Distributed Databases Principles & Systems, Stefano Ceri, Giuseppe Pelagatti, TMH. 2. Principles of Distributed Database Systems, M. Tamer Ozsu, Patrick Valduriez , Pearson

Education, 2nd Edition. REFERENCE BOOKS:

1. Distributed database systems by Chhanda Ray from Pearson Education, 2009 2. Principles of Distributed database systems by Tamer and Ozsu from Pearson, 2006.

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GRID AND CLOUD COMPUTING Objectives:

To implement Basics, techniques and tools for Grid & Cloud Computing. To understand any kind of heterogeneous resources over a network using open standards To implement the service models.

UNIT-I System models for advanced computing –clusters of cooperative computing, grid computing and cloud computing; software systems for advanced computing-service oriented software and parallel and distributed programming models with introductory details, Features of grid and cloud platform. UNIT-II Cloud Computing services models and features in Saas , Paas and Iaas. Service oriented architecture and web services; Features of cloud computing architectures and simple case studies. UNIT-III Virtualization- Characteristic features, Taxonomy Hypervisor, Virtualization and Cloud Computing, Pros and Cons of Cloud Computing, Technology Examples/Case Studies. UNIT-IV Cloud programming Environmental- Map Reduce Hadoop Library from Apache, Open Source Cloud Software Systems –Eucalyptus. UNIT-V Grid Architecture and Service modeling, Grid resource management, Grid Application trends. TEXT BOOKS:

1. Distributed and Cloud Computing, Kaittwang Geoffrey C.Fox and Jack J Dongrra, Elsevier India 2012.

2. Mastering Cloud Computing- Raj Kumar Buyya, Christian Vecchiola and S.Tanurai Selvi, TMH, 2012.

REFERENCE BOOKS:

1. Cloud Computing, John W. Ritting House and James F Ramsome, CRC Press, 2012. 2. Enterprise Cloud Computing, Gautam Shroff , Cambridge University Press,2012.

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ADHOC AND SENSOR NETWORKS Objectives:

To understand the concepts of sensor networks To understand the MAC and transport protocols for adhoc networks To understand the security of sensor networks To understand the applications of adhoc and sensor networks

UNIT I Ad Hoc Wireless Networks Introduction, Issues in Ad hoc wireless networks, Ad hoc wireless Internet MAC protocols for Ad hoc Wireless Networks Issues in Designing a MAC Protocol for Ad hoc Wireless Networks, Design Goals for a MAC Protocol for Ad hoc Wireless Networks, Classifications of the MAC Protocols, Other MAC Protocols. UNIT II Routing Protocols for Ad Hoc Wireless Networks Issues in Designing a Routing Protocol for Ad hoc Wireless Networks, Classifications of Routing Protocols Transport Layer for Ad Hoc Wireless Networks Issues in Designing a Transport layer protocol for Ad hoc Wireless Networks, Design goals of a Transport layer protocol for Ad hoc Wireless Networks, Classification of Transport layer solutions, TCP over Ad hoc Wireless Networks, Other Transport layer protocols for Ad hoc Wireless Networks. UNIT III Security protocols for Ad hoc Wireless Networks Security in Ad hoc Wireless Networks, Network Security Requirements, Issues and Challenges in Security Provisioning, Network Security Attacks, Key Management, Secure Routing in Ad hoc Wireless Networks UNIT IV Basics of Wireless, Sensors and Applications: The Mica Mote, Sensing and Communication Range, Design Issues, Energy consumption, Clustering of Sensors, Applications Data Retrieval in Sensor Networks: Classification of WSNs, MAC layer, Routing layer, Transport layer, High-level application layer support, Adapting to the inherent dynamic nature of WSNs. UNIT V Sensor Network Hardware: Components of Sensor Mote, Operating System in Sensors– TinyOS, LA-TinyOS, SOS, RETOS Imperative Language: nesC, Dataflow style language: TinyGALS, Node-Level Simulators, ns-2 and its sensor network extension, TOSSIM TEXT BOOKS:

1. Adhoc Wireless Networks – Architectures and Protocols, C.Siva Ram Murthy, B.S.Murthy, Pearson Education, 2004

2. Ad Hoc and Sensor Networks – Theory and Applications, Carlos Corderio Dharma P. \Aggarwal, World Scientific Publications / Cambridge University Press, March 2006

3. Wireless Sensor Networks – Principles and Practice, Fei Hu, Xiaojun Cao, An Auerbach book, CRC Press, Taylor & Francis Group, 2010

REFERENCE BOOKS:

1. Wireless Sensor Networks: An Information Processing Approach, Feng Zhao, Leonidas Guibas, Elsevier Science imprint, Morgan Kauffman Publishers, 2005, rp2009

2. Wireless Ad hoc Mobile Wireless Networks – Principles, Protocols and Applications, Subir Kumar Sarkar, et al., Auerbach Publications, Taylor & Francis Group, 2008.

3. Ad hoc Networking, Charles E.Perkins, Pearson Education, 2001. 4. Wireless Ad hoc Networking, Shih-Lin Wu, Yu-Chee Tseng, Auerbach Publications, Taylor &

Francis Group, 2007

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5. Wireless Ad hoc and Sensor Networks – Protocols, Performance and Control, Jagannathan Sarangapani, CRC Press, Taylor & Francis Group, 2007, rp 2010.

6. Security in Ad hoc and Sensor Networks, Raheem Beyah, et al., World Scientific Publications / Cambridge University Press, , 2010

7. Ad hoc Wireless Networks – A communication-theoretic perspective, Ozan K.Tonguz, Gialuigi Ferrari, Wiley India, 2006, rp2009.

8. Wireless Sensor Networks – Signal processing and communications perspectives, Ananthram Swami, et al., Wiley India, 2007, rp2009.

9. Handbook on Sensor Networks – Yang Xiao, Hui Chen & Frank Haizhon Li, World Scientific, 2010.

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INFORMATION SECURITY Objectives:

To learn Security Issues in Mobile Communication To learn Application Level Security in Cellular Networks, MANETs To learn Application Level Security in Ubiquitous networks To learn Security for mobile commerce applications

UNIT – I Security Issues in Mobile Communication: Mobile Communication History, Security – Wired Vs Wireless, Security Issues in Wireless and Mobile Communications, Security Requirements in Wireless and Mobile Communications, Security for Mobile Applications, Advantages and Disadvantages of Application – level Security UNIT – II Security of Device, Network, and Server Levels: Mobile Devices Security Requirements, Mobile Wireless network level Security, Server Level Security, Application Level Security in Wireless Networks: Application of WLANs, Wireless Threats, Some Vulnerabilities and Attach Methods over WLANs, Security for 1g Wi-Fi Applications, Security for 2g Wi-Fi Applications, Recent Security Schemes for Wi-Fi Applications UNIT – III Application Level Security in Cellular Networks: Generations of Cellular Networks, Security Issues and attacks in cellular networks, GSM Security for applications, GPRS Security for applications, UMTS security for applications, 3G security for applications, Some of Security and authentication Solutions, Application Level Security in MANETs: MANETs, Some applications of MANETs, MANET Features, Security Challenges in MANETs, Security Attacks on MANETs, External Threats for MANET applications, Internal threats for MANET Applications, Some of the Security Solutions UNIT – IV Application Level Security in Ubiquitous networks: Ubiquitous Computing, Need for Novel Security Schemes for UC, Security Challenges for UC, Security Attacks on UC networks, Some of the security solutions for UC, Application Level Security in Heterogeneous wireless networks: Introduction, Some of the Heterogeneous wireless network architectures, Heterogeneous network application in Disaster management, Security problems and attacks in heterogeneous wireless networks, Some security solutions for heterogeneous wireless networks UNIT - V Security for mobile commerce applications: M-Commerce Applications, M-Commerce Initiatives, Security Challenges in mobile e-commerce, Types of attacks on mobile e-commerce, A Secure M-commerce model based on wireless local area network, Some of M-Commerce Security Solutions TEXT BOOKS:

1. Wireless & Mobile Network Security: Pallapa Venkataram, Satish Babu, TMH, 2010. 2. Fundamentals of Mobile and Pervasive Computing, Frank Adelstein, K.S.Gupta et al, TMH

2005. REFERENCE BOOKS:

1. Wireless Security Models, Threats and Solutions, Randall k. Nichols, Panos C. Lekkas, TMH, 2006.

2. 802.11 Security, Bruce Potter & Bob Fleck, SPD O’REILLY 2005. 3. Guide to Wireless Network Security, Springer. 4. Hacking Exposed Wireless: Johnny Cache, 2nd Edition, Joshua Wright, Vincent Lu,

Mc Graw Hill.

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MACHINE LEARNING (ELECTIVE – III)

Objectives: To be able to formulate machine learning problems corresponding to different applications. To understand a range of machine learning algorithms along with their strengths and

weaknesses. To understand the basic theory underlying machine learning. To be able to apply machine learning algorithms to solve problems of moderate complexity. To be able to read current research papers and understands the issues raised by current

research. UNIT I INTRODUCTION - Well-posed learning problems, designing a learning system, Perspectives and issues in machine learning Concept learning and the general to specific ordering – Introduction, A concept learning task, Concept learning as search, Find-S: finding a maximally specific hypothesis, Version spaces and the candidate elimination algorithm, Remarks on version spaces and candidate elimination, Inductive bias UNIT II Decision Tree learning – Introduction, Decision tree representation, Appropriate problems for decision tree learning, The basic decision tree learning algorithm, Hypothesis space search in decision tree learning, Inductive bias in decision tree learning, Issues in decision tree learning Artificial Neural Networks – Introduction, Neural network representation, Appropriate problems for neural network learning, Perceptions, Multilayer networks and the back propagation algorithm, Remarks on the back propagation algorithm, An illustrative example face recognition Advanced topics in artificial neural networks Evaluation Hypotheses – Motivation, Estimation hypothesis accuracy, Basics of sampling theory, A general approach for deriving confidence intervals, Difference in error of two hypotheses, Comparing learning algorithms UNIT III Bayesian learning – Introduction, Bayes theorem, Bayes theorem and concept learning, Maximum likelihood and least squared error hypotheses, Maximum likelihood hypotheses for predicting probabilities, Minimum description length principle, Bayes optimal classifier, Gibs algorithm, Naïve bayes classifier, An example learning to classify text, Bayesian belief networks The EM algorithm Computational learning theory – Introduction, Probability learning an approximately correct hypothesis, Sample complexity for Finite Hypothesis Space, Sample Complexity for infinite Hypothesis Spaces, The mistake bound model of learning - Instance-Based Learning- Introduction, k -Nearest Neighbor Learning, Locally Weighted Regression, Radial Basis Functions, Case-Based Reasoning, Remarks on Lazy and Eager Learning Genetic Algorithms – Motivation, Genetic Algorithms, An Illustrative Example, Hypothesis Space Search, Genetic Programming, Models of Evolution and Learning, Parallelizing Genetic Algorithms UNIT IV Learning Sets of Rules – Introduction, Sequential Covering Algorithms, Learning Rule Sets: Summary, Learning First Order Rules, Learning Sets of First Order Rules: FOIL, Induction as Inverted Deduction, Inverting Resolution Analytical Learning - Introduction, Learning with Perfect Domain Theories: Prolog-EBG Remarks on Explanation-Based Learning, Explanation-Based Learning of Search Control Knowledge UNIT V Combining Inductive and Analytical Learning – Motivation, Inductive-Analytical Approaches to Learning, Using Prior Knowledge to Initialize the Hypothesis, Using Prior Knowledge to Alter the Search Objective, Using Prior Knowledge to Augment Search Operators, Reinforcement Learning – Introduction, The Learning Task, Q Learning, Non-Deterministic, Rewards and Actions, Temporal Difference Learning, Generalizing from Examples, Relationship to Dynamic Programming

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TEXT BOOK: 1. Machine Learning – Tom M. Mitchell, - MGH

REFERENCE BOOK: 1. Machine Learning: An Algorithmic Perspective, Stephen Marsland, Taylor & Francis

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PATTERN RECOGNITION (ELECTIVE -III)

Objectives: To implement pattern recognition and machine learning theories To design and implement certain important pattern recognition techniques To apply the pattern recognition theories to applications of interest To implement the entropy minimization, clustering transformation and feature ordering

UNIT I INTRODUCTION - Basic concepts, Applications, Fundamental problems in pattern Recognition system design, Design concepts and methodologies, Examples of Automatic Pattern recognition systems, Simple pattern recognition model DECISION AND DISTANCE FUNCTIONS - Linear and generalized decision functions, Pattern space and weight space, Geometrical properties, implementations of decision functions, Minimum-distance pattern classifications. UNIT II PROBABILITY - Probability of events: Random variables, Joint distributions and densities, Movements of random variables, Estimation of parameter from samples. STATISTICAL DECISION MAKING - Introduction, Baye’s theorem, Multiple features, Conditionally independent features, Decision boundaries, Unequal cost of error, estimation of error rates, the leaving-one-out-techniques, characteristic curves, estimating the composition of populations. Baye’s classifier for normal patterns. UNIT III NON PARAMETRIC DECISION MAKING - Introduction, histogram, kernel and window estimation, nearest neighbour classification techniques. Adaptive decision boundaries, adaptive discriminant functions, Minimum squared error discriminant functions, choosing a decision making techniques. CLUSTERING AND PARTITIONING - Hierarchical Clustering: Introduction, agglomerative clustering algorithm, the single-linkage, complete-linkage and average-linkage algorithm. Ward’s method Partition clustering-Forg’s algorithm, K-means’s algorithm, Isodata algorithm. UNIT IV PATTERN PREPROCESSING AND FEATURE SELECTION: Introduction, distance measures, clustering transformation and feature ordering, clustering in feature selection through entropy minimization, features selection through orthogonal expansion, binary feature selection. UNIT V SYNTACTIC PATTERN RECOGNITION & APPLICATION OF PATTERN RECOGNITION Introduction, concepts from formal language theory, formulation of syntactic pattern recognition problem, syntactic pattern description, recognition grammars, automata as pattern recognizers, Application of pattern recognition techniques in bio-metric, facial recognition, IRIS scon, Finger prints, etc., TEXT BOOKS: 1. Gose. Johnsonbaugh. Jost. “ Pattern recognition and Image Analysis”, PHI. 2. Tou. Rafael. Gonzalez. “Pattern Recognition Principle”, Pearson Education

REFERENCE BOOK: 1. Richard duda, Hart. David Strok, “Pattern Classification”, John Wiley. 2. Digital Image Processing, M.Anji Reddy, Y.Hari Shankar, BS Publications.

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DATA MINING (ELECTIVE –III)

Objectives: To develop the abilities of critical analysis to data mining systems and applications. To implement practical and theoretical understanding of the technologies for data mining To understand the strengths and limitations of various data mining models

UNIT I Introduction: Fundamentals of data mining, Data Mining Functionalities, Classification of Data Mining systems, Data Mining Task Primitives, Integration of a Data Mining System with a Database or a Data Warehouse System, Major issues in Data Mining. Data Preprocessing: Need for Preprocessing the Data, Data Cleaning, Data Integration and Transformation, Data Reduction, Discretization and Concept Hierarchy Generation. UNIT II Mining Frequent Patterns, Associations and Correlations: Basic Concepts, Efficient and Scalable Frequent Item set Mining Methods, Mining various kinds of Association Rules, From Association Mining to Correlation Analysis, Constraint-Based Association Mining – UNIT III Classification and Prediction: Issues Regarding Classification and Prediction, Classification by Decision Tree Induction, Bayesian Classification, Rule-Based Classification, Classification by Back propagation, Support Vector Machines, Associative Classification, Lazy Learners, Other Classification Methods, Prediction, Accuracy and Error measures, Evaluating the accuracy of a Classifier or a Predictor, Ensemble Methods UNIT IV Cluster Analysis Introduction :Types of Data in Cluster Analysis, A Categorization of Major Clustering Methods, Partitioning Methods, Hierarchical Methods, Density-Based Methods, Grid-Based Methods, Model-Based Clustering Methods, Clustering High-Dimensional Data, Constraint-Based Cluster Analysis, Outlier Analysis - Mining Streams, Time Series and Sequence Data: Mining Data Streams, Mining Time-Series Data, Mining Sequence Patterns in Transactional Databases, Mining Sequence Patterns in Biological Data, Graph Mining, Social Network Analysis and Multirelational Data Mining: UNIT V Mining Object, Spatial, Multimedia, Text and Web Data: Multidimensional Analysis and Descriptive Mining of Complex Data Objects, Spatial Data Mining, Multimedia Data Mining, Text Mining, Mining the World Wide Web. - Applications and Trends in Data Mining: Data Mining Applications, Data Mining System Products and Research Prototypes, Additional Themes on Data Mining and Social Impacts of Data Mining. TEXT BOOKS: 1. Data Mining – Concepts and Techniques - Jiawei Han & Micheline Kamber, Morgan Kaufmann

Publishers, 2nd Edition, 2006. 2. Introduction to Data Mining – Pang-Ning Tan, Michael Steinbach and Vipin Kumar, Pearson

education. 3. Data Mining Techniques – Arun K Pujari, University Press REFERENCE BOOKS: 1. Data Warehousing in the Real World – Sam Aanhory & Dennis Murray Pearson Edn Asia. 2. Data Warehousing Fundamentals – Paulraj Ponnaiah Wiley student Edition 3. The Data Warehouse Life cycle Tool kit – Ralph Kimball Wiley student edition 4. Building the Data Warehouse by William H Inmon, John Wiley & Sons Inc, 2005. 5. Data Mining Introductory and advanced topics –Margaret H Dunham, Pearson education

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STORAGE AREA NETWORKS

(ELECTIVE-IV) Objectives:

To understand Storage Area Networks characteristics and components. To become familiar with the SAN vendors and their products To learn Fibre Channel protocols and how SAN components use them to communicate with

each other To become familiar with Cisco MDS 9000 Multilayer Directors and Fabric Switches

Thoroughly learn Cisco SAN-OS features. To understand the use of all SAN-OS commands. Practice variations of SANOS features

UNIT I: Introduction to Storage Technology Review data creation and the amount of data being created and understand the value of data to a business, challenges in data storage and data management, Solutions available for data storage, Core elements of a data center infrastructure, role of each element in supporting business activities UNIT II: Storage Systems Architecture Hardware and software components of the host environment, Key protocols and concepts used by each component ,Physical and logical components of a connectivity environment ,Major physical components of a disk drive and their function, logical constructs of a physical disk, access characteristics, and performance Implications, Concept of RAID and its components , Different RAID levels and their suitability for different application environments: RAID 0, RAID 1, RAID 3, RAID 4, RAID 5, RAID 0+1, RAID 1+0, RAID 6, Compare and contrast integrated and modular storage systems ,High-level architecture and working of an intelligent storage system UNIT III: Introduction to Networked Storage Evolution of networked storage, Architecture, components, and topologies of FC-SAN, NAS, and IP-SAN, Benefits of the different networked storage options, understand the need for long-term archiving solutions and describe how CAS fulfills the need, understand the appropriateness of the different networked storage options for different application environments UNIT IV: Information Availability & Monitoring & Managing Datacenter List reasons for planned/unplanned outages and the impact of downtime, Impact of downtime, Differentiate between business continuity (BC) and disaster recovery (DR) ,RTO and RPO, Identify single points of failure in a storage infrastructure and list solutions to mitigate these failures , Architecture of backup/recovery and the different backup/recovery topologies , replication technologies and their role in ensuring information availability and business continuity, Remote replication technologies and their role in providing disaster recovery and business continuity capabilities Identify key areas to monitor in a data center, Industry standards for data center monitoring and management, Key metrics to monitor for different components in a storage infrastructure, Key management tasks in a data center UNIT V: Securing Storage and Storage Virtualization Information security, Critical security attributes for information systems, Storage security domains, List and analyzes the common threats in each domain, Virtualization technologies, block-level and file-level virtualization technologies and processes Case Studies The technologies described in the course are reinforced with EMC examples of actual solutions. Realistic case studies enable the participant to design the most appropriate solution for given sets of criteria. TEXT BOOK: 1. EMC Corporation, Information Storage and Management, Wiley. REFERENCE BOOKS: 1. Robert Spalding, “Storage Networks: The Complete Reference“, Tata McGraw Hill, Osborne,

2003.

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2. Marc Farley, “Building Storage Networks”, Tata McGraw Hill ,Osborne, 2001. 3. Meeta Gupta, Storage Area Network Fundamentals, Pearson Education Limited, 2002.

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ADVANCED COMPUTER NETWORKS

(ELECTIVE-IV) Objectives:

The objective of this course is to build a solid foundation in computer networks concepts and design

To understand computer network architectures, protocols, and interfaces. The OSI reference model and the Internet architecture, Network applications. The course will expose students to the concepts of traditional as well as modern day computer

networks - wireless and mobile, multimedia-based. Students completing this course will understand the key concepts and practices employed in

modern computer networking Prerequisite: Computer Networks Course description: This course will enable the student to refresh the fundamentals of Computer Networks in Unit I. Unit II describes the architecture, components, and operation of routers, and explains the principles of Routing and Routing protocols. Especially the Routing protocols need to be understood thoroughly with the help of any freely downloadable simulator tool. Through Unit III a student can learn the technologies and protocols needed to design and implement a converged switched network. This section explains how to configure a switch for basic functionality and how to implement Virtual LANs, VTP, and Inter-VLAN routing in a converged network. Students need to develop the necessary skills to implement a WLAN in a small-to-medium network. This course in Unit IV discusses the WAN technologies and network services required by converged applications in enterprise networks. Unit V makes the student to implement networking using Java programs. Suggested Simulator tools: NS-2/NS-3, OPNET, Packet Tracer, Boson, Wireshark. UNIT I: Review Computer Networks and the Internet: History of Computer Networking and the Internet, Networking Devices, The Network edge, The Network core, Access Networks and Physical media, ISPs and Internet Backbones. Networking Models: 5-layer TCP/IP Model, 7-Layer OSI Model, Internet Protocols and Addressing, Equal-Sized Packets Model: ATM. UNIT II: Network Routing Routing and its concepts: Structure of a Router, Basic Router Configuration, Building a Routing Table, Static Routing, Dynamic Routing – Distance Vector Routing Protocol (RIPv1, RIPv2, EIGRP), Link State Routing Protocols (OSPF). UNIT III: LAN Switching Switching and its concepts: Structure of a Switch, Basic Switch Configuration, Virtual LANs (VLANs), VLAN Trunking Protocol (VTP), Spanning Tree Protocol (STP), Inter-VLAN Routing. UNIT IV: Wide Area Networks (WANs) Introduction to WANs, Point-to-Point Protocol (PPP) concepts, Frame Relay concepts, Dynamic Host Configuration Protocol (DHCP), Network Address Translation (NAT), IPv6. UNIT V: Network Programming using Java TCP sockets, UDP sockets (datagram sockets), Server programs that can handle one connection at a time and multiple connections (using multithreaded server), Remote Method Invocation (Java RMI) - Basic RMI Process, Implementation details - Client-Server Application. TEXT BOOKS:

Computer Networking: A Top-Down Approach Featuring the Internet, James F. Kurose, Keith W.Ross, Fifth Edition, Pearson Education, 2012.

Network Fundamentals, Mark Dye, Pearson Education. Routing Protocols & Concepts, Rick Graziani, Pearson Education.

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LAN Switching & Wireless, Wayne Lewis, Pearson Education. Accessing the WAN, Bob Vachon, Pearson Education. An Introduction to Network Programming with Java, Jan Graba, Springer, rp 2010.

REFERENCE BOOKS:

Computer Networks: A Systems approach, Larry L. Peterson & Bruce S. Davie, Fifth edition, Elsevier, rp2012.

Computer Networks: A Top-Down Approach, Behrouz A. Forouzan, Firoz Mosharaf, Tata McGraw Hill, 2012.

Java Network Programming,3rd edition, E.R. Harold, SPD, O’Reilly.(Unit V) An Engineering Approach to Computer Networking, S.Keshav, Pearson Education, 1997. Computer Networks: Principles, Technologies And Protocols For Network Design, Natalia Olifer,

Victor Olifer, Wiley India, 2006. Computer Networks, Andrew S. Tanenbaum, Fifth Edition, Prentice Hall. Computer and Communication Networks, Nader F. Mir, Pearson Education, 2007 Data Communications and Networking, Behrouz A. Forouzan, Fourth Edition, Tata McGraw Hill,

2007. Computer Networks, Bhushan Trivedi, Oxford University Press, 2011. Fundamentals of Business Data Communications, Jerry FitzGerald and Alan Dennis, Tenth

Edition, Wiley, 2009. Internetworking with TCP/IP: Principles, Protocols and Architecture, Volume 1, Douglas E.

Comer, 4th edition, PHI, 2005. Next-Generation Internet: Architectures and Protocols, Byrav Ramamurthy et al, Cambridge,

2011.

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PERVASIVE COMPUTING (ELECTIVE – IV)

Objectives: To discover the characteristics of pervasive computing applications including the basic

computing application problems, performance objectives and quality of services, major system components and architectures of the systems.

UNIT I Pervasive Computing Application - Pervasive Computing devices and Interfaces - Device technology trends, Connecting issues and protocols UNIT II Pervasive Computing and web based Applications - XML and its role in Pervasive Computing - Wireless Application Protocol (WAP) Architecture and Security – Wireless Mark-Up language (WML) – Introduction UNIT III Voice Enabling Pervasive Computing - Voice Standards - Speech Applications in Pervasive Computing and security UNIT IV PDA in Pervasive Computing – Introduction - PDA software Components, Standards, emerging trends - PDA Device characteristics - PDA Based Access Architecture UNIT V User Interface Issues in Pervasive Computing, Architecture - Smart Card- based Authentication Mechanisms - Wearable computing Architecture TEXT BOOKS: 1. Jochen Burkhardt, Horst Henn, Stefan Hepper, Thomas Schaec & Klaus Rindtorff. --- Pervasive

Computing Technology and Architecture of Mobile Internet Applications, Addision Wesley, Reading, 2002.

2. 2. Uwe Ha nsman, Lothat Merk, Martin S Nicklous & Thomas Stober: Principles of Mobile Computing, Second Edition, Springer- Verlag, New Delhi, 2003.

REFERENCE BOOKS: 1. Rahul Banerjee: Internetworking Technologies: An Engineering Perspective, Prentice –Hall of

India, New Delhi, 2003. (ISBN 81-203-2185-5) 2. Rahul Banerjee: Lecture Notes in Pervasive Computing, Outline Notes, BITS-Pilani, 2003.

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GRID COMPUTING LAB

1. Distributed algorithm for resources allocation (Networking) Description The objective of this experiment is to deploy and evaluate a distributed algorithm for dynamic network resources allocation. The aim is to explore the scalability and reliability issues of the proposed algorithm which is running on a real experimental platform (such as GRID 5000). Multiple software entities, responsible for exchanging control data, will be distributed over multiple nodes interconnected together via high speed network. Tools used JAVA 2. Simulation of Chord with SimGrid (Networking) Description Large-scale simulation of the Chord peer-to-peer algorithm with SimGrid. Tools used SimGrid 3. HPC performance modeling (Networking) Description In these experiments we continue investigating performance model for HPC-based network such as Infini-Band. Tools :OpenMPI . Parallelization Using MPI There are a number of parallel software environments that allow users to use the networked computers as a unified computing resource, e.g. PVM (Parallel Virtual Machine), MPI (Message Passing Interface) and so on. MPI is a set of specifications that has become a de-factor standard in mes-sage passing protocol 5. Play Ping-Pong using 2 processors on the SMA Hydra Cluster Write a short program to estimate the message latency ts and reciprocal of the bandwidth tc for SMA Hydra Cluster. 6. Parallel your code for calculating the value of PI using Monte Carlo Method from Computational Lab1. This question will focus on the parallelization of the sequential code what you have written in the computational lab1 to evaluate PI number using Monte Carlo method. 7. Write simple Java programs (clients) for accessing the functionality of grid services

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parallel computing

Documents

insertion sort

lab parallel algorithms

linked representation

data structureslinear

linear data structures

tpd c advanced data

heap sort

cloud computing