distributed processing applications

8/10/2019 Distributed Processing Applications

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Introduction

Categories

Motivation

ArchitectureCommercial Applications

Examples of Applications

Issues and challenges

Advantages and Disadvantages Various Research Papers

Conclusion


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Definition

Distributed computing utilizes a network of manycomputers, each accomplishing a portion of anoverall task, to achieve a computational result

much more quickly than with a single computer. A distributed system is one in which hardware or

software components located at networkedcomputers communicate and coordinate theiractions only by message passing.

In the term distributed computing, the worddistributed means spread out across space. Thus,distributed computing is an activity performedon a spatially distributed system.


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Various applications of distributive processing are used in the

following fields :

Science

Life Sciences

Cryptography Internet

Financial

Mathematics

Language

Art

Puzzles/Games

Miscellaneous

Distributed Human Project

Collaborative Knowledge Bases


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The main motivations in moving to a distributed system are the following:

Inherently distributed applications. Distributed systems have come intoexistence in some very natural ways, e.g., in our society people aredistributed and information should also be distributed. Distributeddatabase system information is generated at different branch offices(subdatabases), so that a local access can be done quickly. The systemalso provides a global view to support various global operations.

Performance/cost. The parallelism of distributed systems reduces

processing bottlenecks and provides improved all-around performance,i.e., distributed systems offer a better price/performance ratio.

Resource sharing. Distributed systems can efficiently upport informationand resource (hardware and software) sharing for users at differentlocations.

Flexibility and extensibility. Distributed systems are capable ofincremental growth and have the added advantage of facilitatingmodification or extension of a system to adapt to a changing environmentwithout disrupting its operations.

Availability and fault tolerance. With the multiplicity of storage units andprocessing elements, distributed systems have the potential ability tocontinue operation in the presence of failures in the system.

Scalability. Distributed systems can be easily scaled to include additional

resources (both hardware and software).


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Following architectures are realized using distributiveprocessing:

Client-server:

Smart client code contacts the server for data, thenformats and displays it to the user. Input at the client iscommitted back to the server when it represents apermanent change.

3-tier architecture:

Three tier systems move the client intelligence to a middle

tier so that stateless clients can be used. This simplifies

application deployment. Most web applications are 3-Tier.

N-tier architecture:

N-Tier refers typically to web applications which further

forward their requests to other enterprise services. This

type of application is the one most responsible for the

success of application servers.


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Tight coupling (Clustered) :

Tightly coupled architecture refers typically to a cluster of

machines that closely work together, running a shared

process in parallel. The task is subdivided in parts that aremade individually by each one and then put back together

to make the final result.

Peer-to-peer :

Peer-to-peer is an architecture where there is no special

machine or machines that provide a service or manage thenetwork resources. Instead all responsibilities are

uniformly divided among all machines, known as peers.

Peers can serve both as clients and servers.

Space based :

Space based refers to an infrastructure that creates the

illusion (virtualization) of one single address-space. Data

are transparently replicated according to application

needs. Decoupling in time, space and reference is

achieved.


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Database Management System

Distributed computing using mobile agents

Local intranet Internet (World Wide Web)

JAVA Remote Method Invocation (RMI)


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Local Intranet

A portion of Internet that is separately administered &

supports internal sharing of resources (file/storage systems

and printers) is called local intranet.


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JAVA RMI Embedded in language Java:-

Object variant of remote procedure call

Adds naming compared with RPC (Remote Procedure Call)

Restricted to Java environments

RMI Architecture


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Internet Gomez Distributed PEER Client

(peerReview)

Evaluate the performance of large websites to

find bottlenecks.

Life Sciences - Compute AgainstCancer(CAC)

Create immediate impact in the lives of cancer

patients and their families today, while at the

same time empowering the research that will

result in improved therapies and perhaps even

the cure.


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Collaborative Knowledge Bases Wikipedia A collaborative project to produce a complete

a free encyclopedia from scratch. The encyclopedia is available in many non-

English languages.

Distributed Human Projects- Open Mind IndoorCommon Sense

Help teach indoor mobile robots to be

smarter. It will create a repository ofknowledge which will enable people tocreate more intelligent mobile robots foruse in home and office environments.


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Heterogeneity of components :- variety or differences that apply to computer

hardware, network, OS, programming language andimplementations by different developers.

All differences in representation must be deal with ifto do message exchange.

Example : different call for exchange message in UNIXdifferent from Windows.

Openness:- System can be extended and re-implemented in

various ways.

Cannot be achieved unless the specification and

documentation are made available to softwaredeveloper.

The most challenge to designer is to tackle thecomplexity of distributed system; design by differentpeople.


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Security:-

Security for information resources in distributed

system have 3 components :

a. Confidentiality : protection against disclosure tounauthorized individuals.

b. Integrity : protection against alteration/corruption

c. Availability : protection against interference with themeans to access the resources.

The challenge is to send sensitive information

over Internet in a secure manner and to identify

a remote user or other agent correctly.


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Scalability :-

Distributed computing operates at many

different scales, ranging from small Intranet to

Internet.

A system is scalable if there is significant

increase in the number of resources and users.

The challenges is :

a. controlling the cost of physical resources.

b. controlling the performance loss.

c. preventing software resource running out.

d. avoiding performance bottlenecks.


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Failure Handling :- Failures in a distributed system are partial

some components fail while others can function.

Thats why handling the failures are difficulta. Detecting failures : to manage the presence offailures cannot be detected but may be suspected.

b. Masking failures : hiding failure not guaranteed in theworst case.

Concurrency :- Where applications/services process concurrency,

it will effect a conflict in operations with oneanother and produce inconsistence results.

Each resource must be designed to be safe in aconcurrent environment.


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Network problem:-

If the network underlying a distributed system saturates

or goes down, then the distributed system will be

effectively disabled thus negating most of the

advantages of the distributed system. Security:-

Security is a major hazard since easy access to data

means easy access to secret data as well.


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Distributed Computing research issues in Grid

Computing by Henri Casanova:This paper discusses the major issues raised

by grid computing in the field of distributed

computing. It takes into account the various

shortcomings of the previous research donein the field of distributed processing when

applied to grid computing. The scalable and

timely propagation of dynamic information

concerning both application data and gridresources in grid computing requires a

scalable event based interaction which is

difficult even for distributed systems.


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Distributed computing in mobile environment

by Apekshit and Chandrakant Sharma:

This paper considers central issues of

distributed computing in a mobileenvironment(i.e., cellular and ad hoc

networks ,peer to peer systems, mobile

virtual reality and cooperative robotics. Its

aim is to light on the first brick of a commonview for mobile systems.

It proposes a distributed algorithm for

solving the h out of k mutual exclusion

problem (also known as resource allocution

problem) for ad hoc mobile networks.


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The concept of distributed computing is the most

efficient way to achieve the optimization.

Distributed computing is anywhere : intranet,

Internet or mobile ubiquitous computing (laptop,

PDAs, pagers, smart watches, hi-fi systems)

It deals with hardware and software systems, thatcontain more than one processing / storage and

run in concurrently.

Main motivation factor is resource sharing; such as

files , printers, web pages or database records.

Grid computing and cloud computing are form of

distributed computing.

distributed processing applications

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