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28-01-2011, 01:59 PM
Post: #1
DISTRIBUTED COMPUTING SYSTEM ppt.



.ppt  DISTRIBUTED COMPUTING ).ppt (Size: 99.5 KB / Downloads: 284)

Presented By
Shrilatha suvarna B.(4nm03mca75



INTRODUCTION
Computer architectures consisting of interconnected, multiple processors are basically of two types:

1). Tightly coupled system

2). Loosely coupled system

Tightly coupled systems
In these systems, there is a single system wide primary memory (address space) that is shared by all the processors . Usually tightly coupled systems are referred to as parallel processing systems.

Loosely coupled systems
In these systems, the processors do not share memory, and each processor has its own local memory .Loosely coupled systems are referred to as distributed computing systems, or simply distributed systems

DEFINITION
A distributed computing system is basically a collection of processors interconnected by a communication network in which each processor has its own local memory and other peripherals, and the communication between any two processors of the system takes place by message passing over the communication network

Advantages Of Distributed Computing System
Inherently Distributed applications:
several applications are inherently distributed in nature and require distributed computing system for their realization

Information Sharing among Distributed Users:
In a distributed computing system, information generated by one of the users can be easily and efficiently shared by the users working at other nodes of the system .The use of distributed computing systems by a group of users to work cooperatively is known as computer-supported cooperative working (CSCW), or groupware .

Resource Sharing:
Information is not the only thing that can be shared in a distributed computing system. Sharing of software resources such as software libraries and databases as well as hardware resources such as printers, hard disks, and plotters can also be done in a very effective way among all the computers and the users of a single distributed computing system.

Extensibility and Incremental Growth:
It is possible to gradually extend the power and functionality of a distributed computing system by simply adding additional resources (both hardware and software) to the system as and when the need arises . Incremental growth is very attractive feature because for most existing and proposed applications it is practically impossible to predict future demands of the system. Extensibility is also easier in a distributed computing system because addition of new resources to an existing system can be performed without significant disruption of the normal functioning of the system.

Shorter Response Times and Higher Throughput:
The multiple processors of the distributed computing system can be utilized properly for providing shorter response times and higher throughput than a single processor centralized system. Another method often used in distributed computing systems for achieving better overall performance is to distribute the load more evenly among the multiple processors by moving the jobs from currently overloaded processors to lightly loaded ones


Higher Reliability:
Reliability refers to the degree of tolerance against errors and component failures in a system. A reliable system prevents loss of information even in the event of component failures An important aspect of reliability is availability, which refers to the fraction of time for which a system is available for use.

Better Flexibility in Meeting User’s Needs:
Performing different types of computers are usually more suitable for different types of computation. A distributed computing system may have a pool of different types of computers, in which case the most appropriate one can be selected for processing a user’s job depending on the nature of the job.

Better Price-Performance Ratio:
With the rapidly increasing power and reduction in prize of the microprocessors, combined with the increasing speed of communication network, distributed computing systems potentially have a much better price performance ratio than a single large centralized system. More cost-effective Then the centralized system is that they facilitate resource sharing among multiple computers

CONCLUSION
Despite the increased complexity and the difficulty of building distributed computing systems, the installation and the use of distributed computing systems are rapidly increasing. This is mainly because the advantages of distributed computing systems overcome their disadvantages.


21-03-2011, 09:37 AM
Post: #2
RE: DISTRIBUTED COMPUTING SYSTEM ppt.
Presented By
Prashanth U B


.ppt  DISTRIBUTED_COMPUTING_11.ppt (Size: 372.5 KB / Downloads: 112)
INTRODUCTION
Computer architectures consisting of interconnected, multiple processors are basically of two types:
1). Tightly coupled system
2). Loosely coupled system
 Tightly coupled systems
In these systems, there is a single system wide primary memory (address space) that is shared by all the processors . Usually tightly coupled systems are referred to as parallel processing systems.
 Loosely coupled systems
 In these systems, the processors do not share memory, and each processor has its own local memory .Loosely coupled systems are referred to as distributed computing systems, or simply distributed systems
DEFINITION
A distributed computing system is basically a collection of processors interconnected by a communication network in which each processor has its own local memory and other peripherals, and the communication between any two processors of the system takes place by message passing over the communication network
 Models Used In Distributed Computing System
1) Minicomputer Model:
 2) Workstation model:
 3)Workstation-Server Model:
 Processor-Pool model :
 Hybrid Model:
Advantages Of Distributed Computing System
 Inherently Distributed applications:
several applications are inherently distributed in nature and require distributed computing system for their realization
 Information Sharing among Distributed Users:
In a distributed computing system, information generated by one of the users can be easily and efficiently shared by the users working at other nodes of the system .The use of distributed computing systems by a group of users to work cooperatively is known as computer-supported cooperative working (CSCW), or groupware
Resource Sharing:
Information is not the only thing that can be shared in a distributed computing system. Sharing of software resources such as software libraries and databases as well as hardware resources such as printers, hard disks, and plotters can also be done in a very effective way among all the computers and the users of a single distributed computing system.
Extensibility and Incremental Growth:
It is possible to gradually extend the power and functionality of a distributed computing system by simply adding additional resources (both hardware and software) to the system as and when the need arises . Incremental growth is very attractive feature because for most existing and proposed applications it is practically impossible to predict future demands of the system. Extensibility is also easier in a distributed computing system because addition of new resources to an existing system can be performed without significant disruption of the normal functioning of the system.
Shorter Response Times and Higher Throughput:
The multiple processors of the distributed computing system can be utilized properly for providing shorter response times and higher throughput than a single processor centralized system. Another method often used in distributed computing systems for achieving better overall performance is to distribute the load more evenly among the multiple processors by moving the jobs from currently overloaded processors to lightly loaded ones
Higher Reliability:
Reliability refers to the degree of tolerance against errors and component failures in a system. A reliable system prevents loss of information even in the event of component failures An important aspect of reliability is availability, which refers to the fraction of time for which a system is available for use.
Better Flexibility in Meeting User’s Needs:
Performing different types of computers are usually more suitable for different types of computation. A distributed computing system may have a pool of different types of computers, in which case the most appropriate one can be selected for processing a user’s job depending on the nature of the job.
Better Price-Performance Ratio:
With the rapidly increasing power and reduction in prize of the microprocessors, combined with the increasing speed of communication network, distributed computing systems potentially have a much better price performance ratio than a single large centralized system. More cost-effective Then the centralized system is that they facilitate resource sharing among multiple computers
CONCLUSION
Despite the increased complexity and the difficulty of building distributed computing systems, the installation and the use of distributed computing systems are rapidly increasing. This is mainly because the advantages of distributed computing systems overcome their disadvantages.
21-04-2012, 05:06 PM
Post: #3
RE: DISTRIBUTED COMPUTING SYSTEM ppt.
Distributed Computing Systems


.ppt  Week 1 -- Remote Procedure Call.ppt (Size: 360 KB / Downloads: 116)


Remote Procedure Call (RPC)

Fundamental idea: –

Server process exports an interface of procedures or functions that can be called by client programs
similar to library API, class definitions, etc.

Clients make local procedure/function calls

As if directly linked with the server process
Under the covers, procedure/function call is converted into a message exchange with remote server process

Result

The hard work of building messages, formatting, uniform representation, etc., is buried in the stubs
Where it can be automated!
Client and server designers can concentrate on the semantics of application
Programs behave in familiar way


RPC Model

A server defines the service interface using an interface definition language (IDL)
the IDL specifies the names, parameters, and types for all client-callable server procedures

A stub compiler reads the IDL declarations and produces two stub functions for each server function

Marshalling Arguments

Marshalling is the packing of function parameters into a message packet
the RPC stubs call type-specific functions to marshal or unmarshal the parameters of an RPC
Client stub marshals the arguments into a message
Server stub unmarshals the arguments and uses them to invoke the service function
on return:
the server stub marshals return values
the client stub unmarshals return values, and returns to the client program
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