SlideShare a Scribd company logo
1 of 4
Q. Explain Distributed Computing System Models?

Distributed Computing System Models
Distributed Computing system models can be broadly classified
into five categories. They are
•

Minicomputer model

•

Workstation model

•

Workstation – server model

•

Processor – pool model

•

Hybrid model

Minicomputer Model
The minicomputer model is a simple extension of the centralized
time-sharing system. A distributed computing system based on
this model consists of a few minicomputers (they may be large
supercomputers as well) interconnected by a communication
network. Each minicomputer usually has multiple users
simultaneously logged on to it. For this, several interactive
terminals are connected to each minicomputer. Each user is
logged on to one specific minicomputer, with remote access to
other minicomputers. The network allows a user to access remote
resources that are available on some machine other than the one
on to which the user is currently logged. The minicomputer model
may be used when resource sharing (such as sharing of
information databases of different types, with each type of
database located on a different machine) with remote users is
desired. The early ARPAnet is an example of a distributed
computing system based on the minicomputer model.
Workstation Model
A distributed computing system based on the workstation model
consists of several workstations interconnected by a
communication network. An organization may have several
workstations located throughout a building or campus, each
workstation equipped with its own disk and serving as a singleuser computer. It has been often found that in such an
environment, at any one time a significant proportion of the
workstations are idle (not being used), resulting in the waste of
large amounts of CPU time. Therefore, the idea of the
workstation model is to interconnect all these workstations by a
high-speed LAN so that idle workstations may be used to process
jobs of users who are logged onto other workstations and do not
have sufficient processing power at their own workstations to get
their jobs processed efficiently.
Workstation – Server Model
The workstation model is a network of personal workstations,
each with its own disk and a local file system. A workstation with
its own local disk is usually called a diskful workstation and a
workstation without a local disk is called a diskless workstation.
With the proliferation of high-speed networks, diskless
workstations have become more popular in network
environments than diskful workstations, making the workstationserver model more popular than the workstation model for
building distributed computing systems.
A distributed computing system based on the workstation-server
model consists of a few minicomputers and several workstations
(most of which are diskless, but a few of which may be diskful)
interconnected by a communication network.
Note that when diskless workstations are used on a network, the
file system to be used by these workstations must be
implemented either by a diskful workstation or by a
minicomputer equipped with a disk for file storage. One or more
of the minicomputers are used for implementing the file system.
Other minicomputers may be used for providing other types of
services, such as database service and print service. Therefore,
each minicomputer is used as a server machine to provide one or
more types of services. Therefore in the workstation-server
model, in addition to the workstations, there are specialized
machines (may be specialized workstations) for running server
processes (called servers) for managing and providing access to
shared resources. For a number of reasons, such as higher
reliability and better scalability, multiple servers are often used
for managing the resources of a particular type in a distributed
computing system. For example, there may be multiple file
servers, each running on a separate minicomputer and
cooperating via the network, for managing the files of all the
users in the system. Due to this reason, a distinction is often
made between the services that are provided to clients and the
servers that provide them. That is, a service is an abstract entity
that is provided by one or more servers. For example, one or
more file servers may be used in a distributed computing system
to provide file service to the users.
In this model, a user logs onto a workstation called his or her
home workstation. Normal computation activities required by the
user's processes are performed at the user's home workstation,
but requests for services provided by special servers (such as a
file server or a database server) are sent to a server providing
that type of service that performs the user's requested activity
and returns the result of request processing to the user's
workstation. Therefore, in this model, the user's processes need
not migrated to the server machines for getting the work done by
those machines.
Processor – Pool Model
The processor-pool model is based on the observation that most
of the time a user does not need any computing power but once
in a while the user may need a very large amount of computing
power for a short time (e.g., when recompiling a program
consisting of a large number of files after changing a basic shared
declaration). Therefore, unlike the workstation-server model in
which a processor is allocated to each user, in the processor-pool
model the processors are pooled together to be shared by the
users as needed. The pool of processors consists of a large
number of microcomputers and minicomputers attached to the
network. Each processor in the pool has its own memory to load
and run a system program or an application program of the
distributed computing system
Hybrid Model
Out of the four models described above, the workstation-server
model, is the most widely used model for building distributed
computing systems. This is because a large number of computer
users only perform simple interactive tasks such as editing jobs,
sending electronic mails, and executing small programs. The
workstation-server model is ideal for such simple usage.
However, in a working environment that has groups of users who
often perform jobs needing massive computation, the processorpool model is more attractive and suitable.

More Related Content

What's hot

Centralized vs distrbution system
Centralized vs distrbution systemCentralized vs distrbution system
Centralized vs distrbution systemzirram
 
Operating system 20 threads
Operating system 20 threadsOperating system 20 threads
Operating system 20 threadsVaibhav Khanna
 
Load Balancing in Parallel and Distributed Database
Load Balancing in Parallel and Distributed DatabaseLoad Balancing in Parallel and Distributed Database
Load Balancing in Parallel and Distributed DatabaseMd. Shamsur Rahim
 
Distributed database
Distributed databaseDistributed database
Distributed databasesanjay joshi
 
Distributed Computing
Distributed Computing Distributed Computing
Distributed Computing DrisyaK3
 
distributed shared memory
 distributed shared memory distributed shared memory
distributed shared memoryAshish Kumar
 
Advantage of distributed database over centralized database
Advantage of distributed database over centralized databaseAdvantage of distributed database over centralized database
Advantage of distributed database over centralized databaseAadesh Shrestha
 
Distributed data base management system
Distributed data base management systemDistributed data base management system
Distributed data base management systemSonu Mamman
 
Clustering concepts
Clustering conceptsClustering concepts
Clustering conceptsHarish43
 
Distributed database system
Distributed database systemDistributed database system
Distributed database systemM. Ahmad Mahmood
 
MySQL real-time replication configuration
MySQL real-time replication configurationMySQL real-time replication configuration
MySQL real-time replication configurationkelechi Anyanwu
 
Distributed computing
Distributed computingDistributed computing
Distributed computingshivli0769
 

What's hot (20)

Desktop and multiprocessor systems
Desktop and multiprocessor systemsDesktop and multiprocessor systems
Desktop and multiprocessor systems
 
Centralized vs distrbution system
Centralized vs distrbution systemCentralized vs distrbution system
Centralized vs distrbution system
 
Database System Architectures
Database System ArchitecturesDatabase System Architectures
Database System Architectures
 
Operating system 20 threads
Operating system 20 threadsOperating system 20 threads
Operating system 20 threads
 
Multi threading models
Multi threading modelsMulti threading models
Multi threading models
 
Load Balancing in Parallel and Distributed Database
Load Balancing in Parallel and Distributed DatabaseLoad Balancing in Parallel and Distributed Database
Load Balancing in Parallel and Distributed Database
 
Distributed database
Distributed databaseDistributed database
Distributed database
 
Lecture 4 Cluster Computing
Lecture 4 Cluster ComputingLecture 4 Cluster Computing
Lecture 4 Cluster Computing
 
Distributed Computing
Distributed Computing Distributed Computing
Distributed Computing
 
Distributed database
Distributed databaseDistributed database
Distributed database
 
distributed shared memory
 distributed shared memory distributed shared memory
distributed shared memory
 
Advantage of distributed database over centralized database
Advantage of distributed database over centralized databaseAdvantage of distributed database over centralized database
Advantage of distributed database over centralized database
 
Distributed data base management system
Distributed data base management systemDistributed data base management system
Distributed data base management system
 
Thread
ThreadThread
Thread
 
Clustering concepts
Clustering conceptsClustering concepts
Clustering concepts
 
Distributed computing
Distributed computingDistributed computing
Distributed computing
 
Distributed database system
Distributed database systemDistributed database system
Distributed database system
 
MySQL real-time replication configuration
MySQL real-time replication configurationMySQL real-time replication configuration
MySQL real-time replication configuration
 
Distributed computing
Distributed computingDistributed computing
Distributed computing
 
Os views
Os viewsOs views
Os views
 

Viewers also liked

Mobile App Developers Survey on Mobile Devices with Embedded Pico Projection
Mobile App Developers Survey on Mobile Devices with Embedded Pico ProjectionMobile App Developers Survey on Mobile Devices with Embedded Pico Projection
Mobile App Developers Survey on Mobile Devices with Embedded Pico Projectioncompoundphotonics
 
System models for distributed and cloud computing
System models for distributed and cloud computingSystem models for distributed and cloud computing
System models for distributed and cloud computingpurplesea
 
Distributed computing ).ppt him
Distributed computing ).ppt himDistributed computing ).ppt him
Distributed computing ).ppt himHimanshu Saini
 
Distributed Systems
Distributed SystemsDistributed Systems
Distributed SystemsRupsee
 
Cloud computing simple ppt
Cloud computing simple pptCloud computing simple ppt
Cloud computing simple pptAgarwaljay
 

Viewers also liked (8)

MOBILE SURVEY DEVICES
MOBILE  SURVEY  DEVICESMOBILE  SURVEY  DEVICES
MOBILE SURVEY DEVICES
 
Mobile App Developers Survey on Mobile Devices with Embedded Pico Projection
Mobile App Developers Survey on Mobile Devices with Embedded Pico ProjectionMobile App Developers Survey on Mobile Devices with Embedded Pico Projection
Mobile App Developers Survey on Mobile Devices with Embedded Pico Projection
 
System models for distributed and cloud computing
System models for distributed and cloud computingSystem models for distributed and cloud computing
System models for distributed and cloud computing
 
Distributed computing ).ppt him
Distributed computing ).ppt himDistributed computing ).ppt him
Distributed computing ).ppt him
 
Distributed Systems
Distributed SystemsDistributed Systems
Distributed Systems
 
Cloud computing ppt
Cloud computing pptCloud computing ppt
Cloud computing ppt
 
Cloud computing simple ppt
Cloud computing simple pptCloud computing simple ppt
Cloud computing simple ppt
 
Cs6703 grid and cloud computing unit 1
Cs6703 grid and cloud computing unit 1Cs6703 grid and cloud computing unit 1
Cs6703 grid and cloud computing unit 1
 

Similar to Models in ds

Distributed system notes unit I
Distributed system notes unit IDistributed system notes unit I
Distributed system notes unit INANDINI SHARMA
 
Distributed Operating System
Distributed Operating SystemDistributed Operating System
Distributed Operating SystemAjithaG9
 
Symmetric multiprocessing and Microkernel
Symmetric multiprocessing and MicrokernelSymmetric multiprocessing and Microkernel
Symmetric multiprocessing and MicrokernelManoraj Pannerselum
 
Types of operating system
Types of operating systemTypes of operating system
Types of operating systemMohammad Alam
 
Computing Environments.pptx
Computing Environments.pptxComputing Environments.pptx
Computing Environments.pptxMSivani
 
Distributed Operating System
Distributed Operating SystemDistributed Operating System
Distributed Operating SystemSanthiNivas
 
Operating Systems
Operating SystemsOperating Systems
Operating Systemsachal02
 
1. What important part of the process switch operation is not shown .pdf
1. What important part of the process switch operation is not shown .pdf1. What important part of the process switch operation is not shown .pdf
1. What important part of the process switch operation is not shown .pdffathimaoptical
 
L4Network Architecture.pptx
L4Network Architecture.pptxL4Network Architecture.pptx
L4Network Architecture.pptxGarimaJain745610
 
Overview of Distributed Systems
Overview of Distributed SystemsOverview of Distributed Systems
Overview of Distributed Systemsvampugani
 
paradigms cloud.pptx
paradigms cloud.pptxparadigms cloud.pptx
paradigms cloud.pptxgunvinit931
 
Distributed Computing system
Distributed Computing system Distributed Computing system
Distributed Computing system Sarvesh Meena
 
Distributed Operating System.pptx
Distributed Operating System.pptxDistributed Operating System.pptx
Distributed Operating System.pptxharpreetkaur1129
 
Cloud ready reference
Cloud ready referenceCloud ready reference
Cloud ready referenceHelly Patel
 

Similar to Models in ds (20)

Distributed system notes unit I
Distributed system notes unit IDistributed system notes unit I
Distributed system notes unit I
 
Distributed Operating System
Distributed Operating SystemDistributed Operating System
Distributed Operating System
 
Symmetric multiprocessing and Microkernel
Symmetric multiprocessing and MicrokernelSymmetric multiprocessing and Microkernel
Symmetric multiprocessing and Microkernel
 
Types of operating system
Types of operating systemTypes of operating system
Types of operating system
 
unit 4-1.pptx
unit 4-1.pptxunit 4-1.pptx
unit 4-1.pptx
 
lect 1TO 5.pptx
lect 1TO 5.pptxlect 1TO 5.pptx
lect 1TO 5.pptx
 
Computing Environments.pptx
Computing Environments.pptxComputing Environments.pptx
Computing Environments.pptx
 
Client server
Client serverClient server
Client server
 
Distributed Operating System
Distributed Operating SystemDistributed Operating System
Distributed Operating System
 
Presentation1.pptx
Presentation1.pptxPresentation1.pptx
Presentation1.pptx
 
SOFTWARE COMPUTING
SOFTWARE COMPUTINGSOFTWARE COMPUTING
SOFTWARE COMPUTING
 
unit 1.pptx
unit 1.pptxunit 1.pptx
unit 1.pptx
 
Operating Systems
Operating SystemsOperating Systems
Operating Systems
 
1. What important part of the process switch operation is not shown .pdf
1. What important part of the process switch operation is not shown .pdf1. What important part of the process switch operation is not shown .pdf
1. What important part of the process switch operation is not shown .pdf
 
L4Network Architecture.pptx
L4Network Architecture.pptxL4Network Architecture.pptx
L4Network Architecture.pptx
 
Overview of Distributed Systems
Overview of Distributed SystemsOverview of Distributed Systems
Overview of Distributed Systems
 
paradigms cloud.pptx
paradigms cloud.pptxparadigms cloud.pptx
paradigms cloud.pptx
 
Distributed Computing system
Distributed Computing system Distributed Computing system
Distributed Computing system
 
Distributed Operating System.pptx
Distributed Operating System.pptxDistributed Operating System.pptx
Distributed Operating System.pptx
 
Cloud ready reference
Cloud ready referenceCloud ready reference
Cloud ready reference
 

Recently uploaded

Artificial Intelligence Chap.5 : Uncertainty
Artificial Intelligence Chap.5 : UncertaintyArtificial Intelligence Chap.5 : Uncertainty
Artificial Intelligence Chap.5 : UncertaintyKhushali Kathiriya
 
Data Cloud, More than a CDP by Matt Robison
Data Cloud, More than a CDP by Matt RobisonData Cloud, More than a CDP by Matt Robison
Data Cloud, More than a CDP by Matt RobisonAnna Loughnan Colquhoun
 
Real Time Object Detection Using Open CV
Real Time Object Detection Using Open CVReal Time Object Detection Using Open CV
Real Time Object Detection Using Open CVKhem
 
Apidays New York 2024 - Scaling API-first by Ian Reasor and Radu Cotescu, Adobe
Apidays New York 2024 - Scaling API-first by Ian Reasor and Radu Cotescu, AdobeApidays New York 2024 - Scaling API-first by Ian Reasor and Radu Cotescu, Adobe
Apidays New York 2024 - Scaling API-first by Ian Reasor and Radu Cotescu, Adobeapidays
 
From Event to Action: Accelerate Your Decision Making with Real-Time Automation
From Event to Action: Accelerate Your Decision Making with Real-Time AutomationFrom Event to Action: Accelerate Your Decision Making with Real-Time Automation
From Event to Action: Accelerate Your Decision Making with Real-Time AutomationSafe Software
 
Understanding Discord NSFW Servers A Guide for Responsible Users.pdf
Understanding Discord NSFW Servers A Guide for Responsible Users.pdfUnderstanding Discord NSFW Servers A Guide for Responsible Users.pdf
Understanding Discord NSFW Servers A Guide for Responsible Users.pdfUK Journal
 
Apidays New York 2024 - The value of a flexible API Management solution for O...
Apidays New York 2024 - The value of a flexible API Management solution for O...Apidays New York 2024 - The value of a flexible API Management solution for O...
Apidays New York 2024 - The value of a flexible API Management solution for O...apidays
 
Exploring the Future Potential of AI-Enabled Smartphone Processors
Exploring the Future Potential of AI-Enabled Smartphone ProcessorsExploring the Future Potential of AI-Enabled Smartphone Processors
Exploring the Future Potential of AI-Enabled Smartphone Processorsdebabhi2
 
The 7 Things I Know About Cyber Security After 25 Years | April 2024
The 7 Things I Know About Cyber Security After 25 Years | April 2024The 7 Things I Know About Cyber Security After 25 Years | April 2024
The 7 Things I Know About Cyber Security After 25 Years | April 2024Rafal Los
 
Why Teams call analytics are critical to your entire business
Why Teams call analytics are critical to your entire businessWhy Teams call analytics are critical to your entire business
Why Teams call analytics are critical to your entire businesspanagenda
 
Tata AIG General Insurance Company - Insurer Innovation Award 2024
Tata AIG General Insurance Company - Insurer Innovation Award 2024Tata AIG General Insurance Company - Insurer Innovation Award 2024
Tata AIG General Insurance Company - Insurer Innovation Award 2024The Digital Insurer
 
MINDCTI Revenue Release Quarter One 2024
MINDCTI Revenue Release Quarter One 2024MINDCTI Revenue Release Quarter One 2024
MINDCTI Revenue Release Quarter One 2024MIND CTI
 
Apidays New York 2024 - The Good, the Bad and the Governed by David O'Neill, ...
Apidays New York 2024 - The Good, the Bad and the Governed by David O'Neill, ...Apidays New York 2024 - The Good, the Bad and the Governed by David O'Neill, ...
Apidays New York 2024 - The Good, the Bad and the Governed by David O'Neill, ...apidays
 
Cloud Frontiers: A Deep Dive into Serverless Spatial Data and FME
Cloud Frontiers:  A Deep Dive into Serverless Spatial Data and FMECloud Frontiers:  A Deep Dive into Serverless Spatial Data and FME
Cloud Frontiers: A Deep Dive into Serverless Spatial Data and FMESafe Software
 
Axa Assurance Maroc - Insurer Innovation Award 2024
Axa Assurance Maroc - Insurer Innovation Award 2024Axa Assurance Maroc - Insurer Innovation Award 2024
Axa Assurance Maroc - Insurer Innovation Award 2024The Digital Insurer
 
Repurposing LNG terminals for Hydrogen Ammonia: Feasibility and Cost Saving
Repurposing LNG terminals for Hydrogen Ammonia: Feasibility and Cost SavingRepurposing LNG terminals for Hydrogen Ammonia: Feasibility and Cost Saving
Repurposing LNG terminals for Hydrogen Ammonia: Feasibility and Cost SavingEdi Saputra
 
Boost PC performance: How more available memory can improve productivity
Boost PC performance: How more available memory can improve productivityBoost PC performance: How more available memory can improve productivity
Boost PC performance: How more available memory can improve productivityPrincipled Technologies
 
Apidays Singapore 2024 - Building Digital Trust in a Digital Economy by Veron...
Apidays Singapore 2024 - Building Digital Trust in a Digital Economy by Veron...Apidays Singapore 2024 - Building Digital Trust in a Digital Economy by Veron...
Apidays Singapore 2024 - Building Digital Trust in a Digital Economy by Veron...apidays
 
Scaling API-first – The story of a global engineering organization
Scaling API-first – The story of a global engineering organizationScaling API-first – The story of a global engineering organization
Scaling API-first – The story of a global engineering organizationRadu Cotescu
 

Recently uploaded (20)

Artificial Intelligence Chap.5 : Uncertainty
Artificial Intelligence Chap.5 : UncertaintyArtificial Intelligence Chap.5 : Uncertainty
Artificial Intelligence Chap.5 : Uncertainty
 
Data Cloud, More than a CDP by Matt Robison
Data Cloud, More than a CDP by Matt RobisonData Cloud, More than a CDP by Matt Robison
Data Cloud, More than a CDP by Matt Robison
 
Real Time Object Detection Using Open CV
Real Time Object Detection Using Open CVReal Time Object Detection Using Open CV
Real Time Object Detection Using Open CV
 
Apidays New York 2024 - Scaling API-first by Ian Reasor and Radu Cotescu, Adobe
Apidays New York 2024 - Scaling API-first by Ian Reasor and Radu Cotescu, AdobeApidays New York 2024 - Scaling API-first by Ian Reasor and Radu Cotescu, Adobe
Apidays New York 2024 - Scaling API-first by Ian Reasor and Radu Cotescu, Adobe
 
From Event to Action: Accelerate Your Decision Making with Real-Time Automation
From Event to Action: Accelerate Your Decision Making with Real-Time AutomationFrom Event to Action: Accelerate Your Decision Making with Real-Time Automation
From Event to Action: Accelerate Your Decision Making with Real-Time Automation
 
Understanding Discord NSFW Servers A Guide for Responsible Users.pdf
Understanding Discord NSFW Servers A Guide for Responsible Users.pdfUnderstanding Discord NSFW Servers A Guide for Responsible Users.pdf
Understanding Discord NSFW Servers A Guide for Responsible Users.pdf
 
Apidays New York 2024 - The value of a flexible API Management solution for O...
Apidays New York 2024 - The value of a flexible API Management solution for O...Apidays New York 2024 - The value of a flexible API Management solution for O...
Apidays New York 2024 - The value of a flexible API Management solution for O...
 
Exploring the Future Potential of AI-Enabled Smartphone Processors
Exploring the Future Potential of AI-Enabled Smartphone ProcessorsExploring the Future Potential of AI-Enabled Smartphone Processors
Exploring the Future Potential of AI-Enabled Smartphone Processors
 
+971581248768>> SAFE AND ORIGINAL ABORTION PILLS FOR SALE IN DUBAI AND ABUDHA...
+971581248768>> SAFE AND ORIGINAL ABORTION PILLS FOR SALE IN DUBAI AND ABUDHA...+971581248768>> SAFE AND ORIGINAL ABORTION PILLS FOR SALE IN DUBAI AND ABUDHA...
+971581248768>> SAFE AND ORIGINAL ABORTION PILLS FOR SALE IN DUBAI AND ABUDHA...
 
The 7 Things I Know About Cyber Security After 25 Years | April 2024
The 7 Things I Know About Cyber Security After 25 Years | April 2024The 7 Things I Know About Cyber Security After 25 Years | April 2024
The 7 Things I Know About Cyber Security After 25 Years | April 2024
 
Why Teams call analytics are critical to your entire business
Why Teams call analytics are critical to your entire businessWhy Teams call analytics are critical to your entire business
Why Teams call analytics are critical to your entire business
 
Tata AIG General Insurance Company - Insurer Innovation Award 2024
Tata AIG General Insurance Company - Insurer Innovation Award 2024Tata AIG General Insurance Company - Insurer Innovation Award 2024
Tata AIG General Insurance Company - Insurer Innovation Award 2024
 
MINDCTI Revenue Release Quarter One 2024
MINDCTI Revenue Release Quarter One 2024MINDCTI Revenue Release Quarter One 2024
MINDCTI Revenue Release Quarter One 2024
 
Apidays New York 2024 - The Good, the Bad and the Governed by David O'Neill, ...
Apidays New York 2024 - The Good, the Bad and the Governed by David O'Neill, ...Apidays New York 2024 - The Good, the Bad and the Governed by David O'Neill, ...
Apidays New York 2024 - The Good, the Bad and the Governed by David O'Neill, ...
 
Cloud Frontiers: A Deep Dive into Serverless Spatial Data and FME
Cloud Frontiers:  A Deep Dive into Serverless Spatial Data and FMECloud Frontiers:  A Deep Dive into Serverless Spatial Data and FME
Cloud Frontiers: A Deep Dive into Serverless Spatial Data and FME
 
Axa Assurance Maroc - Insurer Innovation Award 2024
Axa Assurance Maroc - Insurer Innovation Award 2024Axa Assurance Maroc - Insurer Innovation Award 2024
Axa Assurance Maroc - Insurer Innovation Award 2024
 
Repurposing LNG terminals for Hydrogen Ammonia: Feasibility and Cost Saving
Repurposing LNG terminals for Hydrogen Ammonia: Feasibility and Cost SavingRepurposing LNG terminals for Hydrogen Ammonia: Feasibility and Cost Saving
Repurposing LNG terminals for Hydrogen Ammonia: Feasibility and Cost Saving
 
Boost PC performance: How more available memory can improve productivity
Boost PC performance: How more available memory can improve productivityBoost PC performance: How more available memory can improve productivity
Boost PC performance: How more available memory can improve productivity
 
Apidays Singapore 2024 - Building Digital Trust in a Digital Economy by Veron...
Apidays Singapore 2024 - Building Digital Trust in a Digital Economy by Veron...Apidays Singapore 2024 - Building Digital Trust in a Digital Economy by Veron...
Apidays Singapore 2024 - Building Digital Trust in a Digital Economy by Veron...
 
Scaling API-first – The story of a global engineering organization
Scaling API-first – The story of a global engineering organizationScaling API-first – The story of a global engineering organization
Scaling API-first – The story of a global engineering organization
 

Models in ds

  • 1. Q. Explain Distributed Computing System Models? Distributed Computing System Models Distributed Computing system models can be broadly classified into five categories. They are • Minicomputer model • Workstation model • Workstation – server model • Processor – pool model • Hybrid model Minicomputer Model The minicomputer model is a simple extension of the centralized time-sharing system. A distributed computing system based on this model consists of a few minicomputers (they may be large supercomputers as well) interconnected by a communication network. Each minicomputer usually has multiple users simultaneously logged on to it. For this, several interactive terminals are connected to each minicomputer. Each user is logged on to one specific minicomputer, with remote access to other minicomputers. The network allows a user to access remote resources that are available on some machine other than the one on to which the user is currently logged. The minicomputer model may be used when resource sharing (such as sharing of information databases of different types, with each type of database located on a different machine) with remote users is desired. The early ARPAnet is an example of a distributed computing system based on the minicomputer model. Workstation Model A distributed computing system based on the workstation model
  • 2. consists of several workstations interconnected by a communication network. An organization may have several workstations located throughout a building or campus, each workstation equipped with its own disk and serving as a singleuser computer. It has been often found that in such an environment, at any one time a significant proportion of the workstations are idle (not being used), resulting in the waste of large amounts of CPU time. Therefore, the idea of the workstation model is to interconnect all these workstations by a high-speed LAN so that idle workstations may be used to process jobs of users who are logged onto other workstations and do not have sufficient processing power at their own workstations to get their jobs processed efficiently. Workstation – Server Model The workstation model is a network of personal workstations, each with its own disk and a local file system. A workstation with its own local disk is usually called a diskful workstation and a workstation without a local disk is called a diskless workstation. With the proliferation of high-speed networks, diskless workstations have become more popular in network environments than diskful workstations, making the workstationserver model more popular than the workstation model for building distributed computing systems. A distributed computing system based on the workstation-server model consists of a few minicomputers and several workstations (most of which are diskless, but a few of which may be diskful) interconnected by a communication network. Note that when diskless workstations are used on a network, the file system to be used by these workstations must be implemented either by a diskful workstation or by a minicomputer equipped with a disk for file storage. One or more of the minicomputers are used for implementing the file system. Other minicomputers may be used for providing other types of
  • 3. services, such as database service and print service. Therefore, each minicomputer is used as a server machine to provide one or more types of services. Therefore in the workstation-server model, in addition to the workstations, there are specialized machines (may be specialized workstations) for running server processes (called servers) for managing and providing access to shared resources. For a number of reasons, such as higher reliability and better scalability, multiple servers are often used for managing the resources of a particular type in a distributed computing system. For example, there may be multiple file servers, each running on a separate minicomputer and cooperating via the network, for managing the files of all the users in the system. Due to this reason, a distinction is often made between the services that are provided to clients and the servers that provide them. That is, a service is an abstract entity that is provided by one or more servers. For example, one or more file servers may be used in a distributed computing system to provide file service to the users. In this model, a user logs onto a workstation called his or her home workstation. Normal computation activities required by the user's processes are performed at the user's home workstation, but requests for services provided by special servers (such as a file server or a database server) are sent to a server providing that type of service that performs the user's requested activity and returns the result of request processing to the user's workstation. Therefore, in this model, the user's processes need not migrated to the server machines for getting the work done by those machines. Processor – Pool Model The processor-pool model is based on the observation that most of the time a user does not need any computing power but once in a while the user may need a very large amount of computing power for a short time (e.g., when recompiling a program consisting of a large number of files after changing a basic shared
  • 4. declaration). Therefore, unlike the workstation-server model in which a processor is allocated to each user, in the processor-pool model the processors are pooled together to be shared by the users as needed. The pool of processors consists of a large number of microcomputers and minicomputers attached to the network. Each processor in the pool has its own memory to load and run a system program or an application program of the distributed computing system Hybrid Model Out of the four models described above, the workstation-server model, is the most widely used model for building distributed computing systems. This is because a large number of computer users only perform simple interactive tasks such as editing jobs, sending electronic mails, and executing small programs. The workstation-server model is ideal for such simple usage. However, in a working environment that has groups of users who often perform jobs needing massive computation, the processorpool model is more attractive and suitable.