Distributed Processing

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  • Designed by: IMTIAZ HUSSAIN

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  • 1. BY: IMTIAZ HUSSAIN 048 M. EHSAN ULLAH 012 HAFIZ ABUBAKAR 096(06) MUHAMMAD IDREES 027 DISTRIBUTING PROCESSING
  • 2. OUTLINE
    • Distributed Processing
    • Distributed System
    • Architecture
    • Form of D.P
    • Techniques
    • Challenges
    • Advantage/Disadvantage
  • 3. What is Distributed Processing
    • Distributed Processing is a technique of distributing the information over a number of devices.
    • The devices may be computers or data terminals with some level of intelligence.
    • The devices are interconnected with communication facilities.
  • 4. What is Distributed System
    • A distributed system is one in which components located at networked computers communicate and coordinate their actions only by passing messages .
    • Examples
      • The internet
      • An intranet which is a portion of the internet managed by an organization
  • 5. Architecture
    • Software layers
    • System architectures
    • Interfaces and objects
    • Design requirements for distributed architectures
  • 6. Software layers
    • Applications, services
    • Middleware
    • Operating system
    • Computer and network hardware
  • 7. System architectures
    • Client-server model
    • Services provided by multiple servers
    • Proxy srvers and caches
    • Peer processes
  • 8. Design requirements for distributed architectures
    • Performance issues
    • Use of caching and replication
    • Dependability issues
  • 9. Design requirements for distributed architectures
    • Performance issues
      • Responsiveness
      • Balancing computer loads
      • Quality of services
    • Caching and replication
      • The performance issues often appear to be major obstacles to the successful deployment of DS, but much progress has been made in the design of systems that overcome them by the use of data replication and caching.
    • Dependability issues
      • Correctness
      • Security
      • Fault tolerance
  • 10. Form of Distributed Processing
    • Distributed Applications
    • Distributed Devices
    • Network Management and Control
    • Distributed Data
  • 11. Distributed Applications
    • One application splits up into components that are dispersed among a number of machines
    • One application replicated on a number of machines
    • A number of different applications distributed among a number of machines
    • Can be characterized by vertical or horizontal partitioning
  • 12. Distributed Devices
    • Support a distributed set of devices that can be controlled by processors, e.g. ATMs or laboratory interface equipments
    • Distribution of processing technology to various locations of the manufacturing process in factory automation
  • 13. Techniques of Distributed Processing
    • Centralized
    • Decentralized
    • Parallel
    • Open Distributed Processing
    • Clustering
  • 14. Centralized
    • Centralized Processing  is done at a central location, using terminals that are attached to a central computer
    • The central computer performs the computing functions and controls the remote terminals. This type of system relies totally on the central computer.
  • 15. Centralized
    • Example : Client/server is the most common example of centralized processing, where server is controlling all the activities on the network.
  • 16. Decentralized
    • Computer systems in different locations. Although data may be transmitted between the computers periodically
    • Example: Yahoo server is the example of the decartelized processing. On each login it connects you to a different server .
  • 17. Parallel Processing
    • Parallel processing is the simultaneous processing of the same task on two or more microprocessors in order to obtain faster results
    • Multiple processor
    • Multiple computer
    • Shared memory resources
  • 18. Open Distributed Processing
    • ODP is a reference model in computer science, which provides a coordinating framework for the standardization of open distributed processing (ODP).
    • It supports distribution, interworking, platform and technology independence, and portability, together with an enterprise architecture framework for the specification of ODP systems.
  • 19. Clustering
    • A cluster is a group of individual computer systems that can be made to appear as one computer system.
    • Clustering is just one form of parallel computing.
    • key points that distinguishes clustering from other is the ability to view the cluster as either a single entity or a collection of stand-alone systems
    • For example : a cluster of web servers can appear as one large web server, but at the same time, individual systems within the cluster can be accessed as individual systems,
  • 20. Clustering
    • Example:
      • Internet is an example of clustering, where different server are working but they look like a single server.
  • 21. Challenges
    • Heterogeneity
    • Security
    • Scalability
    • Failure handling
    • Concurrency
  • 22. Advantages
    • Quicker response time
      • By locating processing power close to user, response time is typically improved. This means that the system responds rapidly to commands entered by users.
    • Lower costs
      •   Long-distance communication costs are declining at a slower rate than the cost of computer power
      • Distributed processing can reduce the volume of data that must be transmitted over long-distances and thereby reduce long-distance costs.
    • Improved data integrity
      • High degrees of accuracy and correctness may be achieved by giving users control over data entry and storage.
  • 23. Advantages
    • Reduced host processor costs
      •   The productive life of a costly mainframe can be extended by off-loading some its processing tasks to other, less expensive machines
    • Resource sharing
      • One of the main advantages of developing microcomputer networks is because they make it possible to share expensive resources such as high-speed, color laser printers, fast data storage devices, and high-priced software packages.
  • 24. Disadvantage
    • Complexities
      • A lot of extra programming is required to set up a distributed system
    • Network failure
      • Since distributed system will be connected through network and in case of network failure non of the systems will work
    • Security
      • The information need to be passed between the network. And it can be tracked and can be used for illegal purpose.
    • Costly software
    • Not all situations are suitable for distributed computing
  • 25.