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Chapter 3 : Distributed Data Processing. Business Data Communications, 5e. Centralized Data Processing. Centralized computers, processing, data, control, support What are the advantages? Economies of scale (equipment and personnel) Lack of duplication Ease in enforcing standards, security.

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Chapter 3 distributed data processing

Chapter 3 : Distributed Data Processing

Business Data Communications, 5e


Centralized data processing
Centralized Data Processing

  • Centralized computers, processing, data, control, support

  • What are the advantages?

    • Economies of scale (equipment and personnel)

    • Lack of duplication

    • Ease in enforcing standards, security


Distributed data processing
Distributed Data Processing

  • Computers are dispersed throughout organization

  • Allows greater flexibility in meeting individual needs

  • More redundancy

  • More autonomy


Why is ddp increasing
Why is DDP Increasing?

  • Dramatically reduced workstation costs

  • Improved user interfaces and desktop power

  • Ability to share data across multiple servers


Ddp pros cons
DDP Pros & Cons

  • There are no “one-size-fits-all” solutions

  • Key issues

    • How does it affect end-users?

    • How does it affect management?

    • How does it affect productivity?

    • How does it affect bottom-line?


Benefits of ddp

Responsiveness

Availability

Correspondence to Org. Patterns

Resource Sharing

Incremental Growth

Increased User Involvement & Control

End-user Productivity

Distance & location independence

Privacy and security

Vendor independence

Flexibility

Benefits of DDP


Drawbacks of ddp

More difficulty test & failure diagnosis

More components and dependence on communication means more points of failure

Incompatibility of components

Incompatibility of data

More complex management & control

Difficulty in control of corporate information resources

Suboptimal procurement

Duplication of effort

Drawbacks of DDP


Client server architecture
Client/Server Architecture

  • Combines advantages of distributed and centralized computing

  • Cost-effective, achieves economies of scale

  • Flexible, scalable approach


Intranets
Intranets

  • Uses Internet-based standards & TCP/IP

  • Content is accessible only to internal users

  • A specialized form of client/server architecture

  • Can be managed (unlike Internet)


Extranets
Extranets

  • Similar to intranet, but provides access to controlled number of outside users

    • Vendors/suppliers

    • Customers


Distributed applications
Distributed applications

  • Vertical partitioning

    • One application dispersed among systems

    • Example: Retail chain POS, inventory, analysis

  • Horizontal partitioning

    • Different applications on different systems

    • One application replicated on systems

    • Example: Office automation


Other forms of ddp
Other forms of DDP

  • Distributed devices

    • Example: ATM machines

  • Network management

    • Centralized systems provide management and control of distributed nodes


Distributed data
Distributed data

  • Centralized database

    • Pro: No duplication of data

    • Con: Contention for access

  • Replicated database

    • Pro: No contention

    • Con: High storage and data reorg/update costs

  • Partitioned database

    • Pro: No duplication, limited contention

    • Con: Ad hoc reports more difficult to assemble


Networking implications
Networking Implications

  • Connectivity requirements

    • What links between components are necessary?

  • Availability requirements

    • Percentage of time application or data is available to users

  • Performance requirements

    • Response time requirements


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