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

Distributed Data Processing

• Computers are dispersed throughout organization

• Allows greater flexibility in meeting individual needs

• More redundancy

• More autonomy

Why is DDP Increasing?

• Dramatically reduced workstation costs

• Improved user interfaces and desktop power

• Ability to share data across multiple servers

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

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

Client/Server Architecture

• Combines advantages of distributed and centralized computing

• Cost-effective, achieves economies of scale

• Flexible, scalable approach

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

• Similar to intranet, but provides access to controlled number of outside users– Vendors/suppliers– Customers

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

• Distributed devices– Example: ATM machines

• Network management– Centralized systems provide management and

control of distributed nodes

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

• 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