Business data communications 5e by stallings chapter 03

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
• What are the disadvantages???


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

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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