1. Chapter 3 : Distributed Data Processing Business Data Communications, 4e

2. 2 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 How is data communications implemented? Holiday Inn Holiday Inn Examples? Holiday InnHoliday Inn Figure 3.1 (p.42)

3. 3 Distributed Data Processing Computers are dispersed throughout organization Allows greater flexibility in meeting individual needs More redundancy More autonomy How is data communications implemented? Examples? J.P. Morgan (Figure 3.2, p.44)J.P. Morgan

4. Why is DDP Increasing? Dramatically reduced workstation costs Improved user interfaces and desktop power Better end-user programming Ability to share data across multiple servers

5. 5 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?

6. 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

7. 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 controlling information resources Suboptimal procurement Duplication of effort

8. Reasons for DDP Need for new applications On large centralized systems, development can take years On small distributed systems, development can be component-based and very fast Need for short response time Centralized systems result in contention among users and processes Distributed systems provide dedicated resources

9. The DP “ Pendulum ” Centralized systems (mainframes, etc) Distributed systems (PCs) Networked systems Client-Server computing

10. Client/Server Architecture Combines advantages of distributed and centralized computing Cost-effective, achieves economies of scale Flexible, scalable approach

11. Intranets Uses Internet-based standards & TCP/IP Content is accessible only to internal users A specialized form of client/server architecture

12. Extranets Similar to intranet, but provides access to controlled number of outside users Vendors/suppliers Customers

13. Virtual Private Networks - VPN Use encryption and authentication Provide secure connection to LAN via insecure network (Internet) Cheaper than real private networks, but less reliable Encryption performed by firewall or routers

14. VPN (Virtual Private Network)

15. VPN 技術 穿隧技術 (Tunneling) IPSec (IP Security) PPTP (Point-to-Point Tunneling Protocol) L2TP (Layer 2 Tunneling Protocol) 加解密技術 (Encryption/Decryption) Private/Public/Hybrid Key Encryption 密鑰管理 (Key Management) SKIP (Simple Key Management for IP) IKE (ISAKMP/Oakley) 使用者與設備身份認證技術 (Authentication) Username/Password + Token Number X.509 Certificate by Certificate Authority (CA)

16. What is distributed? Distributed applications One application dispersed among systems One application replicated on systems Different applications on different systems Distributed data centralized database (not distributed data) replicated database partitioned database

17. Distributed applications Horizontal partitioning Different applications on different systems One application replicated on systems Example: Office automation Vertical partitioning One application dispersed among systems Example: Retail chain POS, inventory, analysis

18. 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

19. 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