Chapter 3 : Distributed Data Processing

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Chapter 3 Distributed Data Processing

• Business Data Communications, 5e

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Objectives

• Difference between Pros Cons of Centralize
  Distributed data processing (DDP)
• Why DDP system needs data communications and
  networking
• Different forms of DDP for applications
• Different forms of DDP for distributed database.
• Requirements of DDP for networking facilities
• motivation towards Client/server.

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Intro

• Until recently only data type of information
  required to use communication. Now all 4 types of
  information (i.e. data, voice, video, image) use
  similar communication technology.
• This chapter looks into different types of Data
  Communications
• We look into two extreme Centralize Distributed
  data processing.
• The computing function in most organizations is
  implemented somewhere along a spectrum between
  these two extremes.

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Centralized Data Processing

• A Centralized Data Processing Centre may consists
  of
• Centralized computers,
• Centralized processing,
• Centralized data,
• Centralized control,
• Centralized support staff
• The Basic advantages
• Economies of scale (equipment and personnel)
• Lack of duplication
• Ease in enforcing standards, security

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Example of Centralized Data Processing
Dallas County Information Systems Architecture
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Example of Distributed Data Processing
Facility is a WLAN that supports both data
traffic and VoIP. The WLAN connects to the
outside world via a satellite link that connects
to the Internet, to Carnivals private wide area
network (WAN), and to the public switched
telephone network (PSTN) in the US.
Carnival Valor Wireless LAN
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Holiday Inn Information Systems
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Distributed Data Processing

• Computers are dispersed throughout organization
  with some means of interconnection among them
• Allows greater flexibility in meeting individual
  needs
• More redundancy
• More autonomy

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Why is DDP Increasing?

• Means and Motive
• Dramatically reduction in hardware costs
• Dramatically increased distributed processing
  capabilities (Hardware capabilities)
• Dramatically increased need for new applications
  and shorter development times
• Ability to share data across multiple servers

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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?

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Benefits of DDP

• Responsiveness
• Availability
• Correspondence to Organizational Patterns
• Resource Sharing
• Incremental Growth
• Increased User Involvement Control

• End-user Productivity
• Distance location independence
• Privacy and security
• Vendor independence
• Flexibility

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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

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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

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The DP Pendulum

• Centralized systems (mainframes, etc)
• Distributed systems (PCs)
• Networked systems
• Client-Server computing

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Client/Server Architecture

• Is Client/Server Distributed or Centralized?
• Combines advantages of distributed and
  centralized computing
• Positive aspects of Client/Server architecture
• Cost-effective, achieves economies of scale by
  centralizing support for specialized functions
  (e.g. file database servers)
• Provide universal access to information by
  authorized users
• Flexible, scalable approach (File server db
  server can be on the same computer, or db
  services can be provided by several
  geographically dispersed machines.
  Computers-Services can share processors for
  smaller Information systems or split among
  processors in larger systems to increase
  availability)
• Example of Servers Database, Printing Fax,
  File Storage, Communication Front Ends, Gateways
  Bridges

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Intranets Provides users the features and
applications of the Internet but isolated within
the organization.

• Latest Development in DDP
• Uses Internet-based standards,
• e.g. Hyper Text Markup Language (HTML) and Simple
  Mail Transfer Protocol (SMTP)
• Uses TCP/IP for LAN WAN but isolated within an
  organization
• Content is not accessible to public only
  accessible by the intended users
• A specialized form of client/server architecture
• Can be managed (unlike Internet)

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Extranets

• Based on Client/Server model for operation
• Similar to intranet, but provides access to
  controlled number of outside users
• Vendors/suppliers
• Customers
• Utilizing Web technologies, provides more than
  simple Web access rather extensive access to
  corporate resources in an enforced security
  environment.

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Forms of Distributed Data Processing
This general definition doesnt show different
forms of DDP

• DDP System Dispersed Interconnected Computing
  Facility in an organization
• DDP can take one or more of the following forms
• Distributed Applications
• Distributed Device Controllers
• Distributed Control
• Distributed Data

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Distributed Applications

• Two dimensions characterize the distribution of
  applications
• Allocation of Application Functions
• Vertical or Horizontal

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Distributed Applications (cntd.)

• Allocation of Application Functions
• 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

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Distributed Applications (cntd.)

• 2. Partitioning Distributed Applications
• Horizontal partitioning
• Vertical partitioning

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Distributed Applications (cntd.)

• Horizontal Partitioned DDP
• Different applications on different machines
• One application replicated on a number of
  machines
• In general Data Processing is distributed among a
  number of computers that have a peer relation,
  no Master/Slave relation, or no Client/Server
  concept.
• Horizontal partitioning reflects
• Autonomous operation of computers
• Load balancing
• Organizational decentralization
• Examples
• Office automation support system
• Air traffic control system

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Distributed Applications (cntd.)

• Vertical Partitioned DDP
• One application split up into components that are
  dispersed among a number of machines
• Data processing is distributed in a hierarchical
  fashion.
• Consists of a central computer system with one or
  more levels of satellite systems.
• The nature of the partition reflects structure of
  the organization or the task or both.
• The main Objective in Vertical Partitioned DDP
  Assign processing load to the level of the
  hierarchy at which it is most cost-effectivegtbest
  features of both centralizes DDP are combined
• Examples Insurance, Retail chain point-of-sale,
  Inventory, Process control

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Distributed Devices

• Controlling distributed set of devices that can
  via processors. For example Automatic Teller
  Machines (ATM), laboratory interface, factory
  automation.
• Factory automation contains distributed sensors,
  PLC, ?p.

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Network Management

• A Distributed System Requires
• Management and Control of Distributed System
  Management of Communications facility including
  control of access to some of the facility.
• Central Network Management System to interact
  with each computer in the system each computer
  must include some management control logic to
  be able to interact with the Central Network
  Management.

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Distributed Database

• Where portions of the data are dispersed among a
  number of computers.
• Must include a DIRECTORY that identifies the
  location of each data element in the db.
• 3 way of organizing
• Centralized
• Replicated
• Partitioned

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Distributed data

• Centralized database (often used with Vertical
  DDP, for security/integrity)
• Pro No duplication of data
• Con Contention for access
• Replicated database (all or part copied in more
  than one computer, Real-Time, Near RT 30Minutes,
  Deferred-once or twice a day)
• 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

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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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