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Distributed Processing Chapter 1 : Introduction Problem There are n nodes, each of which has a value. A node wants to know the maximum value among the n nodes. Centralized Approach : A server maintains the values of n nodes and each node reports its value to the server.

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problem
Problem
  • There are n nodes, each of which has a value. A node wants to know the maximum value among the n nodes.
  • Centralized Approach:
    • A server maintains the values of n nodes and each node reports its value to the server.
    • Then the query node sends a message to ask the maximum value to the server, which will answer to the query.
  • Distributed Approach:
    • Each node communicates with its 6 nearest neighbor nodes to inform its value.
    • Then the query node eventually finds the maximum value by exchanging information with its neighbor nodes.
discussion
Discussion
  • Question 1: Find the algorithm for distributed approach.
  • Question 2: Compare the performance
    • In terms of the number of communications
  • Question 3: Make a comparison table for the two approaches
definition of a distributed system
Definition of a Distributed System
  • Distributed system :

1) A collection of (scalability)

2) independent computers that (heterogeneity)

3) appears to its users as a single coherent system(transparency)

  • Distributed System versus Parallel System
    • Separated Operating System vs. Single Operating System
    • Message Passing vs. Shared Memory
why distributed system
Why Distributed System ?
  • Performance
  • Incremental Growth (Scalability)
    • 1 single mainframe of price W
    • N small machines of price W/N
  • Fault Tolerance
    • 1 single mainframe : critical weak point
    • Failure of a machine : replacement by other machines
  • Geographical Distribution and Availability
    • Flexible configuration
      • e.g. 1 Disk server, 3 Computing servers, 1 Graphic server, etc.
    • Geographical availability
distributed system scalibility and heterogeneity
Distributed System - Scalibility and Heterogeneity

1.1

A distributed system organized as middleware. Heterogeneity and Scalability

distributed system transparency
Distributed System - Transparency

Different forms of transparency in a distributed system.

distributed system heterogeneity

Server C

Driver for B

Driver for C

Driver for A

Server B

Server A

Distributed System : Heterogeneity

Application Program or Client

Client has to be provided with one different driver for each server

distributed system heterogeneity and object oriented approach

Server C

Server B

Server A

Distributed System : Heterogeneity and Object-Oriented Approach

Application Program or Client

Predefined interface

Wrapping with predefined interface

Encapsulation : Object-Oriented Approach

multiprocessors 1
Multiprocessors (1)
  • A bus-based multiprocessor.

1.7

multiprocessors 2
Multiprocessors (2)

(a) A crossbar switch

(b) An omega switching network

1.8

software concepts
Software Concepts
  • An overview of
    • DOS (Distributed Operating Systems)
    • NOS (Network Operating Systems)
    • Middleware
issues in system design
Issues in System Design
  • Transparency
  • Flexibility
  • Reliability
  • Performance
  • Scalability
  • Interoperability
transparency
Transparency
  • Hiding physical details about
    • Location
    • Migration
    • Duplication
    • Relocation
    • Concurrency
    • Parallelism
    • Location
    • Access
flexibility
Flexibility
  • Should be easy to modify functionality and architecture
  • To provide with Configurability, Avalability and Autonomy
  • Micro-Kernel vs. Monolithic Kernel
    • Monolithic Kernel : Provides all functionalities of OS. example. UNIX
    • Micro-Kernel
      • Minimal subset of OS + what users want
    • Example
      • Kernel Watch
reliability
Reliability
  • Important Goal of Distributed System
    • Reliability
    • Security
    • Fault-Tolerance
  • Failure Probability P
    • Should be P = P1·P2·P3 … ·Pn
    • But often P = P1+ P2+ P3 … + Pn in reality
performance and scalability
Performance and Scalability
  • Improve performance by parallelism
  • Throughput T
    • Ideally should be T = T·n when n is the number of sites
    • In reality T <T·n
      • Due to some Bottleneck

Throughput

Number of sites

??

granularity of parallelism
Granularity of Parallelism
  • Unit of Task
    • Fine-Granularity vs. Coarse Granularity
  • Fine-Granularity
    • Large number of small tasks
    • Need a large amount of inter-task communication
    • Not good for distributed system (good for Parallel system)
  • Coarse-Granularity
    • Small number of big tasks
    • Only small amount of inter-task communication
    • Good for distributed system
interoperability
Interoperability
  • Easy to collaborate with other systems in run-time
    • Compatibility, Portability
  • How to achieve Interoperability
    • Well-Defined API set
    • Standardization
multiprocessors 123
Multiprocessors (1)
  • A bus-based multiprocessor.

1.7

multiprocessors 224
Multiprocessors (2)

(a) A crossbar switch

(b) An omega switching network

1.8

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