Distributed Processing Chapter 1 : Introduction

1 / 25

# Distributed Processing - PowerPoint PPT Presentation

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.

I am the owner, or an agent authorized to act on behalf of the owner, of the copyrighted work described.

## PowerPoint Slideshow about 'Distributed Processing' - Lucy

Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author.While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server.

- - - - - - - - - - - - - - - - - - - - - - - - - - E N D - - - - - - - - - - - - - - - - - - - - - - - - - -
Presentation Transcript

### Distributed ProcessingChapter 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.
• 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
• 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
• 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 ?
• 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

1.1

A distributed system organized as middleware. Heterogeneity and Scalability

Distributed System - Transparency

Different forms of transparency in a distributed system.

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

Server C

Server B

Server A

Application Program or Client

Predefined interface

Wrapping with predefined interface

Encapsulation : Object-Oriented Approach

Multiprocessors (1)
• A bus-based multiprocessor.

1.7

Multiprocessors (2)

(a) A crossbar switch

(b) An omega switching network

1.8

Software Concepts
• An overview of
• DOS (Distributed Operating Systems)
• NOS (Network Operating Systems)
• Middleware
Issues in System Design
• Transparency
• Flexibility
• Reliability
• Performance
• Scalability
• Interoperability
Transparency
• Location
• Migration
• Duplication
• Relocation
• Concurrency
• Parallelism
• Location
• Access
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
• 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
• 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
• 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
• Easy to collaborate with other systems in run-time
• Compatibility, Portability
• How to achieve Interoperability
• Well-Defined API set
• Standardization
Multiprocessors (1)
• A bus-based multiprocessor.

1.7

Multiprocessors (2)

(a) A crossbar switch

(b) An omega switching network

1.8