DISTRIBUTED SYSTEMS – ARCHITECTURE MODELS

Janani C Krishnamani

CSC 8320

Fall 2011

OUTLINE

Introduction Architecture models

System architectures Communication Network architectures

Examples Future Ideas

INTRODUCTION

WHAT ARE DISTRIBUTED SYSTEMS?

Collection of independent computers that appear to the user as one single entity

Examples Systems in a LAN, WAN, MAN World Wide Web Torrent networks Clusters Cloud servers

WHY INTERCONNECT SYSTEMS? [1]

To pass a message from one system to another

Share common resources Beneficial to use multiple low end processors

than one high end processor Fault tolerance through redundancy

CLASSIFICATION

CLASSIFICATION [2]

Based on system architecture Client – Server model Peer – Peer model

Based on communication network Bus Switched

Based on level of coupling Tightly coupled (parallel) Loosely coupled (distributed)

BASED ON SYSTEM ARCHITECTURE : CLIENT SERVER MODEL

One server acts as the principal control agent Several nodes report to the server Advantages:

Better control and security Concentration of functions in high performance

servers Disadvantages:

Not robust due to lack of redundancy Performance suffers if the number of clients

increases Examples:

Workstation – Server Model Processor Pool Model

BASED ON SYSTEM ARCHITECTURE : WORKSTATION – SERVER MODEL

Many workstations connect to the network. Workstations provide local processing and an

interface to the network. Consist of one or more client workstations

connected to one or more server workstations using a communication network.

Mainly used for resource sharing

BASED ON SYSTEM ARCHITECTURE : PROCESSOR POOL MODEL

All the processing is moved to a pool of processors

No concept of a home machine Workstations are dummy terminals with good

graphical display Terminals have minimum intelligence like

remote booting, remote mounting of file systems, virtual terminal handling and packet assembly and disassembly services

BASED ON SYSTEM ARCHITECTURE : PEER – PEER MODEL

All the nodes in the network have equal privilege

No special routing server required. The nodes themselves take care of routing the data

Peers – both suppliers and consumers As the number of nodes increases, the

bandwidth increases Reduces single point failures It is less secure Usually used for sharing of resources – files,

audio - visual media

BASED ON COMMUNICATION NETWORK : BUS – BASED INTERCONNECTION

Usually used in Point – Point connection systems

System connected by computer bus The access to communication media is time

shared IEEE 802 LAN Standard

Ethernet, Token Bus, Token Ring, Fiber Distributed data Interface (FDDI), Fiber Queue Dual Buses (FQDB)

BASED ON COMMUNICATION NETWORK : SWITCH – BASED INTERCONNECTION

Usually used in multi point connection systems

Systems connected by network switches The access to communication media is both

time and space shared – but cost equally higher than bus

Private switches – Crossbar, multistage switch

Public switch systems – Integrated Services Digital Network (ISDN), Asynchronous Transfer Mode (ATM

Switches in public networks also perform routing

BASED ON LEVEL OF COUPLING : LOOSELY COUPLED SYSTEMS

Each processor has its own memory Runs its own OS Do not communicate frequently Can be placed in geographically separate

regions Also called distributed computing

BASED ON LEVEL OF COUPLING : TIGHTLY COUPLED SYSTEMS

Processors share a common memory Run on a single OS Communicate very frequently Usually connected through high speed

connection methods Also called parallel computing

LEVEL OF COUPLING

Microprocessors Clusters LAN Global Internet

SmallFast

LargeSlow

More Tightly Coupled More Loosely Coupled

Closer in physical proximity Farther in physical proximity

GRID COMPUTING [3]

Complete nodes connected by a conventional network interface like Ethernet.

Not tightly coupled. Can be geographically diverse.

The communication is not high speed - works fine in environments that require less communication.

A single task is adequately parallelized and each part is given to a different node that computes it independently - so no concurrency issues involved.

CLOUD COMPUTING

WHAT IS CLOUD COMPUTING [4]

Parallel and distributed system consisting of a collection of inter-connected and virtualized computers

Presented to the user as a single computer Services provided:

Software as service Platform as service Infrastructure as service

Advantages Speed of Operation Power saving Abstraction Virtualization

EXAMPLES

FOLDING@HOME [6]

Grid computing project designed to perform computationally intensive simulations of protein folding and other molecular dynamics

The most powerful distributed computing cluster in the world – Guinness 2007

Primary contributors – thousands of everyday personal computers

Processes run in the background utilizing cpu idle time

In late March 2011 Folding@home briefly peaked above the 7 native petaFLOP barrier.

WINDOWS AZURE PLATFORM [7]

On demand platform used to build, host and scale web applications through windows datacenter.

Platform as a service Build, host and maintain web applications

running on Microsoft Datacenter OS – Windows Azure Services

Live Services SQL Azure AppFabric SharePoint Services Dynamic CRM Services

FUTURE…

FUTURE OF DISTRIBUTED COMPUTING…

An expanded peer - peer network with every personal computer interconnected with every other.

Utilization of CPU cycles and hard disks during idle time

Improvements in security and performance that void the need for a centralized control server and a data center

REFERENCES

[1] http://en.wikipedia.org/wiki/Distributed_computing#Architectures

[2] http://en.wikipedia.org/wiki/Grid_computing [3] http://en.wikipedia.org/wiki/Cloud_computing [4] Ghosh, Anup; Arce, Ivan; , "Guest Editors'

Introduction: In Cloud Computing We Trust - But Should We?," Security & Privacy, IEEE , vol.8, no.6, pp.14-16, Nov.-Dec. 2010doi: 10.1109/MSP.2010.177

[5] http://en.wikipedia.org/wiki/Folding@Home [6] http://en.wikipedia.org/wiki/Blue_Gene/ [7] http://en.wikipedia.org/wiki/Windows_Azure

THANK YOU!