MATRUSRI ENGINEERING COLLEGE�DEPARTMENT OF COMPUTER SCIENCE AND ENGINEERING

SUBJECT NAME: DISTRIBUTED SYSTEMS

CLASS : BE VII SEMESTER

FACULTY NAME: A V MURALI KRISHNA

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UNIT-1

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Introduction: Characteristics & Properties OF Distributes Systems – Taxonomy - Types OF Distributed Systems Design GOALS – Transparency Issues.

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Architectures: Architectural Styles, System Architectures, Architectures VERSUS Middleware, AND Selfmanagement IN Distributed Systems. Processes: Threads, Virtualization, Software Agents, Clients, Servers, AND Code Migration

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Communication: Inter PROCESS COMMUNICATION Mechanisms,remote Procedure Call, Remote Method Invocation, Message-oriented Communication, Stream- Oriented Communication, AND Multicast Communication.

Syllabus

INTRODUCTION:��

PRELIMINARY CONCEPTS

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OUTCOMES:

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A distributed system in its most simplest definition is a group of computers working together as to appear as a single computer to the end-user.

These machines have a shared state, operate concurrently and can fail independently without affecting the whole system’s uptime

In Distributed Systems this course, you will learn a range of fundamental and applied techniques in distributed systems. The learning objectives for Distributed Systems are:�1. Apply knowledge of distributed systems techniques and methodologies.

2. Explain the design and development of distributed systems and distributed

systems applications.

3.To communicate that design to others.

CONTENTS:�1) Characterstics Of Distributed Systems�2) Types Of Distributed Systems

OUTCOMES:

One of the great benefits  that it provides interoperable communications between all types of hardware and all kinds of operating systems.

MODULE-I

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Definition of a Distributed System

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A distributed system is:

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A collection of independent computers �that appears to its users �as a single coherent system

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Definition of a Distributed System

A distributed system organized as middleware. �The middleware layer extends over multiple machines, �and offers each application the same interface

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Goals of Distributed Systems

• Easily Connect Users/Resources
• Exhibit Distribution Transparency
• Support Openness
• Be Scalable:
• in size
• geographically
• administratively

Looking at these goals helps use answer the question: “Is building a distributed system worth the effort?”

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Transparency in a Distributed System

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Scalability Limitations

Examples of scalability limitations

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Scaling Techniques (1)

1.4

The difference between letting (a) a server �or (b) a client check forms as they are being filled

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Scaling Techniques (2)

1.5

An example of dividing the DNS name space into zones

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Characteristics of decentralized algorithms:

• No machine has complete information about the system state.
• Machines make decisions based only �on local information.
• Failure of one machine does not ruin �the algorithm.
• There is no implicit assumption that a global clock exists.

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Pitfalls when Developing � Distributed Systems

• The network is reliable
• The network is secure
• The network is homogeneous
• The topology does not change
• Latency is zero
• Bandwidth is infinite
• Transport cost is zero
• There is one administrator

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Types of Distributed Systems

• Distributed Computing Systems

• High Performance Computing (HPC)

• Distributed Information Systems

• Transaction Processing Systems (TPS)
• Enterprise Application Integration (EAI)

• Distributed Pervasive Systems

• Ubiquitous Systems

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Clustered Systems Architecture

A. Frank - P. Weisberg

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Cluster Computing Systems

• Collection of similar workstations/PCs, closely connected by means of a high-speed LAN:
• Each node runs the same OS.
• Homogeneous environment
• Can serve as a supercomputer
• Excellent for parallel programming
• Examples: Linux-based Beowulf clusters, MOSIX (from Hebrew University).

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Architecture for Cluster Computing System

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Cluster Configurations

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Grid Computing Systems

• Collection of computer resources, usually owned by multiple parties and in multiple locations, connected together such that users can share access to their combined power:
• Can easily span a wide-area network
• Heterogeneous environment
• Crosses administrative/geographic boundaries
• Supports Virtual Organizations (VOs)
• Examples: EGEE - Enabling Grids for E-SciencE (Europe), Open Science Grid (USA).

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Architecture for Grid Computing Systems

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Cloud Computing Systems (1)

• Collection of computer resources, usually owned by a single entity, connected together such that users can lease access to a share of their combined power:
• Location independence: the user can access the desired service from anywhere in the world, using any device with any (supported) system.
• Cost-effectiveness: the whole infrastructure is owned by the provider and requires no capital outlay by the user.
• Reliability: enhanced by way of multiple redundant sites, though outages can occur, leaving users unable to remedy the situation.

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Cloud Computing Systems (2)

• Scalability: user needs can be tailored to available resources as demand dictates – cost benefit is obvious.
• Security: low risk of data loss thanks to centralization, though problems with control over sensitive data need to be solved.
• Readily consumable: the user usually does not �need to do much deployment or customization, �as the provided services are easy to adopt and ready-to-use.
• Examples: Amazon EC2 (Elastic Compute Cloud), Google App Engine, IBM Enterprise Data Center, �MS Windows Azure, SUN Cloud Computing.

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Transaction Processing Systems (TPS)

The role of a TP monitor in distributed systems

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Enterprise Application Integration

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