What is System Definition A system is a

What is System � Definition “A system is a set of principles or procedures according to which something is done; an organized scheme or method that is called System. ”

What Is Distributed System � Definition: �A Distributed System is collection of number of computers that are connected through a networks and communicate and coordinate their action by passing messages.

Examples of Distributed System � Internet � Intranet � ATM Machines � Networks of Workstations “The Sharing of Resources is main motivation for Constructing Distributed System”.

Features of Distributed System � Concurrency v Number of Program is executed concurrently. � No global clock v Not require any global clock for sharing resources between users. � Scalability v Addition of more resources to increase performance or availability � Functional Separation v Each system have different functionality and service. � Independent Failure v Machine connected in a distributed system may fail independently. But failure will not affect the running of other components.

Features of Distributed system(Cont. ) � Inherent distribution v Information, people and system are inherently distributed. � Reliability v If one machine crashes, the system as a whole can still survive. � Economy v Sharing of resources by many entities help to reduce the cost of ownership. � Diversity v Many types of machines are present in a distributed system. � Decentralization v No single point of Control

Nodes of Distributed System � What is Node? v Definition Node is point where any system can transmit, receive and retransmit the information to other system in a networks. � Types of Nodes: - Ø Client Ø Server Ø Peer

Nodes of Distributed System(Cont. ) Ø Client Any device that make a request is termed as client. Ø Fat Client It is known as rich client that have personal computer and laptop can operate independently. Ø Thin Client It is known as poor client that use resources of host computer. Ø Hybrid Client It is a combination or mixture of fat and thin client Ø Server is provide the response to those client that make request. Ø Peer is capable for sending, receiving and resending the information among the networks.

Distributed Computing & It’s Paradigms � Definition �A problem is divided into many tasks, each tasks that is solved by one or more computers that is called distributed computing.

The Message Passing Paradigm A process sends a message representing a request. � The message is delivered to a receiver, which processes the request, and sends a message in response. � In turn, the reply may trigger a further request, which leads to a subsequent reply, and so forth. �

The Client-Server Paradigm � � � The client-server model assigns asymmetric roles to two collaborating processes i. e. client & Server. The server plays the role of a service provider which waits passively for the arrival of requests. The client issues specific requests to the server and awaits response.

The Message System Paradigm � � A message system serves as an intermediary among separate, independent processes. The message system acts as a switch for messages, through which processes exchange messages asynchronously. A sender deposits a message with the message system, which forwards it to a message queue associated with each receiver. Once a message is sent, the sender is free to move on to other tasks.

Remote Procedure Call(RPC) A RPC involves two independent processes. � A process, A, wishing to make a request to another process, issues a procedure call to B, passing with the call a list of argument values. � In local procedure calls, a RPC triggers a predefined action in a procedure provided by process B. � At the completion of the procedure, process B returns a value to process A. �

Remote Method Invocation (RMI) Remote method invocation is the object-oriented equivalent of remote method calls. � In this model, a process invokes the methods in an object, which may reside in a remote host. � As with RPC, arguments may be passed with the invocation. �

The Network Services Paradigm Service providers register themselves with directory servers on a network. � A process desiring a particular service contacts the directory server at run time, and � If the service is available, will be provided a reference to the service. � if the service is available, will be provided a reference to the service. �

The Object Request Broker Paradigm(ORB) In ORB paradigm, an application issues requests to an object request broker (ORB). � ORB directs the request to an appropriate object that provides the desired service. � Because the ORB contain the object service reference. �

The Object Space Paradigm The object space paradigm assumes the existence of logical entities known as object spaces. � The participants of an application converge in a common object space. � A provider places objects as entries into an object space, and � � The requesters who subscribe to the space access the entries.

The Mobile Agent Paradigm A mobile agent is a transportable program or object. � In this model, an agent is launched from an originating host. � The agent travels from host to host according to an itinerary that it carries. � At each stop, the agent accesses the necessary resources or services, and performs the necessary tasks to accomplish its mission. �

Models of distributed System � Definition: - �It is represent that how the component of the system is connected and coordinate their action by passing message. � Types of Models: - �Architecture Model It define the way in which the component of the system interact with one another. �Interaction Model It define the performance and with difficulty of setting time limits in a distributed system. �Failure Model It define a precise specification of the faults that can be exhibited by processes and communication channels.

Example of Architecture model 1. 2. 3. Client-server model Peer-to-Peer model Proxy server Model

Example of Interaction model � Synchronous interaction model �In it lower and upper bound on execution time of processes can be set. �Transmitted message are received within a known bounded time. � Asynchronous Interaction model �In asynchronous interaction model of distributed system has no bounds.

Example of Failure model � Omission Failure �It refer to case when a process or communication channel fail to perform action. � Timing Failure �It is applicable in synchronous distributed system where time limit are set on process execution time, message delivery time and clock drift rate. � Arbitrary Failure �It is also known as Byzantine failure that is used to describe the worst possible failure semantics in which any type of error may occur.