An Algorithm for Optimized Time, Cost, and Reliability in a Distributed Computing System

Distributed Computing System (DCS) refers to multiple computer systems working on a single problem. A distributed system consists of a collection of autonomous computers, connected through a network which enables computers to coordinate their activities and to share the resources of the system. In distributed computing, a single problem is divided into many parts, and each part is solved by different computers. As long as the computers are networked, they can communicate with each other to solve the problem. DCS consists of multiple software components that are on multiple computers, but run as a single system. The computers that are in a distributed system can be physically close together and connected by a local network, or they can be geographically distant and connected by a wide area network. The ultimate goal of distributed computing is to maximize performance in a time effective, cost-effective, and reliability effective manner. In DCS the whole workload is divided into small and independent units, called tasks and it allocates onto the available processors. It also ensures fault tolerance and enables resource accessibility in the event that one of the components fails. The problem is addressed of assigning a task to a distributed computing system. The assignment of the modules of tasks is done statically. We have to give an algorithm to solve the problem of static task assignment in DCS, i.e. given a set of communicating tasks to be executed on a distributed system on a set of processors, to which processor should each task be assigned to get the more reliable results in lesser time and cost. In this paper an efficient algorithm for task allocation in terms of optimum time or optimum cost or optimum reliability is presented where numbers of tasks are more then the number of processors.