Cost Optimization Technique of Task Allocation in Heterogeneous Distributed Computing System

A Distributed Computing System (DCS) is a network of workstations, personal computer and /or other computing systems. Such system may be heterogeneous in the sense that the computing nodes may have different speeds and memory capacities. A DCS accepts tasks from users and executes different modules of these tasks on various nodes of the system. Task allocation in a DCS is a common problem and a good number of task allocation algorithms have been proposed in the literature. In such environment an application runs in a DCS can be accessible on every node present within the DCS. In such cases if number of tasks is less than or equal to available processors in the DCS, we can assign these task without any trouble. But this allocation becomes complicated when numbers of tasks are greater than the numbers of processors. The problem of task allocation for processing of ‘m’ tasks to ‘n’ processors (m>n) in a DCS is addressed here through a new modified tasks allocation technique. The model, presented in this paper allocates the tasks to the processor of different processing capacity to increase the performance of the DCS. The technique presented in this paper is based on the consideration of processing cost of the task to the processors. We have tried a new technique to assign all the tasks as per the required availability of processors and their processing capacity so that all the tasks of application get execute in the DCS.