Optimal Approach for Tasks Allocation Based on Fusion of Unallocated Tasks in Distributed Systems
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Abstract
Distributed Computing Systems (DCS) have become a key platform in order to achieve optimal cost by allocating number of tasks to different processors for execution in task allocation problems. The tasks allocation is an essential phase in DCS. Efficient use of available processors enhances the performances of the distributed systems and provide optimal results. In this paper we presents a new mathematical model consisting of a set of m tasks to n processors (where, m >> n) which performs static allocation in such a manner that maximizes the overall throughput of the system and optimizes the overall system cost. The heuristic model deals with the load balancing and optimal tasks allocation by the fusion of the unallocated tasks with the other allocated tasks. The suggested algorithm is capable enough to obtain the minimum average fused cost, the overall optimal cost, mean service rate and the total throughput of the system. Keywords: DCS, Task Allocation, Parallel Computation, EC, ITCC, Processors Utilization, Throughput, Load Balancing.
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