Improving Task Division Algorithms Using Heuristic Algorithms

Information Technology

Scheduling task is one of the core steps to efficiently exploit the capabilities of heterogeneous distributed computing systems. Therefore using heuristic algorithms is a suitable approach in order to cope with its difficulty. Existing system make use of three heuristics such as minmin, maxmin and sufferage in assigning independent tasks to processors in heterogeneous computing systems. All three heuristics are known to run by assigning N tasks to K processors. Since this three heuristics in the system are further combine, obtaining two hybrid algorithms. The motivation behind the former hybrid algorithm is to address the drawback of MaxMin in solving problem instances with highly skewed cost distributions while also improving the running time performance of MaxMin. Furthermore the hybrid algorithm improves the running time performance of Sufferage without degrading its solution quality. Objectives of heuristic algorithms are increase in system throughput, efficiency and reduction in task completion time. But there is no need of checking time to complete the task to a processor. Instead of that in this proposed system a new algorithm is developed which is totally based on only load factor. Load on processor means checking how many other tasks the processor is currently executing. This will reduces the time required to complete the task without affecting on the throughput and efficiency.

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