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An Efficient Task Scheduling of Multiprocessor Using Genetic Algorithm Based on Task Height

Ashish Sharma and Mandeep Kaur

Static task scheduling in multiprocessor frameworks is one of the well-defined NP hard problem. Due to optimal utilization of processors and in addition investing less time, the scheduling of tasks in multiprocessor frameworks is of extraordinary significance. To solve NP hard problem using traditional strategies takes reasonable measures of time. Over the time, various heuristic procedures were presented for comprehending it. Therefore, heuristic methods such as genetic algorithms are appropriate methods for task scheduling in multiprocessor system. In this paper, a new GA for static task scheduling in multiprocessor systems has been presented whose priority of tasks’ execution is based on the height of task in graph and other mentioned parameters and then scheduling is performed. This proposed method is simulated and then compared with basic genetic algorithm.