Metaheuristic Approach for Scheduling Real-Time Tasks to the Heterogeneous Processors
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Abstract
In this paper, we addressed the problem of partitioning periodic real-time tasks in a Heterogeneous multiprocessor platform by considering both timing constraints and energy consumption perspectives: our objective is to compute the feasible partitioning solution that results in reducing energy consumption on heterogeneous processors by using advance ant colony optimization. A local search heuristic and Max-Min Ant System can be used in Advance Ant Colony Optimization to improve the task assignment solution in term of both resource utilization and energy consumption. AACO can also provides task priority for an independent task .Extensive Java Agent Development Framework (JADE) multi agent simulator results clearly show that the proposed approach provides more approximate, effective and efficient way for reducing its energy consumption.
Keywords: - Task Scheduling, Heterogeneous Processors, Ant Colony Optimization, Local search Heuristic, Max-Min Ant System.
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