International Journal of Computer Applications
Power efficient design of real-time embedded systems based on multiprocessors becomes more important as system functionality is increasingly realized through heuristic approaches. This paper targets energy-efficient scheduling of tasks over multiple processors, where tasks share a common deadline. It addresses the problem of energy-aware static partitioning of periodic real-time tasks on heterogeneous multiprocessor platforms. A modified particle swarm optimization variant based on priority assignment and min-min algorithms for task partitioning is proposed. The proposed approach aims to minimize the overall energy consumption, meanwhile avoid deadline violations.