A New Hybrid Genetic Algorithm-based Approach for Critical Multiprocessor Real-Time Scheduling with Low Power Optimization

Abstract

This paper work deals with the presentation of an hybrid genetic approach which allocates and schedules, on a multiprocessor architecture, a system of real-time tasks while balancing the load on the processors. In addition, this hybrid heuristic approach takes into account the safety critical applications which is the focus of our work. We have carried out a performance analysis showing that the proposed hybrid genetic approach has results better than the classical GAs in terms of load balancing, minimum response time and good flexibility.