A Multi-objective Hybrid Genetic Algorithm for Energy Saving Task Scheduling in CMP System

There are two important factors in the power-performance issues of chip multi-processor (CMP) system: the execution time of tasks and the system energy consumption. Most of exist energy saving methods are not designed to reduce the system energy while cut the execution time down. This paper represents a multi-objective hybrid genetic algorithm (MHGA) which can make the execution time of tasks minimize while reducing the system power consumption. We analyze the problem of energy saving task scheduling on CMP system and a novel coding scheme of genetic algorithm. Based on that, we improve the crossover and mutation operator of genetic algorithm. We propose the multi-objective genetic algorithm by using simulated annealing algorithm to enhance the search ability. Simulation results demonstrate that using our algorithm can make the efficiency of task scheduling on CMP increase, make both the execution time of task and energy consumption of system decrease.