Energy consumption and schedule length minimisation of multiprocessor systems using genetic algorithm

Multiprocessors have emerged as a powerful computing means for running real-time applications, especially where a uniprocessor system would not be sufficient enough to execute all the tasks. The high performance and reliability of multiprocessors have made them a powerful computing resource. Such computing environment requires an efficient algorithm to determine when and on which processor a given task should be executed. This paper focuses the combinational optimisation problem, namely, the problem of minimising schedule length with energy consumption constraint and the problem of minimising energy consumption with schedule length constraint for independent parallel tasks on homogeneous and heterogeneous multiprocessor computers. These problems emphasise the trade-off between power and performance and are defined such that the power-performance product is optimised by fixing one factor and minimising the other and vice versa. The performance of the proposed algorithm with optimal solution is validated analytically and compared with genetic algorithm.