Authors: Paulraj Ranjithkumar; Sankaran Palani
Addresses: Department of Electronics and Communication Engineering, K.S. Rangasamy College of Technology, Tiruchengode, Tamil Nadu, India. ' Department of Electronics and Communication Engineering, K.S. Rangasamy College of Technology, Tiruchengode, Tamil Nadu, India
Abstract: Multiprocessors have emerged as a powerful computing means for running real-time applications, especially where a uniprocessor system would not be sufficient to execute all the tasks. Such a computing environment requires an efficient algorithm to determine when and on which processor a given task should be executed. An efficient scheduling of parallel tasks onto the multiprocessors is known to be an NP-hard problem. This paper focuses on 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. 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 other and vice versa. The performance of the proposed algorithm with optimal solution is validated analytically and compared with Particle Swarm Optimisation (PSO) and Genetic Algorithm (GA).
Keywords: DVS; dynamic voltage scaling; evolutionary algorithms; energy minimisation; scheduling; multiprocessors; energy efficiency; combinatorial optimisation; energy consumption; schedule length; parallel tasks; particle swarm optimisation; PSO; genetic algorithms; GAs.
International Journal of Computer Applications in Technology, 2012 Vol.44 No.3, pp.217 - 225
Available online: 12 Sep 2012 *Full-text access for editors Access for subscribers Purchase this article Comment on this article