Authors: Jyoti Thaman; Manpreet Singh
Addresses: Department of Computer Science & Engineering, MM University, Ambala, Haryana 134003, India ' Department of Computer Science & Engineering, MM University, Ambala, Haryana 134003, India
Abstract: Cloud computing is the most recent computing paradigm where IT services are provided and delivered over the internet on demand. With increasing demand for cloud services models, some new challenges in cloud computing are also gaining importance. Increasing energy concern has not even spared cloud environment for considering energy conscious solutions. The scheduling problem for cloud environment has a lot of awareness as the cloud subscriber's tasks could be mapped to the available resources to achieve better results. Traditional heuristics are popularly used to obtain schedules for given tasks and resources. Best efforts results from these heuristics depend upon the tasks and resources at disposal. Meta-heuristic-based scheduling solutions are iteration-based solutions. Meta-heuristic performs search over solution space and converges in minimum number of iterations. A novel heuristic Nearest Neighbour (NN) and a hybrid variant of Particle Swarm Optimisation (PSO) as Nearest Neighbour Cost-Aware PSO (NNCA_PSO) have been proposed and implemented in this paper. Performance of NNCA_PSO has been evaluated for various parameters like makespan, energy consumption, utilisation and economic efficiency. NNCA_PSO has been proved to be stable like PSO and finds near-optimal solutions.
Keywords: makespan; energy efficiency; cost-aware; heuristic; scheduling; adaptive; optimisation; swarm; hybrid; nearest neighbour; objective function.
International Journal of Grid and Utility Computing, 2017 Vol.8 No.3, pp.241 - 253
Received: 19 Aug 2015
Accepted: 06 Mar 2016
Published online: 31 Oct 2017 *