P EMMANUEL NICHOLAS
Articles written in Sadhana
Volume 44 Issue 10 October 2019 Article ID 0215
The number of cloud users and their aspiration for completion of tasks at less energy consumption and operating cost are rapidly increasing. Hence, the authors of this paper aim to minimize the makespan and operating cost by optimally scheduling the tasks and allocating the resources of cloud service. The optimum task scheduling and resource allocation are obtained for each objective function using the simple genetic algorithm. Further, the non-dominated solutions of the dual objectives are obtained using the non-dominated sorting geneticalgorithm-II, the most successful multi-objective optimization technique. A complex cloud service problem consisting of ten tasks, fifteen subtasks and fifteen heterogeneous resources is considered to investigate the proposed method. The numerical results obtained in the single objective and multi objective optimizationproblems show that the makespan and the operating cost are significantly reduced using the simple genetic algorithm and a wide range of non-dominated solutions are obtained in the multi-objective optimization problem, by which the cloud users shall be benefitted to choose the most appropriate solution based on the otherdesign constraints they have.