Abstract
In cloud Infrastructure as a Service (IaaS) environment, selecting the Virtual Machines (VM) from different data centers, with multiple objectives like reduction in response time, minimization in cost and energy consumption, is a complex issue due to the heterogeneity of the services in terms of resources and technology. The existing solutions are computationally intensive; rely heavily on obtaining single trade-off solution by aggregating multiple objectives in a priori fashion which inversely affects the quality of solution. This article describes the new hybrid multiobjective heuristic algorithm based on Non-dominated Sorting Genetic Algorithm-II (NSGA-II) and Gravitational Search Algorithm (GSA) called as NSGA-II & GSA to facilitate selection of VM for scheduling of an application. The simulation results show that the proposed algorithm outperforms and fulfills the prescribed objective as compared to other multiobjective scheduling algorithms.
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Naik, K., Meera Gandhi, G., Patil, S.H. (2019). Multiobjective Virtual Machine Selection for Task Scheduling in Cloud Computing. In: Verma, N., Ghosh, A. (eds) Computational Intelligence: Theories, Applications and Future Directions - Volume I. Advances in Intelligent Systems and Computing, vol 798. Springer, Singapore. https://doi.org/10.1007/978-981-13-1132-1_25
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DOI: https://doi.org/10.1007/978-981-13-1132-1_25
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