Abstract
Cloud computing has gained momentum in the recent times, due to the features it provides, like rapid elasticity and on-demand service. It involves the interaction between the user and a Resource Broker. The Resource Broker accepts the user jobs along with the requirements, and provides the results and the status of the job back to the user. The user jobs can be data intensive or computational intensive. The resource is allocated according to the type of the user job. The proposed Particle Swarm Optimization technique with migration optimizes the allocation process using computation and network based parameters. Migration efficiently eliminates the problems of over-utilization of resources. The clustering of virtual machines has also been explored in two dimensions namely resource clustering and idle clustering to increase the utilization of resources.
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Valliyammai, C., Mythreyi, R. (2019). A Dynamic Resource Allocation Strategy to Minimize the Operational Cost in Cloud. In: Abraham, A., Dutta, P., Mandal, J., Bhattacharya, A., Dutta, S. (eds) Emerging Technologies in Data Mining and Information Security. Advances in Intelligent Systems and Computing, vol 755. Springer, Singapore. https://doi.org/10.1007/978-981-13-1951-8_28
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DOI: https://doi.org/10.1007/978-981-13-1951-8_28
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