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Power aware virtual machine placement in IaaS cloud using discrete firefly algorithm by K. Balaji; P. Sai Kiran; M. Sunil Kumar is a Materials Science article available to read on EtoBox.

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Cloud Computing is a widely adopted computing model that offloads the in-house processing workloads to remote servers. In recent years, the adoption of cloud computing and related models have increased multifold. The cloud data center consumes an enormous amount of electricity and becomes a major issue for emitting greenhouse gases. The most important power conservation strategy used in IaaS cloud is scheduling the virtual machine appropriately into the physical servers to minimize the number active servers. As the number of active servers decreases, the power consumption of a data center will also decrease. The fundamental aim of the proposed work is to schedule the virtual machine as dense as possible in a minimal number of servers using the proposed modified discrete firefly algorithm for power consumption. The proposed algorithm will effectively explore the large search space to find a placement that uses minimal power consumption in the data centers. The proposed algorithm is executed to place virtual machines of various configurations in IaaS cloud and the results are compared with Genetic Algorithm and Particle Swarm Optimization shows its superiority. Keywords Virtual machi

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Author

K. Balaji; P. Sai Kiran; M. Sunil Kumar

Publisher

Springer Science and Business Media LLC

Published

2022

Language

EN

Field

Materials Science (Physical Sciences)