Abstract
Virtualization is the essence of cloud computing. It facilitates the providers by virtualizing the storage, servers and other resources which aids in providing the computing services on shared and demand basis via internet. Virtual machine allocation is critical to achieving this goal, which accounts for effective resource usage with minimum expenditure. An efficient allocation results in effective resource utilization thus reducing wastage. This article proposes a genetic-based method exploiting the dual chromosome representation technique. The primary objective is to lessen the imbalance in resource utilization by reducing resource wastage. Another aim is to limit the power usage of the data center by diminishing the active servers’ volume. Lastly, the algorithm is evaluated against other existing work corresponding to several metrics which is further supported by the simulation procedure. The analysis from the result obtained displays a better performance of the algorithm by improving resource wastage, active server’s volume, CPU, and memory utilization.
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Srivastava, A., Kumar, N. (2023). Virtual Machine Allocation Using Genetic-Based Algorithm in Cloud Infrastructure. In: Rawat, S., Kumar, S., Kumar, P., Anguera, J. (eds) Proceedings of Second International Conference on Computational Electronics for Wireless Communications. Lecture Notes in Networks and Systems, vol 554. Springer, Singapore. https://doi.org/10.1007/978-981-19-6661-3_24
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DOI: https://doi.org/10.1007/978-981-19-6661-3_24
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