Abstract
This paper presents a Particle Swarm Optimization-based method for optimizing the energy consumption in data centers. A particle position is mapped on a data center configuration (i.e. allocation of virtual machines on the data center’s servers) which is evaluated using a fitness function that considers the energy consumed by the servers’ hardware resources and by the data center’s cooling system as evaluation criteria. The Particle Swarm Optimization-based method is triggered each time a workload arrives to be accommodated on the data center’s servers. The proposed method has been integrated in the CloudSim framework and has been evaluated on randomly generated logs.
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Pop, C.B., Chifu, V.R., Cozac, I.S.A., Antal, M., Pop, C. (2016). Optimizing the Data Center Energy Consumption Using a Particle Swarm Optimization-Based Approach. In: Altmann, J., Silaghi, G., Rana, O. (eds) Economics of Grids, Clouds, Systems, and Services. GECON 2015. Lecture Notes in Computer Science(), vol 9512. Springer, Cham. https://doi.org/10.1007/978-3-319-43177-2_12
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DOI: https://doi.org/10.1007/978-3-319-43177-2_12
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