Abstract
Cloud computing datacenters contain hundreds of servers that host different kinds of services for a wide spectrum of customers. These datacenters have substantial energy demands for their operation, thus promoting the need for optimizing their power consumption and energy demands. Resources allocation and optimized scheduling of incoming tasks are at the heart of any successful power management technique used for datacenters. In this work we focus on the efficient utilization of servers in the datacenter to optimize power consumption. The goal is to develop task allocation techniques that contributes to the overall optimization of energy demands by optimizing the consumption of the datacenter servers. The allocation problem is modeled using Integer Linear Programming (ILP) techniques, where models are formulated with the objective of minimizing the total power consumed by the active and idle cores of the servers. Preliminary results show that an optimization driven servers’ allocation strategy produces noticeable improvement in power consumption when compared to scheduling techniques such as round robin.
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Osman, A., Sagahyroon, A., Aburukba, R., Aloul, F. (2019). Towards Energy Efficient Servers’ Utilization in Datacenters. In: Arai, K., Bhatia, R., Kapoor, S. (eds) Intelligent Computing. CompCom 2019. Advances in Intelligent Systems and Computing, vol 997. Springer, Cham. https://doi.org/10.1007/978-3-030-22871-2_19
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DOI: https://doi.org/10.1007/978-3-030-22871-2_19
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