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Geographical Load Balancing across Green Datacenters

Abstract : "Geographic Load Balancing" is a strategy for reducing the energy cost of data centers spreading across different terrestrial locations. In this paper, we focus on load balancing among micro-datacenters powered by renewable energy sources. We model via a Markov Chain the problem of scheduling jobs by prioritizing datacenters where renewable energy is currently available. Not finding a convenient closed form solution for the resulting chain, we use mean field techniques to derive an asymptotic approximate model which instead is shown to have an extremely simple and intuitive steady state solution. After proving, using both theoretical and discrete event simulation results, that the system performance converges to the asymptotic model for an increasing number of datacenters, we exploit the simple closed form model's solution to investigate relationships and trade-offs among the various system parameters.
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https://hal.inria.fr/hal-01413636
Contributor : Giovanni Neglia <>
Submitted on : Saturday, December 10, 2016 - 12:44:55 PM
Last modification on : Monday, March 29, 2021 - 2:47:23 PM
Long-term archiving on: : Tuesday, March 28, 2017 - 12:27:51 AM

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Giovanni Neglia, Matteo Sereno, Giuseppe Bianchi. Geographical Load Balancing across Green Datacenters. ACM SIGMETRICS Performance Evaluation Review, Association for Computing Machinery, 2016, Special issue on the 2016 Greenmetrics Workshop, 44 (2), pp.64 - 69. ⟨10.1145/3003977.3003998⟩. ⟨hal-01413636⟩

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