A renewable energy-aware power allocation for cloud data centers: A game theory approach

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TitreA renewable energy-aware power allocation for cloud data centers: A game theory approach
Type de publicationJournal Article
Year of Publication2021
AuteursBenblidia MAnis, Brik B, Esseghir M, Merghem-Boulahia L
JournalCOMPUTER COMMUNICATIONS
Volume179
Pagination102-111
Date PublishedNOV 1
Type of ArticleArticle
ISSN0140-3664
Mots-clésCloud data centers, game theory, Green Networking, Power dispatching, renewable energy, smart grid
Résumé

With the rapid emerging of Internet of Things (IoT) devices and the proliferation of cloud-based applications, the cloud computing industry is becoming a vital element for ensuring our daily services. However, cloud computing uses large scale data centers equipped with energy-hungry servers and huge power facilities that massively consume power. This presents a real challenge which can negatively influence the power grid, while exposing the environment to global warming issues. Therefore, minimizing cloud data center power consumption is a challenging problem and has to be addressed. In this paper, we look at renewable energy in the context of a smart grid-cloud architecture and investigate the issue of grid power dispatching to cloud data centers. Since cloud data centers have a non-cooperative nature regarding power demand from the power stations, we model our power allocation problem as a non-cooperative game. Afterwards, we prove the existence and the uniqueness of Nash equilibrium. Moreover, we formulate the payoff function of our game as a non-linear optimization problem before resolving it using Lagrange multipliers and Karush-Kuhn-Tucker (KKT) conditions. Thus, we determine the assigned optimal quantity to each data center based on three main criteria : renewable energy usage, number of critical running applications and workload charge. Extensive simulations are performed by comparing our scheme with an existing work. Results show that our scheme outperforms the comparing approach with a percentage of 31.2% in terms of power load rate and significantly reduces emissions of carbon dioxide.

DOI10.1016/j.comcom.2021.08.001