Minimizing the operational cost of data centers via geographical electricity price diversity

Zichuan Xu, Weifa Liang

    Research output: Contribution to journalConference articlepeer-review

    25 Citations (Scopus)


    Data centers, serving as infrastructures for cloud services, are growing in both number and scale. However, they usually consume enormous amounts of electric power, which lead to high operational costs of cloud service providers. Reducing the operational cost of data centers thus has been recognized as a main challenge in cloud computing. In this paper we study the minimum operational cost problem of fair request rate allocations in a distributed cloud environment by incorporating the diversity of time-varying electricity prices in different regions, with an objective to fairly allocate requests to different data centers for processing while keeping the negotiated Service Level Agreements (SLAs) between request users and the cloud service provider to be met, where the data centers and web portals of a cloud service provider are geographically located in different regions. To this end, we first propose an optimization framework for the problem. We then devise a fast approximation algorithm with a provable approximation ratio by exploiting combinatorial properties of the problem. We finally evaluate the performance of the proposed algorithm through experimental simulation on real-life electricity price data sets. Experimental results demonstrate that the proposed algorithm is very promising, which not only outperforms other existing heuristics but also is highly scalable.

    Original languageEnglish
    Article number6676683
    Pages (from-to)99-106
    Number of pages8
    JournalIEEE International Conference on Cloud Computing, CLOUD
    Publication statusPublished - 2013
    Event2013 IEEE 6th International Conference on Cloud Computing, CLOUD 2013 - Santa Clara, CA, United States
    Duration: 27 Jun 20132 Jul 2013


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