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Cross Service Providers Workload Balancing for Data Centers in Deregulated Electricity Markets

机译:交叉服务提供商在解除管制电力市场中的数据中心工作负载均衡

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摘要

The emerging Internet of things and 5G applications boost a continuously increasing demand for data processing, which results in an enormous energy consumption of data centers (DCs). Considering that existing distributed geographical load balancing is approaching the limit in reducing the energy cost of DCs, cloud service providers (SPs) are motivated to pursue a higher level of cooperation. In this context, cross-SP workload balancing among the DCs operated by different SPs represents a future trend of the DC industry. This article investigates the optimal cross-SP workload balancing when it couples with the electricity markets. First, we assume that there is a central operator (CO) coordinating the DCs owned by various SPs. A noncooperative game is formulated to model the interaction between utilities and CO, which serves as a price maker. Under the centralized coordination of CO, an optimal solution is obtained with an iterative algorithm. Taking into account the computation and privacy issues, a decentralized algorithm is then proposed by utilizing techniques in a state-based potential game. Numerical results corroborate the effectiveness of the proposed algorithm. Simulations using Google workload trace show that the workload balancing among cross-SP DCs results in a lower DC operation cost than the existing price taker approach.
机译:新兴的东西和5G应用程序促进了对数据处理的不断增加的需求,这导致数据中心的巨大能量(DCS)。考虑到现有的分布式地理负荷平衡正在降低降低DCS能源成本的限制,云服务提供商(SPS)有动力追求更高的合作水平。在这种情况下,由不同SPS运营的DC之间的跨SP工作负载平衡代表了直流行业的未来趋势。本文通过电力市场耦合,调查最佳的Cross-SP工作量平衡。首先,我们假设有一个中央运算符(CO)协调各种SP拥有的DCS。非支持游戏制定以模拟公用事业和公司之间的互动,该公司用作价格制造商。在CO的集中协调下,用迭代算法获得最佳解决方案。考虑到计算和隐私问题,然后通过利用基于状态的潜在游戏中的技术来提出分散算法。数值结果证实了所提出的算法的有效性。使用Google Workload Trace的模拟显示Cross-SP DC之间的工作负载平衡导致DC运行成本低于现有的价格接受方法。

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