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Joint optimization of VM placement and request distribution for electricity cost cut in geo-distributed data centers

机译:联合优化VM布置和请求分配,以降低地理分布数据中心的用电成本

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The rising demand on cloud services has made the electricity cost become the main operational expenditure (OPEX) to data center providers. By exploring the geographical distribution feature of data centers and the electricity price diversity in modern multi-electricity market, data center resizing technique emerges as a promising solution to lowering the electricity cost. Since services are usually provided by leasing virtual machines (VMs) over geo-distributed data centers, the corresponding user requests must be distributed only to these VMs. This motivates us to study the electricity cost minimization problem with the joint consideration of VM placement, user request distribution and data center resizing in geo-distributed data centers with heterogeneous electricity prices. To the best of our knowledge, we are the first to study this optimization problem, which is formulated as a mixed-integer linear programming (MILP) problem and then solved by a computation-efficient heuristic algorithm in large-scale systems. The high efficiency of our proposal is validated by extensive simulation based studies.
机译:对云服务的不断增长的需求已使电力成本成为数据中心提供商的主要运营支出(OPEX)。通过探索数据中心的地理分布特征和现代多电市场中的电价多样性,数据中心调整大小技术成为降低电费的有前途的解决方案。由于服务通常是通过在地理分布的数据中心上租用虚拟机(VM)来提供的,因此相应的用户请求必须仅分配给这些VM。这促使我们结合VM的放置,用户请求分配和具有不同电价的地理分布数据中心中数据中心的大小的综合考虑来研究使电费最小化的问题。据我们所知,我们是第一个研究此优化问题的人,该问题被公式化为混合整数线性规划(MILP)问题,然后在大型系统中通过计算效率高的启发式算法进行求解。我们的建议的高效率已通过广泛的基于模拟的研究得到验证。

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