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Operating Cost Reduction for Distributed Internet Data Centers

机译:分布式互联网数据中心的运营成本降低

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In order to provide low latency, pay-as-you-go infrastructure, Cloud service provider has built a large number of geo-distributed data centers. Nowadays, energy cost has become increasingly important fraction of data center operating cost. Researchers' attentions are attracted to propose many methods to reduce the electricity cost for data centers. However, another significant operating cost, Internet bandwidth cost, has been neglected. Because both the electricity prices and bandwidth prices are varied with time and regions, it is not easy to minimize the operating cost while response to workload timely. As a solution, based on Lyapunov optimization framework, we propose an online control policy to achieve close-to-optimal performance with tradeoff between cost and delay. The advantage of our solution is that we do not need any future knowledge on the stochastic model (e.g., bandwidth prices and electricity prices). The results from our simulations on real workload trace and price data demonstrated that our solution is effective.
机译:为了提供低延迟,支付代理基础架构,云服务提供商建立了大量地理分布式数据中心。如今,能源成本已经变得越来越重要的数据中心运营成本。研究人员的注意被吸引,提出了许多方法来降低数据中心的电力成本。但是,另一种显着的运营成本,互联网带宽成本被忽视。由于电价和带宽价格随时间和地区而异,因此在及时响应工作载荷时,并不容易降低运营成本。作为基于Lyapunov优化框架的解决方案,我们提出了一个在线控制政策,以在成本和延迟之间的权衡之间实现近似最佳性能。我们解决方案的优势在于我们不需要对随机模型的任何未来知识(例如,带宽价格和电力价格)。我们对真实工作量跟踪和价格数据的模拟的结果表明我们的解决方案是有效的。

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