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Energy and Network Aware Workload Management for Sustainable Data Centers with Thermal Storage

机译:具有热存储功能的可持续数据中心的能源和网络感知工作负载管理

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Reducing the carbon footprint of data centers is becoming a primary goal of large IT companies. Unlike traditional energy sources, renewable energy sources are usually intermittent and unpredictable. How to better utilize the green energy from these renewable sources in data centers is a challenging problem. In this paper, we exploit the opportunities offered by geographical load balancing, opportunistic scheduling of delay-tolerant workloads, and thermal storage management in data centers to facilitate green energy integration and reduce the cost of brown energy usage. Moreover, bandwidth cost variations between users and data centers are considered. Specifically, this problem is first formulated as a stochastic program, and then, an online control algorithm based on the Lyapunov optimization technique, called Stochastic Cost Minimization Algorithm (SCMA), is proposed to solve it. The algorithm can enable an explicit trade-off between cost saving and workload delay. Numerical results based on real-world traces illustrate the effectiveness of SCMA in practice.
机译:减少数据中心的碳足迹已成为大型IT公司的主要目标。与传统能源不同,可再生能源通常是间歇性且不可预测的。如何更好地利用数据中心这些可再生资源的绿色能源是一个具有挑战性的问题。在本文中,我们利用地理负载平衡,容错工作负载的机会性调度以及数据中心中的热量存储管理提供的机会,以促进绿色能源集成并降低棕色能源的使用成本。而且,考虑了用户和数据中心之间的带宽成本变化。具体来说,首先将该问题表述为一个随机程序,然后提出一种基于Lyapunov优化技术的在线控制算法,称为随机成本最小化算法(SCMA)。该算法可以在节省成本和工作负载延迟之间进行明确的权衡。基于实际轨迹的数值结果说明了SCMA在实践中的有效性。

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