COCA:用于数据中心成本最小化和碳中和的在线分布式资源管理

Shaolei Ren, Yuxiong He
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引用次数: 32

摘要

由于巨大的能源消耗和相关的环境问题,数据中心受到越来越大的压力,需要将长期净碳足迹减少到零,即碳中和。在本文中,我们提出了一种称为COCA(优化成本最小化和碳中和)的在线算法,用于最小化数据中心运营成本,同时在没有长期未来信息的情况下满足碳中和。与现有的研究不同,COCA支持分布式服务器级资源管理:每个服务器自主调整其处理速度,并以最佳方式决定要处理的工作负载量。我们证明,与具有未来信息的最优算法相比,COCA实现了接近最小的运行成本(包括电力和延迟成本),同时限制了可能违反碳中和的行为。我们还进行了基于痕量的模拟研究来补充分析,结果表明,COCA将成本降低了25%以上(与最先进的技术相比),同时减少了碳足迹。
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COCA: Online distributed resource management for cost minimization and carbon neutrality in data centers
Due to the enormous energy consumption and associated environmental concerns, data centers have been increasingly pressured to reduce long-term net carbon footprint to zero, i.e., carbon neutrality. In this paper, we propose an online algorithm, called COCA (optimizing for COst minimization and CArbon neutrality), for minimizing data center operational cost while satisfying carbon neutrality without long-term future information. Unlike the existing research, COCA enables distributed server-level resource management: each server autonomously adjusts its processing speed and optimally decides the amount of workloads to process. We prove that COCA achieves a close-to-minimum operational cost (incorporating both electricity and delay costs) compared to the optimal algorithm with future information, while bounding the potential violation of carbon neutrality. We also perform trace-based simulation studies to complement the analysis, and the results show that COCA reduces cost by more than 25% (compared to state of the art) while resulting in a smaller carbon footprint.
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