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Managing Server Energy and Operational Costs in Hosting Centers

机译:在托管中心管理服务器能源和运营成本

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The growing cost of tuning and managing computer systems is leading to out-sourcing of commercial services to hosting centers. These centers provision thousands of dense servers within a relatively small real-estate in order to host the applications/services of different customers who may have been assured by a service-level agreement (SLA). Power consumption of these servers is becoming a serious concern in the design and operation of the hosting centers. The effects of high power consumption manifest not only in the costs spent in designing effective cooling systems to ward off the generated heat, but in the cost of electricity consumption itself. It is crucial to deploy power management strategies in these hosting centers to lower these costs towards enhancing profitability. At the same time, techniques for power management that include shutting down these servers and/or modulating their operational speed, can impact the ability of the hosting center to meet SLAs. In addition, repeated on-off cycles can increase the wear-and-tear of server components, incurring costs for their procurement and replacement. This paper presents a formalism to this problem, and proposes three new online solution strategies based on steady state queuing analysis, feedback control theory, and a hybrid mechanism borrowing ideas from these two. Using real web server traces, we show that these solutions are more adaptive to workload behavior when performing server provisioning and speed control than earlier heuristics towards minimizing operational costs while meeting the SLAs.
机译:调整和管理计算机系统的成本不断增长,导致将商业服务外包给托管中心。这些中心在相对较小的房地产中提供数千个密集服务器,以托管可能已通过服务级别协议(SLA)保证的不同客户的应用程序/服务。这些服务器的功耗正成为托管中心的设计和运营中的一个严重问题。高功耗的影响不仅体现在设计有效的冷却系统以抵御产生的热量上所花费的成本,而且还体现在电力消耗本身的成本上。在这些托管中心部署电源管理策略以降低这些成本以提高盈利能力至关重要。同时,用于电源管理的技术(包括关闭这些服务器和/或调节其运行速度)可能会影响托管中心满足SLA的能力。此外,重复的开关周期会增加服务器组件的磨损,从而增加其采购和更换成本。本文提出了解决该问题的形式,并基于稳态排队分析,反馈控制理论和从这两者借鉴的混合机制,提出了三种新的在线解决方案策略。通过使用真实的Web服务器跟踪,我们显示出这些解决方案在执行服务器配置和速度控制时比早期的启发式方法更能适应工作负载行为,从而在满足SLA的同时将运营成本降至最低。

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