QoS Promotion in Energy-Efficient Datacenters Through Peak Load Scheduling

QoS Promotion in Energy-Efficient Datacenters Through Peak Load Scheduling
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通过峰值负载调度提升节能数据中心的 QoS

DOI:
10.1109/tcc.2018.2886187
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发表时间:
2018-12
影响因子:
6.5
通讯作者:
Xiao Qin
Xiao Qin
中科院分区:
计算机科学2区
文献类型:
--
作者:
Cheng Hu;Yuhui Deng;Geyong Min;Ping Huang;Xiao Qin

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为了构建节能的数据中心,一种广泛使用的方法是根据需要动态地操纵可用硬件资源的数量。然而,当突发性工作负载出现时,需要额外的时间开销来进行资源调整,从而导致性能下降。为了探讨这个问题,我们提出了一个可理解的分析,在一个虚拟机的请求处理。从分析中,我们发现,当工作负载过载时(即,峰值负载出现),通过推迟一些请求的调度,可以大大增加QoS保证请求的数量。受此启发,我们提出了一个峰值负载调度控制(PLSC)的方法,以促进现代能源效率的网络中心的峰值负载的服务质量(QoS)。然而,峰值负载通常很难识别。为了克服这个困难,PLSC通过利用其维护的两层请求队列来跟踪驻留在VM中的请求数量。当数量超过VM的能力时,这意味着峰值负载出现。在这种情况下,PLSC将一些延迟容忍请求添加到辅助队列。辅助队列中的请求的调度以比主队列中的请求的优先级低的优先级来控制。通过将关键请求保留在主队列中,PLSC可以缩短关键请求的响应时间。此外,PLSC扩展了QoS保证请求的数量。通过模拟一个典型的节能数据中心,进行了全面的实验,以证明PLSC的有效性。实验结果表明,PLSC显着提高了工作负载的QoS,而对节能的影响可以忽略不计。
To build energy-efficient datacenters, one widely used way is to dynamically manipulate the quantity of available hardware resources on demand. However, when bursty workloads appear, additional time overhead is required for resource gearing, thus incurring a performance degradation. To explore this problem, we present an intelligible analysis on the request handing in a VM. From the analysis, we find that, when workloads are overloaded (i.e., peak loads appear), the number of QoS guaranteed requests can be greatly increased by deferring the scheduling of a few requests. Inspired by this finding, we propose a Peak Load Scheduling Control (PLSC) method to promote the Quality of Service (QoS) of peak loads for modern energy-efficient datacenters. However, peak loads are usually difficult to identify. To overcome this difficulty, PLSC tracks the number of requests residing in a VM by leveraging a two-tier request queue maintained by it. When the number exceeds the capability of the VM, it means that peak loads appear. In this case, PLSC adds some delay-tolerant requests to the secondary queue. The scheduling of requests in the secondary queue is controlled with a lower priority than that of requests in the primary queue. Sequentially, with critical requests maintained in the primary queue, PLSC shortens the response time of critical requests. In addition, PLSC expands the number of QoS-guaranteed requests. Comprehensive experiments are conducted to attest the effectiveness of PLSC, by simulating a typical energy-efficient datacenter. The experimental results show that PLSC significantly promotes the QoS of workloads with a negligible impact on energy saving.
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