Suppressing the Interference Within a Datacenter: Theorems, Metric and Strategy

doi:10.1109/TPDS.2024.3354418

	Suppressing the Interference Within a Datacenter: Theorems, Metric and Strategy
	Liu, Yuhang 1,2; Deng, Xin 1,2; Zhou, Jiapeng 1,2; Chen, Mingyu 1,2; Bao, Yungang 1,2
	2024-05-01
发表期刊	IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS
ISSN	1045-9219
卷号	35 期号:5 页码:732-750
摘要	As the paradigm of cloud computing, a datacenter accommodates many co-running applications sharing system resources. Although highly concurrent applications improve resource utilization, the resulting resource contention can increase the uncertainty of quality of services (QoS). Previous studies have shown that achieving high resource utilization and high QoS simultaneously is challenging. Moreover, quantifying the intensity of interference across multiple concurrent applications in a datacenter, where applications can be either latency-critical (LC) or best-effort (BE), poses a significant challenge. To address these issues, we propose Ah-Q, which comprises two theorems, a metric, and a scheduling strategy. First, we present the necessary and sufficient conditions to precisely test whether a datacenter is both QoS guaranteed and high-throughput. We also present a theorem that reveals the relationship between tail latency and throughput. Our theoretical results are insightful and useful for building datacenters that have desirable performance. Second, we propose the "System Entropy" (E-S) to quantitatively measure the interference within a datacenter. Interference arises due to resource scarcity or irrational scheduling, and effective scheduling can alleviate resource scarcity. To assess the effectiveness of a resource scheduling strategy, we introduce the concept of "resource equivalence". We evaluate various resource scheduling strategies to demonstrate the correctness and effectiveness of the proposed theory. Third, we introduce a new resource scheduling strategy, ARQ, that leverages both isolation and sharing of resources. Our evaluations show that ARQ significantly outperforms state-of-the-art strategies PARTIES and CLITE in reducing the tail latency of LC applications and increasing the IPC of BE applications.
关键词	Interference Tail Quality of service Entropy Throughput Cloud computing Resource management Datacenter high-throughput performance uncertainty quality of services (QoS) resource contention
DOI	10.1109/TPDS.2024.3354418
收录类别	SCI
语种	英语
资助项目	National Key Research and Development Program of China
WOS研究方向	Computer Science ; Engineering
WOS类目	Computer Science, Theory & Methods ; Engineering, Electrical & Electronic
WOS记录号	WOS:001189846600002
出版者	IEEE COMPUTER SOC
引用统计	被引频次：1[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://119.78.100.204/handle/2XEOYT63/38715
专题	中国科学院计算技术研究所期刊论文_英文
通讯作者	Liu, Yuhang
作者单位	1.Univ Chinese Acad Sci, Beijing 100190, Peoples R China 2.Chinese Acad Sci, Inst Comp Technol, Beijing 100045, Peoples R China
推荐引用方式 GB/T 7714	Liu, Yuhang,Deng, Xin,Zhou, Jiapeng,et al. Suppressing the Interference Within a Datacenter: Theorems, Metric and Strategy[J]. IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS,2024,35(5):732-750.
APA	Liu, Yuhang,Deng, Xin,Zhou, Jiapeng,Chen, Mingyu,&Bao, Yungang.(2024).Suppressing the Interference Within a Datacenter: Theorems, Metric and Strategy.IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS,35(5),732-750.
MLA	Liu, Yuhang,et al."Suppressing the Interference Within a Datacenter: Theorems, Metric and Strategy".IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS 35.5(2024):732-750.