Sharp Waiting-Time Bounds for Multiserver Jobs

Q1 Mathematics
Yige Hong, Weina Wang
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引用次数: 0

Abstract

Multiserver jobs, which are jobs that occupy multiple servers simultaneously during service, are prevalent in today’s computing clusters. But, little is known about the delay performance of systems with multiserver jobs. We consider queueing models for multiserver jobs in scaling regimes where the system load becomes heavy and meanwhile, the total number of servers in the system and the number of servers that a job needs become large. Prior work has derived upper bounds on the queueing probability in this scaling regime. However, without proper lower bounds, the existing results cannot be used to differentiate between policies. In this paper, we study the delay performance by establishing sharp bounds on the steady-state mean waiting time of multiserver jobs, where the waiting time of a job is the time spent in queueing rather than in service. We first characterize the exact order of the mean waiting time under the first come, first serve (FCFS) policy. Then, we prove a lower bound on the mean waiting time of all policies, which has an order gap with the mean waiting time under FCFS. We show that the lower bound is achievable by a priority policy that we call smallest need first (SNF).Funding: This research was supported in part by the National Science Foundation [Grant ECCS-2145713].Supplemental Material: The online appendix is available at https://doi.org/10.1287/stsy.2023.0006 .
多服务器工作的急剧等待时间界限
多服务器作业是指在服务过程中同时占用多个服务器的作业,在当今的计算集群中非常普遍。但是,人们对多服务器作业系统的延迟性能知之甚少。我们考虑了多服务器作业在系统负载变得很重,同时系统中服务器总数和作业所需的服务器数量变得很大的扩展状态下的排队模型。之前的工作已经推导出了这种扩展机制下的排队概率上限。但是,由于没有适当的下限,现有结果无法用于区分不同的策略。在本文中,我们通过建立多服务器作业稳态平均等待时间的尖锐界限来研究延迟性能,其中作业的等待时间是指排队时间,而不是服务时间。我们首先描述了先来先服务(FCFS)策略下平均等待时间的精确阶数。然后,我们证明了所有策略下平均等待时间的下限,该下限与 FCFS 下的平均等待时间存在阶差。我们证明,我们称之为 "最小需求优先(SNF)"的优先策略可以实现该下限:本研究得到了美国国家科学基金会[Grant ECCS-2145713]的部分资助:在线附录可在 https://doi.org/10.1287/stsy.2023.0006 上获取。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Stochastic Systems
Stochastic Systems Decision Sciences-Statistics, Probability and Uncertainty
CiteScore
3.70
自引率
0.00%
发文量
18
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