{"title":"Designing Low-Complexity Heavy-Traffic Delay-Optimal Load Balancing Schemes: Theory to Algorithms","authors":"Xingyu Zhou, Fei Wu, Jian Tan, Yin Sun, N. Shroff","doi":"10.1145/3219617.3219670","DOIUrl":null,"url":null,"abstract":"We establish a unified analytical framework for designing load balancing algorithms that can simultaneously achieve low latency, low complexity, and low communication overhead. We first propose a general class ¶ of load balancing policies and prove that they are both throughput optimal and heavy-traffic delay optimal. This class ¶ includes popular policies such as join-shortest-queue (JSQ) and power-of- d as special cases, but not the recently proposed join-idle-queue (JIQ) policy. In fact, we show that JIQ is not heavy-traffic delay optimal even for homogeneous servers. By exploiting the flexibility offered by the class ¶, we design a new load balancing policy called join-below-threshold (JBT-d), in which the arrival jobs are preferentially assigned to queues that are no greater than a threshold, and the threshold is updated infrequently. JBT-d has several benefits: (i) JBT-d belongs to the class ¶i and hence is throughput optimal and heavy-traffic delay optimal. (ii) JBT-d has zero dispatching delay, like JIQ and other pull-based policies, and low message overhead due to infrequent threshold updates. (iii) Extensive simulations show that JBT-d has good delay performance, comparable to the JSQ policy in various system settings.","PeriodicalId":210440,"journal":{"name":"Abstracts of the 2018 ACM International Conference on Measurement and Modeling of Computer Systems","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2017-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"22","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Abstracts of the 2018 ACM International Conference on Measurement and Modeling of Computer Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3219617.3219670","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 22
Abstract
We establish a unified analytical framework for designing load balancing algorithms that can simultaneously achieve low latency, low complexity, and low communication overhead. We first propose a general class ¶ of load balancing policies and prove that they are both throughput optimal and heavy-traffic delay optimal. This class ¶ includes popular policies such as join-shortest-queue (JSQ) and power-of- d as special cases, but not the recently proposed join-idle-queue (JIQ) policy. In fact, we show that JIQ is not heavy-traffic delay optimal even for homogeneous servers. By exploiting the flexibility offered by the class ¶, we design a new load balancing policy called join-below-threshold (JBT-d), in which the arrival jobs are preferentially assigned to queues that are no greater than a threshold, and the threshold is updated infrequently. JBT-d has several benefits: (i) JBT-d belongs to the class ¶i and hence is throughput optimal and heavy-traffic delay optimal. (ii) JBT-d has zero dispatching delay, like JIQ and other pull-based policies, and low message overhead due to infrequent threshold updates. (iii) Extensive simulations show that JBT-d has good delay performance, comparable to the JSQ policy in various system settings.