{"title":"Intelligent flow control algorithm for microservice system","authors":"Yudong Li, Yuqing Zhang, Zhangbing Zhou, LinLin Shen","doi":"10.1049/ccs2.12013","DOIUrl":null,"url":null,"abstract":"<p>In microservice systems, availability can be ensured through a variety of measures, such as fault tolerance and flow limiting, which are collectively called the flow control. In the current mainstream system design, the flow control rules are usually fixed and set manually, which cannot be dynamically adjusted according to the flow shape. The performance of the system is thus not fully explored. To mitigate this problem, an adaptive dynamic flow control algorithm is proposed. Based on the system's monitoring data and current flow, the algorithm calculates the flow-limiting threshold in real time, and then it implements fine-grained service adaptive flow control to improve the resource utilization. Experimental results show that the performance of the adaptive automatic flow control is better than that of the traditional static method on resource utilization.</p>","PeriodicalId":33652,"journal":{"name":"Cognitive Computation and Systems","volume":"3 3","pages":"276-285"},"PeriodicalIF":1.2000,"publicationDate":"2021-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ietresearch.onlinelibrary.wiley.com/doi/epdf/10.1049/ccs2.12013","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Cognitive Computation and Systems","FirstCategoryId":"1085","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1049/ccs2.12013","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE","Score":null,"Total":0}
引用次数: 1
Abstract
In microservice systems, availability can be ensured through a variety of measures, such as fault tolerance and flow limiting, which are collectively called the flow control. In the current mainstream system design, the flow control rules are usually fixed and set manually, which cannot be dynamically adjusted according to the flow shape. The performance of the system is thus not fully explored. To mitigate this problem, an adaptive dynamic flow control algorithm is proposed. Based on the system's monitoring data and current flow, the algorithm calculates the flow-limiting threshold in real time, and then it implements fine-grained service adaptive flow control to improve the resource utilization. Experimental results show that the performance of the adaptive automatic flow control is better than that of the traditional static method on resource utilization.