{"title":"Simulation of self-stabilizing algorithms in distributed systems","authors":"M. Flatebo, A. Datta","doi":"10.1109/SIMSYM.1992.227579","DOIUrl":null,"url":null,"abstract":"The property of self-stabilization in distributed systems was originally introduced by Dijkstra (1974). Depending on the connectivity and propagation delay in the system, each machine gets a partial view of the global state. The set of global states can be split up into two categories, legal and illegal. In a self-stabilizing system, regardless of the initial state of the system, legal or illegal, the system automatically converges to a legal state in a finite number of steps. Also, if an error occurs in the system causing the system to be put into an illegal state, the system again corrects itself and converges to a legal state in a finite amount of time. Many self-stabilizing algorithms have been developed, but the complexity of self-stabilizing algorithms is difficult to determine. This paper provides an experimental analysis of various self-stabilizing algorithms in order to help determine the efficiency of these algorithms and to compare algorithms which solve the same problem.<<ETX>>","PeriodicalId":215380,"journal":{"name":"Proceedings. 25th Annual Simulation Symposium","volume":"125 4 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1992-04-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"12","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings. 25th Annual Simulation Symposium","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SIMSYM.1992.227579","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 12
Abstract
The property of self-stabilization in distributed systems was originally introduced by Dijkstra (1974). Depending on the connectivity and propagation delay in the system, each machine gets a partial view of the global state. The set of global states can be split up into two categories, legal and illegal. In a self-stabilizing system, regardless of the initial state of the system, legal or illegal, the system automatically converges to a legal state in a finite number of steps. Also, if an error occurs in the system causing the system to be put into an illegal state, the system again corrects itself and converges to a legal state in a finite amount of time. Many self-stabilizing algorithms have been developed, but the complexity of self-stabilizing algorithms is difficult to determine. This paper provides an experimental analysis of various self-stabilizing algorithms in order to help determine the efficiency of these algorithms and to compare algorithms which solve the same problem.<>