{"title":"Estimating task response time with contentions for real-time distributed systems","authors":"W. Chu, Chi-Man Sit","doi":"10.1109/REAL.1988.51122","DOIUrl":null,"url":null,"abstract":"Response time is affected by interprocessor communications, precedence relationships among the modules, module assignments, and processor scheduling policies. Furthermore, due to sharing of resources and data among the processors, contention delays are incurred. A task response time model that considers all these factors is proposed. A Petri net is used to represent resource contention, and the task control flow graph represents module precedence and logical relationships. A queuing network with resource contention is used to estimate the response time of each module. Module response time consists of delays at the processors and resource queues and is estimated by approximating the extended queuing network as independent finite capacity queuing systems. The module response time is mapped onto a control flow graph, and task response time is obtained by aggregating the module response times in accordance with their precedence relationship in the control flow graph. The task response time derived from the analytical model compares well with that from the simulation.<<ETX>>","PeriodicalId":116211,"journal":{"name":"Proceedings. Real-Time Systems Symposium","volume":"37 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1988-12-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"12","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings. Real-Time Systems Symposium","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/REAL.1988.51122","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
Response time is affected by interprocessor communications, precedence relationships among the modules, module assignments, and processor scheduling policies. Furthermore, due to sharing of resources and data among the processors, contention delays are incurred. A task response time model that considers all these factors is proposed. A Petri net is used to represent resource contention, and the task control flow graph represents module precedence and logical relationships. A queuing network with resource contention is used to estimate the response time of each module. Module response time consists of delays at the processors and resource queues and is estimated by approximating the extended queuing network as independent finite capacity queuing systems. The module response time is mapped onto a control flow graph, and task response time is obtained by aggregating the module response times in accordance with their precedence relationship in the control flow graph. The task response time derived from the analytical model compares well with that from the simulation.<>