{"title":"An adaptive overload management strategy for periodic real-time tasks","authors":"Jiali Xia, Ze-yu Han, Hui Chen, Chengying Mao","doi":"10.1109/GRC.2009.5255050","DOIUrl":null,"url":null,"abstract":"By analyzing the relationships of preemption and abortion among the jobs of the real-time tasks, the overload management strategy (OMS) divides the jobs into two types: steady-finished-jobs and absolute-aborted-jobs. While scheduling the jobs, the steady-finished-jobs are released and the absolute-aborted-jobs are rejected. In this way, the cascaded preemption among the jobs could be avoided. Also, the system resource could be efficiently utilized. The results of the simulation show that, the OMS could adaptively deal with the static or dynamic task set. Additionally, by applying OMS, the scheduling algorithms can obviously improve the performance of the real-time system.","PeriodicalId":388774,"journal":{"name":"2009 IEEE International Conference on Granular Computing","volume":"23 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 IEEE International Conference on Granular Computing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/GRC.2009.5255050","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
By analyzing the relationships of preemption and abortion among the jobs of the real-time tasks, the overload management strategy (OMS) divides the jobs into two types: steady-finished-jobs and absolute-aborted-jobs. While scheduling the jobs, the steady-finished-jobs are released and the absolute-aborted-jobs are rejected. In this way, the cascaded preemption among the jobs could be avoided. Also, the system resource could be efficiently utilized. The results of the simulation show that, the OMS could adaptively deal with the static or dynamic task set. Additionally, by applying OMS, the scheduling algorithms can obviously improve the performance of the real-time system.
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