{"title":"设计新的周期任务调度算法LLF_DM,并与现有的EDF、LLF和DM算法进行比较","authors":"V. Prajapati, Apurva Shah, Prem Balani","doi":"10.1109/ISSP.2013.6526871","DOIUrl":null,"url":null,"abstract":"The most challenging part of scheduling in real time systems is to achieve successful completion of a job before its deadline. Mainly two categories of algorithms i.e. static and dynamic tried to achieve this but both categories failed either in under-loaded condition or in over-loaded condition. Dynamic algorithms achieve optimum results in under-loaded condition but fail to achieve the same in over-loaded condition. On the other side static algorithms do not achieve optimum performance in underloaded condition but perform well in over-loaded condition. So our idea behind designing new scheduling algorithm is to achieve optimum performance in under-loaded condition and to achieve high performance in over-loaded condition. To achieve this we schedule jobs according to dynamic scheduling algorithm LLF (Least Laxity First) when system is under-loaded and when system becomes overloaded we schedule jobs according to static algorithm DM (Deadline Monotonic). In this paper we have proposed a LLF_DM algorithm which achieves optimum performance in under-loaded condition and achieves very high performance in over loaded condition.","PeriodicalId":354719,"journal":{"name":"2013 International Conference on Intelligent Systems and Signal Processing (ISSP)","volume":"62 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":"{\"title\":\"Design of new scheduling algorithm LLF_DM and its comparison with existing EDF, LLF, and DM algorithms for periodic tasks\",\"authors\":\"V. Prajapati, Apurva Shah, Prem Balani\",\"doi\":\"10.1109/ISSP.2013.6526871\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The most challenging part of scheduling in real time systems is to achieve successful completion of a job before its deadline. Mainly two categories of algorithms i.e. static and dynamic tried to achieve this but both categories failed either in under-loaded condition or in over-loaded condition. Dynamic algorithms achieve optimum results in under-loaded condition but fail to achieve the same in over-loaded condition. On the other side static algorithms do not achieve optimum performance in underloaded condition but perform well in over-loaded condition. So our idea behind designing new scheduling algorithm is to achieve optimum performance in under-loaded condition and to achieve high performance in over-loaded condition. To achieve this we schedule jobs according to dynamic scheduling algorithm LLF (Least Laxity First) when system is under-loaded and when system becomes overloaded we schedule jobs according to static algorithm DM (Deadline Monotonic). In this paper we have proposed a LLF_DM algorithm which achieves optimum performance in under-loaded condition and achieves very high performance in over loaded condition.\",\"PeriodicalId\":354719,\"journal\":{\"name\":\"2013 International Conference on Intelligent Systems and Signal Processing (ISSP)\",\"volume\":\"62 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-03-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"6\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2013 International Conference on Intelligent Systems and Signal Processing (ISSP)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ISSP.2013.6526871\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 International Conference on Intelligent Systems and Signal Processing (ISSP)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISSP.2013.6526871","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Design of new scheduling algorithm LLF_DM and its comparison with existing EDF, LLF, and DM algorithms for periodic tasks
The most challenging part of scheduling in real time systems is to achieve successful completion of a job before its deadline. Mainly two categories of algorithms i.e. static and dynamic tried to achieve this but both categories failed either in under-loaded condition or in over-loaded condition. Dynamic algorithms achieve optimum results in under-loaded condition but fail to achieve the same in over-loaded condition. On the other side static algorithms do not achieve optimum performance in underloaded condition but perform well in over-loaded condition. So our idea behind designing new scheduling algorithm is to achieve optimum performance in under-loaded condition and to achieve high performance in over-loaded condition. To achieve this we schedule jobs according to dynamic scheduling algorithm LLF (Least Laxity First) when system is under-loaded and when system becomes overloaded we schedule jobs according to static algorithm DM (Deadline Monotonic). In this paper we have proposed a LLF_DM algorithm which achieves optimum performance in under-loaded condition and achieves very high performance in over loaded condition.