{"title":"Efficient CPU Scheduling: A Genetic Algorithm based Approach","authors":"Snehal Kamalapur, Neeta Deshpande","doi":"10.1109/ISAHUC.2006.4290681","DOIUrl":null,"url":null,"abstract":"Operating system's performance and throughput are highly affected by CPU scheduling. The scheduling is considered as an NP problem. An efficient scheduling improves system performance. This paper presents and evaluates a method for process scheduling. In this paper, we will discuss the use of genetic algorithms to provide efficient process scheduling. We will evaluate the performance and efficiency of the proposed algorithm in comparison with other deterministic algorithms by simulation. The results shows that proposed GA-based algorithm gives better performance measure. This paper attempts to present evaluation of proposed GA based scheduling against existing traditional algorithms.","PeriodicalId":165524,"journal":{"name":"2006 International Symposium on Ad Hoc and Ubiquitous Computing","volume":"21 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2006-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"10","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2006 International Symposium on Ad Hoc and Ubiquitous Computing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISAHUC.2006.4290681","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 10
Abstract
Operating system's performance and throughput are highly affected by CPU scheduling. The scheduling is considered as an NP problem. An efficient scheduling improves system performance. This paper presents and evaluates a method for process scheduling. In this paper, we will discuss the use of genetic algorithms to provide efficient process scheduling. We will evaluate the performance and efficiency of the proposed algorithm in comparison with other deterministic algorithms by simulation. The results shows that proposed GA-based algorithm gives better performance measure. This paper attempts to present evaluation of proposed GA based scheduling against existing traditional algorithms.