{"title":"A survey on variants of genetic algorithm for scheduling workflow of tasks","authors":"Bini Mariam Varghese, R. Raj","doi":"10.1109/ICONSTEM.2016.7560870","DOIUrl":null,"url":null,"abstract":"Scheduling is a vital issue in cloud computing in order to facilitate optimized usage of resources. Genetic algorithms are used in optimization techniques as they are class of heuristic approaches that have their inspirations from evolutionary ideas of natural evolution. The cloud scheduling optimization problem is modelled as a population of candidate solutions and the genetic algorithm is applied for benefitting the fittest candidates. This paper presents a broad overview on the formalization of works contributed by variants of Genetic Algorithm to the field of Scheduling which can be applied to cloud computing.","PeriodicalId":256750,"journal":{"name":"2016 Second International Conference on Science Technology Engineering and Management (ICONSTEM)","volume":"50 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"12","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 Second International Conference on Science Technology Engineering and Management (ICONSTEM)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICONSTEM.2016.7560870","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
Scheduling is a vital issue in cloud computing in order to facilitate optimized usage of resources. Genetic algorithms are used in optimization techniques as they are class of heuristic approaches that have their inspirations from evolutionary ideas of natural evolution. The cloud scheduling optimization problem is modelled as a population of candidate solutions and the genetic algorithm is applied for benefitting the fittest candidates. This paper presents a broad overview on the formalization of works contributed by variants of Genetic Algorithm to the field of Scheduling which can be applied to cloud computing.