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  • 标题:A Comparative Study on Various Scheduling Algorithms in Cloud Environment
  • 本地全文:下载
  • 作者:P Kowsik ; K.Rajakumari
  • 期刊名称:International Journal of Innovative Research in Computer and Communication Engineering
  • 印刷版ISSN:2320-9798
  • 电子版ISSN:2320-9801
  • 出版年度:2014
  • 卷号:2
  • 期号:11
  • 出版社:S&S Publications
  • 摘要:Cloud computing is an emerging technology and it allows users to pay as you need and has the highperformance. Cloud computing is a heterogeneous system as well and it holds large amount of application data. In theprocess of scheduling some intensive data or computing an intensive application, it is acknowledged that optimizing thetransferring and processing time is crucial to an application program. Due to novelty of cloud computing field, there isno many standard task scheduling algorithm used in cloud environment. Especially that in cloud, there is a highcommunication cost that prevents well known task schedulers to be applied in large scale distributed environment.Today, researchers attempt to build job scheduling algorithms that are compatible and applicable in Cloud Computingenvironment Job scheduling is most important task in cloud computing environment because user have to pay forresources used based upon time. Hence efficient utilization of resources must be important and for that schedulingplays a vital role to get maximum benefit from the resources. In this paper we have surveyed different types ofscheduling algorithms and tabulated their various parameters, scheduling factors and so on. Existing workflowscheduling algorithms does not consider reliability and availability. In this paper presents a novel heuristic schedulingalgorithm, called hyper-heuristic scheduling algorithm (HHSA), to find better scheduling solutions for cloud computingsystems. The results show that HHSA can significantly reduce the makespan of task scheduling compared with theother scheduling algorithms.
  • 关键词:Cloud Computing; Particle Swarm; Optimization; Simulated Annealing; Improved Particle; Swarm;Optimization; Proposed Algorithm; scheduling; Heuristic Algorithm
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