{"title":"A distributed quality of service-enabled load balancing approach for cloud environment","authors":"Minakshi Sharma, Rajneesh Kumar, Anurag Jain","doi":"10.1108/ijpcc-02-2021-0038","DOIUrl":null,"url":null,"abstract":"\nPurpose\nDuring high demand for the virtualized resources in cloud environment, efficient task scheduling achieves the desired performance criteria by balancing the load in the system.\n\n\nDesign/methodology/approach\nIt is a task scheduling approach used for load balancing in cloud environment. Task scheduling in such an environment is used for the task execution on a suitable resource by considering some parameters and constraints to achieve performance.\n\n\nFindings\nThe presented mechanism is an extension of the previous proposed work quality of service (QoS)-enabled join minimum loaded queue (JMLQ) (Sharma et al., 2019c). The proposed approach has been tested in the CloudSim simulator, and the results show that the proposed approach achieves better results in comparison to QoS-enabled JMLQ and its other variants in the cloud environment.\n\n\nOriginality/value\n90%\n","PeriodicalId":210948,"journal":{"name":"Int. J. Pervasive Comput. Commun.","volume":"10 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-02-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Int. J. Pervasive Comput. Commun.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1108/ijpcc-02-2021-0038","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
Purpose
During high demand for the virtualized resources in cloud environment, efficient task scheduling achieves the desired performance criteria by balancing the load in the system.
Design/methodology/approach
It is a task scheduling approach used for load balancing in cloud environment. Task scheduling in such an environment is used for the task execution on a suitable resource by considering some parameters and constraints to achieve performance.
Findings
The presented mechanism is an extension of the previous proposed work quality of service (QoS)-enabled join minimum loaded queue (JMLQ) (Sharma et al., 2019c). The proposed approach has been tested in the CloudSim simulator, and the results show that the proposed approach achieves better results in comparison to QoS-enabled JMLQ and its other variants in the cloud environment.
Originality/value
90%
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