A QoS-Enabled Load Balancing Approach for Cloud Computing Environment Join Minimum Loaded Queue (JMLQ)

IF 0.6 Q4 COMPUTER SCIENCE, THEORY & METHODS International Journal of Grid and High Performance Computing Pub Date : 2022-01-01 DOI:10.4018/ijghpc.301587
Minakshi Sharma, Rajneesh Kumar, Anurag Jain
{"title":"A QoS-Enabled Load Balancing Approach for Cloud Computing Environment Join Minimum Loaded Queue (JMLQ)","authors":"Minakshi Sharma, Rajneesh Kumar, Anurag Jain","doi":"10.4018/ijghpc.301587","DOIUrl":null,"url":null,"abstract":"Cloud computing delivers the on-demand virtualized resources to its consumer for servicing their request on a metered basis. During the high demand of cloud resources the load on system increases that may unbalance the system which affects the quality of service parameters (QoS) adversely that leads to violations of service level agreement (SLA). Role of load balancing is significant in such an environment as it enhances the distribution of workload across multiple devices for example across network links, a cluster of servers, disk drives, etc. The present research work introduced a multi scheduler for balancing the load across the system that aims to optimize the QoS parameters such as response time, resource utilization, and the average waiting time by exploiting these virtual resources in the cloud environment. The performance of the proposed approach analyzed and tested in CloudSim that to optimize these parameters for the current approach. The authors found that our QoS enabled JMLQ approach achieved better results in comparison to our previous JMLQ approach and other variants.","PeriodicalId":43565,"journal":{"name":"International Journal of Grid and High Performance Computing","volume":"22 1","pages":"1-19"},"PeriodicalIF":0.6000,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Grid and High Performance Computing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.4018/ijghpc.301587","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"COMPUTER SCIENCE, THEORY & METHODS","Score":null,"Total":0}
引用次数: 1

Abstract

Cloud computing delivers the on-demand virtualized resources to its consumer for servicing their request on a metered basis. During the high demand of cloud resources the load on system increases that may unbalance the system which affects the quality of service parameters (QoS) adversely that leads to violations of service level agreement (SLA). Role of load balancing is significant in such an environment as it enhances the distribution of workload across multiple devices for example across network links, a cluster of servers, disk drives, etc. The present research work introduced a multi scheduler for balancing the load across the system that aims to optimize the QoS parameters such as response time, resource utilization, and the average waiting time by exploiting these virtual resources in the cloud environment. The performance of the proposed approach analyzed and tested in CloudSim that to optimize these parameters for the current approach. The authors found that our QoS enabled JMLQ approach achieved better results in comparison to our previous JMLQ approach and other variants.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
一种支持qos的云计算环境下加入最小负载队列(JMLQ)的负载均衡方法
云计算将按需虚拟化资源交付给用户,以便按计量的方式为其请求提供服务。在对云资源的高需求期间,系统的负载会增加,可能导致系统失衡,从而影响服务参数质量,导致SLA (service level agreement)失效。在这样的环境中,负载平衡的作用非常重要,因为它增强了跨多个设备(例如跨网络链接、服务器集群、磁盘驱动器等)的工作负载分布。本研究引入了一种用于系统负载平衡的多调度器,旨在通过利用云环境中的虚拟资源,优化响应时间、资源利用率和平均等待时间等QoS参数。在CloudSim中对所提出方法的性能进行了分析和测试,以优化当前方法的这些参数。作者发现,与之前的JMLQ方法和其他变体相比,启用QoS的JMLQ方法取得了更好的结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
CiteScore
1.70
自引率
10.00%
发文量
24
期刊最新文献
A Potent View on the Effects of E-Learning Pre-Cutoff Value Calculation Method for Accelerating Metric Space Outlier Detection A Security Method for Cloud Storage Using Data Classification An Energy-Efficient Multi-Channel Design for Distributed Wireless Sensor Networks On Allocation Algorithms for Manycore Systems With Network on Chip
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1