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

IF 0.6 Q4 COMPUTER SCIENCE, THEORY & METHODS
Minakshi Sharma, Rajneesh Kumar, Anurag Jain
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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.
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。
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来源期刊
CiteScore
1.70
自引率
10.00%
发文量
24
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