云系统上分布式节点的并行模糊负载均衡算法

IF 0.6 Q4 COMPUTER SCIENCE, THEORY & METHODS
Mostefa Hamdani, Youcef Aklouf, Hadj Ahmed Bouarara
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引用次数: 1

摘要

云计算是一种IT组织概念,它将Internet置于业务活动的核心,允许其使用硬件资源。近年来,负载均衡一直是一个活跃的研究领域,并且在云环境中发挥了非常重要的作用。在这个领域有广泛的改进。在本文中,我们提出了一种新的负载均衡算法,该算法基于云平台中最近服务器的权重。我们使用模糊逻辑来表示不同节点的权重。此外,我们并行地实现了单独的请求,并使用令牌来高效地分派任务。实验结果表明,本文提出的方法在总体响应时间、数据中心处理时间、总虚拟机成本和总数据传输成本等方面有效地改善了负载均衡过程。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Parallel Fuzzy Load Balancing Algorithm for Distributed Nodes Over a Cloud System
Cloud Computing is an IT organization concept that places the Internet at the heart of business activity, allowing it to use hardware resources. In recent years, Load Balancing has been an active area of research, and has played a very important role in the case of the Cloud environment. There is a wide range of improvements in this arena. In this paper, we propose a new Load Balancing algorithm, based on the weights of the nearest servers in the cloud platform. We use the fuzzy logic to represent the weight of the different nodes. Moreover, we implement separate requests in parallel, and use a token to dispatch tasks efficiently. The several scenarios in this paper are considered for experimentation and compare the result of existing Round Robin, Throttled Load Balancing, Equal Spread Load and proposed algorithm .The experiment results show that this approach improves the Load Balancing process effectively in terms of overall response time, data center processing time, total virtual machine cost, and total data transfer cost.
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来源期刊
CiteScore
1.70
自引率
10.00%
发文量
24
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