基于mean-variance的服务集群负载均衡方法

doi:10.11959/j.issn.1000-0801.2017027

电信科学 ›› 2017, Vol. 33 ›› Issue (1): 1-8.doi: 10.11959/j.issn.1000-0801.2017027

• 研究与开发 • 下一篇

基于mean-variance的服务集群负载均衡方法

包晓安,魏雪,陈磊,胡国亨,张娜

浙江理工大学，浙江杭州 310018
浙江理工大学，浙江杭州310018

修回日期:2017-01-09 出版日期:2017-01-01 发布日期:2017-06-04
作者简介:包晓安（1973-），男，浙江理工大学教授，主要研究方向为软件工程及软件测试、智能信息处理。|魏雪（1990-），女，浙江理工大学硕士生，主要研究方向为网关负载调度和智能优化算法。|陈磊（1992-），男，浙江理工大学硕士生，主要研究方向为智能信息处理及嵌入式设备视频采集。|胡国亨（1992-），男，浙江理工大学硕士生，主要研究方向为智能信息处理及物联网协议。|张娜（1977-），女，浙江理工大学副教授，主要研究方向为软件工程及软件性能分析、软件测试技术。
基金资助:
国家自然科学基金资助项目(61379036);国家自然科学基金资助项目(61502430);国家自然科学基金委中丹合作项目(61361136002);浙江省重大科技专项重点工业项目(2014C01047);浙江理工大学“521人才培养计划”基金资助项目

Load balancing method of service cluster based on mean-variance

Xiaoan BAO,Xue WEI,Lei CHEN,Guoheng HU,Na ZHANG

Zhejiang Sci-Tech University,Hangzhou 310018,China

Revised:2017-01-09 Online:2017-01-01 Published:2017-06-04
Supported by:
The National Natural Science Foundation of China(61379036);The National Natural Science Foundation of China(61502430);China-Denmark Cooperation Program of the National Natural Science Foundation of China(61361136002);Major Science and Technology Projects of Zhejiang Province(2014C01047);521 Talent Project of Zhejiang Sci-Tech University

摘要/Abstract

摘要：

大量并发请求任务进行分配时，负载调度机制是通过最小化响应时间及最大化节点利用率实现网络中节点的负载均衡，在基于遗传算法的负载均衡算法中，适应度函数设计对服务集群负载均衡效率产生重要的影响。对此提出了一种基于mean-variance的服务集群负载均衡方法对适应度函数进行优化，采用投资组合选择模型mean-variance进行最小化响应时间，以得到每个服务器资源利用率的权重，从而获得最优的分配组合，进而提高适应度函数的准确性和有效性。在不同服务环境下与其他模型进行比较，仿真结果表明，本文的负载均衡算法在节点利用率和响应时间方面使服务集群得到了更好的均衡。

关键词: 负载均衡, mean-variance模型, 遗传算法, 负载调度

Abstract:

When a large number of concurrent requests are allocated,the load scheduling mechanism is to achieve the load balancing of nodes in the network by minimizing the response time and maximizing the utilization ratio of nodes.In the load balancing algorithm based on genetic algorithm,the fitness function is designed to have an important influence on the load balancing efficiency.A service cluster load balancing method based on mean-variance was proposed to optimize the fitness function.The investment portfolio selection model mean-variance was used to minimize the response time,which was used to get the weight of each server's resource utilization,so as to obtain the optimal allocation combination.This method improves the accuracy and efficiency of the fitness function.Compared with other models in different service environment,the simulation results show that the load balancing algorithm makes the service cluster get a better balance performance in terms of node utilization and response time.

Key words: load balancing, mean-variance model, genetic algorithm, load scheduling

中图分类号:

TP393

包晓安,魏雪,陈磊,胡国亨,张娜. 基于mean-variance的服务集群负载均衡方法[J]. 电信科学, 2017, 33(1): 1-8.

Xiaoan BAO,Xue WEI,Lei CHEN,Guoheng HU,Na ZHANG. Load balancing method of service cluster based on mean-variance[J]. Telecommunications Science, 2017, 33(1): 1-8.

图/表 8

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T_α	T_β	P_i	数组
3	7	1	〈3,7,1〉
5	3	4	〈5,3,4〉
2	4	3	〈2,4,3〉
7	1	4	〈7,1,4〉
10	9	2	〈10,9,2〉
1	5	2	〈1,5,2〉
4	16	1	〈4,16,1〉
6	2	3	〈6,2,3〉
9	8	4	〈9,8,4〉
8	14	1	〈8,14,1〉

参数	数值
服务节点	3
负载均衡管理单元	1
任务量/个	3000
群体大小	20
迭代次数/次	35
交叉概率	0.8%
变异概率	0.15%
乘子R	1.2
乘子D	0.8
常量系数k₁、k₂、k₃	0.4,0.4,0.2

基于mean-variance的服务集群负载均衡方法

Load balancing method of service cluster based on mean-variance

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