基于排队论综合指标评估的动态负载均衡算法

doi:10.11959/j.issn.1000-0801.2018204

Abstract

Abstract:

Internet communication,computer cluster and cloud environment have complex and dynamic characteristics,which can cause load imbalance easily,reduce the service efficiency and increase the energy consumption.Therefore,the load balancing technology becomes the focus of research.The existing load balancing strategy uses the occupancy of CPU,memories,processes to estimate the current load of each server.But it is hard to guarantee its accuracy.Aiming at this problem,a dynamic load balancing algorithm based on queuing theory comprehensive index evaluation was proposed.Firstly,queuing theory model was introduced to estimate the real-time load of each server,and then the tasks of input queue was distributed to each server separately according to the load comprehensive index of each server.Experimental results show that this method can balance the load of each server effectively and reduce the average waiting time of the task requests,which is of great application value.

Key words: load balancing, queuing theory, performance

Wenbo WANG,Qingwei YE,Yu ZHOU,Zhihua LU. Dynamic load balancing algorithm based on queuing theory comprehensive index evaluation[J]. Telecommunications Science, 2018, 34(7): 86-91.

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[1]	李永平, 邹华 . 应用服务器的负载平衡技术和实现方案[J]. 电信科学, 2013,29(10): 15-18. LI Y P , ZOU H . Load balancing technology and implementation scheme of application servers[J]. Telecommunications Science, 2013,29(10): 15-18.
[2]	DHINESH B L D , KRISHNA P V . Honey bee behavior inspired load balancing of tasks in cloud computing environments[J]. Applied Soft Computing, 2013,13(5): 2292-2303.
[3]	孙乔, 邓仆侨, 王志强 ,等. 一种基于分布式服务器集群的可扩展负载均衡策略技[J]. 电信科学, 2017,33(9): 190-196. SUN Q , DENG P Q , WANG Z Q ,et al. A scalable load balancing strategy based on distributed server cluster[J]. Telecommunications Science, 2017,33(9): 190-196.
[4]	THAKUR A , GORAYA M S . A taxonomic survey on load balancing in cloud[J]. Journal of Network and Computer Applications, 2017(98): 43-57.
[5]	包晓安, 魏雪, 陈磊 ,等. 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. BAO X A , WEI X , CHEN L ,et al. Load balancing for server cluster based on mean-variance[J]. Telecommunications Science, 2017,33(1): 1-8.
[6]	郑相全, 郭伟, 葛利嘉 ,等. 一种基于跨层设计和蚁群优化的自组网负载均衡路由协议[J]. 电子学报, 2006(7): 1199-1208. ZHENG X Q , GUO W , GE L J ,et al. A load balancing routing protocol for ad hoc networks based on cross layer design and ant colony optimization[J]. Chinese Journal of Electronics, 2006(7): 1199-1208.
[7]	MILANI A S , NAVIMIPOUR N J . Load balancing mechanisms and techniques in the cloud environments:systematic literature review and future trends[J]. Journal of Network and Computer Applications, 2016(71): 86-98.
[8]	陈超, 赵跃龙, 王文丰 ,等. 基于反馈的改进动态负载均衡策略[J]. 计算机工程, 2010,36(14): 34-36,39. CHEN C , ZHAO Y L , WANG W F ,et al. An improved dynamic load balancing strategy based on feedback[J]. Computer Engineering, 2010,36(14): 34-36,39.
[9]	YIN F , JIANG C J , DENG R ,et al. Grid resource management policies for load-balancing and energy-saving by vacation queuing theory[J]. Computers ＆ Electrical Engineering, 2009,35(6): 966-979.
[10]	KUMAR M , SHARMA S C . Dynamic load balancing algorithm for balancing the workload among virtual machine in cloud computing[J]. Procedia Computer Science, 2017(115): 322-329.
[11]	ZHANG Z J , FAN W G . Web server load balancing:a queueing analysis[J]. European Journal of Operational Research, 2008,186(2): 681-693.
[12]	CIARDO G , RISKA A , SMIRINI E . Equiload:a load balancing policy for clustered Web servers[J]. Performance Evaluation, 2001(46): 670-684.
[13]	KO Y M , CHO Y . A distributed speed scaling and load balancing algorithm for energy efficient data centers[J]. Performance Evaluation, 2014(79): 120-133.
[14]	ROSS S . Queueing theory[J]. Introduction to Probability Models, 2014: 481-558.
[15]	于国防, 王耀才, 庄立运 ,等. 基于分配器队列模糊控制的集群负载平衡[J]. 计算机工程, 2008(6): 129-130,136. YU G F , WANG Y C , ZHUANG L Y ,et al. Cluster load balancing based on fuzzy control of distributor queue[J]. Computer Engineering, 2008(6): 129-130,136.

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