Computer Engineering and Applications ›› 2015, Vol. 51 ›› Issue (11): 67-71.

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Classified load balancing algorithm based on prediction mechanism

LIAN Jiadian1, LIU Hongli1, XIE Haibo2, GONG Xia1, XU Xiaobo1   

  1. 1.College of Electrical and Information Engineering, Hunan University, Changsha 410082, China
    2.Changsha Graland Science and Technology Development Co., Ltd, Changsha 410004, China
  • Online:2015-06-01 Published:2015-06-12


连加典1,刘宏立1,谢海波2,龚  霞1,胥小波1   

  1. 1.湖南大学 电气与信息工程学院,长沙 410082
    2.长沙宏地科技开发有限公司,长沙 410004

Abstract: In order to solve the problem of uneven distribution of load in server cluster, considering the increasing load and performance of server nodes based on the type of users’ history requests, a classified load balancing algorithm based on prediction mechanism is proposed. Load balancing node establishes single exponential smoothing model to forecast load based on the type of users’ requests, and divides the predicted load with three classes: low load, normal load and heavy load. Load balancing node performs the scheduling and management based on the predicted load, and realizes load balancing of the system. Using the OPNET simulation software for testing, the result of simulation shows that the algorithm can effectively improve the efficiency of load balancing, and has a better load balancing result.

Key words: Web server cluster, load classification, load prediction, single exponential smoothing, OPNET

摘要: 为解决服务器集群负载分配不均的问题,根据用户访问的请求类型,综合考虑用户历史请求引起的负载增量和服务器节点性能,提出了基于预测机制的分级负载均衡算法。负载均衡节点根据用户访问的请求类型建立一次指数平滑预测模型,对相应请求类型引起的负载进行预测,并将预测负载划分为低负载、正常负载、重负载等三个负载等级,根据负载等级对用户请求进行调度,从而实现负载均衡。使用OPNET仿真软件进行测试,结果表明该算法能有效提高负载均衡效率,有较好的负载均衡效果。

关键词: Web服务器集群, 负载分级, 负载预测, 一次指数平滑, OPNET