Journal of Computer Applications ›› 2018, Vol. 38 ›› Issue (10): 2976-2981.DOI: 10.11772/j.issn.1001-9081.2018030548

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Dynamic algorithm of load balancing based on D-S evidence theory with improved weight

TAI Yingying, PANG Ying, DUAN Keke, FU Yunpeng   

  1. College of Information, Liaoning University, Shenyang Liaoning 110036, China
  • Received:2018-03-19 Revised:2018-05-14 Online:2018-10-10 Published:2018-10-13
  • Supported by:
    This work is partially supported by the General Scientific Research Project of Liaoning Provincial Education Department (W2015171), the Liaoning Provincial Social Science Fund (L17BTJ001).


邰滢滢, 庞影, 段苛苛, 付云鹏   

  1. 辽宁大学, 信息学院, 沈阳 110036
  • 通讯作者: 邰滢滢
  • 作者简介:邰滢滢(1978-),女,辽宁西丰人,副教授,博士,主要研究方向:图形图像处理、负载平衡;庞影(1993-),女,辽宁营口人,硕士研究生,主要研究方向:负载均衡决策算法;段苛苛(1987-),女,河南洛阳人,讲师,博士,主要研究方向:传感器数据处理;付云鹏(1978-),女,辽宁铁岭人,副教授,博士,主要研究方向:统计数据分析。
  • 基金资助:

Abstract: To solve the problem of load unbalance among servers in large network games, a load balancing strategy based on Dempster/Shafer (D-S) evidence theory was proposed. The multiple factors which influenced the servers were taken as parameters. Firstly, according to D-S evidence theory, the multiple factors affecting the performance of the server were used as the criteria, the dynamic weight was computed by comparing the historic data with the threshold, and then the basic belief function was set up according to the relationship between the dynamic weight and original reliability. After that, the belief functions corresponding to different criteria was calculated, and the calculation results were merged by the rules of evidence synthesis. Lastly, whether the server was overloaded or not was evaluated by the analysis of aforementioned results. Simulation results show that compared with the dynamic load balancing algorithm based on negative feedback, the proposed algorithm is more accurate and more realistic; the running time of the proposed algorithm is obviously less than that of the dynamic load balancing algorithm based on negative feedback and the weighted loop algorithm. Analysis indicates that the proposed algorithm can effectively reduce the delay of running judgement and make a quick deduction for the server load according to the historical parameters, and the dicision results are more reliable and more consistent with the actual situation.

Key words: large network game, Dempster/Shafer (D-S) evidence theory, belief function, load balancing, evidence fusion

摘要: 针对大型网络游戏中易出现的服务器集群负载不均衡的问题,提出基于改进权重的D-S(Dempster和Shafer)证据理论的负载平衡判别策略。首先,根据D-S证据理论,将影响服务器性能的多因素作为判据,利用历史数据与阈值大小的比较规则计算动态权重,再依据动态权重与原始信度的关系建立基本信任函数;然后,计算不同判据对应结果的信任函数,使用证据合成规则作深层融合;最后分析合成结果,最终推断服务器是否超载。模拟实验结果表明,与基于负反馈机制的动态均衡算法相比,所提算法的准确率更高,更符合真实情况;且所提算法的运行时间明显少于基于负反馈机制的动态均衡算法以及加权循环算法。实验结果表明,新算法有效缩短了运行判断的延迟,能够根据历史参数对当前服务器负载情况快速作出推断,且决策结果可信度高,更符合实际情况。

关键词: 大型网络游戏, Dempster/Shafer证据理论, 信任函数, 负载平衡, 证据融合

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