摘要
针对网络负载均衡过程中节点负载变化趋势难以预测的问题,在分析网络负载模糊时序变化特性的基础上,设计了可变阶自循环误差校正机制,构建了网络负载直觉模糊时间序列(IFTS)预测模型,并将基于IFTS的负载预测与网络动态负载均衡相融合,提出了基于IFTS的网络动态负载均衡方法,有效地提升了网络负载预测精度,增强了动态负载均衡系统运行效率,改善了网络整体服务质量。并通过典型实例验证了该方法的有效性和优越性。
Aiming at the problem that the load changing trend of node is difficult to be predicted during network load balancing,on the basis of analyzing the fuzzy time sequence variation characteristics of network coad,the variable order self-circulation error correction mechanism is designed,and the intuitionistic fuzzy time series(IFTS) prediction model is defined for the network load. Meanwhile,by combining the load prediction based on IFTS with the dynamic load balancing theory,a new method of dynamic load balancing(DLB) based on IFTS is proposed,which effectively improves the network load prediction precision,improves the dynamic load balancing system work efficiency and improves the network overall service quality. Finally,the validity and superiority of the proposed method are verified by a typical example.
作者
任神河
郑寇全
关冬冬
惠军华
REN Shen-he;ZHENG Kou-quan;GUAN Dong-dong;XI Jun-hua(Xianyang Normal University,Xianyang 712000,China;Institute of Information and Communication,National University of Defense Technology,Xi’an 710106,China;Xi’an Flight Academy of Air Force,Xi’an 710306,China)
出处
《火力与指挥控制》
CSCD
北大核心
2019年第8期55-60,共6页
Fire Control & Command Control
基金
国家自然科学基金（61309022,61703426）
陕西省自然科学基金（2013JQ8031）
咸阳师范学院专项科研基金资助项目（XSYK17007）
关键词
直觉模糊集
时间序列
动态负载均衡
预测
intuitionistic fuzzy sets
time sequences
dynamic load balancing
prediction
