东北大学学报（自然科学版）

东北大学学报(自然科学版) ›› 2011, Vol. 32 ›› Issue (9): 1233-1236.DOI: -

• 论著 • 上一篇    下一篇

基于小波神经网络预测的Ad Hoc网络分簇算法

沙毅;黄烨;黄丽;张立立;   

  1. 东北大学信息科学与工程学院;上海市人民政府办公信息处理中心;
  • 收稿日期:2013-06-19 修回日期:2013-06-19 发布日期:2013-04-04
  • 通讯作者: -
  • 作者简介:-
  • 基金资助:
    国家自然科学基金资助项目(10878017)

WNNP-based clustering algorithm for ad hoc networks

Sha, Yi (1); Huang, Ye (2); Huang, Li (1); Zhang, Li-Li (1)   

  1. (1) School of Information Science and Engineering, Northeastern University, Shenyang 110819, China; (2) Office Information Processing Centre, Shanghai Municipal People's Government, Shanghai 200000, China
  • Received:2013-06-19 Revised:2013-06-19 Published:2013-04-04
  • Contact: Sha, Y.
  • About author:-
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摘要： 针对Ad Hoc网络拓扑结构的动态特性,利用小波神经网络预测模型对节点地理位置进行预测.将预测的总保持时间与阈值比较,可以测得簇在下一时刻的稳定性.如果该簇结构在下一时刻趋于不稳定,则在链路失效之前启动路由预修复机制,以避免链路频繁断裂,从而大幅提高了网络性能.仿真结果表明,与传统最小ID算法和未加预测机制的LWCA分簇算法进行比较,所提出的分簇算法分组投递率分别提高了7%和5%,路由中断次数降低了约63%和50%.

关键词: Ad Hoc网络, 加权分簇算法, AODV, 地理位置预测, 小波神经网络预测

Abstract: According to the dynamic characteristics of ad hoc network topology, a wavelet neural network prediction (WNNP) model was used to predict the geometrical location of the nodes. Comparing the predicted total holding time with the threshold, the stabilization of a cluster in next time can be measured. If the cluster tends to be unstable in next time, a routing pre-repair mechanism can be initiated before the link failure to avoid frequent breaks of links. Thus the network performance is significantly improved. Simulation results show that compared with the lowest-identifier (lowest ID) algorithm and location-based WCA (LWCA) which has no prediction model, WNNP-LWCA can improve by 7% and 5% of the packet delivery rate, reduce by 63% and 50% of the broken routing number, and maintain the stabilization of the cluster.

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