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%.
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.
出处
《东北大学学报（自然科学版）》
EI
CAS
CSCD
北大核心
2011年第9期1233-1236,共4页
Journal of Northeastern University(Natural Science)
基金
国家自然科学基金资助项目(10878017)
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
ad hoc network
weighted clustering algorithm（WCA）
AODV
location prediction
WNNP（wavelet neural network prediction）
