基于流量预测的Ad Hoc网络负载均衡协议

针对AdHoc网络中的负载均衡问题,提出了一种基于小波神经网络方法预测节点流量的路由协议WNNP-LBRP,协议中的流量值以MAC层接口队列长度来衡量.该协议利用小波神经网络预测模型计算节点下一时刻的流量值及动态阈值,并对二者进行比较,避免将重负载节点作为中间节点而导致网络拥塞,从而在网络出现拥塞之前提前更新路径,实现网络负载的平均分配.仿真结果表明,WNNP-LBRP协议与LBR-AODV协议和AODV协议相比,网络性能得到提高:减少了丢包现象,降低了端到端时延和路由开销.

Load Balancing Routing Protocol Based on Traffic Prediction for Ad Hoc Network

For the load balancing of ad hoc networks, a routing protocol based on traffic prediction with wavelet neural network (WNNP-LBRP) was proposed, where the number of packets buffered in the interface of the MAC layer was a measure of node traffic. The node traffic and its dynamic threshold were calculated using the wavelet neural network prediction model and then were compared with each other in order to avoid taking a heavy-load node as an intermediate node, which would result in network congestion. Thus, the link could be updated before congestion and the network load could be distributed evenly. Simulation results showed that the WNNP-LBRP outperforms the LBR-AODV and AODV, that is, the packet delivery ratio is increased and the end-to-end delay and routing overhead are reduced.