基于粒子滤波步行长度预测的移动ad hoc网络路由算法

针对移动ad hoc网络拓扑结构变化大、路由复杂度高、数据传输性能低等问题,提出了一种新的移动通信系统自适应路由算法。为了使得网络拓扑结构更接近移动网络间歇性连接的特点,该算法在网络结构上采用了一种改进的Levy Walk移动模型。采用一种粒子滤波步行长度预测的方法,通过蒙特卡罗抽样得到递归贝叶斯滤波器,并在粒子滤波后进行步行长度预测,确定消息的副本数量,从而减少由于节点转发过多消息副本带来的能量消耗量,提高消息的传递效率。实验仿真结果表明：与基于改进蚁群优化和利润优化模型的路由算法相比,该算法的消息传递成功率分别提高了0.08和0.04,节点平均能量效率提高了17.9%和13.4%,在提升数据传输成功率和节能上具有较好效果。

A mobile ad hoc network routing algorithm based on walking length prediction after particle filtering

For the problems of mobile ad hoc network( MANET) such as big change of topology structure, high routing complexity,and low data transmission performance,this paper proposes a new mobile commu-nication system using an adaptive routing algorithm. In order to make the network topology closer to the characteristics of the mobile network intermittent connection,an improved Levy Walk Mobility Model is a-dopted in the network structure. And then,a particle filtering walking length method prediction is used to get a recursive Bayesian filter throush Monte Carlo sampling,and the walking length is predicted after parti-cle filtering to determine the number of copies of message, thereby reducing the energy consumption for node forwarding a copy to bring too many messages and improve the message delivery efficiency. Simulation results show that compared with two routing algorithms of ant colony-based optimization and profit optimi-zation-based model,the proposed algorithm improves the message passing success rate of 0. 08 and 0. 04, node average energy efficiency of 17. 9% and 13. 4%,respectively. So it achieves better results in impro-ving the success rate of data transfer and saving energy.