高动态网络中基于α-β滤波的OLSR协议

An OLSR Protocol Based on α-β Filtering in Highly Dynamic Networks

针对航空高动态无人机网络中节点运动轨迹的连续性和运动状态的记忆性,使用具有高动态无人机飞行特性的三维Gauss-Markov移动模型仿真分析OLSR协议。结合无人机运动的记忆性和OLSR协议的周期性发送HELLO消息进行链路探测的特点,提出了一种在OLSR协议中基于α-β滤波的相邻节点链路质量预测算法;该算法通过接收到的信号强度求得节点间距离测量值,并预测节点间的距离和相对速度,克服不可靠链路的影响。仿真结果表明,相比传统的OLSR协议,改进的协议有效地提高了网络的分组交付率,降低了网络负载。

Aiming to the continuous trajectory and memorial movement state of node in aero highly dynamic UVA （unmanned aerial vehicle） networks,a 3D Gauss-Markov mobility model which has this kind of characteristic is used to simulate performance of the OLSR protocol.Considering the memorial movement of UVA and the link detecting of periodic HELLO messages in OLSR,an OLSR protocol based on α-β filtering algorithm is proposed to predict the quality of neighbor node link.The proposed algorithm use received signal intensity to acquire the measured values which can predict the distance and relative velocity to overcome the effect of unstable links.The simulation results show that the proposed protocol provides an effective method of improving packet delivery rate and reducing networks overload compared with the traditional OLSR protocol.