An Adaptive Beacon Exchange Algorithm Based on Link Broken Probability

In mobile wireless sensor networks, greedy geographical routing protocols usually adopt a period beacon exchange algorithm to build and update neighbor table, which brings about the phenomenon of temporary communication blindness in the mobility scenery. To address this problem, we propose a new adaptive beacon exchange algorithm based on link broken probability which corresponds with the running time of mobility scenery. Impact of node mobility on network connectivity is analyzed based on the Markov chain model of link status. The formula of link broken probability is derived from theoretical analysis. Then, the work node calculates variable beacon period according to the link broken probability threshold relative to up node. Idle node calculates variable beacon period according to the threshold link broken probability relative to its all neighbors. The threshold probability can be adjusted to meet the performance requirement of networks. Forwarding node removes the next hop from neighbors table, if it did not receive the feedback beacon after two beacon periods. The adaptive beacon exchange algorithm can get the accurate neighbors table and mitigate the phenomenon of temporary communication blindness. Simulation shows that the proposed algorithm can obtain high packet success delivery ratio and low consumption. So it is scalable and applicable to large-scale mobile wireless sensor networks.