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为了在能量受限的无线传感器网络中以较低的控制开销选择出具有高分组递交率的链路,提出一种基于贝叶斯估计的依概率链路选择算法(BPLS).该算法将链路探测过程分成若干轮,在每轮中对链路分组递交率进行贝叶斯估计,依据估计结果决定下一轮探测中选择该链路的概率.在此基础上设计了可靠的路由算法.仿真结果表明:BPLS算法能够快速挑选出高质量链路;当控制开销较低时,选出质量最高链路的成功率比naive算法提高10%~20%;基于BPLS的树形路由在分组递交率和每分组能耗上优于基本的树形路由.
In order to select a link with high packet delivery rate with lower control overhead in a wireless sensor network with limited energy, a Bayesian Estimation Based Probabilistic Link Selection (BPLS) algorithm is proposed, The road probing process is divided into several rounds, Bayesian estimation of link packet delivery rate in each round, and the probability of selecting the link in the next round of probing are determined according to the estimation results. On this basis, a reliable routing algorithm is designed. Simulation results show that the BPLS algorithm can pick out the high-quality links quickly. When the control overhead is low, the success rate of selecting the highest quality link is 10% ~ 20% higher than that of the naive algorithm. When the tree routing based on BPLS is submitted in groups Rate and energy per packet are superior to basic tree routing.