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无线传感器网络(Wireless Sensor Networks,WSN)中发生拥塞时,距离Sink节点不同传输距离的节点之间,会产生带宽分配的不公平.针对这种不公平性,本文从理论上进行了证明,并提出一种考虑公平性的量子粒子群拥塞控制算法(QPIDDF):在PID队列管理算法中引入量子粒子群算法,以适应无线传感网络的复杂环境,从而缓解传感网络的节点级拥塞;根据网络拥塞状况和分组传输距离,对距离Sink不同传输距离的节点之间的进队列概率进行重新调整,以此来提高网络负载公平性.通过NS2仿真分析表明,该机制能较好的控制节点的队列长度,对网络的公平性与能耗性能有较好的改善.
In the case of congestion in Wireless Sensor Networks (WSN), the bandwidth allocation is not fair between the nodes with different transmission distances from Sink nodes. In view of this unfairness, this paper proves that A quantum particle swarm optimization algorithm (QPIDDF) with fairness is proposed. Quantum particle swarm optimization (PSO) is introduced into the PID queue management algorithm to adapt to the complex environment of wireless sensor networks and to alleviate node-level congestion in sensor networks. Network congestion and packet transmission distance, re-adjust the queue probabilities of nodes with different transmission distances from Sink, so as to improve the network load fairness.The NS2 simulation analysis shows that this mechanism can better control the node’s Queue length, the network’s fairness and energy consumption performance better.