基于RSSI的WSN吞吐量自适应优化策略

Adaptive throughput optimization for wireless sensor networks based on RSSI

基于MicaZ型节点参数分别建立了ARQ技术和FEC技术的吞吐量模型,分析并仿真了各参数对吞吐量的影响,得出ARQ技术的最优数据帧长和FEC技术的最优BCH码,进而提出了一种基于RSSI测距技术的吞吐量自适应优化策略,以适应无线传感器网络(WSN)中动态变化的网络拓扑。该策略依据RSSI测距技术测量节点间的通信距离,自适应地为数据包选择最优的差错控制策略来提高WSN的吞吐量。仿真结果表明,在吞吐量和动态范围方面,该策略整体上优于单纯的ARQ或者FEC方案。

The throughput model for ARQ and FEC are presented based on the MicaZ node.By analyzing the various parame-ters on throughput,the optimal frame length of ARQ and the optimal FEC parameters are derived.Then,an adaptive throughput opti-maization strategy based on RSSI is proposed,which can adapt to the dynamic changes of network topology in WSN. In the strategy, the range measurement technology called RSSI is used to measure the communication distance between nodes,and the throughput is improved by adapting the error control strategy .The simulation results show that the performance of this scheme outperforms the in-dividual ARQ or FEC technique in terms of throughput and dynamic range.