Adaptive and Efficient Time Synchronization Optimization Algorithm in Wireless Sensor Networks
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摘要: 针对无线传感器网络全网多跳自适应时间同步效率低的问题，在接收端与接收端同步模型基础上，该文提出一种自适应高效无线传感器网络时间同步优化算法(AEO)。首先，双节点同步时，从节点接收来自参考节点的同步消息并进行确认，在同步周期结束后通过拟合估计和数据更新完成时间修正，构建交互参数同步包，并与主节点进行信息交换完成同步过程。其次，全网同步时，建立Voronoi多边形拓扑结构，认定拓扑结构中参考节点和邻域节点身份(ID)，参考节点覆盖区域间通过邻域节点交换同步信息，实现自适应多区域节点联合时间同步。仿真结果表明该算法在双节点时间同步中能够保证同步误差较小，网络能耗较低；同时，Voronoi拓扑相较于其他典型拓扑，在连通效率和收敛时间方面均有所改进。Abstract: To solve the problem of low efficiency for multiple-hop adaptive time synchronization in Wireless Sensor Networks (WSN), an Adaptive and Efficient time synchronization Optimization (AEO) algorithm is proposed based on receiver-receiver time synchronization model. Firstly, in pairwise time synchronization, slave node receives the synchronization message from reference node and confirmed. After the synchronization period, the time correction is realized by fitting estimation and data update. Then the interactive parameter synchronization package is constructed. The slave node exchanges interactive parameter synchronization package with the master to realize pairwise synchronization. Secondly, the Voronoi polygon topology is established. The network also identifies the IDentification (ID) of reference nodes and neighbor nodes in the topology. The coverage area of reference nodes exchange synchronization information by neighboring nodes to realize adaptive regions joint time synchronization. The simulation results show that the algorithm has less synchronization errors and lower network energy consumption in pairwise time synchronization. Meanwhile, the Voronoi topology improves connectivity efficiency and convergence time compared with other typical topologies.
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表 1 仿真参数
参数 设置值 最大数据报大小 127 Byte 最大网络范围 500 m × 500 m 网络节点数量 100～500 最大感知半径 20 m 最大通信半径 40 m 参考节点数量 10～50 信标包数量 5～15 信标间隔 1 s 周期数 1～5 仿真时间 5 h 节点初始能量 5 W·s 发送端能量消耗 50 nW·s/bit 接收端能量消耗 50 nW·s/bit 
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