Sha Chao, Qiu Jian-Mei, Li Shu-Yan, Qiang Meng-Ye, Wang Ru-Chuan
College of Computer, Nanjing University of Posts and Telecommunications, Nanjing 210003, China.
Provincial Key Laboratory for Computer Information Processing Technology, Soochow University, Suzhou 215006, China.
Sensors (Basel). 2016 Jun 21;16(6):923. doi: 10.3390/s16060923.
To balance energy consumption and reduce latency on data transmission in Wireless Sensor Networks (WSNs), a type of low-latency data gathering method with multi-Sink (LDGM for short) is proposed in this paper. The network is divided into several virtual regions consisting of three or less data gathering units and the leader of each region is selected according to its residual energy as well as distance to all of the other nodes. Only the leaders in each region need to communicate with the mobile Sinks which have effectively reduced energy consumption and the end-to-end delay. Moreover, with the help of the sleep scheduling and the sensing radius adjustment strategies, redundancy in network coverage could also be effectively reduced. Simulation results show that LDGM is energy efficient in comparison with MST as well as MWST and its time efficiency on data collection is higher than one Sink based data gathering methods.
为了平衡无线传感器网络(WSN)中的能量消耗并减少数据传输延迟,本文提出了一种多汇聚节点的低延迟数据收集方法(简称为LDGM)。网络被划分为几个由三个或更少数据收集单元组成的虚拟区域,每个区域的领导者根据其剩余能量以及到所有其他节点的距离来选择。只有每个区域的领导者需要与移动汇聚节点通信,这有效地降低了能量消耗和端到端延迟。此外,借助睡眠调度和感知半径调整策略,还可以有效减少网络覆盖中的冗余。仿真结果表明,与最小生成树(MST)以及最小权重生成树(MWST)相比,LDGM具有能量效率,并且其数据收集的时间效率高于基于单个汇聚节点的数据收集方法。