Zhang Ying, Wang Jun, Han Dezhi, Wu Huafeng, Zhou Rundong
College of Information Engineering, Shanghai Maritime University, Shanghai 201306, China.
Department of Electrical and Computer Engineering, University of Central Florida, Orlando, FL 32816, USA.
Sensors (Basel). 2017 Jul 3;17(7):1554. doi: 10.3390/s17071554.
Due to the high-energy efficiency and scalability, the clustering routing algorithm has been widely used in wireless sensor networks (WSNs). In order to gather information more efficiently, each sensor node transmits data to its Cluster Head (CH) to which it belongs, by multi-hop communication. However, the multi-hop communication in the cluster brings the problem of excessive energy consumption of the relay nodes which are closer to the CH. These nodes' energy will be consumed more quickly than the farther nodes, which brings the negative influence on load balance for the whole networks. Therefore, we propose an energy-efficient distributed clustering algorithm based on fuzzy approach with non-uniform distribution (EEDCF). During CHs' election, we take nodes' energies, nodes' degree and neighbor nodes' residual energies into consideration as the input parameters. In addition, we take advantage of Takagi, Sugeno and Kang (TSK) fuzzy model instead of traditional method as our inference system to guarantee the quantitative analysis more reasonable. In our scheme, each sensor node calculates the probability of being as CH with the help of fuzzy inference system in a distributed way. The experimental results indicate EEDCF algorithm is better than some current representative methods in aspects of data transmission, energy consumption and lifetime of networks.
由于高能效和可扩展性,聚类路由算法已在无线传感器网络(WSN)中得到广泛应用。为了更高效地收集信息,每个传感器节点通过多跳通信将数据传输到其所属的簇头(CH)。然而,簇内的多跳通信带来了靠近簇头的中继节点能量消耗过大的问题。这些节点的能量消耗速度将比距离较远的节点更快,这对整个网络的负载平衡产生了负面影响。因此,我们提出了一种基于模糊方法的非均匀分布的节能分布式聚类算法(EEDCF)。在簇头选举过程中,我们将节点能量、节点度和邻居节点的剩余能量作为输入参数进行考虑。此外,我们利用高木、菅野和康(TSK)模糊模型代替传统方法作为我们的推理系统,以确保定量分析更加合理。在我们的方案中,每个传感器节点借助模糊推理系统以分布式方式计算成为簇头的概率。实验结果表明,EEDCF算法在数据传输、能量消耗和网络寿命方面优于一些当前具有代表性的方法。