Zhao Xiaoqiang, Ren Shaoya, Quan Heng, Gao Qiang
School of Communication and Information Engineering, Xi'an University of Posts and Telecommunications, Xi'an 710121, China.
Shaanxi Key Laboratory of Information Communication Network and Security, Xi'an University of Posts and Telecommunications, Xi'an 710121, China.
Sensors (Basel). 2020 Feb 4;20(3):820. doi: 10.3390/s20030820.
Wireless sensor network (WSN) nodes are devices with limited power, and rational utilization of node energy and prolonging the network lifetime are the main objectives of the WSN's routing protocol. However, irrational considerations of heterogeneity of node energy will lead to an energy imbalance between nodes in heterogeneous WSNs (HWSNs). Therefore, in this paper, a routing protocol for HWSNs based on the modified grey wolf optimizer (HMGWO) is proposed. First, the protocol selects the appropriate initial clusters by defining different fitness functions for heterogeneous energy nodes; the nodes' fitness values are then calculated and treated as initial weights in the GWO. At the same time, the weights are dynamically updated according to the distance between the wolves and their prey and coefficient vectors to improve the GWO's optimization ability and ensure the selection of the optimal cluster heads (CHs). The experimental results indicate that the network lifecycle of the HMGWO protocol improves by 55.7%, 31.9%, 46.3%, and 27.0%, respectively, compared with the stable election protocol (SEP), distributed energy-efficient clustering algorithm (DEEC), modified SEP (M-SEP), and fitness-value-based improved GWO (FIGWO) protocols. In terms of the power consumption and network throughput, the HMGWO is also superior to other protocols.
无线传感器网络（WSN）节点是功率有限的设备，合理利用节点能量并延长网络寿命是WSN路由协议的主要目标。然而，对节点能量异构性的不合理考虑会导致异构无线传感器网络（HWSN）中节点间的能量不平衡。因此，本文提出了一种基于改进灰狼优化器（HMGWO）的HWSN路由协议。首先，该协议通过为异构能量节点定义不同的适应度函数来选择合适的初始簇；然后计算节点的适应度值并将其作为灰狼优化算法中的初始权重。同时，根据狼与猎物之间的距离以及系数向量动态更新权重，以提高灰狼优化算法的优化能力，并确保选择最优簇头（CH）。实验结果表明，与稳定选举协议（SEP）、分布式节能聚类算法（DEEC）、改进SEP（M-SEP）和基于适应度值的改进灰狼优化算法（FIGWO）协议相比，HMGWO协议的网络生命周期分别提高了55.7%、31.9%、46.3%和27.0%。在功耗和网络吞吐量方面，HMGWO也优于其他协议。
