[论文解读] Whale Optimization Based Energy-Efficient Cluster Head Selection Algorithm for Wireless Sensor Networks

Ashwin Jadhav, T. Shankar|arXiv (Cornell University)|Nov 26, 2017

Energy Efficient Wireless Sensor Networks参考文献 38被引用 50

一句话总结

本文提出 WOA-C，即基于鲸鱼优化算法的聚类方法，用于在无线传感器网络中选择能量感知的簇头，采用节点剩余能量与相邻节点能量之和作为适应度函数，并与 LEACH 相比显示出更长的寿命、能源效率和稳定性。

ABSTRACT

Wireless Sensor Network (WSN) consists of many individual sensors that are deployed in the area of interest. These sensor nodes have major energy constraints as they are small and their battery can't be replaced. They collaborate together in order to gather, transmit and forward the sensed data to the base station. Consequently, data transmission is one of the biggest reasons for energy depletion in WSN. Clustering is one of the most effective techniques for energy efficient data transmission in WSN. In this paper, an energy efficient cluster head selection algorithm which is based on Whale Optimization Algorithm (WOA) called WOA-Clustering (WOA-C) is proposed. Accordingly, the proposed algorithm helps in selection of energy aware cluster heads based on a fitness function which considers the residual energy of the node and the sum of energy of adjacent nodes. The proposed algorithm is evaluated for network lifetime, energy efficiency, throughput and overall stability. Furthermore, the performance of WOA-C is evaluated against other standard contemporary routing protocols such as LEACH. Extensive simulations show the superior performance of the proposed algorithm in terms of residual energy, network lifetime and longer stability period.

研究动机与目标

• 通过减少数据传输能量损耗来提升无线传感器网络的能源效率。
• 开发一种使用鲸鱼优化算法（WOA）的簇头选择方法，以优化路由和聚类。
• 引入一个将节点残余能量与相邻节点能量结合的适应度函数来引导簇头选择。
• 在网络寿命、吞吐量、能源效率和稳定期等指标上评估 WOA-C。

提出的方法

• 采用鲸鱼优化算法（WOA-C）搜索最优簇头。
• 定义一个将节点残余能量与相邻节点能量之和结合的适应度函数来指导簇头选择。
• 通过仿真将 WOA-C 的性能与 LEACH 等标准路由协议进行比较。
• 评估网络寿命、能源效率、吞吐量和稳定期以证明改进。

实验结果

研究问题

• RQ1 鲸鱼优化算法是否能够在无线传感器网络中有效选择能量感知的簇头？
• RQ2 相较于 LEACH，WOA-C 是否提升网络寿命、能源效率、吞吐量和稳定期？
• RQ3 将残余能量与邻接节点能量纳入适应度函数对簇头选择有何影响？
• RQ4 在典型部署情景下，WOA-C 对整个无线传感器网络性能有什么影响？

主要发现

• WOA-C 使用基于节点残余能量和相邻节点能量的适应度函数来选择能量感知的簇头。
• 仿真结果显示，与 LEACH 相比，残余能量保持更高、网络寿命更长、稳定期更长。
• 在评估场景中，WOA-C 显示出更高的能源效率和吞吐量。