基于鲸群的无线传感器网络节能路由算法

IF 4.3 2区综合性期刊 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC

IEEE Sensors Journal Pub Date : 2024-04-30 DOI:10.1109/JSEN.2024.3390424

Bing Zeng;Jiewen Deng;Yan Dong;Xuebing Yang;Lingxiang Huang;Zhao Xiao

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引用次数: 0

摘要

开发高能效路由算法是降低无线传感器网络（WSN）能耗的关键，而 WSN 高能效路由是一个组合优化问题。许多研究人员试图用元启发式算法来优化这一问题。然而，由于 WSNs 路由问题的单独编码和迭代规则，大多数元启发式算法都不适合设计 WSNs 路由算法。为了解决这些问题，本文在 WSA-IC 算法的基础上提出了一种基于计数器迭代的鲸群算法（WSA-ICR）。WSA-ICR 算法考虑了平衡网络中每个节点的能耗和路径长度，设计了一个新的能效目标函数。然后，从个体编码、个体初始化、两个体间距离计算、个体移动规则和局部搜索五个方面对 WSA 算法进行了改进。WSA-ICR 算法与几种能效优化路由算法进行了比较。仿真结果表明，WSA-ICR 算法在平衡整个网络的能量消耗、延长网络生命周期和收敛速度等方面表现出色。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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A Whale Swarm-Based Energy Efficient Routing Algorithm for Wireless Sensor Networks

Developing energy-efficient routing algorithms is key to reducing energy consumption of wireless sensor networks (WSNs), and the WSNs energy-efficient routing is a combinatorial optimization problem. Many researchers try to optimize it with metaheuristics. However, most metaheuristics are inappropriate in designing routing algorithms for WSNs due to the individual coding and iteration rule for WSNs routing problem. To solve these problems, this article proposes a whale swarm algorithm with iterative counter-based routing (WSA-ICR) algorithm based on the WSA-IC algorithm. The WSA-ICR algorithm considers the energy consumption of each node and path length in the balanced network and designs a new energy efficiency objective function. Then, the WSA algorithm is improved from five aspects: individual coding, individual initialization, distance calculation between two individuals, individual movement rules, and local search. The WSA-ICR algorithm is compared with several energy efficiency optimization routing algorithms. The simulation results show that the WSA-ICR algorithm has excellent performance in balancing the energy consumption of the whole network, prolonging the network life cycle and convergence speed.

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来源期刊

IEEE Sensors Journal 工程技术-工程：电子与电气

CiteScore

7.70

自引率

14.00%

发文量

2058

审稿时长

5.2 months

期刊介绍： The fields of interest of the IEEE Sensors Journal are the theory, design , fabrication, manufacturing and applications of devices for sensing and transducing physical, chemical and biological phenomena, with emphasis on the electronics and physics aspect of sensors and integrated sensors-actuators. IEEE Sensors Journal deals with the following: -Sensor Phenomenology, Modelling, and Evaluation -Sensor Materials, Processing, and Fabrication -Chemical and Gas Sensors -Microfluidics and Biosensors -Optical Sensors -Physical Sensors: Temperature, Mechanical, Magnetic, and others -Acoustic and Ultrasonic Sensors -Sensor Packaging -Sensor Networks -Sensor Applications -Sensor Systems: Signals, Processing, and Interfaces -Actuators and Sensor Power Systems -Sensor Signal Processing for high precision and stability (amplification, filtering, linearization, modulation/demodulation) and under harsh conditions (EMC, radiation, humidity, temperature); energy consumption/harvesting -Sensor Data Processing (soft computing with sensor data, e.g., pattern recognition, machine learning, evolutionary computation; sensor data fusion, processing of wave e.g., electromagnetic and acoustic; and non-wave, e.g., chemical, gravity, particle, thermal, radiative and non-radiative sensor data, detection, estimation and classification based on sensor data) -Sensors in Industrial Practice