A Fuzzy Multi-Objective Framework for Energy Optimization and Reliable Routing in Wireless Sensor Networks via Particle Swarm Optimization  

作　　者：Medhat A.Tawfeek Ibrahim Alrashdi Madallah Alruwaili Fatma M.Talaat 

机构地区：[1]Department of Computer Science,College of Computer and Information Sciences,Jouf University,Sakaka,72341,Aljouf,Saudi Arabia [2]Department of Computer Engineering and Networks,College of Computer and Information Sciences,Jouf University,Sakaka,72341,Aljouf,Saudi Arabia [3]Faculty of Artificial Intelligence,Kafrelsheikh University,Kafrelsheikh,33516,Egypt [4]Faculty of Computer Science&Engineering,New Mansoura University,Gamasa,35712,Egypt

出　　处：《Computers, Materials & Continua》2025年第5期2773-2792,共20页计算机、材料和连续体(英文)

基　　金：funded by Deanship of Graduate studies and Scientific Research at Jouf University under grant No.(DGSSR-2023-2-02038).

摘　　要：Wireless Sensor Networks(WSNs)are one of the best technologies of the 21st century and have seen tremendous growth over the past decade.Much work has been put into its development in various aspects such as architectural attention,routing protocols,location exploration,time exploration,etc.This research aims to optimize routing protocols and address the challenges arising from conflicting objectives in WSN environments,such as balancing energy consumption,ensuring routing reliability,distributing network load,and selecting the shortest path.Many optimization techniques have shown success in achieving one or two objectives but struggle to achieve the right balance between multiple conflicting objectives.To address this gap,this paper proposes an innovative approach that integrates Particle Swarm Optimization(PSO)with a fuzzy multi-objective framework.The proposed method uses fuzzy logic to effectively control multiple competing objectives to represent its major development beyond existing methods that only deal with one or two objectives.The search efficiency is improved by particle swarm optimization(PSO)which overcomes the large computational requirements that serve as a major drawback of existing methods.The PSO algorithm is adapted for WSNs to optimize routing paths based on fuzzy multi-objective fitness.The fuzzy logic framework uses predefined membership functions and rule-based reasoning to adjust routing decisions.These adjustments influence PSO’s velocity updates,ensuring continuous adaptation under varying network conditions.The proposed multi-objective PSO-fuzzy model is evaluated using NS-3 simulation.The results show that the proposed model is capable of improving the network lifetime by 15.2%–22.4%,increasing the stabilization time by 18.7%–25.5%,and increasing the residual energy by 8.9%–16.2% compared to the state-of-the-art techniques.The proposed model also achieves a 15%–24% reduction in load variance,demonstrating balanced routing and extended network lifetime.Furthermore,analysis usi

关 键 词：Wireless sensor networks particle swarm optimization fuzzy multi-objective framework routing stability 

分 类 号：TP393[自动化与计算机技术—计算机应用技术]