Enhancing the Lifetime of Wireless Sensor Networks Using Fuzzy Logic LEACH Technique-Based Particle Swarm Optimization

Abstract

Wireless sensor networks (WSNs) have attracted significant attention because of their widespread use in health care, habitat tracking, disaster prevention, agriculture, monitoring areas, fire tracking, and other real-life applications. The lifetime of WSNs must be prolonged to increase their use for various applications. One of the most effective methods for improving the network's lifetime is clustering with the optimal cluster head (CH). This study proposes a fuzzy Logic (FL) low-energy adaptive clustering hierarchy (LEACH) technique-based particle swarm optimization (PSO). It employs hybrid PSO and a K-means clustering algorithm for cluster formation. It selects the primary CH (PCH) and secondary CH (SCH) using FL. Extensive simulations were conducted using a simulation program to validate the proposed protocol's performance. Furthermore, the proposed protocol was compared with traditional algorithms, such as fuzzy c-means (FCM) clustering and FLS-based CH selection to enhance the sustainability of WSNs for environmental monitoring applications, LEACH-Fuzzy clustering protocol, and LEACH based on energy consumption equilibrium. The results confirmed that the proposed protocol efficiently balances energy consumption to improve wireless sensor network performance and to maximize throughput. The simulated results indicated that network lifetime was improved by more than 46% and packet transmission by 17.6%.

Fuzzy‐based techniques for clustering in wireless sensor networks (WSNs): Recent advances, challenges, and future directions

“…They considered parameters such as distance and energy to improve network stability. In Gamal et al, 73 the authors proposed the FL‐LEACH algorithm that considers PSO and K‐means cluster‐based algorithms to set up a cluster. The authors considered three factors for selecting the primary CH (PCH), namely, energy, distance of a node to the center of the cluster, and distance of that node to the BS.…”

Energy-Efficient Distributed Cluster-Tree Based Routing Protocol for Applications IoT-Based WSN

“…Tan et al [22] proposed a sector tree routing protocol based on a clustering technique for efficient energy, in which the nodes in a cluster communicate with each other based on the MST connecting. Gamal et al [10] have proposed hybrid particle swarm optimization and a K-means clustering hierarchy algorithm to construct clusters to enhance the lifespan of WSNs. According to this proposal, the Fuzzy logic theory is used to choose CHN with two criteria: residual energy level and distance from CHNs to BS.…”

“…To attain this goal, numerous researchers have proposed efficient energy routing schemes for WSN, in which the clustering mechanism is one of the most useful methods [9,24,25]. According to the clustering method, the network system is partitioned into various clusters; each cluster involves one cluster head node (CHN) and some cluster members (CMs) [10]. CMs only sense the external environment and transmit their acquired data to their CHN, whereas a CHN is responsible for receiving and aggregating data and then relaying the assembled data packets to the BS [19].…”

An Opportunistic Routing for Energy-Harvesting Wireless Sensor Networks With Dynamic Transmission Power and Duty Cycle

“…The limited battery power capacity is one of the major constraints in the application of traditional wireless sensor networks [1], [2], [3]. Energy harvesting (EH) technology has become a promising solution to this problem [4], [5], [6], [7].…”