Simulation results demonstrate that compared with three other algorithms, the proposed algorithm achieves a more balanced energy consumption distribution among nodes, significantly extends the network’s stability period, and further enhances the overall network lifetime.
Abstract
To address premature node failure in wireless sensor networks (WSNs) caused by limited energy and uneven energy consumption, this article proposes a tree-based routing algorithm with local update capability. Building upon traditional tree-based routing architecture, this algorithm classifies nodes into different tiers according to their residual energy, geographical location, and current connectivity status. These tiers undergo real-time dynamic updates to adapt to packet transmission demands. Routing paths are adaptively adjusted based on tier variations: when a node’s tier rapidly decreases, its associated routes undergo local updates to minimize energy consumption, thereby prolonging the life time of lower-tier nodes as effectively as possible. Simulation results demonstrate that compared with three other algorithms, the proposed algorithm achieves a more balanced energy consumption distribution among nodes, significantly extends the network’s stability period, and further enhances the overall network lifetime.
The core research goal of this paper is to optimize dynamic routing protocols to improve the performance of the classic LEACH protocol in heterogeneous WSNs through a real-time adaptive scheme, which relies on two core methods: a cluster head selection mechanism based on the residual energy criterion, and a priority hop count strategy.
V. Barbudhe, Shruti Dixit· International journal of com...· 0 citations
The results indicate that E2CMR improves energy efficiency, network stability, and routing performance and is applicable for large-scale energy-constrained WSNs.
S. Priyadarshini, A. T.· International journal of com...· 0 citations
: To guarantee dependable and timely data transfer, dynamic communication networks including Mobile Ad Hoc Networks (MANETs), Wireless Sensor Networks (WSNs), Internet of Things (IoT) system, and Vehicular Ad Hoc Networks (VANETs) need effective routing techniques. Because of node mobility, network congestion, energy limitations, and frequent topology changes, conventional routing protocols frequently suffer from performance degradation. This study suggests and optimized routing architecture for dynamic communication networks that combines the Artificial Bee Colony (ABC) optimization method with K-Means clustering in order to overcome these difficulties. Network nodes are arranged into effective clusters using the K-Means clustering technique. Which lowers routing overhead and increases network scalability. The Artificial Bee Colony method takes into account factors including residual energy, communication distance, link quality, and network congestion to determine the best cluster heads and find effective routing patterns. Enhancing route stability, minimizing packet loss, lowering end-to-end latency, and improving network performance are the goals of the hybrid framework. The suggested method enables effective resource use and allows adaptive decision-making in the face of shifting network conditions. Performance measures such Packet Delivery Ratio, throughput, Energy Consumption, Routing Overhead, and Network Lifetime will be used in simulation tests to assess the framework efficacy. The anticipated outcomes show that in dynamic communication contexts, the suggested hybrid routing model can greatly outperform optimization-based routing techniques and conventional routing protocols.
I. Jansi, G. Jagatheeshkumar· International Journal of Sci...· 0 citations
The suggested ORB-PEGASIS algorithm increases the network lifetime of the HetWSNs by, according to a comparison of the obtained results with various algorithms, including PEGASIS-E by 68.42%, PEGASIS by 112.8%, PEG-ACO by 60.43%, and IEEPB-KMO by 58.47%.
G. S. Prashanth, P. G. Suprith, T. R. Yashavanthakumar· International Journal of Wir...· 0 citations
Low-Energy Adaptive Clustering Hierarchy (LEACH) is one of the earliest and most influential hierarchical routing protocols developed for Wireless Sensor Networks (WSNs). It was designed to reduce energy consumption by organizing sensor nodes into clusters and periodically rotating the cluster-head role among nodes to balance energy usage and extend network lifetime. This survey presents a comprehensive review of the LEACH protocol, describing its architecture, clustering mechanism, setup and steady-state phases, and data aggregation process. The paper examines the key advantages of LEACH, including energy efficiency, scalability, and reduced communication overhead, while also discussing its limitations such as random cluster-head selection, uneven cluster distribution, and limited performance in heterogeneous or large-scale networks. Furthermore, the survey summarizes the major LEACH variants proposed to overcome these challenges, including centralized, multi-hop, mobile, and energy-aware extensions. A comparative overview of these variants is provided based on their design objectives and performance improvements. Finally, the survey highlights current research trends involving LEACH integration with Internet of Things (IoT) applications, machine learning techniques, artificial intelligence, and energy-harvesting technologies, while identifying future research directions for improving reliability, scalability, security, and overall network performance in next-generation wireless sensor networks.
Mohsen R. Kareem· International Journal of Adv...· 0 citations
A distributed K-means clustering algorithm integrated with a modified low energy adaptive clustering hierarchy-improved energy distance protocol for clustering and CH selection achieves improved network lifetime, energy balancing, and scalability while maintaining competitive throughput performance compared with existing protocols.
M. Arafat, M. Drieberg, A. A. Aziz et al.· Engineering Research Express· 0 citations
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