Developing a novel energy efficient routing protocol in WSN using adaptive remora optimization algorithm

Kaviarasan, Solayan; Srinivasan, Rajkumar

doi:10.1016/j.eswa.2023.122873

Cited by 5 publications

(1 citation statement)

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“…Afterward, they used the high search efficiency of the algorithm to obtain a better clustering scheme, saving network energy consumption. Solayan et al 31 proposed an energy-efficient routing protocol based on heuristic strategy, which integrates energy consumption, distance, throughput, packet transmission rate, path loss and other factors into a fitness function, and uses adaptive remora optimization algorithm(ROA) for CH selection. In addition to saving energy, the protocol extends the life of the network.…”

Section: Related Workmentioning

confidence: 99%

Energy Efficient Cluster-Based Routing Protocol for WSN using Multi-Strategy Fusion Snake Optimizer and Minimum Spanning Tree

Yang,

Zhang,

et al. 2024

Preprint

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In recent years, the widespread adoption of wireless sensor networks (WSN) has resulted in the growing integration of the Internet of Things (IoT). However, WSN encounters limitations related to energy and sensor node lifespan, making the development of an efficient routing protocol a critical concern. Cluster technology offers a promising solution to this challenge. This study introduces a novel cluster routing protocol for WSN. The system selects cluster heads and relay nodes utilizing the Multi-Strategy Fusion Snake Optimizer (MSSO) and employs the Minimum Spanning Tree algorithm for inter-cluster routing planning, thereby extending the system’s lifecycle and conserving network energy. In pursuit of an optimal clustering scheme, the paper also introduces tactics involving dynamic parameter updating, adaptive alpha mutation, and bi-directional search optimization within MSSO. These techniques significantly increase the algorithm convergence speed and expand the available search space.Furthermore, a novel efficient clustering routing model for WSN is presented. The model generates different objective functions for selecting cluster heads and relay nodes, considering factors such as location, energy, base station distance, intra-cluster compactness, inter-cluster separation, and other relevant criteria. When selecting cluster heads, the fuzzy C-means algorithm is integrated into MSSO to improve the optimization performance of the algorithm. When planning inter-cluster routing, the next hop node is selected for the relay node based on distance, residual energy, and direction.The experimental results demonstrate that the proposed protocol reduces energy consumption by at least 26.64% compared to other cluster routing protocols including LEACH, ESO, EEWC, GWO, and EECHS-ISSADE. Additionally, it increases the network lifetime of WSN by at least 25.84%, extends the stable period by at least 52.43%, and boosts the network throughput by at least 40.99%.

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Section: Related Workmentioning

confidence: 99%