A novel energy efficient QoS secure routing algorithm for WSNs

Quality of Service (QoS) routing protocol is a hot topic in the research field of wireless sensor networks (WSNs). However, the task of identifying an optimal path that simultaneously meets multiple QoS constraints is acknowledged as an NP-hard problem, with its complexity intensifying in proportion...

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Bibliographic Details
Published in:Scientific reports Vol. 14; no. 1; pp. 25969 - 25
Main Authors: Fei, Hongmei, Jia, Dingyi, Zhang, Baitao, Li, Chaoqun, Zhang, Yao, Luo, Tao, Zhou, Jie
Format: Journal Article
Language:English
Published: London Nature Publishing Group UK 29.10.2024
Nature Publishing Group
Nature Portfolio
Subjects:
639/705/1046
639/705/117
639/705/258
639/705/531
Algorithms
Energy consumption
Energy efficiency
Humanities and Social Sciences
Latency
Levy flight
multidisciplinary
Optimization
Quality of Service
Science
Science (multidisciplinary)
Snake Optimization Algorithm
Wireless Sensor Networks
Snake Optimization Algorithm
Levy flight
Wireless Sensor Networks
Quality of Service
ISSN:2045-2322, 2045-2322
Online Access:Get full text
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Summary:Quality of Service (QoS) routing protocol is a hot topic in the research field of wireless sensor networks (WSNs). However, the task of identifying an optimal path that simultaneously meets multiple QoS constraints is acknowledged as an NP-hard problem, with its complexity intensifying in proportion to the network’s nodal count. Therefore, a novel heuristic multi-objective trust routing method, the Levy Chaos Adaptive Snake Optimization-based Multi-Trust Routing Method (LCASO-MTRM), is proposed, aiming to enhance link bandwidth while simultaneously reducing latency, packet loss, and energy consumption. The proposed method incorporates innovative chaos and adaptive operators within the LCASO framework. The chaos operator enhances population diversity, expands the solution space, and accelerates the search process. Meanwhile, the adaptive operator improves convergence, enhances robustness, and effectively prevents stagnation. Additionally, this paper introduces a novel multi-objective QoS routing model that integrates a link trust mechanism, allowing for a more accurate assessment of link trust levels and a precise reflection of the current link status. The effectiveness of LCASO-MTRM is demonstrated through simulation comparisons with the Improved Particle Swarm Optimization (IPSO), Improved Artificial Bee Colony Algorithm (IABC), and Cloned Whale Optimization Algorithm (CWOA). Simulation results demonstrate that LCASO-MTRM significantly reduces energy consumption by 49.53%, latency by 22.56%, and packet loss by 40.21%, while increasing bandwidth by 6.13%, outperforming the other algorithms.
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ISSN:2045-2322
2045-2322
DOI:10.1038/s41598-024-77686-y