An Optimized Approach of Dynamic Target Nodes in Wireless Sensor Network Using Bio Inspired Algorithms for Maritime Rescue

Maritime search and rescue plays an important part in ensuring the safety of life at sea. When using wireless Sensor Network (WSN) technologies in maritime, nevertheless, it endures from situations where the measurement information is inadequate. In computing and networking for maritime applications...

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Bibliographic Details
Published in:IEEE transactions on intelligent transportation systems 2023-02, Vol.24 (2), p.2548-2555
Main Authors: Rani, Shalli, Babbar, Himanshi, Kaur, Pardeep, Alshehri, Mohammad Dahman, Shah, Syed Hassan Ahmed
Format: Article
Language:English
Subjects:
Algorithms
anchor nodes
Computing time
Global Positioning System
Heuristic algorithms
Hidden Markov models
Localization
Location awareness
Maximum likelihood estimation
Moving targets
Nodes
Particle swarm optimization
salp swarm algorithm
Sensors
Swarm intelligence
Wireless sensor network
Wireless sensor networks
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Summary:Maritime search and rescue plays an important part in ensuring the safety of life at sea. When using wireless Sensor Network (WSN) technologies in maritime, nevertheless, it endures from situations where the measurement information is inadequate. In computing and networking for maritime applications, Wireless Sensor Network (WSNs) is a rising inflexion because of its amazing features. Simultaneously, there are some challenges faced by WSNs and node localization is one of them. Node localization is an important factor because until the location of reporting node is unknown, the data sensed by that node is totally useless. The main aim of this paper is towards gaining more improvement in localization by using swarm intelligence algorithm. To achieve this aim, a range-free and distributed method by using the application of salp swarm algorithm for moving target node in network for maritime rescue is proposed. The results are compared with existing algorithm Particle Swarm Optimization (PSO) and Butterfly Optimization Algorithm (BOA). The proposed method has approximately 10% less localization error as compared to PSO and BOA. The proposed algorithm is validated in terms of localization accuracy, localized nodes, localization errors and computing time.
ISSN:1524-9050
1558-0016
DOI:10.1109/TITS.2021.3129914