Cluster Formation for Underwater Routing in UnetStack3
No Thumbnail Available
Date
2025
Authors
Journal Title
Journal ISSN
Volume Title
Publisher
Springer Science and Business Media Deutschland GmbH
Abstract
Underwater Acoustics Sensor Networks (UASNs) are utilized in a range of underwater applications, including sea habitat monitoring, offshore research, and mineral exploration. Due to the underwater current, low bandwidth, high water pressure, fluctuations in link quality between nodes, propagation latency, and error probability, underwater communication is challenging. Because of these difficulties, data transmission in UASNs is unreliable during routing. One strategy to improve routing speed is to use an opportunistic routing technique. The sender will transmit the data to the set of neighbours in opportunistic routing such that at least one neighbour can receive and forward the data. The main processes in opportunistic routing include evaluating the adjacent nodes, picking the group of neighbours, and coordinating among the selected nodes to transfer the received data. The optimum next-hops during routing are picked. The numerous properties of neighbouring nodes are analysed and the neighbouring nodes are used for forming clusters that are utilised to choose the best next-hops. In this paper, a novel approach for sensor node clustering technique for UASNs is proposed. Here, it is assumed that the neighbours of a sender node are already ranked. A suitable algorithm like TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) is employed to search for the best next-hops and determines a set of candidates to be considered for cluster formation. The protocol has been implemented and simulated in UnetStack3, an agent-based network stack for underwater communication. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.
Description
Keywords
Cluster Head, Cluster members, Euclidean distance, Opportunistic routing protocol, Underwater acoustic sensor networks, UnetStack
Citation
Lecture Notes in Networks and Systems, 2025, Vol.1307 LNNS, , p. 485-496
