Underwater Acoustic Sensor Networks With Cost Efficiency for Internet of Underwater Things SCIE SCOPUS

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Title
Underwater Acoustic Sensor Networks With Cost Efficiency for Internet of Underwater Things
Author(s)
Song, Yujae
KIOST Author(s)
Song, Yujae(송유재)
Publication Year
2021-02
Abstract
Despite the potential benefits of Internet of Underwater Things, a number of issues hinder its realization, including the need for communication reliability and cost-effectiveness. This article aims to optimize network design to implement cost-effective underwater acoustic sensor networks (UASNs) with 3D topology while supporting diverse communication quality of service (QoS) requirements. First, we present an analytical framework based on a queueing system that evaluates communication performances of UASNs, wherein each underwater sensor distributed within a 3D space under the sea surface performs fountain code (FC)-based automatic repeat request (ARQ) transmissions under the slotted-Aloha medium access control protocol. Under the proposed framework, we evaluate communication performances given in terms of successful FC-based ARQ transmission probability and the average queueing delay of an underwater sensor. When evaluating the performances, we formulate the service time of each underwater sensor as a function of network parameters, i.e., the density of data sink and amount of redundancy for FC-based ARQ transmission, before solving a function for accurate service time, such that each sensor can be represented by an M/G/1 queue. Further, our analysis can formulate an optimization problem that aims at minimizing total cost incurred to install and operate 3D UASNs, without compromising two communication QoS requirements. To solve this problem, we propose a recursive algorithm to approach an optimal solution in reasonable time. Numerical evaluations demonstrate the validity of the proposed algorithm.
ISSN
0278-0046
URI
https://sciwatch.kiost.ac.kr/handle/2020.kiost/37565
DOI
10.1109/tie.2020.2970691
Bibliographic Citation
IEEE Transactions on Industrial Electronics, v.68, no.2, pp.1707 - 1716, 2021
Publisher
Institute of Electrical and Electronics Engineers
Type
Article
Document Type
Article
Publisher
Institute of Electrical and Electronics Engineers
Related Researcher
Research Interests

Maritime 5G and B5G,Maritime IoT,Deep reinforcement learning and its maritime applications,차세대 해양통신,해양 IoT,심층강화학습 및 해양통신 적용

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