ACOA-AFSA Fusion Dynamic Coded Cooperation Routing for Different Scale Multi-Hop Underwater Acoustic Sensor Networks

Yougan Chen; Jianying Zhu; Lei Wan; Shenqin Huang; Xinhai Zhang; Xiaomei Xu

doi:10.1109/ACCESS.2020.3029533

IEEE Access (Jan 2020)

ACOA-AFSA Fusion Dynamic Coded Cooperation Routing for Different Scale Multi-Hop Underwater Acoustic Sensor Networks

Yougan Chen,
Jianying Zhu,
Lei Wan,
Shenqin Huang,
Xinhai Zhang,
Xiaomei Xu

Affiliations

Yougan Chen: ORCiD; Key Laboratory of Underwater Acoustic Communication and Marine Information Technology (Xiamen University), Ministry of Education, Xiamen, China
Jianying Zhu: ORCiD; Key Laboratory of Underwater Acoustic Communication and Marine Information Technology (Xiamen University), Ministry of Education, Xiamen, China
Lei Wan: ORCiD; Key Laboratory of Underwater Acoustic Communication and Marine Information Technology (Xiamen University), Ministry of Education, Xiamen, China
Shenqin Huang: ORCiD; Key Laboratory of Underwater Acoustic Communication and Marine Information Technology (Xiamen University), Ministry of Education, Xiamen, China
Xinhai Zhang: ORCiD; Key Laboratory of Underwater Acoustic Communication and Marine Information Technology (Xiamen University), Ministry of Education, Xiamen, China
Xiaomei Xu: ORCiD; Key Laboratory of Underwater Acoustic Communication and Marine Information Technology (Xiamen University), Ministry of Education, Xiamen, China

DOI: https://doi.org/10.1109/ACCESS.2020.3029533
Journal volume & issue: Vol. 8
pp. 186773 – 186788

Abstract

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The limited energy supply of underwater nodes is one of the key issues for the multi-hop underwater acoustic sensor networks (UWA-SN). In this paper, the fusion scheme based on ant colony optimization algorithm (ACOA), artificial fish swarm algorithm (AFSA) and dynamic coded cooperation (DCC) strategy, named as ACOA-AFSA fusion DCC routing algorithm, has been proposed for routing in the multi-hop UWA-SN, aiming at simultaneously reducing the energy consumption and enhancing the robustness. In the proposed ACOA-AFSA fusion DCC routing algorithm, the randomness of the AFSA and the positive feedback mechanism of the ACOA enable the algorithm to find the global optimal routing more efficient and accurate. In addition, most existing routing protocols consider the large-scale networks (more than 100 nodes), while the medium- and small-scale networks (less than 100 nodes) are more practical in nowadays' multi-hop UWA-SN. The network scale affects the optimal design of routing protocols in terms of energy saving. Considering the practical situation, we compare the proposed scheme with other four existing artificial intelligence (AI) routing algorithms in the medium- and small- scale multi-hop UWA-SN, which is instructive for application of AI in practical multi-hop UWA-SN. The simulation results show that the proposed ACOA-AFSA fusion DCC routing algorithm can reduce the energy consumption by 40.1% compared to that with non-cooperative strategy in the multi-hop UWA-SN with 20 nodes. The proposed routing algorithm also consumes less energy than other four existing AI routing algorithms in the medium-scale multi-hop UWA-SN with 50 nodes or 100 nodes. However, for the small-scale case with 10 nodes, the advantage is not very obvious. In the meantime, the proposed ACOA-AFSA fusion DCC algorithm is compatible with the ACOA-AFSA fusion non-cooperative algorithm, and the complexity is acceptable, which is very appealing to the time-varying marine environments.

Published in IEEE Access

ISSN: 2169-3536 (Online)
Publisher: IEEE
Country of publisher: United States
LCC subjects: Technology: Electrical engineering. Electronics. Nuclear engineering
Website: https://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=6287639

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