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

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

doi:10.1109/access.2020.3029533

Abstract

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.

Highlights

The ocean accounts for about two-thirds of the Earth’s surface and plays an important role in maintaining human life
Motivated by [11], to simultaneously reduce energy consumption and effectively improve network robustness, we propose ant colony optimization algorithm (ACOA)-artificial fish swarm algorithm (AFSA) fusion cooperative routing algorithm for multi-hop underwater acoustic sensor networks (UWA-SN) in this paper, which combines the ACOA-AFSA with cooperative strategy and considers the feasibility in different scale underwater acoustic networks
The main contributions of this paper are as bellow: 1) Based on the ACOA-AFSA fusion routing algorithm in [11], we propose a routing protocol, named as ACOA-AFSA fusion dynamic coded cooperation (DCC) routing algorithm, which combines DCC communication with ACOA-AFSA fusion routing algorithm for the multi-hop UWA-SN

Summary

Introduction

The ocean accounts for about two-thirds of the Earth’s surface and plays an important role in maintaining human life. It is an important source of global development elements. The associate editor coordinating the review of this manuscript and approving it for publication was Emrecan Demirors. Underwater acoustic communication and networking technology can be flexibly applied to different scenarios, such as different coverage distances, water depths, network structures, and etc. It can be widely used in practical observations in the ocean to realize

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Results

Conclusion