Abstract

The increasing demands for real-time marine monitoring call for the wide deployment of Marine Monitoring Networks (MMNs). The low-rate underwater communications over a long distance, long propagation delay of underwater acoustic channel, and high deployment costs of marine sensors in a large-scale three-dimensional space bring great challenges in the network deployment and management of MMN. In this paper, we first propose a multitier, hierarchical network architecture of MMN with the support of edge computing (HMMN-EC) to enable efficient monitoring services in a harsh marine environment, taking into consideration the salient features of marine communications. Specifically, HMMN-EC is composed of three subnetworks, i.e., underwater acoustic subnetwork, the sea-surface wireless subnetwork, and the air wireless subnetwork, with a diversity of network nodes with different capabilities. We then jointly investigate the deployment diverse network nodes with various constraints in different subnetworks of HMMN-EC. To this end, we formulate a Multiobjective Optimization (MO) problem to minimize the network deployment cost while achieving the maximal network lifetime, subject to the limited energy of different marine nodes and the complex deployment environment. To solve the formulated problem, we present an Ant-Colony-based Efficient Topology Optimization (AC-ETO) algorithm to find the optimal locations of nodes in different subnetworks of MMN in a large-scale deployment. The time complexity of the proposed algorithm is also analyzed. Finally, extensive simulations are carried out to validate the superior performance of the proposed algorithm compared with some existing solutions.

Highlights

  • With the deepening of humans’ understanding of the ocean, as well as the rapid development of science and technology, great attention has been paid to the ocean because of its huge economic potential and strategic importance

  • We model the HMMN-EC as a directed graph G = (V, E ), where V represents the set of nodes

  • We further study the performance of the proposed algorithm Ant-Colony-based Efficient Topology Optimization (AC-ETO) under different network scales and compare the results with the solutions of P1 obtained by Gurobi

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Summary

Introduction

With the deepening of humans’ understanding of the ocean, as well as the rapid development of science and technology, great attention has been paid to the ocean because of its huge economic potential and strategic importance. Most existing works of the deployment of marine monitoring sensor networks in the literature proposed different algorithms to improve the network coverage. In [9,10,11,12], different algorithms were proposed to deploy sensors and surface gateways in a underwater sensor network These works mainly focus on the deployment of underwater acoustic networks (UANs). To the best of our knowledge, no existing work on the deployment of marine monitoring network study the deployment of an integrated multitier hierarchical network architecture, which includes underwater acoustic subnetwork, sea-surface wireless subnetwork, and air wireless subnetwork. (3) An Ant-Colony-based Efficient Topology Optimization (AC-ETO) algorithm is presented to solve the formulated MO problem in various network scenarios of different numbers of nodes.

Related Works
Network Model
Energy Model
Problem Formulation
Minimization of the Total Network Deployment Cost
Maximization of the Network Lifetime
Algorithm Description
Simulations and Discussion
Performance Validation in Small-Scale and Medium-Scale Networks
Performance Analysis of Gurobi and AC-ETO in Different Network Scenarios
Findings
Performance Comparison of AC-ETO and a Greedy Algorithm
Conclusions
Full Text
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