AUV-Based Efficient Data Collection Scheme for Underwater Linear Sensor Networks

IF 4.1 4区计算机科学 Q2 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE

International Journal on Semantic Web and Information Systems Pub Date : 2022-01-01 DOI:10.4018/ijswis.299858

Z. Ahmed, M. Ayaz, Mohammad Hijji, Muhammad Zahid Abbas, Aneel Rahim

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引用次数: 3

Abstract

The research on Underwater Wireless Sensor Networks (UWSNs) has grown considerably in recent years where the main focus remains to develop a reliable communication protocol to overcome its challenges between various underwater sensing devices. The main purpose of UWSNs is to provide a low cost and an unmanned data collection system for a range of applications such as offshore exploration, pollution monitoring, oil and gas pipeline monitoring, surveillance, etc. One of the common types of UWSN is Linear Sensor Network (LSN) which specially targets to monitor the underwater oil and gas pipelines. Under this application, in most of the previously proposed works, networks are deployed without considering the heterogeneity and capacity of the various sensor nodes. This negligence leads to the problem of inefficient data delivery from the sensor nodes deployed on the pipeline to the surface sinks. In addition, the existing path planning algorithms do not consider the network coverage of heterogeneous sensor nodes.

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基于auv的水下线性传感器网络高效数据采集方案

近年来，水下无线传感器网络(UWSNs)的研究得到了长足的发展，研究的重点是开发一种可靠的通信协议，以克服各种水下传感设备之间的通信挑战。UWSNs的主要目的是为海上勘探、污染监测、油气管道监测、监视等一系列应用提供低成本的无人数据采集系统。线性传感器网络(LSN)是一种常见的水下传感器网络，专门用于水下油气管道的监测。在这种应用下，在大多数先前提出的工作中，网络的部署没有考虑各个传感器节点的异构性和容量。这种疏忽导致了从部署在管道上的传感器节点到地面接收器的数据传输效率低下的问题。此外，现有的路径规划算法没有考虑异构传感器节点的网络覆盖。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

International Journal on Semantic Web and Information Systems 工程技术-计算机：人工智能

CiteScore

6.20

自引率

12.50%

发文量

审稿时长

20 months

期刊介绍： The International Journal on Semantic Web and Information Systems (IJSWIS) promotes a knowledge transfer channel where academics, practitioners, and researchers can discuss, analyze, criticize, synthesize, communicate, elaborate, and simplify the more-than-promising technology of the semantic Web in the context of information systems. The journal aims to establish value-adding knowledge transfer and personal development channels in three distinctive areas: academia, industry, and government.