Energy Efficient Multi-Objective Evolutionary Routing Scheme for Reliable Data Gathering in Internet of Underwater Acoustic Sensor Networks

Loading...
Publication Logo

Date

2019

Journal Title

Journal ISSN

Volume Title

Publisher

Elsevier

Open Access Color

Green Open Access

Yes

OpenAIRE Downloads

OpenAIRE Views

Publicly Funded

No
Impulse
Top 10%
Influence
Top 10%
Popularity
Top 10%

Research Projects

Journal Issue

Abstract

Earth's surface is covered with two-thirds of water. The marine world covers the lakes, rivers and sea and is rich in natural resources largely unexplored by human beings. Recently, underwater wireless sensor network (UWSN) with the advancement in the Internet of underwater smart things has emerged as promising networking techniques to explore the mysteries of vastly unexplored ocean environments for several underwater applications. These applications include offshore exploration, pollution monitoring, disaster prevention, oceanographic data collection, offshore oil fields monitoring, tactical surveillance applications and several others. However, the underwater channel impairments caused by multipath effects, fading, bit errors, variable and high latency and low bandwidth severely limits the data transmission reliability for UWSNs-based applications. This results in poor quality-aware data gathering in UWSNs. Therefore, designing a quality of service (QoS)-aware data gathering protocol to monitor and explore oceans is challenging in the underwater environments. In this paper, we propose a bio-inspired multi-objective evolutionary routing protocol (called MERP) for UWSNs-based applications. The designed routing protocol exploits the features of the natural evolution of the multi-objective genetic algorithm in order to provide reliable and energy-aware information gathering in UWSNs. The extensive simulation results show that the developed protocol attains its defined goals compared to existing UWSNs-based routing protocols during monitoring and exploring underwater environments. (C) 2019 Elsevier B.V. All rights reserved.

Description

Ngadi, Md Asri/0000-0003-4907-6359; Phd, Muhammad Faheem,/0000-0003-4628-4486;

Keywords

Multi-Objective, Evolutionary, Acoustic Sensor Network, Underwater Sensor Network, Internet of Underwater Things, QA75 Electronic computers. Computer science, 303

Fields of Science

0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology

Citation

WoS Q

Q1

Scopus Q

Q1
OpenCitations Logo
OpenCitations Citation Count
39

Source

Ad Hoc Networks

Volume

93

Issue

Start Page

101912

End Page

PlumX Metrics
Citations

Scopus : 54

Captures

Mendeley Readers : 42

SCOPUS™ Citations

57

checked on Mar 04, 2026

Web of Science™ Citations

45

checked on Mar 04, 2026

Page Views

1

checked on Mar 04, 2026

Downloads

5

checked on Mar 04, 2026

Google Scholar Logo
Google Scholar™
OpenAlex Logo
OpenAlex FWCI
6.2046
Altmetrics Badge

Sustainable Development Goals