Citation: Zhu, R.; Huang, X.; Huang,
X.; Li, D.; Yang, Q. An On-Site-Based
Opportunistic Routing Protocol for
Scalable and Energy-Efficient
Underwater Acoustic Sensor
Networks. Appl. Sci. 2022, 12, 12482.
https://doi.org/10.3390/app122312482
Academic Editor: Subhas
Mukhopadhyay
Received: 9 November 2022
Accepted: 1 December 2022
Published: 6 December 2022
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Article
An On-Site-Based Opportunistic Routing Protocol for Scalable
and Energy-Efficient Underwater Acoustic Sensor Networks
Rongxin Zhu
1,2
, Xiwen Huang
3
, Xiangdang Huang
1,3
, Deshun Li
1,3
and Qiuling Yang
1,3,
*
1
School of Cyberspace Security, Hainan University, Haikou 570228, China
2
School of Mathematics and Information Science, Nanjing Normal University of Special Education,
Nanjing 210038, China
3
School of Computer Science and Technology, Hainan University, Haikou 570228, China
* Correspondence: yql0515@163.com
Abstract:
With the advancements in wireless sensor networks and the Internet of Underwater Things
(IoUT), underwater acoustic sensor networks (UASNs) have attracted much attention, which has
also been widely used in marine engineering exploration and disaster prevention. However, UASNs
still face many challenges, including high propagation latency, limited bandwidth, high energy
consumption, and unreliable transmission, influencing the good quality of service (QoS). In this
paper, we propose a routing protocol based on the on-site architecture (SROA) for UASNs to improve
network scalability and energy efficiency. The on-site architecture adopted by SROA is different
from most architectures in that the data center is deployed underwater, which makes the sink nodes
closer to the data source. A clustering method is introduced in SROA, which makes the network
adapt to the changes in the network scale and avoid single-point failure. Moreover, the Q-learning
algorithm is applied to seek optimal routing policies, in which the characteristics of underwater
acoustic communication such as residual energy, end-to-end delay, and link quality are considered
jointly when constructing the reward function. Furthermore, the reduction of packet retransmissions
and collisions is advocated using a waiting mechanism developed from opportunistic routing (OR).
The SROA realizes opportunistic routing to choose candidate nodes and coordinate packet forwarding
among candidate nodes. The scalability of the proposed routing protocols is also analyzed by varying
the network size and transmission range. According to the evaluation results, with the network scale
ranging from 100 to 500, the SROA outperforms the existing routing protocols, extensively decreasing
energy consumption and end-to-end delay.
Keywords:
routing protocol; underwater sensor networks; Q-Learning; clustering; Internet of
Underwater Things (IoUT)
1. Introduction
During recent years, Underwater Acoustic Sensor Networks (UASNs) have gained
much attention for the potential to explore and monitor the underwater environment [
1
].
UASN is one of the fundamental techniques of the Internet of Underwater Things (IoUT),
which was developed from the concept of terrestrial Internet of Things (IoT) [
2
]. Large-scale
UASN enables the extension of IoT to ocean applications, considered to be a promising
solution for exploring the oceans [
3
]. One of the key problems for these applications is how
to collect and forward the sensed data from the source node to the sink node [4].
Owing to the unique features of the underwater acoustic environment, routing in
UASNs confronts crucial challenges, such as signal propagation delay, limited bandwidth,
and low energy efficiency [
5
]. Scaling up or down the network size according to the
actual demand in the underwater environment is usually necessary, while maintaining the
reliability of the network. Adaptive formation of the network is taken into consideration
in this article, enabling nodes to independently join or leave the network. Moreover, the
Appl. Sci. 2022, 12, 12482. https://doi.org/10.3390/app122312482 https://www.mdpi.com/journal/applsci
