Open AccessReinforcement Learning-Based Routing Protocol for Underwater Wireless Sensor Networks: A Comparative Survey
Author(s) -
Rehenuma Tasnim Rodoshi,
Yujae Song,
Wooyeol Choi
Publication year - 2021
Publication title -
ieee access
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.587
H-Index - 127
ISSN - 2169-3536
DOI - 10.1109/access.2021.3128516
Subject(s) - aerospace , bioengineering , communication, networking and broadcast technologies , components, circuits, devices and systems , computing and processing , engineered materials, dielectrics and plasmas , engineering profession , fields, waves and electromagnetics , general topics for engineers , geoscience , nuclear engineering , photonics and electrooptics , power, energy and industry applications , robotics and control systems , signal processing and analysis , transportation
Underwater wireless sensor networks (UWSNs) have emerged as a promising networking technology owing to their various underwater applications. Many applications require sensed data to be routed to a centralized location. However, the routing of sensor networks in underwater environments presents several challenges in terms of underwater infrastructure, including high energy consumption, narrow bandwidths, and longer propagation delays than other sensor networks. Efficient routing protocols play a vital role in this regard. Recently, reinforcement learning (RL)-based routing algorithms have been investigated by different researchers seeking to exploit the learning procedure via trial-and-error methods of RL. RL algorithms are capable of operating in underwater environments without prior knowledge of the infrastructure. This paper discusses all routing protocols proposed for RL-based UWSNs. The advantages, disadvantages, and suitable application areas are also mentioned. The protocols are compared in terms of the key ideas, RL designs, optimization criteria, and performance-evaluation techniques. Moreover, research challenges and outstanding research issues are also highlighted, to indicate future research directions.