CLORP: Cross-Layer Opportunistic Routing Protocol for Underwater Sensor Networks Based on Multiagent Reinforcement Learning-Reference-Cited by-同舟云学术

CLORP: Cross-Layer Opportunistic Routing Protocol for Underwater Sensor Networks Based on Multiagent Reinforcement Learning

Published:2024-05-15 Issue:10 Volume:24 Page:17243-17258
ISSN:1530-437X
Container-title:IEEE Sensors Journal
language:
Short-container-title:IEEE Sensors J.

Author:

Liu Shuai¹^ORCID,Wang Jingjing¹^ORCID,Shi Wei¹^ORCID,Han Guangjie²^ORCID,Yan Shefeng³^ORCID,Li Jiaheng⁴^ORCID

Affiliation:

1. College of Information Science and Technology, Qingdao University of Science and Technology, Qingdao, China

2. Department of Internet of Things Engineering, Hohai University, Changzhou, China

3. Institute of Acoustics, Chinese Academy of Sciences, Beijing, China

4. College of Ocean and Earth Sciences and the National and Local Joint Engineering Research Center for Navigation and Location Service Technology, Xiamen University, Xiamen, China

Funder

National Natural Science Foundation of China

Natural Science Foundation of Shandong

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/7361/10530892/10492498.pdf?arnumber=10492498

Reference52 articles.

1. Strengthening the Achilles’ Heel: An AUV-Aided Message Ferry Approach Against Dissemination Vulnerability in UASNs

2. Stochastic Optimization-Aided Energy-Efficient Information Collection in Internet of Underwater Things Networks

3. Enabling Sustainable Underwater IoT Networks With Energy Harvesting: A Decentralized Reinforcement Learning Approach

4. Adaptive Scheduling MAC Protocol in Underwater Acoustic Broadcast Communications for AUV Formation

5. A systematic review on energy efficiency in the internet of underwater things (IoUT): Recent approaches and research gaps