Routing Protocol Design for Underwater Optical Wireless Sensor Networks: A Multiagent Reinforcement Learning Approach
- 23 April 2020
- journal article
- research article
- Published by Institute of Electrical and Electronics Engineers (IEEE) in IEEE Internet of Things Journal
- Vol. 7 (10) , 9805-9818
Abstract
Underwater optical wireless sensor networks (UOWSNs) have been attracting many interests for advantages of high transmission rate, ultra-wide bandwidth, and low latency. However, due to limited energy resources and highly-dynamic topology caused by water flow movement, it is challenging to provide a low-consumption and reliable routing in UOWSNs. To tackle this issue, in this paper, we propose an efficient routing protocol based on multi-agent reinforcement learning, termed as DMARL, for UOWSNs. The network is firstly modeled as a distributed multi-agent system, and residual energy and link quality are considered into the routing protocol design to improve the adaptation to a dynamic environment and the support of prolonging network life. Additionally, two optimization strategies are proposed to accelerate the convergence of the reinforcement learning algorithm. On the basis, a reward mechanism is provided for the distributed system. Simulation results show that DMARL-based routing protocol has low energy consumption and high packet delivery ratio (over 90%), and it is suitable for networks where the average number of neighbour nodes is less than 14.Keywords
Funding Information
- National Natural Science Foundation of China (61471177, 61901302)
- Open Research Fund from Shenzhen Research Institute of Big Data (2019ORF01014)
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