This short paper proposes a Q-learning-based opportunistic routing protocol to prolong the network lifetime of the Internet of Underwater Things (IoUT). The proposed protocol exploits the broadcasting feature of opportunistic routing to obtain real-ti...
This short paper proposes a Q-learning-based opportunistic routing protocol to prolong the network lifetime of the Internet of Underwater Things (IoUT). The proposed protocol exploits the broadcasting feature of opportunistic routing to obtain real-time updates of changes in the topology and to determine the list of the potential next-forwarders (PNFs). Using Q-learning, a PNF can learn if it should become the next-forwarder. Further discussions on the unaddressed issues, such as, network partitioning and hidden node, are provided.