Hybrid routing method based on clustering and reinforcement learning and ocean communication system

Abstract

The invention belongs to the technical field of ocean communication and discloses a hybrid routing method based on clustering and reinforcement learning and an ocean communication system. The method is characterized by macroscopically learning the Q value of the whole cluster on line to determine the optimal next-hop grid; locally determining a specific node in the optimal grid; selecting a next hop node; realizing a route discovery process in combination with the thought of on-demand routing of an AODV algorithm and the greedy principle of GPSR; when the node needs to send the data packet toa destination node, if the corresponding routing information exists, directly sending the data packet, and if the corresponding routing information does not exist, searching for whether the destination node is in the adjacency list or not, and performing forwarding according to a corresponding node forwarding strategy until the destination node is reached. According to the invention, the floodingof broadcast is reduced, and the routing overhead is reduced; the routing void can be effectively avoided, the selected path is more suitable for the current network state, and the packet loss rate islower.

Description

technical field [0001] The invention belongs to the technical field of marine communication, and in particular relates to a hybrid routing method based on clustering and enhanced learning and a marine communication system. Background technique [0002] At present, due to the lack of marine communication environment infrastructure, the mature wireless communication technology on land cannot be directly applied to the marine communication system. Adhoc is one of the main technologies to realize marine remote communication. [0003] Because the AdHoc network can transmit data in the way of multi-hop forwarding, routing protocols are required to establish a reachable path from the source node to the destination node. The route discovery method and route selection strategy are the core issues of the protocol. According to the route establishment process, it can be divided into the following categories: Active routing protocols such as OLSR, nodes periodically broadcast routing p...

AI Technical Summary

Problems solved by technology

Due to the insufficiency of traditional optimization techniques, the performance improvement of AdHoc networks is not obvious. Therefore, it is necessary to introduce intelligent algorithms into routing protocols and design protocols suitable for fishing AdHoc networks.

Existing Q-learning routing algorithms have their own applicable usage scenarios, and their own advantages and disadvantages, and cannot be directly used in fishing ad hoc networks

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