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Underwater wireless sensor network routing method based on reinforcement learning

A wireless sensor and reinforcement learning technology, which is applied to services based on specific environments, wireless communication, network topology, etc., and can solve the problem that weights are not suitable for using fixed thresholds.

Active Publication Date: 2021-06-11
HARBIN ENG UNIV
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  • Abstract
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  • Claims
  • Application Information

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Problems solved by technology

In summary, UWSN routing design is a multi-objective optimization problem, and the weight of each influencing factor is not suitable for the fixed threshold method when the sensor nodes are in different states

Method used

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  • Underwater wireless sensor network routing method based on reinforcement learning
  • Underwater wireless sensor network routing method based on reinforcement learning
  • Underwater wireless sensor network routing method based on reinforcement learning

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Embodiment Construction

[0033] Embodiments of the present invention are described in detail below, examples of which are shown in the drawings, wherein the same or similar reference numerals designate the same or similar elements or elements having the same or similar functions throughout. The embodiments described below by referring to the figures are exemplary and are intended to explain the present invention and should not be construed as limiting the present invention.

[0034] The following describes the underwater wireless sensor network routing method based on reinforcement learning according to the embodiments of the present invention with reference to the accompanying drawings.

[0035] figure 1 It is a flowchart of an underwater wireless sensor network routing method based on reinforcement learning according to an embodiment of the present invention.

[0036] Such as figure 1 As shown, the underwater wireless sensor network routing method based on reinforcement learning includes the follo...

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Abstract

The invention discloses an underwater wireless sensor network routing method based on reinforcement learning, which comprises the following steps of: initializing sensor nodes in an underwater wireless sensor network UWSN to obtain information of neighbor sensor nodes around the sensor nodes, and establishing a neighbor list; establishing a node packet forwarding adaptability prediction model based on fuzzy logic according to the neighbor list; designing a state-action value updating function between sensor nodes according to the node packet forwarding suitability prediction model, and establishing a first updating strategy based on a target sensor node, a second updating strategy based on a dynamic threshold value and a data packet forwarding strategy based on opportunity attributes; and entering a data packet updating and forwarding process by utilizing a state-action value updating function, and finishing data packet updating and forwarding by utilizing the three strategies. According to the method, network topology changes caused by node mobility can be adaptively coped with, energy and time delay factors are considered at the same time, and the opportunity attribute concept is utilized to further improve the stability of the algorithm.

Description

technical field [0001] The invention relates to the technical field of underwater wireless sensor networks, in particular to a routing method for underwater wireless sensor networks based on reinforcement learning. Background technique [0002] Underwater Internet of Things (IoUT), as an extension of Internet of Things (IoT), makes it possible to monitor large-scale water areas. With the development of wireless communication technology, the underwater wireless sensor network (UWSN) composed of sensor nodes has become a The carrier of this technology, and UWSN routing algorithm design is not only the core of UWSN, but also a hot topic in UWSN related research. [0003] The traditional UWSN routing algorithm mainly considers the current state of the sensor node when making decisions, and lacks flexible control and global control of the entire UWSN. With the improvement of sensor performance and the improvement of intelligent algorithm related theories, intelligent algorithms, ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): H04W40/24H04W40/02H04W40/10H04W40/20H04W40/12H04W4/38H04W84/18
CPCH04W40/246H04W40/248H04W40/02H04W40/10H04W40/20H04W40/12H04W4/38H04W84/18
Inventor 王桐郐成志赵晨龚续付李悦
Owner HARBIN ENG UNIV
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