Delay tolerant network routing algorithm based on multi-agent reinforcement learning

Abstract

The invention discloses a time delay tolerant network routing algorithm based on multi-agent reinforcement learning, and the algorithm is characterized in that the algorithm comprises the following steps: 1, carrying out a Louvian clustering algorithm on time delay tolerant network nodes, and providing a centralized and distributed layered architecture; 2, modeling a DTN node selection next hop problem into a distributed partially observable Markov decision process (De-POMDP) model in combination with positive social characteristics. Compared with the prior art, the technical scheme of the patent provides a layered architecture compared with an existing time delay tolerant network routing scheme based on social attributes, and social information of edge equipment can be conveniently captured; on one hand, routing decisions issued by the computing center are executed in a distributed mode, and on the other hand, routing algorithms are trained in a centralized mode at the computing center according to states transmitted by the service units. Routing forwarding in the delay tolerant network can be carried out by effectively utilizing social characteristics, so that the delivery rate is improved, and the average delay is reduced.

Description

technical field [0001] The invention relates to the technical field of network routing algorithms, in particular to a time-delay tolerant network routing algorithm based on multi-agent reinforcement learning. Background technique [0002] Delay Tolerant Network (DTN) is a wireless ad hoc network that employs store-carry-forward routing decisions in network environments where end-to-end paths do not exist a priori. Compared with traditional wireless networks, DTN has higher flexibility and can be better applied to network environments with high latency and frequent link disconnections. [0003] At present, many routing protocols are used to deal with delay tolerant networks, and most of them rely on the comparison between the indicators of each node to make forwarding strategies. However, due to the unreliability of the link, the efficiency of message delivery is poor. Society-based approaches are more promising than opportunistic-based routing protocols because social attr...

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Problems solved by technology

[0004] For this reason, the present invention proposes a delay-tolerant network routing algorithm based on multi-agent reinforcement learning for the poor delivery rate of conventional routing algorithms in delay-tolerant networks; Modeling the Hop Problem as a Distributed Partially Observable Markov Decision Process (Dec-POMDP) ​​Model

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