An Opportunistic Network Routing Method Oriented to the Recognition of Temporal and Spatial Characteristics Variations

Abstract

The invention relates to an opportunistic network routing method based on spatial-temporal characteristic change cognition, and belongs to the technical field of opportunistic network, cognitive Internet of things and self-organizing network. The method comprises the following steps: S1, a node movement semi-Markov model building stage which is used to predict the probability that a node is in a geographical area at a future time and the utility value of contact between nodes in a future period of time; S2, a node spatial-temporal characteristic change cognition mechanism stage which is used to detect whether the spatial-temporal characteristic change of nodes is consistent with the semi-Markov model; and S3, a routing method adaptive implementation stage which is used for a node carrying a message to compare the utility values of contact with encountering nodes so as to decide whether or not to forward the message. The method provided by the invention can overcome the problems existing in the prior art, and an efficient and smart cognitive self-organizing routing mechanism can be realized.

Description

Technical field [0001] The invention belongs to the technical fields of opportunistic networks, cognitive Internet of Things and self-organizing networks, and relates to a method for opportunistic network routing cognition oriented to temporal and spatial characteristics change. Background technique [0002] Due to the lack of flexible self-management capabilities, the traditional self-organizing routing technology can no longer fully adapt to the increasingly complex transmission environment. The future Internet of Things needs to have service perception, data perception, and environment perception capabilities. It will also have intelligent cognitive capabilities. To truly realize the smart Internet of Things, the Internet of Things needs to be upgraded from "perception" to "cognition" "At the level, it constitutes the cognitive Internet of Things. The core idea of ​​"cognition" is to give nodes the characteristics of autonomy and wisdom, so that they have self-learning abilit...

AI Technical Summary

Problems solved by technology

[0005] At present, the existing opportunistic network routing methods based on the cognition of changes in node spatiotemporal characteristics have the following problems: 1) The model established for opportunistic network nodes ignores the areas between mobile areas and does not conform to the real network environment

2) The transfer area is added to the established semi-Markov model, which will increase the storage space and algorithm complexity of the nodes

The above three problems have a negative impact on the network delivery rate, overhead rate and average message delivery delay performance of the existing routing methods oriented to the change of space-time characteristics, so it is necessary to propose a new technical solution to solve them

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