A non-cooperative inference method for ad Hoc network physical topology

Abstract

The invention relates to a non-cooperative inference method of Ad Hoc network physical topology, belonging to the technical field of wireless networks. The method includes the following steps: S1: using radio positioning to distinguish and locate nodes in the Ad Hoc network; S2: obtaining the size of the network deployment area according to the node differentiation and positioning information; S3: according to the size of the network deployment area and the nodes Calculate the important communication distance of the node by distinguishing the positioning information; S4: Infer the network physical topology according to the distinguishing positioning information of the node and the important communication distance of the node. The invention realizes the automatic inference of the network physical topology under the condition of unknown node communication power and other related parameters, and compared with the existing method, the structural effectiveness of the network physical topology is improved and the calculation complexity of the realization process is reduced.

Description

technical field [0001] The present invention relates to the technical field of wireless networks, in particular to a construction method for Ad Hoc network physical topology non-cooperative inference and optimization. Background technique [0002] Ad Hoc networks can be quickly deployed and do not need to set up network facilities, making them widely used in both civilian and military applications. [0003] Existing research on network topology mainly focuses on logical topology. In the process of physical topology analysis, it is mainly based on the known maximum communication distance of nodes or using the longest distance of the minimum spanning tree constructed by network nodes as the maximum communication distance. Since it is usually deployed in an unsafe area, it is difficult to obtain the maximum communication distance of the node without knowing the relevant parameters such as the communication power of the node. Using the longest distance of the minimum spanning t...

AI Technical Summary

Problems solved by technology

Since it is usually deployed in an unsafe area, it is difficult to obtain the maximum communication distance of a node in the case of unknown node communication power and other related parameters

Using the longest distance of the minimum spanning tree as the maximum communication distance does not take into account the situation that a single node is out of the network and cannot effectively deal with changes in node positions. Every time a node changes its position, the minimum spanning tree must be rebuilt to calculate the longest distance, resulting in increase in computational complexity

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