Covering method based on virtual force and Thiessen polygons

Abstract

The invention discloses a covering method based on virtual force and Thiessen polygons. Wireless nodes are decentralized as much as possible according to a virtual force scheme to increase the initial covering rate of a monitored area, then a Voronoi set partitioning scheme and Minmax precision adjustment are adopted, the condition that the virtual force scheme falls into local optimum is effectively reduced, the convergence speed of the virtual force algorithm is increased by means of a centroid algorithm, and after multiple times of iteration, the wireless nodes can achieve the widest wireless signal covering range in a limited area by means of the covering method.

Description

technical field [0001] The invention relates to a wireless sensor node covering method, in particular to a covering method based on virtual force and Thiessen polygon. Background technique [0002] Wireless Sensor Network (WSN) has a wide range of applications in environmental perception, intrusion detection, disaster monitoring, etc. These applications require wireless sensor networks to cover fixed areas to ensure effective perception and detection. . If the deployment area is large and the detection target requirements are high, a large number of wireless sensor network nodes will be required, which will greatly increase the deployment cost of the network. How to use less wireless sensor nodes to meet the coverage requirements of the network, so as to meet the application requirements, is particularly important. [0003] The wireless sensor network coverage algorithm can be divided into two categories, one is the centralized coverage algorithm, that is, by pre-deploying...

AI Technical Summary

Problems solved by technology

[0004] The particle swarm optimization algorithm has the advantages of fast search speed and simple algorithm, but it does not handle discrete optimization problems well, and it is easy to fall into local optimum

Probabilistic perception model algorithm operation must obtain all global node information, its probability model runs faster, but its subjective influence factors are relatively large

The node-aware direction adjustment algorithm has high algorithm complexity and high requirements on node energy, which is not suitable for large-scale deployment

In the virtual force algorithm, the influence of subjective factors is small, the convergence speed is fast, and there is no need to obtain global node information. It is suitable for large-scale deployment, but it is easy to fall into local optimum

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