A cover hole repair method based on improved k-means and genetic algorithm

Aiming at the problem that the uncertainty of the location of virtual repair nodes in Wireless Sensor Networks (WSNs) changes the topology of the network and causes the network to lose connectivity, a coverage hole repair optimization method based on improved k-means genetic algorithm is proposed. Firstly, use the hole modeling analysis to determine the position of the virtual repair node, and cluster the sensor nodes in the hole area according to the improved k-means algorithm. Secondly, use the improved genetic algorithm to find the shortest path in each cluster in parallel. Finally, the minimum distance principle is used to integrate each cluster into a whole, and the shortest path in the cavity area is found, and the sensing data in the cavity area is transmitted and communicated along the path within a certain period of time. The simulation results show that it is feasible to apply the improved k-means genetic algorithm to the coverage hole repair. Through multiple iterations of the algorithm, the shortest path between repair nodes in the hole can be found to achieve network connectivity, save node energy, and extend the network life cycle.