Networking Optimization Algorithm For Mobile Sensing Nodes Oriented To Industrial Production

Optimization of mobile sensor positions is an important issue in wireless sensor networks because it significantly affects energy consumption, surveillance ability, and lifetime of the network. Vector-based algorithm (VEC) and Voronoi-based algorithm (VOR) are two existing deployment approaches. However, VEC is sensitive to initial deployment, whereas VOR always moves to heal the coverage holes without considering the generation of new holes. Moreover, the nodes in the network may oscillate for a long time before they reach static equilibrium.This paper introduces an initially central deployment model that is cost effective and easy to implement. Based on this model, we present a novel distributed deployment algorithm based on Voronoi diagram- algorithm based on boundary expansion and virtual force (BEVF), and a centralized algorithm based on genetic algorithm (GA) is presented as well. The purpose of the first algorithm (BEVF) is to enable nodes to rapidly move to the boundary and ultimately reach static equilibrium quickly, as well as to maximize network coverage. For one node, only the locations of its nearby nodes and boundary information are needed in the first proposed algorithm, thereby avoiding communication cost for transmitting global information. Meanwhile, at least one sink node must be deployed in the target area to collect and send location information to move the other nodes to the destination one-time in the second proposed algorithm.Finally, we compare GA and BEVF with existing algorithms, the simulation results show that the proposed distributed algorithm achieves a much larger coverage and has smaller energy consumption, and the centralized algorithm achieves better in almost all aspects.