A Hybrid Optimization from Two Virtual Physical Force Algorithms for Dynamic Node Deployment in WSN Applications

Abstract

With the rapid development of unmanned aerial vehicle in space exploration and national defense, large-scale wireless sensor network (WSN) became an important and effective technology. It may require highly accurate locating for the nodes in some real applications. The dynamic node topology control of a large-scale WSN in an unmanned region becomes a hot research topic recently, which helps improve the system connectivity and coverage. In this paper, a hybrid optimization based on two different virtual force algorithms inspired by the interactions among physical sensor nodes is proposed to address the self-consistent node deployment in a large-scale WSN. At the early stage, the deployment algorithm was to deploy the sensor nodes by leveraging the particle motions in dusty plasma to achieve the hexagonal topology of the so-called “Yukawa crystal”. After that, another virtual exchange force model was combined to present a hybrid optimization, which could yield perfect hexagonal topology, better network uniformity, higher coverage rate, and faster convergence speed. The influence of node position, velocity, and acceleration during the node deployment stage on the final network topology are carefully discussed for this scheme. It can aid engineers to control the network topology for a large number of wireless sensors with affordable system cost by choosing suitable parameters based on physical environments or application scenarios in the near future.

Node Deployment Optimization for Wireless Sensor Networks Based on Virtual Force-Directed Particle Swarm Optimization Algorithm and Evidence Theory

“…Yu et al [ 22 ] reported a novel VF model based on virtual spring force (VFA-SF) and examined the associated efficiency in detail using statistical analysis. To place the self-consistent nodes in large-scale WSNs, a hybrid optimization algorithm based on two separate VF algorithms inspired by the interactions among physical sensor nodes was presented in [ 23 ]. Afterward, a method based on a 3D VF model driven by self-adaptive deployment (named 3DVFSD) was proposed in [ 24 ].…”

Fruchterman–Reingold Hexagon Empowered Node Deployment in Wireless Sensor Network Application

“…As shown in Figure 6 , compared with the methods designed for large-scale WSNs, such as the virtual force algorithm inspired by Lennard Jones potential (VFA_LJ) and the virtual force algorithm inspired by Dusty Plasma crystallization (VFA_DP) [ 25 ], the topology produced by the FR-HEX algorithm is obviously more regular in different scale ( and ). VFA_LJ always has some regions with uneven nodes.…”

“…As shown in the Figure 9 a, to achieve the densest coverage between nodes, the relationship between the distance and the sensing radius of the sensor is [ 25 ]. According to the statistics in the table, for large-scale deployment, the is about .…”

Improved Routing Protocol Based on Multiobjective Optimization in Industrial Robot Networks

“…Analytic hierarchy process is more suitable for decisionmaking problems with hierarchical and staggered evaluation indexes, and the target value is difficult to describe quantitatively [4].…”