Optimized Node Deployment Algorithm and Parameter Investigation in a Mobile Sensor Network for Robotic Systems

Abstract

Mobile sensor networks are an important part of modern robotics systems and are widely used in robotics applications. Therefore, sensor deployment is a key issue in current robotics systems research. Since it is one of the most popular deployment methods, in recent years the virtual force algorithm has been studied in detail by many scientists. In this paper, we focus on the virtual force algorithm and present a corresponding parameter investigation for mobile sensor deployment. We introduce an optimized virtual force algorithm based on the exchange force, in which a new shielding rule grounded in Delaunay triangulation is adopted. The algorithm employs a new performance metric called 'pair-correlation diversion', designed to evaluate the uniformity and topology of the sensor distribution. We also discuss the implementation of the algorithm's computation and analyse the influence of experimental parameters on the algorithm. Our results indicate that the area ratio, φ s , and the exchange force constant, G, influence the final performance of the sensor deployment in terms of the coverage rate, the convergence time and topology uniformity. Using simulations, we were able to verify the effectiveness of our algorithm and we obtained an optimal region for the (φ s , G)-parameter space which, in the future, could be utilized as an aid for experiments in robotic sensor deployment.

Investigation of the Shielding Length on Yukawa System Crystallization in Mobile Sensor Network Applications

“…In our previous work, we used a novel performance metric called the PCD to evaluate the proximity between any network coverage topology and perfect hexagonal topology [10], [11]. The method is based on the pair-correlation function g(r ) = (N(r, )S)/(2πr N) within the crystal structure that represents the probability of finding two nodes separated by a distance r .…”

“…where is the network topology to be analyzed, H is the perfect hexagonal topology, and r T is the bound of the radial distance [11].…”

“…How to effectively deploy a sensor network has been a significant research topic in recent years. Many approaches have been proposed for sensor network deployment that have advantages, including: 1) virtual force or potential-based strategies; 2) computational geometry and grid-based methods; and 3) a combination of the above approaches [1]- [11].…”

An Optimized Node Deployment Solution Based on a Virtual Spring Force Algorithm for Wireless Sensor Network Applications

“…However, the topology of their overall network is relatively dense in the center and is sparse in the edge due to some physical reasons. According to the computational geometry-based approach [10,11,12,13], nodes readjust their positions by virtual force generated from adjacent nodes which satisfy a certain geometric condition. As for the method based on biogeography [14,15,16], nodes readjust their positions by simulating biological habits.…”

“…However, in previous virtual force algorithm papers, most of the simulations verifying their deployment methods have been single and not universal [8,9,10,11,16,17]. For example, based on our retests in virtual exchange force [10,11], spring force [17], Van der Waals forces [8], and dusty plasma crystallization [9] algorithms, the experiments may have different deployment effects due to different initial sensor network even using the same simulation parameters. Therefore, in this paper, this is the first time to use a large number of experiments to statistically study the validation and stability of virtual force algorithm.…”