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

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, φs, 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.

[1]  Tao Zhang,et al.  A Node Deployment Algorithm Based on Van Der Waals Force in Wireless Sensor Networks , 2013, Int. J. Distributed Sens. Networks.

[2]  Xiang Li,et al.  Deploying Three-Dimensional Mobile Sensor Networks Based on Virtual Forces Algorithm , 2012, CWSN.

[3]  Wen-Hwa Liao,et al.  A sensor deployment approach using glowworm swarm optimization algorithm in wireless sensor networks , 2011, Expert Syst. Appl..

[4]  Joseph O'Rourke,et al.  Computational Geometry in C. , 1995 .

[5]  Yulai Suen.  A Genetic-Algorithm Based Mobile Sensor Network Deployment Algorithm EE 382 C : Embedded Software Systems Final Report , .

[6]  Jack Snoeyink,et al.  A Comparison of Five Implementations of 3D Delaunay Tessellation , 2005 .

[7]  华建华,et al.  Structural and Dynamical Analysis of a Two—Dimensional Dusty Plasma Lattice , 2003 .

[8]  Derviş Karaboğa,et al.  Artificial bee colony algorithm for dynamic deployment of wireless sensor networks , 2012, Turkish Journal of Electrical Engineering and Computer Sciences.

[9]  Hossam S. Hassanein,et al.  On the robustness of grid-based deployment in wireless sensor networks , 2006, IWCMC '06.

[10]  Tao Zhang,et al.  A Faster Convergence Artificial Bee Colony Algorithm in Sensor Deployment for Wireless Sensor Networks , 2013, Int. J. Distributed Sens. Networks.

[11]  Krishnendu Chakrabarty,et al.  Sensor deployment and target localization based on virtual forces , 2003, IEEE INFOCOM 2003. Twenty-second Annual Joint Conference of the IEEE Computer and Communications Societies (IEEE Cat. No.03CH37428).

[12]  Pramod K. Varshney,et al.  A distributed self spreading algorithm for mobile wireless sensor networks , 2003, 2003 IEEE Wireless Communications and Networking, 2003. WCNC 2003..

[13]  Liao Hongmei,et al.  Wireless Sensor Network Deployment Using an Optimized Artificial Fish Swarm Algorithm , 2012, 2012 International Conference on Computer Science and Electronics Engineering.

[14]  Thomas F. La Porta,et al.  Movement-Assisted Sensor Deployment , 2006, IEEE Trans. Mob. Comput..

[15]  Anis Laouiti,et al.  Redeploying mobile wireless sensor networks with virtual forces , 2009, 2009 2nd IFIP Wireless Days (WD).

[16]  Zhiming Li,et al.  Sensor node deployment in wireless sensor networks based on improved particle swarm optimization , 2009, 2009 International Conference on Applied Superconductivity and Electromagnetic Devices.

[17]  Ian F. Akyildiz,et al.  Wireless sensor networks: a survey , 2002, Comput. Networks.

[18]  Cui,et al.  Structural analysis of a Coulomb lattice in a dusty plasma. , 1996, Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics.

[19]  Zhou Chao.  A Deterministic Sensor Node Deployment Method with Target Coverage Based on Grid Scan , 2012 .

[20]  Haiping Huang,et al.  Sensor Node Deployment in Wireless Sensor Networks based on Ionic Bond-Directed Particle Swarm Optimization , 2014 .

[21]  Mo Li,et al.  A Survey on Topology issues in Wireless Sensor Network , 2006, ICWN.

[22]  Xiangyu Yu,et al.  A Novel Virtual Force Approach for Node Deployment in Wireless Sensor Network , 2012, 2012 IEEE 8th International Conference on Distributed Computing in Sensor Systems.

[23]  Tao Zhang,et al.  A Deployment Method Based on Spring Force in Wireless Robot Sensor Networks , 2014 .

[24]  Wang Long,et al.  Structural and Dynamical Analysis of a Two-Dimensional Dusty Plasma Lattice , 2003 .

[25]  Pei-Ling Chiu,et al.  A near-optimal sensor placement algorithm to achieve complete coverage-discrimination in sensor networks , 2005, IEEE Communications Letters.

[26]  Young-Sik Jeong,et al.  An energy-efficient self-deployment with the centroid-directed virtual force in mobile sensor networks , 2012, Simul..

[27]  Michele Garetto,et al.  A Distributed Sensor Relocatlon Scheme for Environmental Control , 2007, 2007 IEEE Internatonal Conference on Mobile Adhoc and Sensor Systems.

[28]  Gaurav S. Sukhatme,et al.  Mobile Sensor Network Deployment using Potential Fields : A Distributed , Scalable Solution to the Area Coverage Problem , 2002 .