Top > JACIII > Distributed Cooperation Based Priority Coverage Control Strate ...

single-jc.php

JACIII Vol.19 No.2 pp. 191-196
doi: 10.20965/jaciii.2015.p0191
(2015)

Paper:

Views over last 60 days: 729

Distributed Cooperation Based Priority Coverage Control Strategy for Mobile Sensors

Zhi Zheng*,** and Zhihong Peng*

*School of Automation, Beijing Institute of Technology
No. 5 South Street, Zhong Guan Cun, Haidian District, Beijing 100081, China

**School of Mathematics and Computer Science, Fujian Normal University
Fuzhou 350108, China

Received:
July 1, 2014
Accepted:
November 13, 2014
Published:
March 20, 2015
Creative Commons License
Keywords:
mobile sensor, sensing constraints, priority coverage, distributed cooperation, key areas
Abstract
Random deployment and inadequate numbers of sensor nodes may cause low coverage, so we propose a new priority coverage control strategy based on the distributed cooperation of mobile sensors. Sensor nodes are distributed randomly around the region of interest (ROI) and searched for independently. When nodes are found, an unbreakable group is formed under repulsion, attraction and speed consistency control, then searching is begun cooperatively. When some node finds a ROI, it guides the other nodes in the group following it to the ROI. While in the ROI, nodes choose the most important position within the sensing range, then move toward it independently while avoiding collision, eventually, reaching the most important area of the ROI. Under the premise of satisfying key area coverage, sensor nodes are adjusted based on the degree of coverage, maximizing coverage. Simulation results show that the proposed method quickly improves the coverage rate and achieves priority coverage of key areas strongly robustly without being adversely affected by sudden damage to nodes. Applications include coverage with limited amounts of nodes in unknown environments.
Cite this article as:
Z. Zheng and Z. Peng, “Distributed Cooperation Based Priority Coverage Control Strategy for Mobile Sensors,” J. Adv. Comput. Intell. Intell. Inform., Vol.19 No.2, pp. 191-196, 2015.
Data files:
References
  1. [1] Y. Mo, J. Liu, B. Wang, and Q. Wu, “A Novel Swarm Intelligence Algorithm and Its Application in Solving Wireless Sensor Networks Coverage Problems,” J. of Networks, Vol.7, No.12, pp. 2037-2043, 2012.
  2. [2] S. Chamberland, L. Cobo, F. Mourchid, and A. Quintero, “A Wireless Sensor Network Deployment Model With Target Localization Constraints,” Telecommunications Network Strategy and Planning Symp., pp. 1-4, 2012.
  3. [3] C. Ozturk, B. Gorkemli, and D. Karaboga, “Artificial Bee Colony Algorithm for Dynamic Deployment of Wireless Sensor Networks,” Turkish J. of Electrical Engineering & Computer Sciences, Vol.20, No.2, pp. 255-262, 2012.
  4. [4] S. Ding, C. Chen, J. Chen, and B. Xin, “An Improved Particle Swarm Optimization Deployment for Wireless Sensor Networks,” J. of Advanced Computational Intelligence and Intelligent Informatics, Vol.18, No.2, pp. 107-112, 2014.
  5. [5] J. Luo, D. Wang, and Q. Zhang, “On The Double Mobility Problem For Water Surface Coverage With Mobile Sensor Networks,” IEEE Trans. on Parallel and Distributed Systems, Vol.23, No.1, pp. 146-159, 2012.
  6. [6] [6 ]M. Jin, G. Rong, H. Wu, L. Shuai, and X. Guo, “Optimal Surface Deployment Problem in Wireless Sensor Networks,” Proc. of the 31st Annual IEEE Conf. on Computer Communications, Orlando, pp. 2345-2353, 2012.
  7. [7] X. Liu, K. Wu, Y. Zhu, L. Kong, and M. Wu, “Mobility Increases The Surface Coverage of Distributed Sensor Networks,” Computer Networks, Vol.57, pp. 2348-2363, 2013.
  8. [8] C. G. Cassandras, X. Lin, and X. Ding, “An optimal control approach to the multi-agent persistent monitoring problem,” IEEE Trans. on Automatic Control, Vol.58, pp. 947-961, 2013.
  9. [9] H. Mahboubi, J. Habibi, A. G. Aghdam, and K. Sayrafian-Pour, “Distributed Deployment Strategies for Improved Coverage in A Network of Mobile Sensors with Prioritized Sensing Field,” IEEE Trans. on Industrial Informatics, Vol.9, No.1, pp. 451-461, 2013.
  10. [10] R. Olfati-Saber, “Flocking for Multi-Agent Dynamic Systems: Algorithms and Theory,” IEEE Trans. on Automatic Control, Vol.51, No.3, pp. 401-420, 2006.

Creative Commons License  This article is published under a Creative Commons Attribution-NoDerivatives 4.0 Internationa License.

*This site is desgined based on HTML5 and CSS3 for modern browsers, e.g. Chrome, Firefox, Safari, Edge, Opera.

Last updated on Apr. 22, 2024