Journal of East China Normal University(Natural Science) >

2015 , Vol. 2015 >Issue 1: 151 - 160

DOI: https://doi.org/10.3969/j.issn.10005641.2015.01.019

Article

K coverage of WiFi signal node deployment based on AFSA

  • LI Zhong-Xiang ,
  • CHEN Lei
Expand
  • Department of Computer Science and Technology, East China Normal University, Shanghai 200241, China

Received date: 2014-05-01

  Online published: 2015-03-29

Fold

Abstract

On the requirement of multiple wireless coverage in some hot applications like indoor positioning and navigation, multipath routing etc., this paper presented a K coverage placement scheme based on an improved Artificial FishSwarm Algorithm (AFSA). A simple obstacle interference describing model was also designed to make our simulation scenario closer to a real one. The simulative results showed that our method could obviously reduce the number of signal nodes and their aggregation on the premise of coverage.

Key words： K coverage; AFSA; WiFi

Cite this article

LI Zhong-Xiang , CHEN Lei . K coverage of WiFi signal node deployment based on AFSA[J]. Journal of East China Normal University(Natural Science), 2015 , 2015(1) : 151 -160 . DOI: 10.3969/j.issn.10005641.2015.01.019

References

BAI X, XUAN D, YUN Z, et al. Complete optimal deployment patterns for fullcoverage and kconnectivity (k≤ 6) wireless sensor networks［C］//Proceedings of the 9th ACM international symposium on Mobile ad hoc networking and computing. ACM, 2008: 401-410.

ZOU Y, CHAKRABARTY K. Sensor deployment and target localization based on virtual forces［C］//INFOCOM 2003. TwentySecond Annual Joint Conference of the IEEE Computer and Communications. IEEE Societies. IEEE, 2003, 2: 1293-1303

YU X, HUANG W, LAN J, et al. A novel virtual force approach for node deployment in wireless sensor network［C］//Distributed Computing in Sensor Systems (DCOSS), 2012 IEEE 8th International Conference on. IEEE, 2012: 359-363. 

REDA S M, ABDELHAMID M, LATIFA O, et al. Efficient uncertaintyaware deployment algorithms for wireless sensor networks［C］//Wireless Communications and Networking Conference (WCNC), 2012 IEEE. IEEE, 2012: 2163-2167. 

NAVARRO M, DAVIS T W, LIANG Y, et al. ASWP: a longterm WSN deployment for environmental monitoring［C］//Proceedings of the 12th international conference on Information processing in sensor networks. ACM, 2013: 351-352.

HE Y, MENG W X, MA L, et al. Rapid deployment of APs in WLAN indoor positioning system［C］//Proceedings of the 2011 6th International ICST Conference on Communications and Networking in China. IEEE Computer Society, 2011: 268-273.

WANG G, GUO L, DUAN H, et al. Dynamic deployment of wireless sensor networks by biogeography based optimization algorithm［J］. Journal of Sensor and Actuator Networks, 2012, 1(2): 86-96.

WANG Y Y, LIAO H M, HU H Y. Wireless sensor network deployment using an optimized artificial fish swarm algorithm［C］//Computer Science and Electronics Engineering (ICCSEE), 2012 International Conference on. IEEE, 2012, 2: 90-94. 

KIM J E, HAN J, LEE C G. Optimal 3coverage with minimum separation requirements for ubiquitous computing environments［J］. Mobile Networks and Applications, 2009, 14(5): 556-570.

LI F, LUO J, XIN S Q, et al. LAACAD: Load balancing karea coverage through autonomous deployment in wireless sensor networks［C］//Distributed Computing Systems (ICDCS), 2012 IEEE 32nd International Conference on. IEEE, 2012: 566-575.

CHANG C Y, CHEN Y C, CHANG H R. Obstacleresistant deployment algorithms for wireless sensor networks［J］. Vehicular Technology, IEEE Transactions on, 2009, 58(6): 2925-2941.

WU C H, LEE K C, CHUANG Y C. A Delaunay triangulation based method for wireless sensor network deployment［J］. Computer Communications, 2007, 30(14): 27442752.

PATRO A, GOVINDAN S, BANERJEE S. Observing home wireless experience through WiFi APs［C］//Proceedings of the 19th annual international conference on Mobile computing & networking. ACM, 2013: 339-350. 
Options
Outlines

/

〈 〉