research-article

A performance evaluation of a coverage compensation based algorithm for wireless sensor networks

Authors:

Azzedine BoukercheAuthors Info & Claims

MSWiM '08: Proceedings of the 11th international symposium on Modeling, analysis and simulation of wireless and mobile systems

Pages 109 - 116

https://doi.org/10.1145/1454503.1454525

Published: 27 October 2008 Publication History

Abstract

Recent years, coverage has been widely investigated as one of the fundamental quality measurements of wireless sensor networks. In order to maintaining the coverage while saving energy of networks, algorithms have been developed to keep a minimum cover set of sensors working and turn off the redundant sensors. Generally, centralized algorithms can give a better result than distributed algorithms in terms of the number of active sensors. However, the heavy computation requirements and message overhead for collecting geographical location data keep centralized algorithms out of most distributed scenarios. In this article, Based on the idea of coverage compensation a distributed node partition algorithm for random deployments is presented to generate a minimum cover set by using the optimal node distributions created by the centralized algorithms such as GA. A Genetic Algorithm for coverage is proposed too to demonstrate how an optimal coverage node distribution created by GA can be used in a distributed scenario. Ours works are simulated on JGAP and NS2. The simulation result shows that our partition algorithm based on coverage compensation can achieve the same performance as OCOPS in terms of coverage and number of active sensors while using less control messages.

References

[1]

A. Boukerche, X. Fei, R.B. Araujo An energy aware coverage-preserving scheme for wireless sensors network. Proceedings of the 2nd ACM international workshop PE-WASUN '05, pp.205 -- 213.

Digital Library

[2]

A. Boukerche, X. Fei, A coverage-preserving scheme for wireless sensor network with irregular sensing range. Ad Hoc Networks, Volume 5, Issue 8, November 2007, pp. 1303--1316.

Digital Library

[3]

C.-F. Huang and Y.-C. Tseng The coverage problem in a wireless sensor network. ACM MobiCom'03, Sep. 2003, pp. 115--121.

Digital Library

[4]

C.-F. Huang, Y.-C.e Tseng, and L.-C. Lo. The coverage problem in three-dimensional wireless sensor networks. In Proc. IEEE Globecom 2004, pp. 3182--3186.

[5]

D. Tian and N. D. Georganas, A coverage-preserving node scheduling scheme for large wireless sensor networks. ACM Int'l Workshop on Wireless Sensor Networks and Applications (WSNA), 2002.

Digital Library

[6]

G. Fejes Toth, Multiple packing and covering of the plane with circles. ActaMath. Acad. Sci. Hungar., 27 (1976), 135--140.

[7]

H. Zhang and J. Hou, Maintaining sensing coverage and connectivity in large sensor networks. Technical Report UIUC, UIUCDCS-R-2003-2351, 2003.

[8]

J. Zhao, Y. Wen, R. Shang, G. Wang Optimizing sensor node distribution with genetic algorithm in wireless sensor network. Advances in Neural Networks - ISNN 2004, pp. 242--247.

[9]

K. Chakrabarty, S. Iyengar, H. Qi and E. Cho, Grid coverage for surveillance and target location in distributed sensor networks. IEEE Transactions on Computers,vol. 51, no. 12, pp. 1448--1453, December, 2002.

Digital Library

[10]

K. P. Ferentinos, T. A. Tsiligiridis, and K. G. Arvanitis, Energy optimization of wireless sensor networks for environmental measurements. in Proceedings of the International Conference on Computational Intelligence for Measurement Systems and Applications (CIMSA), July 2005.

[11]

M. Cardei and D. Du, Improving wireless sensor network lifetime through power aware organization. ACM Wireless Networks, Vol. 11, No.3, May 2005, pp. 333--340.

Digital Library

[12]

R. Kershner, The number of circles covering a set. Amer. J. Math. 61 (1939), 665--671. 9.

[13]

S. Jin, M. Zhou, and A. S. Wu, Sensor network optimization using a genetic algorithm. in Proceedings of the 7th World Multiconference on Systemics, Cybernetics and Informatics, 2003.

[14]

S. Hussain and A. W. Matin, Base station assisted hierarchical cluster-based routing. in IEEE/ACM International Conference on Wireless and Mobile communications Networks(ICWMC), July 2006.

[15]

S. Hussain, A. W. Matin, and O. Islam, Genetic algorithm for energy efficient clusters in wireless sensor networks. in Fourth International Conference on Information Technology: New Generations (ITNG 2007), April 2007.

Digital Library

[16]

S.Meguerdichian, M.Potkonjak. Low power 0/1 coverage and scheduling techniques in sensor networks. UCLA Technical Reports 030001. January 2003.

[17]

S. Slijepcevic and M. Potkonjak, Power efficient optimization of wireless sensor networks. IEEE Intl. Conf. on Communications, 2001.

[18]

W. J. Blundon, Multiple covering of the plane by circles. Mathmatika 4 (1957), pp. 7--16.

Cited By

Madhu SPrasad RRamotra PEdla DLipare A(2021)A Location-less Energy Efficient Algorithm for Load Balanced Clustering in Wireless Sensor NetworksWireless Personal Communications10.1007/s11277-021-08976-1Online publication date: 31-Aug-2021
https://doi.org/10.1007/s11277-021-08976-1
Prasad RMadhu SRamotra PEdla D(2021)Firework inspired load balancing approach for wireless sensor networksWireless Networks10.1007/s11276-021-02710-2Online publication date: 29-Jul-2021
https://doi.org/10.1007/s11276-021-02710-2
Alkhatib A(2016)Sub-Network Coverage Method as an Efficient Method of Wireless Sensor Networks for Forest Fire DetectionProceedings of the International Conference on Internet of things and Cloud Computing10.1145/2896387.2896450(1-7)Online publication date: 22-Mar-2016
https://dl.acm.org/doi/10.1145/2896387.2896450
Show More Cited By

Index Terms

A performance evaluation of a coverage compensation based algorithm for wireless sensor networks
1. Networks
  1. Network properties
    1. Network structure
  2. Network types
    1. Mobile networks
    2. Wireless access networks

Recommendations

Impact of Interference on Coverage in Wireless Sensor Networks

The quality of surveillance is dependent on the sensing coverage of a wireless sensor network. In the present paper, we examine how interference affects the coverage of a wireless sensor network. The coverage fraction and required number of sensors for ...
Spatial-Temporal Coverage Optimization in Wireless Sensor Networks

Mission-driven sensor networks usually have special lifetime requirements. However, the density of the sensors may not be large enough to satisfy the coverage requirement while meeting the lifetime constraint at the same time. Sometimes, coverage has to ...
Modeling and extending lifetime of wireless sensor networks using genetic algorithm
GEC '09: Proceedings of the first ACM/SIGEVO Summit on Genetic and Evolutionary Computation

To extend the lifetime of the sensor networks as far as possible while maintaining the quality of network coverage is a major concern in the research of coverage control. A systematical analysis on the relationship between the network lifetime and cover ...

Comments

Information & Contributors

Information

Published In

cover image ACM Conferences

MSWiM '08: Proceedings of the 11th international symposium on Modeling, analysis and simulation of wireless and mobile systems

October 2008

430 pages

ISBN:9781605582351

DOI:10.1145/1454503

General Chairs:
Sotiris Nikoketseas
CTI/University of Patras, Greece
,
Nael Abu-Ghazaleh
SUNY at Binghamton, USA
,
Program Chairs:
Brahim Bensaou
University of Science and Technology, Hong Kong
,
Violet R. Syrotiuk
Arizona State University, USA

Copyright © 2008 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

Sponsors

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 27 October 2008

Permissions

Request permissions for this article.

Request Permissions

Check for updates

Author Tags

Qualifiers

Research-article

Conference

MSWiM '08

Sponsor:

MSWiM '08: The 11th ACM International Conference on Modeling, Analysis and Simulation of Wireless and Mobile Systems

October 27 - 31, 2008

British Columbia, Vancouver, Canada

Acceptance Rates

Overall Acceptance Rate 398 of 1,577 submissions, 25%

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

8
Total Citations
View Citations
243
Total Downloads

Downloads (Last 12 months)2
Downloads (Last 6 weeks)0

Reflects downloads up to 07 Mar 2025

Other Metrics

View Author Metrics

Citations

Cited By

Madhu SPrasad RRamotra PEdla DLipare A(2021)A Location-less Energy Efficient Algorithm for Load Balanced Clustering in Wireless Sensor NetworksWireless Personal Communications10.1007/s11277-021-08976-1Online publication date: 31-Aug-2021
https://doi.org/10.1007/s11277-021-08976-1
Prasad RMadhu SRamotra PEdla D(2021)Firework inspired load balancing approach for wireless sensor networksWireless Networks10.1007/s11276-021-02710-2Online publication date: 29-Jul-2021
https://doi.org/10.1007/s11276-021-02710-2
Alkhatib A(2016)Sub-Network Coverage Method as an Efficient Method of Wireless Sensor Networks for Forest Fire DetectionProceedings of the International Conference on Internet of things and Cloud Computing10.1145/2896387.2896450(1-7)Online publication date: 22-Mar-2016
https://dl.acm.org/doi/10.1145/2896387.2896450
Vieira LAlmiron MLoureiro A(2016)Link probability, node degree and coverage in three-dimensional networksAd Hoc Networks10.1016/j.adhoc.2015.08.01137:P2(153-159)Online publication date: 1-Feb-2016
https://dl.acm.org/doi/10.1016/j.adhoc.2015.08.011
Zhu YNi L(2015)A probabilistic approach to statistical QoS provision of event detection in sensor networksWireless Networks10.1007/s11276-015-0980-622:2(439-451)Online publication date: 30-May-2015
https://doi.org/10.1007/s11276-015-0980-6
Pou JGalmes S(2013)A genetic algorithm for spanning tree optimization in sensor networks38th Annual IEEE Conference on Local Computer Networks10.1109/LCN.2013.6761260(324-327)Online publication date: Oct-2013
https://doi.org/10.1109/LCN.2013.6761260
Li ZWang R(2011)An energy-efficient optimization deployment scheme for wireless sensor networksJournal of Electronics (China)10.1007/s11767-011-0415-127:4(507-515)Online publication date: 11-Mar-2011
https://doi.org/10.1007/s11767-011-0415-1
Qu WWang JZhao XLiu Z(2010)The dynamic coverage control strategy for wireless sensor networks2010 International Conference on Networking, Sensing and Control (ICNSC)10.1109/ICNSC.2010.5461612(495-500)Online publication date: Apr-2010
https://doi.org/10.1109/ICNSC.2010.5461612

View Options

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Full Access

Get this Publication

View options

PDF

View or Download as a PDF file.

eReader

View online with eReader.

Figures

Tables

Media

View Table of Conten