ACM Home Page
Please provide us with feedback. Feedback
Design and optimization of distributed sensing coverage in wireless sensor networks
Full text PdfPdf (599 KB)
Source
ACM Transactions on Embedded Computing Systems (TECS) archive
Volume 7 ,  Issue 3  (April 2008) table of contents
Article No. 33  
Year of Publication: 2008
ISSN:1539-9087
Authors
Ting Yan  University of Virginia, Charlottesville, Virginia
Yu Gu  University of Minnesota, Twin Cities, Minnesota
Tian He  University of Minnesota, Twin Cities, Minnesota
John A. Stankovic  University of Virginia, Charlottesville, Virginia
Publisher
ACM  New York, NY, USA
Bibliometrics
Downloads (6 Weeks): 23,   Downloads (12 Months): 230,   Citation Count: 0
Additional Information:

abstract   references   index terms   collaborative colleagues  

Tools and Actions: Request Permissions Request Permissions    Review this Article  
DOI Bookmark: Use this link to bookmark this Article: http://doi.acm.org/10.1145/1347375.1347386
What is a DOI?

ABSTRACT

For many sensor network applications, such as military surveillance, it is necessary to provide full sensing coverage to a security-sensitive area while, at the same time, minimizing energy consumption and extending system lifetime by leveraging the redundant deployment of sensor nodes. In this paper, we propose a surveillance service for sensor networks based on a distributed energy-efficient sensing coverage protocol. In the protocol, each node is able to dynamically decide a schedule for itself to guarantee a certain degree-of-coverage (DOC) with average energy consumption inversely proportional to the node density. Several optimizations and extensions are proposed to enhance the basic design with a better load-balance feature and a longer network lifetime. We consider and address the impact of the target size and the unbalanced initial energy capacity of individual nodes to the network lifetime. Several practical issues such as the localization error, irregular sensing range, and unreliable communication links are addressed as well. Simulation shows that our protocol extends system lift-time significantly with low energy consumption. It outperforms other state-of-the-art schemes by as much as 50% reduction in energy consumption and as much as 130% increase in the half-life of the network.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
1
Ahn, G.-S., Campbell, A. T., Veres, A., and Sun, L.-H. 2002. SWAN: Service differentiation in stateless wireless ad hoc networks. In IEEE INFOCOM.
 
2
Alt, H., Hsu, D., and Snoeyink, J. 1995. Computing the largest inscribed isothetic rectangle. In Proceeding of 7th Canadian Conference on Computational Geometry 67--72.
 
3
Bhatnagar, S., Deb, B. R., and Nath, B. 2001. Service differentiation in sensor networks. In International Symposium on Wireless Personal Multimedia Communications.
4
 
5
Cao, Q., Yan, T., Stankovic, J. A., and Abdelzaher, T. F. 2005. Analysis of target detection performance for wireless sensor networks. In International Conference on Distributed Computing in Sensor Networks (DCOSS).
 
6
Cerpa, A. and Estrin, D. 2002. ASCENT: Adaptive self-configuring sensor networks topologies. In Proceedings of the IEEE Computer and Communications Societies (INFOCOM).
7
 
8
CrossBow Technology, Inc. CrossBow Technology, Inc. Available at http://www.xbow.com/Products/Product_pdf_files/wireless_pdf/6020-0042-0%1_A_MICA2.pdf.
 
9
10
 
11
12
 
13
Guo, C., Zhong, L. C., and Rabaey, J. M. 2001. Low power distributed MAC for ad hoc sensor radio networks. In IEEE GlobeCom.
14
15
16
 
17
 
18
He, T., Vicaire, P., Yan, T., Cao, Q., Zhou, G., Gu, L., Luo, L., Stoleru, R., Stankovic, J. A., and Abdelzaher, T. 2006. Achieving long-term surveillance in VigilNet. In IEEE Infocom.
 
19
20
 
21
H.Takagi and L.Kleinrock. 1984. Optimal transmission ranges for randomly distributed packet radio terminals. IEEE Trans. Commun. 32, 3.
 
22
 
23
Kirkpatrick, D. and Snoeyink, J. 1995. Tentative prune-and-search for computing fixed-points with applications to geometric computation. Fundamental Informatic. 353--370.
 
24
Krishnamachari, B., Estrin, D., and Wicker, S. 2002. Impact of data aggregation in wireless sensor networks. In Proceedings of the International Workshop on Distributed Event-Based Systems.
 
25
 
26
Min, R., Bhardwaj, M., Cho, S.-H., Sinha, A., Shih, E., Wang, A., and Chandrakasan, A. 2000. An architecture for a power-aware distributed microsensor node. In IEEE Workshop on Signal Processing Systems.
 
27
Ramanathan, R. and Rosales-Hain, R. 2000. Topology control of multihop wireless networks using transmit power adjustment. In IEEE INFOCOM.
28
29
 
30
Tian, D. and Georganas, N. 2003. A node scheduling scheme for energy conservation in large wireless sensor networks. Wireless Comm. Mobile Comput. J. 3, 2, 271--290.
31
 
32
Williams, R. 1979. Geometrical foundation of natural structure: A source book of design. Dover, New York.
 
33
34
35
36
37
 
38
Xue, Y. and Li, B. 2001. A location-aided power-aware routing protocol in mobile ad hoc networks. In IEEE GlobeCom.
 
39
 
40
Ye, F., Zhong, G., Lu, S., and Zhang, L. 2002. Energy efficient robust sensing coverage in large sensor networks. Tech. Rept., UCLA.

Collaborative Colleagues:
Ting Yan: colleagues
Yu Gu: colleagues
Tian He: colleagues
John A. Stankovic: colleagues