|
ABSTRACT
Spatial query execution is an essential functionality of a sensor network, where a query gathers sensor data within a specific geographic region. Redundancy within a sensor network can be exploited to reduce the communication cost incurred in execution of such queries. Any reduction in communication cost would result in an efficient use of the battery energy, which is very limited in sensors. One approach to reduce the communication cost of a query is to self-organize the network, in response to a query, into a topology that involves only a small subset of the sensors sufficient to process the query. The query is then executed using only the sensors in the constructed topology.In this article, we design and analyze algorithms for such self-organization of a sensor network to reduce energy consumption. In particular, we develop the notion of a connected sensor cover and design a centralized approximation algorithm that constructs a topology involving a near-optimal connected sensor cover. We prove that the size of the constructed topology is within an log n factor of the optimal size, where n is the network size. We also develop a distributed self-organization version of our algorithm, and propose several optimizations to reduce the communication overhead of the algorithm. Finally, we evaluate the distributed algorithm using simulations and show that our approach results in significant communication cost reduction.
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
|
|
| |
2
|
B. Badrinath, M. Srivastava, K. Mills, J. Sholtz, and K. Sollins, editors.Special Issue on Smart Spaces and Environments, IEEE Personal Communications 2000.
|
| |
3
|
|
| |
4
|
|
| |
5
|
H.Bonnimann and M.Goodrich. Almost optimal set covers in finite vc-dimension.Discrete Computational Geometry 14,1995.
|
| |
6
|
A. Cerpa and D. Estrin. Ascent: Adaptive self-configuring sensor networks topologies.In Proc. of the Conf. on Computer Communications (INFOCOM),2002.
|
 |
7
|
|
| |
8
|
|
| |
9
|
|
| |
10
|
|
| |
11
|
B. Deb, S. Bhatnagar, and B. Nath. Multiresolution state retrieval in sensor networks. In Proceedings of International Workshop on Sensor Network Protocols and Applications (SNPA), 2003.
|
 |
12
|
|
| |
13
|
R. Govindan, J. Hellerstein, W. Hong, S. Madden, M. Franklin, and S. Shenker. The sensor network as a database. Technical report, University of Southern California, Computer Science Department, 2002.
|
| |
14
|
S. Guha and S. Khuller. Approximation algorithms for connected dominating sets. Algorithmica 20(4), 1998.
|
| |
15
|
|
| |
16
|
|
 |
17
|
|
| |
18
|
A. Laouiti, A. Qayyum, and L. Viennot. Multipoint relaying: An effcient technique for flooding in mobile wireless networks. In Proc.of the Hawaii Intl.Conf. on System Sciences (HICSS), 2002.
|
| |
19
|
K. Lieska, E. Laitinen, and J. Lahteenmaki. Radio coverage optimization with genetic algorithms. In Proc. of IEEE Int. Symp. on Personal, Indoor, and Mobile Radio Communications (PIMRC), 1998.
|
| |
20
|
M. Marengoni, B. Draper, A. Hanson, and R. Sitaraman. System to place observers on a polyhedral terrain in polynomial time. Image and Visual Computing, 1996.
|
| |
21
|
S. Meguerdihian, F. Koushanfar, M. Potkonjak, and M. Srivastava. Coverage problems in wireless ad-hoc sensor networks. In Proc.of the Conf. on Computer Communications (INFOCOM), 2001.
|
 |
22
|
|
| |
23
|
G. Pottie and W. Kaiser. Wireless sensor networks. Communications of the ACM 43, 2002.
|
| |
24
|
S. Shakkottai, R. Srikant, and N. Shroff. Unreliable sensor grids: Coverage, connectivity and diameter. In Proceedings of INFOCOM (to appear), 2003.
|
| |
25
|
S. Slijepcevi and M. Potkonjak. Power efficient organization of wireless sensor networks. In Proc. of IEEE Intl. Conf. on Communications (ICC), 2001.
|
| |
26
|
J. Wu and H. Li. A dominating-set-based routing scheme in ad hoc wireless networks. Telecommunication Systems Journal 3, 2001.
|
CITED BY 42
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
Andreas Krause , Carlos Guestrin , Anupam Gupta , Jon Kleinberg, Near-optimal sensor placements: maximizing information while minimizing communication cost, Proceedings of the fifth international conference on Information processing in sensor networks, April 19-21, 2006, Nashville, Tennessee, USA
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
Yanmin Zhu , Lionel M. Ni, Probabilistic wakeup: adaptive duty cycling for energy-efficient event detection, Proceedings of the 10th ACM Symposium on Modeling, analysis, and simulation of wireless and mobile systems, October 22-26, 2007, Chania, Crete Island, Greece
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
David K. Y. Yau , Nung Kwan Yip , Chris Y. T. Ma , Nageswara S. Rao , Mallikarjun Shankar, Quality of monitoring of stochastic events by periodic & proportional-share scheduling of sensor coverage, Proceedings of the 2008 ACM CoNEXT Conference, p.1-12, December 09-12, 2008, Madrid, Spain
|
|
|
Yang Xiao , Yanping Zhang , Miao Peng , Hui Chen , Xiaojiang Du , Bo Sun , Kui Wu, Two and three-dimensional intrusion object detection under randomized scheduling algorithms in sensor networks, Computer Networks: The International Journal of Computer and Telecommunications Networking, v.53 n.14, p.2458-2475, September, 2009
|
|