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Energy-driven detection scheme with guaranteed accuracy
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Source Information Processing In Sensor Networks archive
Proceedings of the 5th international conference on Information processing in sensor networks table of contents
Nashville, Tennessee, USA
POSTER SESSION: Main track table of contents
Pages: 284 - 291  
Year of Publication: 2006
ISBN:1-59593-334-4
Authors
Lige Yu  University of Maryland, College Park, MD
Lin Yuan  University of Maryland, College Park, MD
Gang Qu  University of Maryland, College Park, MD
Anthony Ephremides  University of Maryland, College Park, MD
Sponsor
ACM: Association for Computing Machinery
Publisher
ACM  New York, NY, USA
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Downloads (6 Weeks): 14,   Downloads (12 Months): 80,   Citation Count: 2
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ABSTRACT

This is our first step towards a holistic investigation of the minimum energy for wireless sensor network (WSN) to perform a specific function. We consider wireless sensor networks that perform an event detection function. Each sensor node will repetitively collect a 1-bit information regarding whether the event occurs or not in its neighborhood. A fusion center will make the decision on whether the event occurs based on the information provided by individual sensor nodes. Traditionally, a centralized scheme requires each sensor node to forward all its observations to the fusion center, which results in large energy in communication. A distributed scheme, on the other hand, allows each sensor node to make its own decision and then send out only its 1-bit decision. This reduces communication energy at the cost of increased processing energy and reduced detection accuracy.We propose a hybrid energy-driven scheme where each sensor node sends out its 1-bit decision if that decision exceeds a pre-determined detection accuracy threshold, and sends out all its observations otherwise. This scheme provides WSN designers the flexibility to balance detection accuracy, sensor density, and energy consumption. We develop the optimal decision rules for this scheme. We also propose methods to calculate the detection accuracy threshold for individual sensor node to guarantee the overall detection accuracy at the fusion center. The simulation results show that the hybrid scheme consumes significantly less energy than both centralized and distributed schemes to achieve the same detection accuracy.


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.

 
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L. Yu and A. Ephremides, "Detection Performance and Energy Efficiency Trade-off in a Sensor Network," Proc. of 2003 Allerton Conference, Allerton, IL, October 2003.
 
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J.-F. Chamberland and V. V. Veeravalli, "Decentralized Detection in Sensor Networks," IEEE Trans. on Signal Processing, 51(2):407--416, February 2003.
 
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Y. Zhu, R. S. Blum, Z. Q. Luo, and K. M. Wong, "Unexpected Properties and Optimum-Distributed Sensor Detectors for Dependent Observation Cases," IEEE Trans. on Automatic Control, vol. 45, no. 1, January 2000.
 
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R. Niu, P. Varshney, M. H. Moore, and D. Klamer, "Decision Fusion in a Wireless Sensor Network with a Large Number of Sensors," Proc. of the Seventh International Conference on Information Fusion, Stockholm, Sweden, June 2004.
 
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W. Shi, T. W. Sun, and R. D. Wesel, "Quasiconvexity and Optimal Binary Fusion for Distributed Detection with Identical Sensors in Generalized Gaussian Noise," IEEE Trans. Inform. Theory, vol. 47, pp. 446--450, January 2001.
 
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Q. Zhang, P. K. Varshney, and R. D. Wesel, "Optimal Bi-level Quantization of I.I.D. Sensor Observations for Binary Hypothesis Testing," IEEE Trans. Inform. Theory, July 2002.
 
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L. Yuan and G. Qu, "Energy Efficient Design for Distributed Sensor Networks," Handbook of Sensor Network, Chapter 38, CRC Press, October 2004.
 
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E. J. Duarte-Melo and M. Liu, "Analysis of Energy Consumption and Lifetime of Heterogeneous Wireless Sensor Networks," Proc. of IEEE Globecom, Taipei, Taiwan, November 2002.
 
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D. Maniezzo, K. Yao and G. Mazzini, "Energetic Trade-off between Computing and Communication Resource in Multimedia Surveillance Sensor Network," IEEE MWCN2002, Stockholm, Sweden, September 2002.
 
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B. Krishnamachari, Y. Mourtada, and S. Wicker. "The Energy-Robustness Tradeoff for Routing in Wireless Sensor Networks," IEEE International Conference on Communications, Anchorage, Alaska, May 2003.
 
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A. Boulis, S. Ganeriwal, and M. B. Srivastava, "Aggregation in Sensor Networks: An Energy-Accuracy Trade-off," Elsevier Ad-hoc Networks Journal (special issue on sensor network protocols and applications), 2003.
 
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V. Raghunathan, C. Schurgers, S. Park, and M. Srivastava, "Energy-Aware Wireless Sensor Networks," IEEE Signal Processing, vol. 19, no. 2, pp. 40--50, March 2002.
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Collaborative Colleagues:
Lige Yu: colleagues
Lin Yuan: colleagues
Gang Qu: colleagues
Anthony Ephremides: colleagues