Exploring spatial correlation for link quality estimation in wireless sensor networks

Proceedings - Fourth Annual IEEE International Conference on Pervasive Computing and Communications, PerCom 2006

Volumn 2006, Issue , 2006, Pages 200-209

  Xu, Yingqi ^a   Lee, Wang Chien ^a  

^a PENNSYLVANIA STATE UNIVERSITY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; CORRELATION METHODS; REGRESSION ANALYSIS; SENSORS; TELECOMMUNICATION NETWORKS; WIRELESS TELECOMMUNICATION SYSTEMS;

QUALITY ESTIMATION; WEIGHTED REGRESSION ALGORITHM; WIRELESS COMMUNICATION LINKS; WIRELESS SENSOR NETWORKS;

TELECOMMUNICATION LINKS;

EID: 33750287050     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/PERCOM.2006.25     Document Type: Conference Paper

References (26)

1. G. Anastasi, E. Borgia, M. Conti, E. Gregori, and A. Passarella. Understanding the real behavior of mote and 802.11 ad hoc networks: an experimental approach. Pervasive and Mobile Computing, 1(2):237-256, 2005.
2. N. Bulusu, J. Heidemann, and D. Estrin. GPS-less low cost outdoor localization for very small devices. IEEE Personal Communications Magazine, 7(5):28-34, Oct. 2000.
3. A. Cerpa, N. Busek, and D. Estrin. Scale: A tool for simple connectivity assessment in lossy environments. Technical Report CENS-TR 03-0021, UCLA Computer Science, 2003.
4. A. Cerpa, J. L. Wong, M. Potkonjak, and D. Estrin. Temporal properties of low power wireless links: modeling and implications on multi-hop routing. In Proceedings of the ACM MobiHoc, Urbana-Champaign, IL, 2005.
5. D. De. Couto, D. Aguayo, B. A. Chambers, and R. Morris. Performance of multihop wireless networks: shortest path is not enough. SIGCOMM Comput. Commun. Rev., 33(1):83-88, 2003.
6. D. Ganesan, B. Krishnamachari, A. Woo, D. Culler, D. Estrin, and S. Wicker. Complex behavior at scale: An experimental study of low-power wireless sensor networks. Technical Report UCLA/CSD-TR 02-0013, UCLA Computer Science, 2002.
7. S. Goel and T. Imielinski. Prediction-based monitoring in sensor networks: taking lessons from MPEG. ACM Computer Communication Review, 31(5), October 2001.
8. C. Ouestrin, P. Bodi, R. Thibau, M. Paski, and S. Madde. Distributed regression: an efficient framework for modeling sensor network data. In Proceedings of IPSN, Berkeley, CA, 2004.
9. L. Hu and D. Evans. Localization for mobile sensor networks. In Proceedings of MobiCom, Philadelphia, PA, 2004.
10. B. Karp and H. T. Kung. GPSR: greedy perimeter stateless routing for wireless networks. In Proceedings of MobiCom, pages 243-254, Boston, MA, Aug 2000.
11. F. Kuhn, R. Wattenhofer, and A. Zollinger. Worst-case optimal and average-case efficient geometric ad-hoc routing. In Proceedings of ACM MobiHoc, pages 267-278, Annapolis, MD, Jun. 2003.
12. J. Li, D. Maier, K. Tufte, V. Papadimos, and P. A. Tucker. No pane, no gain: efficient evaluation of sliding-window aggregates over data streams. SIGMOD Rec., 34(1):39-44, 2005.
13. J. Li, D. Maier, K. Tufte, V. Papadimos, and P. A. Tucker. Semantics and evaluation techniques for window aggregates in data streams. In Proceedings of ACM SIGMOD, pages 311-322, Baltimore, Maryland, 2005.
14. D. A. Maltz, J. Broch, and D. B. Johnson. Quantitative lessons from a full-scale multi-hop wireless ad hoc network testbed. In Proceedings of the IEEE Wireless Communications and Network Conference, Sept. 2000.
15. V. Raghunathan, C. Schurgers, S. Park, and M. B. Srivastava. Energy aware wireless microsensor networks. IEEE Signal Processing Magazine, 19(2):40-50, March 2002.
16. K. Seada, M. Zuniga, A. Helmy, and B. Krishnamachari. Energy-efficient forwarding strategies for geographic routing in lossy wireless sensor networks. In Proceedings of ACM SenSys, pages 108-121, Baltimore, MD, USA, 2004.
17. A. Woo and D. Culler. Evaluation of efficient link reliability estimators for low-power wireless networks. Technical Report UCB//CSE-03-1270, U.C. Berkeley, 2003.
18. A. Woo, T. Tong, and D. Culler. Taming the underlying challenges of reliable multihop routing in sensor networks. In Proceedings of ACM SenSys, Los Angeles, CA, 2003.
19. Y. Xu, W. C. Lee, J. Xu, and O. Mitchell. PSGR: Priority-based stateless geo-routing in wireless sensor networks. In To appear in IEEE International Conference on Mobile Ad-hoc and Sensor Systems, Washington, DC, Nov. 2005.
20. Y. Xu, J. Winter, and W.-C. Lee. Dual prediction-based reporting for object tracking sensor networks. In Proceedings of International Conference on Mobile and Ubiquitous Systems: Networking and Services, Boston, MA, Aug. 2004.
21. T. Yan, T. He, and J. A. Stankpvic. Differentiated surveillance for sensor networks. In Proceedings of SenSys, pages 51-62, Los Angeles, CA, 2003.
22. Y. Yu, R. Govindan, and D. Estrin. Geographical and energy aware routing: A recursive data dissemination protocol for wireless sensor networks. Technical Report UCLA/CSD-TR-01-0023, UCLA Computer Science Department, May 2001.
23. J. Zhao and R. Govindan. Understanding packet delivery performance in dense wireless sensor networks. In Proceedings of ACM SenSys, pages 1-13, Los Angeles, CA, Nov. 2003.
24. J. Zhao, R. Govindan, and D. Estrin. Computing aggregates for monitoring wireless sensor networks. In Proceedings of IEEE ICC Workshop on Sensor Network Protocols and Applications, Anchorage Ak, May 2003.
25. G. Zhou, T. He, S. Krishnamurthy, and J. A. Stankovic. Impact of radio irregularity on wireless sensor networks. In Proceedings of MobiSys, pages 125-138, Boston, MA, 2004.
26. M. Zuniga and B. Krishnamachari. Analyzing the transitional region in low power wireless links. In Proceedings of International Conference on Sensor and Ad-hoc Communications and Networks, Santa Clara, CA, Oct. 2004.