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Issue No.05 - May (2009 vol.8)
pp: 622-635
Brian Harrington , Yahoo! Corporation, Sunnyvale
Yan Huang , University of North Texas, Denton
Jue Yang , University of North Texas, Denton
Xinrong Li , University of North Texas, Denton
ABSTRACT
We propose a spatial autocorrelation aware, energy efficient, and error bounded framework for interpolating maps from sensor fields. Specifically, we propose an iterative reporting framework that utilizes spatial interpolation models to reduce communication costs and enforce error control. The framework employs a simple and low overhead in-network coordination among sensors for selecting reporting sensors so that the coordination overhead does not eclipse the communication savings. Due to the probabilistic nature of the first round reporting, the framework is less sensitive to sensor failures and guarantees an error bound for all functional sensors for each epoch. We then propose a graceful integration of temporal data suppression models with our framework. This allows an adaptive utilization of spatial or temporal autocorrelation based on whichever is stronger in different regions of the sensor field. We conducted extensive experiments using data from a real-world sensor network deployment and a large Asian temperature dataset to show that the proposed framework significantly reduces messaging costs and is more resilient to sensor failures. We also implemented our proposed algorithms on a sensor network of MICAz motes. The results show that our algorithms save significant energy and the out of bound errors due to packet loss are below 5%.
INDEX TERMS
Sensor networks, Spatial databases and GIS
CITATION
Brian Harrington, Yan Huang, Jue Yang, Xinrong Li, "Energy-Efficient Map Interpolation for Sensor Fields Using Kriging", IEEE Transactions on Mobile Computing, vol.8, no. 5, pp. 622-635, May 2009, doi:10.1109/TMC.2008.167
REFERENCES
[1] University of Delaware Surface Air Temperature Data, http://climate.geog.udel.edu~climate, 2008.
[2] M.H. Ali, W.G. Aref, and C. Nita-Rotaru, “SPASS: Scalable and Energy-Efficient Data Acquisition in Sensor Databases,” Proc. Fourth ACM Int'l Workshop Data Eng. for Wireless and Mobile Access (MobiDE '05), 2005.
[3] B.A. Bash, J.W. Byers, and J. Considine, “Approximately Uniform Random Sampling in Sensor Networks,” Proc. Int'l Workshop Data Management for Sensor Networks (DMSN '04), 2004.
[4] P. Bonnet, J.E. Gehrke, and P. Seshadri, “Towards Sensor Database Systems,” Proc. Second Int'l Conf. Mobile Data Management (MDM '01), 2001.
[5] D. Chu, A. Deshpande, J. Hellerstein, and W. Hong, “Approximate Data Collection in Sensor Networks Using Probabilistic Models,” Proc. 22nd Int'l Conf. Data Eng. (ICDE '06), 2006.
[6] J. Considine, F. Li, G. Kollios, and J. Byers, “Approximate Aggregation Techniques for Sensor Databases,” Proc. 20th Int'l Conf. Data Eng. (ICDE '04), 2004.
[7] N.A.C. Cressie, Statistics for Spatial Data. John Wiley & Sons, 1991.
[8] A. Deligiannakis, Y. Kotidis, and N. Roussopoulos, “Compressing Historical Information in Sensor Networks,” Proc. ACM SIGMOD, pp. 527-538, 2004.
[9] A. Deshpande, C. Guestrin, S.R. Madden, J.M. Hellerstein, and W. Hong, “Model-Driven Data Acquisition in Sensor Networks,” Proc. 30th Int'l Conf. Very Large Data Bases (VLDB '04), pp. 588-599, 2004.
[10] F. Emekci, S.E. Tuna, D. Agrawal, and E. Abbadi, “Binocular: A System Monitoring Framework,” Proc. Int'l Workshop Data Management for Sensor Networks (DMSN '04), Aug. 2004.
[11] Q. Fang, F. Zhao, and L. Guibas, “Counting Targets: Building and Managing Aggregates in Wireless Sensor Networks,” Technical Report P2002-10298, Palo Alto Research Center, 2002.
[12] D. Ganesan, B. Greenstein, D. Perelyubskiy, D. Estrin, and J. Heidemann, “An Evaluation of Multi-Resolution Storage for Sensor Networks,” Proc. First Int'l Conf. Embedded Networked Sensor Systems (SenSys '03), 2003.
[13] S. Goel, A. Passarella, and T. Imielinski, “Using Buddies to Live Longer in a Boring World,” Technical Report DCS-TR-558, Dept. of Computer Science, Rutgers Univ., 2004.
[14] B. Harrington and Y. Huang, “In-Network Surface Simplification for Sensor Fields,” Proc. 13th ACM Int'l Symp. Advances in Geographic Information Systems (GIS '05), 2005.
[15] Crossbow Technology Inc., Intel Lab Data, http://www.xbow. com/Productsproducts.htm , 2008.
[16] C. Intanagonwiwat, R. Govindan, and D. Estrin, “Directed Diffusion: A Scalable and Robust Communication Paradigm for Sensor Networks,” Proc. ACM MobiCom, pp. 56-67, 2000.
[17] A. Jain, E.Y. Chang, and Y.-F. Wang, “Adaptive Stream Resource Management Using Kalman Filters,” Proc. ACM SIGMOD, 2004.
[18] B. Karp and H.T. Kung, “GPSR: Greedy Perimeter Stateless Routing for Wireless Networks,” Proc. ACM MobiCom, 2000.
[19] Y. Kotidis, “Snapshot Queries: Towards Data-Centric Sensor Networks,” Proc. 21st Int'l Conf. Data Eng. (ICDE '05), pp.131-142, 2005.
[20] B. Krishnamachari, D. Estrin, and S.B. Wicker, “The Impact of Data Aggregation in Wireless Sensor Networks,” Proc. 22nd Int'l Conf. Distributed Computing Systems (ICDCS '02), pp. 575-578, 2002.
[21] D.R. Legates and C.J. Willmott, “Mean Seasonal and Spatial Variability in Global Surface Air Temperature,” Theoretical and Applied Climatology, pp. 11-21, 1990.
[22] M. Li, D. Ganesan, and P. Shenoy, “PRESTO: Feedback-Driven Data Management in Sensor Networks,” Proc. Third ACM/Usenix Symp. Networked Systems Design and Implementation (NSDI '06), May 2006.
[23] X. Li, Y. Jin Kim, R. Govindan, and W. Hong, “Multi-Dimensional Range Queries in Sensor Networks,” Proc. First Int'l Conf. Embedded Networked Sensor Systems (SenSys '03), 2003.
[24] S. Madden, Intel Lab Data, http://berkeley.intel-research.netlabdata /, 2008.
[25] S.R. Madden, M.J. Franklin, J.M. Hellerstein, and W. Hong, “TAG: A Tiny Aggregation Service for Ad-Hoc Sensor Networks,” Proc. Fifth Symp. Operating System Design and Implementation (OSDI '02), 2002.
[26] S.R. Madden, M.J. Franklin, J.M. Hellerstein, and W. Hong, “Design of an Acquisitional Query Processor for Sensor Networks,” Proc. ACM SIGMOD, 2003.
[27] S.R. Madden, R. Szewczyk, M.J. Franklin, and D. Culler, “Supporting Aggregate Queries over Ad-Hoc Wireless Sensor Networks,” Proc. Fourth IEEE Workshop Mobile Computing and Systems Applications (WMCSA '02), 2002.
[28] M. Maroti, B. Kusy, G. Simon, and A. Ledeczi, “The Flooding Time Synchronization Protocol,” Proc. Second Int'l Conf. Embedded Networked Sensor Systems (SenSys '04), pp. 39-49, 2004.
[29] C. Olston, B. Thau Loo, and J. Widom, “Adaptive Precision Setting for Cached Approximate Values,” Proc. ACM SIGMOD, 2001.
[30] S. Sandeep Pradhan and K. Ramchandran, “Distributed Source Coding Using Syndromes (DISCUS): Design and Construction,” Proc. Data Compression Conf. (DCC '99), 1999.
[31] A. Scaglione and S.D. Servetto, “On the Interdependence of Routing and Data Compression in Multi-Hop Sensor Networks,” Proc. ACM MobiCom, pp. 140-147, 2002.
[32] M. Sharifzadeh and C. Shahabi, “Supporting Spatial Aggregation in Sensor Network Databases,” Proc. 12th Ann. ACM Int'l Workshop Geographic Information Systems (GIS '04), 2004.
[33] N. Trigoni, Y. Yao, A. Demers, J. Gehrke, and R. Rajaraman, “WaveScheduling: Energy-Efficient Data Dissemination for Sensor Networks,” Internet draft, 2004.
[34] M.C. Vuran, B. Akan, and I.F. Akyildiz, “Spatio-Temporal Correlation: Theory and Applications for Wireless Sensor Networks,” Computer Networks, vol. 45, no. 3, pp. 245-259, 2004.
[35] M.C. Vuran and I.F. Akyildiz, “Spatial Correlation-Based Collaborative Medium Access Control in Wireless Sensor Networks,” IEEE/ACM Trans. Networking, 2004.
[36] H. Wackernagel, Mulitvariate Geostatistics. Springer, 1995.
[37] A. Woo, T. Tong, and D. Culler, “Taming the Underlying Challenges of Reliable Multihop Routing in Sensor Networks,” Proc. First Int'l Conf. Embedded Networked Sensor Systems (SenSys '03), pp. 14-27, 2003.
[38] Y. Yao and J. Gehrke, “The Cougar Approach to in-Network Query Processing in Sensor Networks,” Proc. ACM SIGMOD, 2002.
[39] 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, Computer Science Dept., Univ. of California, Los Angeles, 2001.
[40] F. Zhao and L. Guibas, “Wireless Sensor Networks: An Information Processing Approach,” Morgan Kaufmann Series in Networking, 2004.
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