The Community for Technology Leaders
RSS Icon
Subscribe
Issue No.11 - Nov. (2012 vol.24)
pp: 1993-2007
Chih-Chieh Hung , National Chiao Tung University, Hsinchu
Wen-Chih Peng , National Chiao Tung University, Hsinchu
Wang-Chien Lee , The Pennsylvania State University, University Park
ABSTRACT
To conserve energy, sensor nodes with similar readings can be grouped such that readings from only the representative nodes within the groups need to be reported. However, efficiently identifying sensor groups and their representative nodes is a very challenging task. In this paper, we propose a centralized algorithm to determine a set of representative nodes with high energy levels and wide data coverage ranges. Here, the data coverage range of a sensor node is considered to be the set of sensor nodes that have reading behaviors very close to the particular sensor node. To further reduce the extra cost incurred in messages for selection of representative nodes, a distributed algorithm is developed. Furthermore, maintenance mechanisms are proposed to dynamically select alternative representative nodes when the original representative nodes run low on energy, or cannot capture spatial correlation within their respective data coverage ranges. Using experimental studies on both synthesis and real data sets, our proposed algorithms are shown to effectively and efficiently provide approximate data collection while prolonging the network lifetime.
INDEX TERMS
Wireless sensor networks, Correlation, Sensors, Maintenance engineering, Energy consumption, Media Access Protocol, spatial correlation and clustering, Approximate data collection, wireless sensor networks
CITATION
Chih-Chieh Hung, Wen-Chih Peng, Wang-Chien Lee, "Energy-Aware Set-Covering Approaches for Approximate Data Collection in Wireless Sensor Networks", IEEE Transactions on Knowledge & Data Engineering, vol.24, no. 11, pp. 1993-2007, Nov. 2012, doi:10.1109/TKDE.2011.224
REFERENCES
[1] The Network Simulator - ns2, http://www.isi.edu/nsnamns/, 2012.
[2] I.F. Akyildiz, W. Su, Y. Sankarasubramaniam, and E. Cayirci, "Wireless Sensor Networks: A Survey," Computer Networks, vol. 38, no. 4, pp. 393-422, 2002.
[3] Q. Cao, T.F. Abdelzaher, T. He, and J.A. Stankovic, "Towards Optimal Sleep Scheduling in Sensor Networks for Rare-Event Detection," Proc. Int'l Conf. Information Processing in Sensor Networks (IPSN), pp. 20-27, 2005.
[4] J. Chou, D. Petrovic, and K. Ramchandran, "A Distributed and Adaptive Signal Processing Approach to Reduce Energy Consumption in Sensor Networks," Proc. INFOCOM, 2003.
[5] D. Chu, A. Deshpande, J.M. Hellerstein, and W. Hong, "Approximate Data Collection in Sensor Networks Using Probabilistic Models," Proc. 22nd Int'l Conf. Data Eng. (ICDE), pp. 48-59, 2006.
[6] Crossbow Technology Co. Mica2 Datasheet, http:/www.xbow. com, 2012.
[7] T.H. Cormen, C.E. Leiserson, R.L. Rivest, and C. Stein, Introduction to Algorithms, second ed. MIT Press, 2001.
[8] A. Deshpande, C. Guestrin, S. Madden, J.M. Hellerstein, and W. Hong, "Model-Driven Data Acquisition in Sensor Networks," Proc. 13th Int'l Conf. Very Large Data Bases (VLDB), pp. 588-599, 2004.
[9] H. Gupta, V. Navda, S.R. Das, and V. Chowdhary, "Efficient Gathering of Correlated Data in Sensor Networks," Proc. MobiHoc, pp. 402-413, 2005.
[10] S.C.-H. Huang, P.-J. Wan, C.T. Vu, Y. Li, and F.F. Yao, "Nearly Constant Approximation for Data Aggregation Scheduling in Wireless Sensor Networks," Proc. INFOCOM, pp. 366-372, 2007.
[11] C.-C. Hung and W.-C. Peng, "Optimizing In-Network Aggregate Queries in Wireless Sensor Networks for Energy Saving," Data and Knowledge Eng., vol. 70, no. 7, pp. 617-641, 2011.
[12] H.V. Jagadish, A.O. Mendelzon, and T. Milo, "Similarity-Based Queries," Proc. 14th ACM Symp. Principles of Database Systems (PODS), pp. 36-45, 1995.
[13] Y. Kotidis, "Snapshot Queries: Towards Data-Centric Sensor Networks," Proc. 21st Int'l Conf. Data Eng. (ICDE), pp. 131-142, 2005.
[14] H. Lee and A. Keshavarzian, "Towards Energy-Optimal and Reliable Data Collection via Collision-Free Scheduling in Wireless Sensor Networks," Proc. INFOCOM, pp. 2029-2037, 2008.
[15] C. Liu, K. Wu, and J. Pei, "A Dynamic Clustering and Scheduling Approach to Energy Saving in Data Collection from Wireless Sensor Networks," Proc. IEEE Second Ann. Comm. Soc. Conf. Sensor and Ad Hoc Comm. and Networks (SECON), 2005.
[16] C. Liu, K. Wu, and J. Pei, "An Energy-Efficient Data Collection Framework for Wireless Sensor Networks by Exploiting Spatiotemporal Correlation," IEEE Trans. Parallel and Distributed System, vol. 18, no. 7, pp. 1010-1023, July 2007.
[17] G. Lu, N. Sadagopan, B. Krishnamachari, and A. Goel, "Delay Efficient Sleep Scheduling in Wireless Sensor Networks," Proc. INFOCOM, pp. 2470-2481, 2005.
[18] S. Madden, Intel Lab Data 2004, http://db.csail.mit.edu/labdatalabdata.html , 2012.
[19] S. Madden, M.J. Franklin, J.M. Hellerstein, and W. Hong, "TAG: A Tiny AGgregation Service for Ad-Hoc Sensor Networks," Proc. Fifth Symp. Operating Systems Design and Implementation (OSDI), 2002.
[20] A. Meka and A.K. Singh, "Distributed Spatial Clustering in Sensor Networks," Proc. 10th Int'l Conf. Advances in Database Technology (EDBT), pp. 980-1000, 2006.
[21] S. Ratnasamy, B. Karp, S. Shenker, D. Estrin, R. Govindan, L. Yin, and F. Yu, "Data-Centric Storage in Sensornets with GHT, a Geographic Hash Table," ACM Mobile Networks and Applications (MONET), vol. 8, no. 4, pp. 427-442, 2003.
[22] X. Tang and J. Xu, "Optimizing Lifetime for Continuous Data Aggregation with Precision Guarantees in Wireless Sensor Networks," IEEE/ACM Trans. Networking, vol. 14, no. 4, pp. 904-917, Aug. 2008.
[23] X. Tang and J. Xu, "Extending Network Lifetime for Precision-Constrained Data Aggregation in Wireless Sensor Networks," Proc. INFOCOM, 2006.
[24] X. Tang and J. Xu, "Adaptive Data Collection Strategies for Lifetime-Constrained Wireless Sensor Networks," IEEE Trans. Parallel and Distributed Systems, vol. 19, no. 6, pp. 721-734, June 2008.
[25] V.S. Tseng and K.W. Lin, "Energy Efficient Strategies for Object Tracking in Sensor Networks: A Data Mining Approach," J. Systems and Software, vol. 80, no. 10 pp. 1678-1698, 2007.
[26] V.S.-M. Tseng, E.H.-C. Lu, and K.W. Lin, "An Energy-Efficient Approach for Real-Time Tracking of Moving Object in Multi-Level Sensor Networks," Proc. IEEE 11th Int'l Conf.Embedded and Real-Time Computing Systems and Applications (RTCSA), pp. 305-310, 2005.
[27] P.-J. Wan, S.C.-H. Huang, L. Wang, Z. Wan, and X. Jia, "Minimum-Latency Aggregation Scheduling in Multihop Wireless Networks," Proc. MobiHoc, pp. 185-194, 2009.
[28] S.-H. Wu, K.-T. Chuang, C.-M. Chen, and M.-S. Chen, "Toward the Optimal Itinerary-Based KNN Query Processing in Mobile Sensor Networks," IEEE Trans. Knowledge and Data Eng., vol. 20, no. 12, pp. 1655-1668, Dec. 2008.
[29] H.-Y. Yang, C.-H. Lin, and M.-J. Tsai, "Distributed Algorithm for Efficient Construction and Maintenance of Connected k-Hop Dominating Sets in Mobile Ad Hoc Networks," IEEE Trans. Mobile Computing, vol. 7, no. 4, pp. 444-457, Apr. 2008.
[30] Y. Yao and J. Gehrke, "The Cougar Approach to In-Network Query Processing in Sensor Networks," SIGMOD Record, vol. 31, no. 3, pp. 9-18, 2002.
[31] W. Ye, J.S. Heidemann, and D. Estrin, "An Energy-Efficient MAC Protocol for Wireless Sensor Networks," Proc. INFOCOM, 2002.
[32] W. Ye, J.S. Heidemann, and D. Estrin, "Medium Access Control with Coordinated Adaptive Sleeping for Wireless Sensor Networks," IEEE/ACM Trans. Networking, vol. 12, no. 3, pp. 493-506, June 2004.
23 ms
(Ver 2.0)

Marketing Automation Platform Marketing Automation Tool