Investigation of In-Network Data Mining Approach for Energy Efficient Data Centric Wireless Sensor Networks

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The continuous improvement in hardware design and advances in wireless communication have enabled the deployment of various wireless applications. Wireless sensor network applications become essential tools for monitoring the activity and evolution of our surrounding environment. However, the wireless sensor nodes are highly resource constrained in terms of limited processing speed, run time memory, persistent storage, communication bandwidth and finite energy. Therefore, for energy efficient in-network data retention and query processing, data mining approach is highly required that reduces the storage space, energy and communication cost consumption. This paper investigates the data mining approach for clustering sensor networks. Results show 99.88% less storage space, 37.6% reduced energy and 80% increased query throughput is achieved using data mining approach for wireless sensor networks.
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Wireless Sensor Networks; Clustering; Energy Efficient; Data Mining; Query Processing; Memory Management

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Lymberopoulos, D.; Savvides, A. XYZ: A Motion Enabled, Power Aware Sensor Node Platform for Distributed Sensor Network Applications. Proc. Int. Symposium on Information Processing in Sensor Networks, 2005, 449-454.

S.S. Rizvi; T.S. Chung. VAQAR: Flash memory based long term in-network vital data sustainability and availability for data centric wireless sensor network applications. Proc. IEEE Youth Conf. Inf. Computing and Telecom., 2009, 363-366.

Rizvi, S.S.; Chung, T.S. PIYA–Proceeding to Intelligent Service Oriented Memory Allocation for Flash Based Sensor Devices in Wireless Sensor Networks. Proc. Int. Conf. on Convergence and Hybrid Information Technology, 2008, 625-630.

Rizvi, S.S.; Chung, T.S. PIYAS-Proceeding to intelligent service oriented memory allocation for flash based data centric sensor devices in wireless sensor networks. Sensors, 2010, 10(1), 292-312.

Zhang, P.; Sadler, C.M.; Lyon, A.S.; Martonosi, M. Hardware Design Experiences in ZebraNet. Proc. ACM Int. Conf. on Embedded Networked Sensor Systems, 2004, 227-238.

Gaber, M. M.; Zaslavsky, A.; Krishnaswamy, S. Mining data streams: a review. SIGMOD Record, 2005, 34(2) 18-26.

Lehsaini, M.; Guyennet, H.; Feham, M. , Cluster-based Self-Organization Scheme for Mobile Wireless Sensor Networks, (2008) International Review on Computers and Software (IRECOS), 3 (2), pp. 185-192.

Tashtarian, F.; Haghighat, A.T.; Yaghmaee, M.H.; Mazinani, S.M.; Honary, M.T. On Global Clustering Algorithm: Layer-Oriented Approach for Multi Hop Wireless Sensor Networks, (2009) International Review on Computers and Software (IRECOS), 4 (5), pp. 567-576.

Ouacha, A.; Lakki, N.; Habbani, A.; Oubaha, J.; Elkoutbi, M.; El Abbadi, J. Energy Consumption of Mobile Intelligent System. (2011) International Review on Computers and Software (IRECOS), 6 (4), pp. 607-614.

Considine, J.; Li, F.; Kollios, G.; Byers, J. Approximate Aggregation Techniques for Sensor Databases. Proc. Int. Conf. Data Engineering, 2004, 449-460.

Madden, S.; Franklin, M.J.; Hellerstein, J.; Hong, W. TAG: a Tiny AGgregation Service for Ad-Hoc Sensor Networks. Proc. Symposium on Operating Systems Design and implementation, 2002, 131-146.

Zeinalipour-Yazti, D.; Neema, S.; Kalogeraki, V.; Gunopulos, D.; Najjar, W. Data Acquisition in Sensor Networks with Large Memories. Proc. Int. Conf. Data Engineering, 2005, 1188-1192.

Banerjee, A.; Mitra, A.; Najjar, W.; Zeinalipour-Yazti, D.; Kalogeraki, V.; Gunopulos D. RISE Co-S: High Performance Sensor Storage and Co-Processing Architecture. Proc. IEEE Com. Society Conf. on Sensor and Ad Hoc Communication and Networks, 2005, 1-12.

Gay, D. Design of Matchbox: The simple Filing System for Motes. In TinyOS 1.x distribution, 2003. Available online: (accessed on 16 January 2012).

Dai, H.; Neufeld, M.; Han, R. ELF: An Efficient Log-Structured Flash File System for Micro Sensor Nodes. Proc. Int. Conf. Embedded Networked Sensor Systems, 2004, 176-187.

Mathur, G.; Desnoyers, P.; Ganesan, D.; Shenoy, P.J. Capsule: An Energy-Optimized Object Storage System for Memory-Constrained Sensor Devices. Proc. Int. Conf. Embedded Networked Sensor Systems, 2006, 195-208.

Zeinalipour-Yazti, D.; Lin, S.; Kalogeraki, V.; Gunopulos, D.; Najjar, W.A. MicroHash: An Efficient Index Structure for Flash-Based Sensor Devices. Proc. USENIX Conf. File and Storage Technology, 2005, 31-44.

Park, B.H.; Kargupta, H. Distributed Data Mining: Algorithms, Systems, and Applications. Data mining handbook, 2002.

Tilak, S.; Abu-ghazaleh, N.; Wendi B. H. Storage management in wireless sensor networks. Int. J. of Ad Hoc and Ubiquitous Computing archive, 2005, 1 (1/2), 47-58.

Basile, T.M.A.B.; Mauro, N.D.M.; Ferilli, S.; Esposito, F. Relational Temporal Data Mining for Wireless Sensor Networks, Proc. Int. Conf. Italian Association for Artificial Intelligence, 2009, 416 – 425.

Ci, S.; Guizani, M.; Sharif, H. Adaptive clustering in wireless sensor networks by mining sensor energy data. Int. J. Computer Communications archive, 2007, 30(14-15), 2968-2975.

Phung, N.; Mohamed, G.; Rohm, U. Resource-aware distributed online data mining for wireless sensor networks. Proc. IEEE Computational Intelligence and Data Mining, 2007, 139 -146.

Cohen, L.; Avrahami, BG.; Last, M.; Kandel, A.; Kipersztok, O. Real-time data mining of non-stationary data streams from sensor networks, Int. J. Information Fusion, 2008, 9(3), 344–353.

Mica 2: Wireless Measurement System, Available online: (accessed on 16 January 2012).

Tiny OS, Available online: (accessed on 16 January 2012).

Introduction to SQL Server 2005 Data Mining, Available online: (accessed on 16 January 2012).

Mathur, G.; Desnoyers, P.; Ganesan, D.; Shenoy P. Ultra-low Power Data Storage for Sensor Networks. Proc. Int. Conf. Information Processing in Sensor Networks, 2006, 374-381.

Lipardi, M., Mattera, D., Sterle, F., MMSE equalization in presence of transmitter and receiver IQ imbalance, (2007) 2007 International Waveform Diversity and Design Conference, WDD, art. no. 4339402, pp. 165-168.

Mattera, D., Tanda, M., Blind symbol timing and CFO estimation for OFDM/OQAM systems, (2013) IEEE Transactions on Wireless Communications, 12 (1), art. no. 6397549, pp. 268-277.

Mattera, D., Tanda, M., Bellanger, M., Frequency-spreading implementation of OFDM/OQAM systems, (2012) Proceedings of the International Symposium on Wireless Communication Systems, art. no. 6328353, pp. 176-180.


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