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Efficient Data Aggregation and Collection in Tree Based Wireless Sensor Networks

M. Ananthi, C. Pavithra, C. Pavithra, E. Sangeetha, D. SreeArthi

Abstract


In several wireless sensor network the energy conservation is a major problem .In this WSN once the energy gets lost the sensor moves to die condition and so it cannot possible to replace the battery in sensor. So energy conservation is difficult in sensor network .The node which is closer to the base station has the responsible for collecting data from the entire node and send it to the base station .such node is called as root node or sink node (e.g., tree topology). This paper achieved the fast data collection by keeping the sink node always in the busy state .In this converge cast algorithm is used which contains Aggregated converge cast and Raw-data converge cast algorithm. TDMA (Time Division Multiple Access) are better fit for fast data collection since they can avoid collision and retransmission of data .Fast data collection with the aim of minimize the schedule length for aggregated converge cast.


Keywords


Fast Data Collection, Energy Efficiency, Aggregated Converge Cast, Raw-Data Converge Cast, TDMA (Time Division Multiple Access).

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References


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.

G. Anastasi, M. Conti, M. Di Francesco and A. Passarella, “Energy Conservation in Wireless Sensor Networks: A Survey”, Ad Hoc Networks, Vol. 7, No. 3, pp. 537-568, 2009.

G. A1nastasi, M. Conti and M. Di Francesco, “Extending the Lifetime of Wireless Sensor Network through Adaptive Sleep”, IEEE Transactions on Industrial Informatics, Vol. 5, No. 3, pp. 351-365, 2009.

Antoni Morell et al., “Data Aggregation and Principal Component Analysis in WSNs”, IEEE Transactions on Wireless Communications, Vol. 15, No. 6, pp. 3908-3919,2010.

S. Toumpis and S. Gitzenis, “Load Balancing in Wireless Sensor Networks using Kirchhoff’s Voltage Law”, Proceedings of IEEE INFOCOM, pp. 1656-1664, 2009.

J. Liang, J. Wang, J. Cao, J. Chen and M. Lu, “An Efficient Algorithm for Constructing Maximum lifetime Tree for Data Gathering Without Aggregation in Wireless Sensor Networks”, Proceedings of IEEE INFOCOM, pp. 1-5, 2010.

Y. Liu, Y. He, M. Le, J. Wang, K. Liu, and L. Mo, “Does Wireless Sensor Network Scale? A Measurement Study on Green Orbs”, IEEE Transactions on Parallel and Distributed Systems, Vol. 24, No. 10, pp. 873-881, 2011.

A. Willig, “Recent and Emerging Topics in Wireless Industrial Communications : A Selection”, IEEE Transactions on Industrial Informatics, Vol. 4, No. 2, pp. 102-124, 2008.

Debraj De and Sajal K. Das, “SREE-Tree: SelfReorganizing Energy-Efficient Tree Topology Management in Sensor Networks”, Proceedings of International Conference on Sustainable Internetand ICT for Sustainability, pp. 113-119, 2015.

S.K.A. Imon, A. Khan, M. Di Francesco and S.K. Das, “Energy-Efficient Randomized Switching for Maximizing Lifetime in Tree-based Wireless Sensor Networks”, IEEE/ACM Transactions on Networking, Vol. 23, No. 5, pp. 1401-1415, 2015.

Ozlem Durmaz Incel, Amitabha Ghosh, Bhaskar Krishnamachari and Krishnakant Chintalapudi, “Fast Data Collection in Tree-Based Wireless Sensor Networks”, IEEE Transactions on Mobile Computing, Vol. 11, No. 1, pp. 8699, 2012.

D. Luo, X. Zhu, X. Wu and G. Chen, “Maximizing Lifetime for the Shortest Path Aggregation Tree in Wireless Sensor Networks”, Proceedings of IEEE INFOCOM, pp.15661574, 2011.


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