International Journal of Engineering Research in Computer Science and Engineering (IJERCSE)

Data Filter Based Clustering method for Data Accuracy of Data Aggregation in WSN

Author : Sakthivel S ¹ R. Nandhakumar ²

Date of Publication :7th February 2016

Abstract: One data aggregation method in a wireless sensor network (WSN) is sending local representative data to the sink node based on the spatial clustering of sampled data. The recent spatial clustering models of sensor node’s data are not appropriate due to its error rates, the representative data are inaccurate when compared with real data. Thus, an value based approach on node’s data is followed to avoid larger deviations. A threshold value is set in each node by default, which excludes nodes with higher data differences from its cluster or aggregation. The excluded node is considered as an Isolated Sensor Node and sends its data directly to the sink, without participating in normal clusters. The proposed clustering method provides good data accuracy in data aggregation when compared to existing systems. The number of active nodes identified using the proposed method is lower than existing systems and it minimizes power consumption. This method provides more data accuracy when compared to existing clustering methods such as Pearson Correlation Coefficient clustering method, ?-local spatial clustering method, and Data Density Correlation Degree Clustering method.

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2. Dariush Ebrahimi and Chadi Assi “A Distributed Method for Compressive Data Gathering in Wireless Sensor Networks” IEEE COMMUNICATIONS LETTERS, VOL. 18, NO. 4, APRIL 2014
3. Changhee Joo, Senior Member, IEEE, and Ness B. Shroff, Fellow, IEEE “On the Delay Performance of InNetwork Aggregation in Lossy Wireless Sensor Networks” IEEE/ACM TRANSACTIONS ON NETWORKING, VOL. 22, NO. 2, APRIL 2014
4. Cheng Wang, Changjun Jiang, Yunhao Liu, Senior Member, IEEE, Xiang-Yang Li, Senior Member, IEEE, and Shaojie Tang “Aggregation Capacity of Wireless Sensor Networks: Extended Network Case” IEEE TRANSACTIONS ON COMPUTERS, VOL. 63, NO. 6, JUNE 2014
5. Junchao Ma, Student Member, IEEE, Wei Lou, Member, IEEE, and Xiang-Yang Li, Senior Member, IEEE “Contiguous Link Scheduling for Data Aggregation in Wireless Sensor Networks” IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS, VOL. 25, NO. 7, JULY 2014
6. Nandini. S. Patil, Prof. P. R. Patil, “Data Aggregation in Wireless Sensor Network”. 2010 IEEE International Conference on Computational Intelligence and Computing Research
7. Ivan Stojmenovic, Fellow, IEEE, "Machine-to-Machine Communications With In-Network Data Aggregation, Processing, and Actuation for Large-Scale Cyber-Physical Systems". IEEE INTERNET OF THINGS JOURNAL, VOL. 1, NO. 2, APRIL 2014
8. M. Lee, and S. Lee, “Data Dissemination for Wireless Sensor Networks”, in Proceedings of the 10 th IEEE International Symposium on Object and ComponentOriented Real-Time Distributed Computing (ISORC’07)
9. Tripti Sharma, Akanksha Dhawan, BijeshKumar, Rahul Singh Rathore, Karan Berry, Vishalakshi Gupta,.“Ant Based Cluster Head Election Algorithm in Wireless Sensor Network to avoid redundancy”. 2014 Fourth International Conference on Communication Systems and Network Technologies.
10. H. Cam, S. Ozdemir, P. Nair, and D.Muthuavina shiappan, “ESPDA: Energy-Efficient and Secure Patternbased Data Aggregation for Wireless Sensor Networks”, in Proceedings of IEEE Sensor- The Second IEEE Conference on Sensors, Toronto, Canada, Oct. 22-24, 2003, pp. 732- 736.
11. Mohammad Sayad Haghighi, Member, IEEE, Yang Xiang, Senior Member, IEEE, Vijay Varadharajan, Senior Member, IEEE, and Barry Quinn, Member, IEEE,. “A Stochastic Time-domain Model for Burst Data Aggregation in IEEE 802.15.4 Wireless Sensor Networks”. JOURNAL OF LATEX CLASS FILES, VOL. X, NO. Y, JUNE 2013
12. Jing (Selena) He, Member, IEEE, Shouling Ji, Student Member, IEEE, Yi Pan, Senior Member, IEEE, and Yingshu Li, Senior Member, IEEE, “Constructing Load-Balanced Data Aggregation Trees in Probabilistic Wireless Sensor Networks” IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS, VOL. 25, NO. 7, JULY 2014.
13. S. Lindsey and C. Raghavendra, “PEGASIS: Powerefficient gathering in sensor information systems,” in 2010 IEEE International Conference on Computational Intelligence and Computing Research Proceedings of IEEE AerospaceConference, vol. 3, Mar. 2002, pp. 1125–1130.
14. Ying Liao, Jianjing Shen, Member, IEEE, Yi Lin, and Changlin Zhou, Senior Member, IEEE,“Quantitative Analysis of Network Configuration in Randomized Distribution Wireless Sensor Networks”. IEEE SENSORS JOURNAL, VOL. 14, NO. 6, JUNE 2014
15. C. Intanagonwiwat, R. Govindan, D. Estrin, J. Heidemann, and F. Silva, “Directed Diffusion for Wireless Sensor Networking”, IEEE/ACM Transactions on Networking, Vol. 11, no. 1, Feb 2003
16. Mohammad Sayad Haghighi, Member, IEEE, Yang Xiang, Senior Member, IEEE, Vijay Varadharajan, Senior Member, IEEE, and Barry Quinn, Member, IEEE,. “A Stochastic Time-domain Model for Burst Data Aggregation in IEEE 802.15.4 Wireless Sensor Networks”. JOURNAL OF LATEX CLASS FILES, VOL. X, NO. Y, JUNE 2013
17. Chalermek Intanagonwiwat, Ramesh Govindan, and Deborah Estrin, “Directed diffusion: a scalable and robust communication paradigm for sensor networks”, (MobiCom 2000) pp 56-67.
18. K. Dasgupta, K. Kalpakis, and P. Namjoshi, “An Efficient Clustering-based Heuristic for Data Gathering and Aggregation in Sensor Networks”, IEEE 2003.
19. E. Fasolo, M. Rossi, J. Widmer, and M. Zorzi, “InNetwork Aggregation Techniques for Wireless Sensor Networks: A Survey”, IEEE Wireless communication 2007.
20. M. Lee and V.W.S. Wong, “An Energy-aware Spanning Tree Algorithm for Data Aggregation in Wireless Sensor Networks,” IEEE PacRrim 2005, Victoria, BC, Canada, Aug. 2005.
21. M. Ding, X. Cheng, and G. Xue, “Aggregation tree construction in sensor networks,” in Proc. of IEEE VTC’03, Vol. 4, Orlando, FL, Oct. 2003.
22. “The Design Space of Wireless Sensor Networks” by Kay R¨omer and Friedemann Mattern http://www.vs.inf.ethz.ch/publ/papers/wsndesignspace.pdf
23. http://en.wikipedia.org/wiki/Wireless_Sensor_Network