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A Muthu Krishnan et al ,Int.J.Computer Technology & Applications,Vol 4 (1), 51-57 ISSN:2229-6093 Figure.5.Event driven Data gathering For a rare and asynchronous event reporting event driven data gathering complies well. This scheme reports to the sink on the occurrence of an event. This method conserves a significant amount of energy at the cost of accuracy. This scheme can lessen the data amount and requires low band width. Fig.5 shows event driven data gathering with low dynamic signal, the more dynamic the data, lesser the energy conservation. If the signal is dynamic lesser will be the energy conservation. Figure.7.Hybrid Data Gathering When the data gathering schemes are combined, the amount of data can be reduced to a considerable level at the cost of minimal reduction in data accuracy. This scheme initiates data driven data gathering only if the data goes beyond threshold value, otherwise it remains in event driven data gathering scheme. This method helps in analyzing the data when the data value is greater than threshold value. Figure.6.Data driven Data gathering . This scheme reports to the sink on the occurrence of an change in data. This method conserves a significant amount of energy at the cost of accuracy. This scheme can lessen the data amount and requires low band width. Fig.6.shows data driven data gathering with data integrity. Figure 8.Performance comparison of different Data Gathering with respect to power. The results of hybrid data gathering outperforms time driven data gathering in energy conservation and event driven data gathering in data accuracy. The results are encouraging us towards energy efficient data collection with data integrity. The system enhances the lifespan of WSN’s. This scheme can be applied to any type of WSN’s topology .In this, no clustering is needed and cluster overheads are avoided and the computational load is very low which is very much apt for energy constrained WSN’s. IJCTA | Jan-Feb 2013 Available online@www.ijcta.com 56
A Muthu Krishnan et al ,Int.J.Computer Technology & Applications,Vol 4 (1), 51-57 ISSN:2229-6093 Conclusion: The hybrid algorithm for data gathering is designed and simulated. From the above results we observe that the modified PED and PAD algorithms using only in moderate resource consumption. The hybrid algorithm achieves data accuracy and adequate data for detailed analysis at moderate resource consumption. The hybrid data gathering scheme achieves 40% energy reduction than the time driven data gathering. The data accuracy has been improved by reducing Root Mean Square Error by 0.2 compare to event driven data gathering. Hybrid algorithm outperforms time driven data gathering in energy conservation and event driven algorithm in data accuracy. The tradeoff between data accuracy and energy conservation is left to the user. Based on the application requirement, the threshold for the switching between event driven and time driven can be adjusted. The adaptive transmission scheme further reduces the data amount by adapting itself to the change in data parameter. The proactive inclusion of neighboring sensor nodes further reinforces the data accuracy and direction of parameter intensification. REFERENCES [1] Römer, Kay; Friedemann Mattern "The Design Space of Wireless Sensor Networks” IEEE Wireless Communications, Dec. 2004. [2] V. Raghunathan, C. Schurgers, S. Park, and M. B. Srivastava, “Energy-Aware wireless Microsensor Networks”, IEEE Signal Processing Magazine, 19 (2002), pp 40-50. [3].Akyildiz IF, Su W, Sankarasubramaniam Y and Cayirci E,”Wireless sensor networks: a survey”. Springer Computer Networks. Vol 38 pp: 393-422, March 2002. [4] A. Manjeshwar and D. P. Agarwal. 2002. APTEEN: A hybrid protocol for efficient routing and comprehensive information retrieval in wireless sensor networks. Parallel and Distributed Processing Symposium, Proceedings International, IPDPS, pp. 195-202. [8] J. Al-Karaki and A. Kamal, “Routing techniques in wireless sensor networks: A survey,” IEEE Wireless Commun., vol. 11, no. 6, pp. 6– 28, Dec. 2004. [9] Byoung-Dai Lee, “An Energy-Efficient Hybrid Data- Gathering Protocol Based on the Dynamic Switching of Reporting Schemes in Wireless Sensor Networks,” Systems Journal,IEEE., vol. 6, no. 6, pp 378-387, Sep.2012. AUTHOR DETAILS: ‣ A.Muthu Krishnan is working as a faculty in Electronics and communication Engineering in Regional centre of Anna University Madurai. He completed his Bachelor degree in Anna University. He completed his Master’s degree in VLSI Design in Anna University of Technology Coimbatore. He has four years of Teaching experience in Electronics and communication Engineering. Currently He is doing his PhD in Anna University,Chennai. ‣ P.Ganesh kumar is working as a professor in Electronics and communication Engineering in KLN College of Engineering, Madurai. He completed his Bachelor degree in Madurai Kamaraj University, Madurai and his masters in Bharathiyar University, Coimbatore. He completed his PhD in Anna University Chennai and his areas of interest are Virtual instrumentation and its applications, Wireless Sensor Networks. [5] Ossama Younis and Sonia Fahmy. 2004. Distributed Clustering in Ad-hoc Sensor Networks: A Hybrid, Energy- Efficient Approach. In Proceedings of IEEE INFOCOM, Hong Kong, an extended version appeared in IEEE Transactions on Mobile Computing, 3(4). [6] S. Lindsey, C. Raghavendra. 2002. PEGASIS: PowerEfficient Gathering in Sensor Information Systems. IEEE Aerospace Conference Proceedings, Vol. 3, 9-16 pp. 1125- 1130. [7] C. Srisathapornphat, C. Jaikaeo, and C. Shen, “Sensor information networking architecture,” in Proc. Int. Workshop Parallel Process., 2000, pp. 22–30. IJCTA | Jan-Feb 2013 Available online@www.ijcta.com 57
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