Analysis of Energy-Efficiency Using Big Data for Wireless Sensor Networks

  • Authors

    • Nandagopal C
    • Nivetha S
    https://doi.org/10.14419/ijet.v7i3.20.27353
  • NS2, Wireless Sensor Network, Big Data, information gathering.

  • The objective is on development in communication technologies on Big Data. DWSN are core control of big data to obtain informations which has various barriers to tackle. They can be tackled by algorithm with routing strategies is tackled. By experiments methodology transmission of signals are analyzed. By these techniques big data algorithm for WSN proposed to information gathering. Networks with WSN are to cluster by the signal strength of received and sensor node energies. The objective of system is to provide long life span network and with less collection of data latency. The clustering of balanced load distribution is organized for sensor to clumps in self-estimation manner. By the existing system it develops cluster with multiple to be balanced load and authenticated with data transmission. In top layer of the header, interior transmission is linked within cluster coordinates with each other for multiple clustering. The information in trajectory planning cluster head moved from the inter clusters. It is designed with antennas to obtain user of multiple numbers into input and output of multiple techniques. The strength of the suggested system is verified through numerical results obtained in NS2.

     

     

  • References

    1. [1] E. Fadel, V. Gungor, L. Nassef, N. Akkari, M. A. Maik, S. Almasri, and I. F. Akyildiz, “A Survey on Wireless Sensor Networks for Smart Grid,†Computer Communications, 2015.

      [2] L. Xuxun, “Atypical Hierarchical Routing Protocols for Wireless Sensor Networks: A Review,†Sensors Journal, IEEE, vol. 15, no. 10, pp. 5372-5383, 2015.

      [3] K. Kredo, and P. Mohapatra, “Medium access control in wireless sensor networks,†Computer Networks, vol. 51, no. 4, pp. 961-994, 2007.

      [4] A. A. Abbasi, and M. Younis, “ Clustering algorithm for networks with wireless network,†Computer communications, vol. 30, no. 14, pp. 2826-2841, 2007.

      [5] Baskar, S., & Dhulipala, V. R. (2016). Comparative Analysis on Fault Tolerant Techniques for Memory Cells in Wireless Sensor Devices. Asian Journal of Research in Social Sciences and Humanities, 6(cs1), 519-528.

      [6] Baskar, S., & Dhulipala, V. R., “M-CRAFT-Modified Multiplier Algorithm to Reduce Overhead in Fault Tolerance Algorithm in Wireless Sensor Networksâ€, Journal of Computational and Theoretical Nanoscience,2018, 15(4), 1395-1401.

      [7] X. Zhu, L. Shen, and T.-S. Yum, “Hausdorff clustering and minimum energy routing for wireless sensor networks,†Vehicular Technology, IEEE Transactions on, vol. 58, no. 2, pp. 990- 997, 2009.

      [8] A. Chamam, and S. Pierre, “A distributed energy-efficient clustering protocol for wireless sensor networks,†Computers & electrical engineering, vol. 36, no. 2, pp. 303-312, 2010.

      [9] N. Dimokas, D. Katsaros, and Y. Manolopoulos, “Energy- efficient distributed clustering in wireless sensor networks,†Journal of parallel and Distributed Computing, vol. 70, no. 4, pp. 371-383, 2010.

      [10] D. Wei, Y. Jin, S. Vural, K. Moessner, and R. Tafazolli, “An energy-efficient clustering solution for wireless sensor networks,†Wireless Communications, IEEE Transactions on, vol. 10, no. 11, pp. 3973-3983, 2011.

      [11] Baskar, S., & Dhulipala, V. R. (2018). Biomedical Rehabilitation: Data Error Detection and Correction Using Two Dimensional Linear Feedback Shift Register Based Cyclic Redundancy Check. Journal of Medical Imaging and Health Informatics, 8(4), 805-808.

      [12] A. Wang, D. Yang, and D. Sun, “A clustering algorithm based on energy information and for wireless sensor networks cluster heads expectation,†Computers & Electrical Engineering, vol. 38, no. 3, pp. 662-671, 2012.

      [13] W. B. Heinzelman, A. P. Chandrakasan, and H. Balakrishnan, “For wireless microsensor networks devolpment of application-specific protocol architecture,†Wireless Communications, IEEE Transactions on, vol. 1, no. 4, pp. 660-670, 2002.

      [14] Shakeel PM, Baskar S, Dhulipala VS, Mishra S, Jaber MM., “Maintaining security and privacy in health care system using learning based Deep-Q-Networksâ€, Journal of medical systems, 2018 Oct 1;42(10):186.https://doi.org/10.1007/s10916-018-1045-z

      [15] Sridhar KP, Baskar S, Shakeel PM, Dhulipala VS., “Developing brain abnormality recognize system using multi-objective pattern producing neural networkâ€, Journal of Ambient Intelligence and Humanized Computing, 2018:1-9. https://doi.org/10.1007/s12652-018-1058-y

      [16] S Vanithamani, N Mahendran, “Performance analysis of queue based scheduling schemes in wireless sensor networksâ€, in proceeding 2014 IEEE international Conference on Electronics and Communication Systems, ISBN: 978-1-4799-2320-5, pp: 1-6, 2014, DOI: 10.1109/ECS.2014.6892593

      [17] Shakeel PM, Baskar S, Dhulipala VS, Jaber MM., “Cloud based framework for diagnosis of diabetes mellitus using K-means clusteringâ€, Health information science and systems, 2018 Dec 1;6(1):16.https://doi.org/10.1007/s13755-018-0054-0

      [18] Sridevi. A and Prasanna Venkatesan. G K D, Certain Investigation on High Energy and spectral Efficient CRAHN based spectrum Aggregation, Journal of Computational and Theoretical Nanoscience, ISSN: 1546-1955 (Print): E-ISSN: 1546-1963, Vol.14, No. 8, pp. 3861–3866, Aug-17.

      [19] P. Mohamed Shakeel; Tarek E. El. Tobely; Haytham Al-Feel; Gunasekaran Manogaran; S. Baskar., “Neural Network Based Brain Tumor Detection Using Wireless Infrared Imaging Sensorâ€, IEEE Access, 2019, Page(s): 1

      [20] T.Srisuji,C.Nandagopal,†Analysis on microstrip patch antennas for wireless communication â€2 nd International conference on Electronics and communication systems(ICECS),ISBN:978-1-4799- 8,pp.538-541,2015

      [21] K. Sujatha, C. Nandagopal “ Realization of gateway relocation using admission control algorithm in mobile WIMAX networksâ€, 4th IEEE International Conference on Advanced Computing(ICoAC), pp. 1-5,2012

  • Downloads

  • How to Cite

    C, N., & S, N. (2018). Analysis of Energy-Efficiency Using Big Data for Wireless Sensor Networks. International Journal of Engineering & Technology, 7(3.20), 846-849. https://doi.org/10.14419/ijet.v7i3.20.27353