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SDQE: Sensor Data Quality Enhancement in Reconfigurable Network for Optimal Reliability

  • B. Prathiba
  • K. Jaya Sankar
  • V. Sumalatha
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 765)

Abstract

The future applications include a multi-technology based paradigm, which includes wireless sensor network, Internet of things and cloud computing to be synchronized for the accurate and real-time analytics. The applications client will be a smart phone user who will request the wireless sensor network data or key data points of sensors through the universal data centers. This paper highlights the problem identification of the sensor data quality and reliability aspects by proposing a model for sensor data quality enhancement (SDQE) by synchronizing the priority of critical data with time factor. The data request prediction based optimization is proposed to maximize the usefulness factor which is the measure of sensor data quality as reliability and minimize the energy consumption. The model is simulated in numerical computing platform and found acceptable response.

Keywords

Wireless sensor network Internet of Things (IoT) Sensor data quality 

References

  1. 1.
    Kocakulak, M., Butun, I.: An overview of wireless sensor networks towards Internet of things. In: IEEE 7th Annual Computing and Communication Workshop and Conference (CCWC), Las Vegas, pp. 1–6 (2017)Google Scholar
  2. 2.
    Çetin, R., Kadioğlu, T., Cesur, E., Ayten, U.E.: Design of wireless sensor network for Internet of Things structure. In: National Conference on Electrical, Electronics and Biomedical Engineering (ELECO), Bursa, pp. 402–405 (2016)Google Scholar
  3. 3.
    Zhu, C., Sheng, Z., Leung, V.C.M., Shu, L., Yang, L.T.: Toward offering more useful data reliably to mobile cloud from wireless sensor network. IEEE Trans. Emerg. Top. Comput. 3(1), 84–94 (2015)CrossRefGoogle Scholar
  4. 4.
    Sen, S.: Invited: context-aware energy-efficient communication for IoT sensor nodes. In: 53rd ACM/EDAC/IEEE Design Automation Conference (DAC), Austin, pp. 1–6 (2016)Google Scholar
  5. 5.
    Prathiba, B., Sankar, K.J., Sumalatha, V.: Enhancing the data quality in wireless sensor networks — a review. In: International Conference on Automatic Control and Dynamic Optimization Techniques (ICACDOT), Pune, pp. 448–454 (2016)Google Scholar
  6. 6.
    Ghorbel, O., Ayedi, W., Snoussi, H., Abid, M.: Fast and efficient outlier detection method in wireless sensor networks. IEEE Sens. J. 15(6), 3403–3411 (2015)CrossRefGoogle Scholar
  7. 7.
    Cecílio, J., Furtado, P.: Existing middleware solutions for wireless sensor networks. In: Wireless Sensors in Heterogeneous Networked Systems. Computer Communications and Networks. Springer, Cham (2014)Google Scholar
  8. 8.
    Ajana, M.E.K., Harroud, H., Boulmalf, M., Elkoutbi, M.: Middleware Architecture in WSN. In: Benhaddou, D., Al-Fuqaha, A. (eds.) Wireless Sensor and Mobile Ad-Hoc Networks. Springer, New York (2015)Google Scholar
  9. 9.
    Alamri, A., Ansari, W.S., Hassan, M.M., Hossain, M.S., Alelaiwi, A., Hossain, M.A.: A survey on sensor-cloud: architecture, applications, and approaches. Int. J. Distrib. Sens. Netw. 9(2) (2013). Article ID 917923CrossRefGoogle Scholar
  10. 10.
    Maddar, H., Kammoun, W., Youssef, H.: Cloudlets architecture for wireless sensor network. In: Madureira, A., Abraham, A., Gamboa, D., Novais, P. (eds.) Intelligent Systems Design and Applications. ISDA 2016. Advances in Intelligent Systems and Computing, vol. 557. Springer, Cham (2017)Google Scholar
  11. 11.
    Baccarelli, E., Cordeschi, N., Mei, A., Panella, M., Shojafar, M., Stefa, J.: Energy-efficient dynamic traffic offloading and reconfiguration of networked data centers for big data stream mobile computing: review, challenges, and a case study. IEEE Netw. 30(2), 54–61 (2016)CrossRefGoogle Scholar
  12. 12.
    Zhu, C., Leung, V.C.M., Wang, H., Chen, W., Liu, X.: Providing desirable data to users when integrating wireless sensor networks with mobile cloud. In: Proceedings of the IEEE 5th International Conference on Cloud Computing Technology and Science (CloudCom), pp. 607–614 (2013)Google Scholar
  13. 13.
    Zhu, C., Sheng, Z., Leung, V.C.M., Shu, L., Yang, L.T.: Toward offering more useful data reliably to mobile cloud from wireless sensor network. IEEE Trans. Emerg. Top. Comput. 3, 84–94 (2015)CrossRefGoogle Scholar
  14. 14.
    Zhu, C., Leung, V.C., Shu, L., Ngai, E.C.H.: Green Internet of Things for smart world. IEEE Access 3, 2151–2162 (2015)CrossRefGoogle Scholar
  15. 15.
    Zhu, C., Leung, V.C., Yang, L.T., Shu, L., Rodrigues, J.J., Li, X.: Trust assistance in sensor-cloud. In: IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS), pp. 342–347. IEEE, April 2015Google Scholar
  16. 16.
    Wan, L., Han, G., Shu, L., Feng, N., Zhu, C., Lloret, J.: Distributed parameter estimation for mobile wireless sensor network based on cloud computing in battlefield surveillance system. IEEE Access 3, 1729–1739 (2015)CrossRefGoogle Scholar
  17. 17.
    Lin, H., Hu, J., Tian, Y., Yang, L., Xu, L.: Toward better data veracity in mobile cloud computing: a context-aware and incentive-based reputation mechanism. Inf. Sci. 387, 238–253 (2017)CrossRefGoogle Scholar

Copyright information

© Springer International Publishing AG, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Department of ECEJawaharlal Nehru Technological UniversityAnantapurIndia
  2. 2.Department of ECEVasavi College of EngineeringHyderabadIndia

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