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Distributed Data Fusion for the Internet of Things

  • Rustem DautovEmail author
  • Salvatore Distefano
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10421)

Abstract

The ubiquitous Internet of Things is underpinned by the recent advancements in the wireless networking technology, which enabled connecting previously scattered devices into the global network. IoT engineers, however, are required to handle current limitations and find the right balance between data transferring range, throughput, and power consumption of wireless IoT devices. As a result, existing IoT systems, based on collecting data from a distributed network of edge devices, are limited by the amount of data they are able to transfer over the network. This means that some sort of data fusion mechanism has to be introduced, which would be responsible for filtering raw data before sending them further to a next node through the network. As a potential way of implementing such a mechanism, this paper proposes utilising Complex Event Processing and introduces a hierarchical distributed architecture for enabling data fusion at various levels.

Keywords

Data fusion Complex Event Processing Distributed architecture Internet of Things Edge computing Cloud computing 

References

  1. 1.
    Brunelli, D., Gallo, G., Benini, L.: Sensormind: virtual sensing and complex event detection for internet of things. In: Gloria, A. (ed.) ApplePies 2016. LNEE, vol. 409, pp. 75–83. Springer, Cham (2017). doi: 10.1007/978-3-319-47913-2_10 CrossRefGoogle Scholar
  2. 2.
    Díaz, M., Martín, C., Rubio, B.: State-of-the-art, challenges, and open issues in the integration of Internet of things and cloud computing. J. Netw. Comput. Appl. 67, 99–117 (2016)CrossRefGoogle Scholar
  3. 3.
    Fonseca, J., Ferraz, C., Gama, K.: A policy-based coordination architecture for distributed complex event processing in the internet of things: doctoral symposium. In: Proceedings of the 10th ACM International Conference on Distributed and Event-Based Systems, pp. 418–421. ACM (2016)Google Scholar
  4. 4.
    Garcia Lopez, P., Montresor, A., Epema, D., Datta, A., Higashino, T., Iamnitchi, A., Barcellos, M., Felber, P., Riviere, E.: Edge-centric computing: vision and challenges. SIGCOMM Comput. Commun. Rev. 45(5), 37–42 (2015)CrossRefGoogle Scholar
  5. 5.
    Guo, Q., Huang, J.: A complex event processing based approach of multi-sensor data fusion in IoT sensing systems. In: 2015 4th International Conference on Computer Science and Network Technology (ICCSNT), vol. 1, pp. 548–551. IEEE (2015)Google Scholar
  6. 6.
    Wang, Y., Cao, K.: A proactive complex event processing method for large-scale transportation internet of things. Int. J. Distrib. Sens. Netw. 10(3), 159052 (2014)CrossRefGoogle Scholar

Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  1. 1.Higher Institute of Information Technology and Information Systems (ITIS)Kazan Federal University (KFU)KazanRussia
  2. 2.University of MessinaMessinaItaly

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