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Sensor Search Using Clustering Technique in a Massive IoT Environment

  • Nandhakumar RamachandranEmail author
  • Varalakshmi Perumal
  • Sakithya Gopinath
  • Monika Jothi
Conference paper
Part of the Lecture Notes in Networks and Systems book series (LNNS, volume 11)

Abstract

The Internet of things contains billions of interconnected things such as physical objects, animals, or human beings that give the power to transfer information over a network without human interaction. The huge amount of data continuously generated by these sensing devices raises the challenge of searching for the most relevant sensor data according to user’s query. Also, the queries specified by users are in natural human language which cannot be processed by sensors. To handle these challenges, devices in an IoT environment are grouped together to form clusters which reduces the search space. Every device is given a unique ipv6 address to identify it within the network. Then, the user’s abstract query is transformed into low level form which can be recognized by sensors. Experimental results show that the search time and response time is improved using this approach in large scale IoT environments.

Keywords

IoT Sensor search Query processing IPv6 

References

  1. 1.
    Fredj, S.B., Boussard, M., Kofman, D., Noirie, L.: A scalable IoT service search based on clustering and aggregation. In: IEEE International Conference on Green Computing and Communications (2013) Google Scholar
  2. 2.
    Li, S., Da Xu, L., Zhao, S.: The internet of things: a survey. Springer Inf. Syst. Front. 17, 243–259 (2015)Google Scholar
  3. 3.
    Al Fuqaha, A., Guizani, M., Mohammadi, M., Aledhari, M., Ayyash, M.: Internet of Things: a survey on enabling technologies, protocols and applications. IEEE Commun. Surv. Tutor. 601–642 (2015)Google Scholar
  4. 4.
    Sarkar, C., Nambi, A.U., Venkatesha Prasad, R., Rahim, A., Neisse, R., Baldini, G.: DIAT: a scalable distributed architecture for IoT. IEEE J. 3 (2015)Google Scholar
  5. 5.
    Perera, C., Zaslavsky, A., Liu, C.H., Compton, M., Christen, P., Georgakopoulos, D.: Sensor search techniques for sensing as a service architecture for the Internet of Things. IEEE Sens. J. 14, 406–419 (2014)Google Scholar
  6. 6.
    Elahi, B.M., Römer, K., Ostermaier, B.: Sensor ranking: a primitive for efficient content-based sensor search. In: ACM International Conference on Information Processing in Sensor Networks, pp. 217–228 (2009)Google Scholar
  7. 7.
    Truong, C., Romer, K., Chen, K.: Fuzzy based sensor search in the Web of things. In: IEEE International Conference on the Internet of Things (IOT) (2012)Google Scholar
  8. 8.
    Ding, Z, Gao, X., Guo, L., Yang, Q.: A hybrid search engine framework for the Internet of Things based on spatial-temporal, value-based, and keyword-based conditions. In: IEEE International Conference on Green Computing and Communications (2012)Google Scholar
  9. 9.
    Ebrahimi, M., Shafieibavani, E., Wong, R.K., Chi, C.H.: A new meta-heuristic approach for efficient search in the Internet of Things. In: IEEE International Conference on Services Computing (2015)Google Scholar
  10. 10.
    Yang, S., Xu, Y., He, Q.: Ontology based service discovery method for Internet of Things. In: IEEE International Conferences on Internet of Things, and Cyber, Physical and Social Computing (2011)Google Scholar

Copyright information

© Springer Nature Singapore Pte Ltd. 2018

Authors and Affiliations

  • Nandhakumar Ramachandran
    • 1
    Email author
  • Varalakshmi Perumal
    • 1
  • Sakithya Gopinath
    • 1
  • Monika Jothi
    • 1
  1. 1.Department of Computer Technology, MIT CampusAnna UniversityChennaiIndia

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