Skip to main content
SpringerLink
Log in

Targeted Content Delivery to IoT Devices Using Bloom Filters

  • Conference paper
  • First Online:
Ad-hoc, Mobile, and Wireless Networks (ADHOC-NOW 2017)

Part of the book series: Lecture Notes in Computer Science ((LNCCN,volume 10517))

Included in the following conference series:

Abstract

The increasing number of smart interactive devices connected to the network opens new business opportunities for digital content and advertisement providers, interested in reaching out to new customer audiences. To this end, they employ various device discovery and data collection techniques to gather user- and device-specific information in order to build a user profile and deliver targeted content accordingly. However, the extreme (and constantly growing) number of smart devices, dynamically connecting to and disconnecting from a network in the IoT scenario, renders existing routing techniques, such as multicasting and broadcasting, unscalable, especially when using the IPv6 128-bit addresses. Moreover, these existing solutions can hardly provide information about technical capabilities of end devices. To address this limitation, this paper discusses the potential of implementing the IoT device discovery for device-specific content delivery, based on device properties, such as screen size and resolution, network connectivity, presence of speakers, supported languages, etc., and presents an approach to enable property-based access to IoT nodes using Bloom filters. The proposed approach demonstrates space- and network-efficient characteristics, as well as provides an opportunity to perform device discovery at various granularity levels.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Notes

  1. 1.

    http://www.squid-cache.org/.

  2. 2.

    It is worth noting that this network population process might be continuously repeated, so as to update the bits related to the actual network connection of a device.

  3. 3.

    https://github.com/aappleby/smhasher/blob/master/src/MurmurHash3.cpp.

References

  1. Google IPv6 statistics (2017). https://www.google.com/intl/en/ipv6/statistics.html. Accessed 14 July 2017

  2. Bloom, B.H.: Space/time trade-offs in hash coding with allowable errors. Commun. ACM 13(7), 422–426 (1970)

    Article  MATH  Google Scholar 

  3. Bonomi, F., Mitzenmacher, M., Panigrahy, R., Singh, S., Varghese, G.: An improved construction for counting Bloom filters. In: Azar, Y., Erlebach, T. (eds.) ESA 2006. LNCS, vol. 4168, pp. 684–695. Springer, Heidelberg (2006). doi:10.1007/11841036_61

    Chapter  Google Scholar 

  4. Broder, A., Mitzenmacher, M.: Network applications of Bloom filters: a survey. Internet Math. 1(4), 485–509 (2004)

    Article  MathSciNet  MATH  Google Scholar 

  5. Ccori, P.C., De Biase, L.C.C., Zuffo, M.K., da Silva, F.S.C.: Device discovery strategies for the IoT. In: Proceedings of 2016 IEEE International Symposium on Consumer Electronics (ISCE), pp. 97–98. IEEE (2016)

    Google Scholar 

  6. Dillinger, P.C., Manolios, P.: Bloom filters in probabilistic verification. In: Hu, A.J., Martin, A.K. (eds.) FMCAD 2004. LNCS, vol. 3312, pp. 367–381. Springer, Heidelberg (2004). doi:10.1007/978-3-540-30494-4_26

    Chapter  Google Scholar 

  7. Estébanez, C., Saez, Y., Recio, G., Isasi, P.: Performance of the most common non-cryptographic hash functions. Softw. Pract. Exp. 44(6), 681–698 (2014)

    Article  Google Scholar 

  8. Fan, L., Cao, P., Almeida, J., Broder, A.Z.: Summary cache: a scalable wide-area web cache sharing protocol. IEEE/ACM Trans. Netw. (TON) 8(3), 281–293 (2000)

    Article  Google Scholar 

  9. Foley, S.N.: A Bloom filter based model for decentralized authorization. Int. J. Intell. Syst. 28(6), 565–582 (2013)

    Article  Google Scholar 

  10. Kalmar, A., Vida, R., Maliosz, M.: Context-aware addressing in the internet of things using Bloom filters. In: Proceedings of 2013 IEEE 4th International Conference on Cognitive Infocommunications (CogInfoCom), pp. 487–492. IEEE (2013)

    Google Scholar 

  11. Nychis, G., Licata, D.R.: The impact of background network traffic on foreground network traffic. In: The Proceeding of the IEEE Global Telecommunications Conference (GLOBECOM), pp. 1–16 (2001)

    Google Scholar 

  12. Sebestyen, G., Hangan, A.: Bloom filters for information retrieval in the context of IoT. In: Proceedings of 2016 IEEE International Conference on Automation, Quality and Testing, Robotics (AQTR), pp. 1–6. IEEE (2016)

    Google Scholar 

  13. Snoeren, A.C., Partridge, C., Sanchez, L.A., Jones, C.E., Tchakountio, F., Kent, S.T., Strayer, W.T.: Hash-based IP traceback. In: ACM SIGCOMM Computer Communication Review, vol. 31, pp. 3–14. ACM (2001)

    Google Scholar 

  14. Spafford, E.H.: Preventing weak password choices. Technical report 91–028, Department of Computer Science, Purdue University (1991)

    Google Scholar 

  15. Tarkoma, S., Rothenberg, C.E., Lagerspetz, E., et al.: Theory and practice of Bloom filters for distributed systems. IEEE Commun. Surv. Tutor. 14(1), 131–155 (2012)

    Article  Google Scholar 

Download references

Acknowledgements

The work presented in this paper was partially supported by the ERASMUS+Key Action 2 (Strategic Partnership) project IOT-OPEN.EU (Innovative Open Education on IoT: improving higher education for European digital global competitiveness), reference no. 2016-1-PL01-KA203-026471. The European Commission support for the production of this publication does not constitute endorsement of the contents which reflects the views only of the authors, and the Commission cannot be held responsible for any use which may be made of the information contained therein.

Author information

Authors and Affiliations

  1. Higher Institute of Information Technology and Information Systems (ITIS), Kazan Federal University (KFU), Kazan, Russia

    Rustem Dautov & Salvatore Distefano

  2. University of Messina, Messina, Italy

    Salvatore Distefano

Authors
  1. Rustem Dautov
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Salvatore Distefano
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Rustem Dautov .

Editor information

Editors and Affiliations

  1. University of Messina, Messina, Italy

    Antonio Puliafito

  2. University of Messina, Messina, Italy

    Dario Bruneo

  3. University of Messina, Messina, Italy

    Salvatore Distefano

  4. Kazan Federal University, Kazan, Russia

    Francesco Longo

Rights and permissions

Reprints and permissions

Copyright information

© 2017 Springer International Publishing AG

About this paper

Cite this paper

Dautov, R., Distefano, S. (2017). Targeted Content Delivery to IoT Devices Using Bloom Filters. In: Puliafito, A., Bruneo, D., Distefano, S., Longo, F. (eds) Ad-hoc, Mobile, and Wireless Networks. ADHOC-NOW 2017. Lecture Notes in Computer Science(), vol 10517. Springer, Cham. https://doi.org/10.1007/978-3-319-67910-5_4

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-67910-5_4

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-67909-9

  • Online ISBN: 978-3-319-67910-5

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation