An adaptive duty-cycle mechanism for energy efficient wireless sensor networks, based on information centric networking design

  • Ghada JaberEmail author
  • Rahim Kacimi
  • Luigi Alfredo Grieco
  • Thierry Gayraud


The information-centric networking (ICN) is an emerging paradigm that grounds networking primitives on content names rather than node locators (as in the current Internet). ICN targets seamless mobility, native muticast/multipath support, and content oriented security to better reflect the needs of today users. ICN could greatly improve the efficiency of content delivery also in wireless sensor networks (WSNs). A WSN typically provides information centric services: in fact, whenever a mote is queried, the asking user is interested to the information acquired by the sensors on top of that mote rather than establishing a point-to-point remote communication. In this manuscript, without lack of generality, we will focus on a particular type of ICN architecture, known as content centric networking (CCN). In such a context, we place our attention on the energy efficiency of forwarding, which is achieved via costly broadcasting. Our objective is to save energy while achieving a high user satisfaction rate. In CCN, when a node requests a content, it sends an interest message and the node with the corresponding content replies with a Content Object message. To enable CCN features, each node maintains three tables: a Content Store to cache contents; a Forwarding Interest Base to store forwarded interests and a Pending Interest Table (PIT) to record unsatisfied interests. In this work, we start by introducing the features of CCN in WSNs and the advantages that it brings. For the forwarding optimization, we come up with an ‘Adaptive and fully Distributed Duty-Cycle for Content-Centric Wireless Sensor Network’ (ADDC-CCWSN) mechanism. ADDC-CCWSN aims to reduce the activity of nodes with a high percentage of unsatisfied interests in their PIT. We argue that the approach can be applied (with some modifications) to any ICN architecture that works as a network of caches in pull mode. We also propose an analytical model for CCN-WSNs to examine the energy consumption of content delivery. In addition, we implement the proposed mechanism on Contiki and, through extensive simulations with Cooja, we demonstrate that our approach achieves a significant gain of energy efficiency compared to a CCN approach with mostly-on sensor nodes while ensuring a high interest satisfaction rate and keeping nearly the same delay.


Wireless sensor networks Information-centric networking Content-centric networking Energy efficiency Modeling Analysis Duty-cycling Interest satisfaction rate 



This work is supported jointly by the neOCampus research Grant [28] and the Occitanie Province.


  1. 1.
    Lee, J., & Kim, D. (2011). Proxy-based mobility management scheme in mobile content centric networking (ccn) environments. IEEE Transactions on Consumer Electronics, 57(2), 595–596.Google Scholar
  2. 2.
    Xylomenos, G., Ververidis, C. N., Siris, V. A., Fotiou, N., Tsilopoulos, C., & Vasilakos, X. (2014). A survey of information-centric networking research. IEEE Communications Surveys & Tutorials, 16(2), 1024–1049.CrossRefGoogle Scholar
  3. 3.
    Raychaudhuri, D., Nagaraja, K., & Venkataramani, A. (2012). Mobilityfirst: A robust and trustworthy mobility-centric architecture for the future internet. SIGMOBILE Mobile Computing and Communications Review, 16(3), 2–13.CrossRefGoogle Scholar
  4. 4.
    Anand, A., Dogar, F., Han, D., Li, B., Lim, H., Machado, M., Wu, W., Akella, A., Andersen, D. G., Byers, J. W., Seshan, S., & Steenkiste, P. (2011) Xia: An architecture for an evolvable and trustworthy internet. In Proceedings of the 10th ACM workshop on hot topics in networks, HotNets-X (pp. 2:1–2:6), New York, NY, USA, 2011. ACM.Google Scholar
  5. 5.
    Jacobson, V., Smetters, D. K., Thornton, J. D., Plass, M. F., Briggs, N. H., & Braynard, R. L. (2009). Networking named content. In: Proceedings of the 5th international conference on Emerging networking experiments and technologies (pp. 1–12). ACM.Google Scholar
  6. 6.
    Ahlgren, B., Dannewitz, C., Imbrenda, C., Kutscher, D., & Ohlman, B. (2012). A survey of information-centric networking. IEEE Communications Magazine, 50(7), 26–36.CrossRefGoogle Scholar
  7. 7.
    Amadeo, M., Campo, C., Molinaro, A., & Mitton, N. (2013). Named data networking: A natural design for data collection in wireless sensor networks. In IEEE Wireless Days (WD), Valencia, Spain, November.Google Scholar
  8. 8.
    Ren, Z., Hail, M. A, & Hellbrück, H. (2013). CCN-WSN-a lightweight, flexible content-centric networking protocol for wireless sensor networks. In IEEE 8th international conference on intelligent sensors, sensor networks and information processing (pp. 123–128). IEEE.Google Scholar
  9. 9.
    Saadallah, B., Lahmadi, A., & Festor, O. (2012). CCNx for Contiki: Implementation details. PhD thesis, INRIA.Google Scholar
  10. 10.
    Anastasi, G., Conti, M., Francesco, M. D., & Passarella, A. (2009). Energy conservation in wireless sensor networks: A survey. Ad hoc Networks, 7(3), 537–568.CrossRefGoogle Scholar
  11. 11.
    Ghali, C., Schlosberg, M. A., Tsudik, G., & Wood, C. A. (2015). Interest-based access control for content centric networks. In Proceedings of the 2Nd ACM Conference on Information-Centric Networking, ACM-ICN ’15 (pp. 147–156), New York, NY, USA. ACM.Google Scholar
  12. 12.
    Dinh, N.-T., & Kim, Y. (2013). Potential of information-centric wireless sensor and actor networking. In International conference on computing, management and telecommunications (ComManTel) (pp. 163–168). IEEE.Google Scholar
  13. 13.
    Waltari, O., & Kangasharju, J. (2016). Content-centric networking in the internet of things. In 13th IEEE annual consumer communications & networking conference (CCNC) (pp 73–78). IEEE.Google Scholar
  14. 14.
    Tmote Sky Datasheet. (2017). Acessed November 22, 2017.
  15. 15.
    Amadeo, M., Campolo, C., Molinaro, A., & Mitton, N. (2013). Named data networking: A natural design for data collection in wireless sensor networks. In Wireless Days (WD), 2013 IFIP (pp. 1–6). IEEE.Google Scholar
  16. 16.
    Cheng, L., Jianwei Niu, Y. G., Luo, C., & He, T. (2016). Achieving efficient reliable flooding in low-duty-cycle wireless sensor networks. IEEE/ACM Transactions on Networking, 24(6), 3676–3689.CrossRefGoogle Scholar
  17. 17.
    Yu, G., & He, T. (2011). Dynamic switching-based data forwarding for low-duty-cycle wireless sensor networks. IEEE Transactions on Mobile Computing, 10(12), 1741–1754.CrossRefGoogle Scholar
  18. 18.
    Carrano, R. C., Passos, D., Magalhaes, L. C. S., & Albuquerque, C. V. N. (2014). Survey and taxonomy of duty cycling mechanisms in wireless sensor networks. IEEE Communications Surveys & Tutorials, 16(1), 181–194.CrossRefGoogle Scholar
  19. 19.
    Fayazbakhsh, S. K., Lin, Y., Tootoonchian, A., Ghodsi, A., Koponen, T., Maggs, B., Ng, K. C., Sekar, V., & Shenker, S. (2013). Less pain, most of the gain: Incrementally deployable icn. In Proceedings of the ACM SIGCOMM 2013 Conference on SIGCOMM, SIGCOMM ’13 (pp. 147–158), New York, NY, USA, ACM.Google Scholar
  20. 20.
    Wang, F., & Liu, J. (2012). On reliable broadcast in low duty-cycle wireless sensor networks. IEEE Transactions on Mobile Computing, 11(5), 767–779.CrossRefGoogle Scholar
  21. 21.
    Yadav, S. (2016). A review on energy efficient protocols in wireless sensor networks. Wireless Networks, 22(1), 335–350.CrossRefGoogle Scholar
  22. 22.
    Gao, S., Zhang, H., & Zhang, B. (2016). Energy efficient interest forwarding in NDN-based wireless sensor networks. Mobile Information Systems, 2016.Google Scholar
  23. 23.
    Baliga, J., Ayre, R., Hinton, K., & Tucker, R. S. (2009). Architectures for energy-efficient iptv networks. In Conference on optical fiber communication-incudes post deadline papers, 2009. OFC 2009 (pp 1–3). IEEE.Google Scholar
  24. 24.
    Che, H., Tung, Y., & Wang, Z. (2002). Hierarchical web caching systems: Modeling, design and experimental results. IEEE Journal on Selected Areas in Communications, 20(7), 1305–1314.CrossRefGoogle Scholar
  25. 25.
    Choi, Nakjung, G., Kyle, K., Daniel, C., & Atkinson, G. (2012). In-network caching effect on optimal energy consumption in content-centric networking. In IEEE international conference on communications (ICC), 2012 (pp. 2889–2894). IEEE.Google Scholar
  26. 26.
    Guan, K., Atkinson, G., Kilper, D. C., & Gulsen, E. (2011). On the energy efficiency of content delivery architectures. In IEEE international conference on communications workshops (ICC) (pp. 1–6). IEEE.Google Scholar
  27. 27.
    Guo, S., Kim, S. M., Zhu, T., Gu, Y., & He, T. (2011). Correlated flooding in low-duty-cycle wireless sensor networks. In 19th IEEE international conference on network protocols (ICNP), 2011 (pp. 383–392). IEEE.Google Scholar
  28. 28.
    NeocampusLabs. (2017). Accessed November 22, 2017.

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  • Ghada Jaber
    • 1
    Email author
  • Rahim Kacimi
    • 1
  • Luigi Alfredo Grieco
    • 1
  • Thierry Gayraud
    • 1
  1. 1.University Paul SabatierToulouseFrance

Personalised recommendations