Advertisement

Distributed Coordination Protocols for Wireless Charging in Sensor Networks

  • Adelina MadhjaEmail author
  • Sotiris Nikoletseas
  • Theofanis P. Raptis
Chapter

Abstract

In this chapter, we investigate the problem of efficient wireless power transfer in wireless sensor networks where special mobile entities called Mobile Chargers, traverse the network and wirelessly replenish the energy of sensor nodes. The methods we present are distributed and use limited network information. More specifically, we propose four new protocols for efficient wireless charging while addressing key issues such as the identification of what are good coordination procedures and what are good trajectories for the Mobile Chargers. Two of our protocols (DC, DCLK) perform distributed, limited network knowledge coordination and charging, while two others (CC, CCGK) perform centralized, global network knowledge coordination and charging. As detailed simulations demonstrate, one of our distributed protocols outperforms a known state-of-the-art method, while its performance gets quite close to the performance of the powerful centralized global knowledge method.

Keywords

Sensor Network Sensor Node Wireless Sensor Network Network Knowledge Mobile Charger 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

References

  1. 1.
  2. 2.
    Angelopoulos, C.M., Nikoletseas, S., Raptis, T.P.: Wireless energy transfer in sensor networks with adaptive, limited knowledge protocols. Comput. Netw. 70, 113–141 (2014)CrossRefGoogle Scholar
  3. 3.
    Angelopoulos, C.M., Nikoletseas, S., Raptis, T.P., Raptopoulos, C., Vasilakis, F.: Improving sensor network performance with wireless energy transfer. Int. J. Ad Hoc Ubiquitous Comput. (2014). Inderscience PublishersGoogle Scholar
  4. 4.
    Dai, H., Wu, X., Xu, L., Chen, G., Lin, S.: Using minimum mobile chargers to keep large-scale wireless rechargeable sensor networks running forever. In: Proceedings of the 22nd International Conference on Computer Communications and Networks (ICCCN), pp. 1–7 (2013)Google Scholar
  5. 5.
    Efstathiou, D., Koutsopoulos, A., Nikoletseas, S.: Analysis and simulation for parameterizing the energy-latency trade-off for routing in sensor networks. In: Proceedings of the 13th ACM International Conference on Modeling, Analysis and Simulation of Wireless and Mobile Systems (MSWiM) (2010)Google Scholar
  6. 6.
    Garey, M.R., Johnson, D.S.: Computers and intractability. W. H. Freeman and Company (1979)Google Scholar
  7. 7.
    Gnawali, O., Fonseca, R., Jamieson, K., Moss, D., Levis, P.: Collection tree protocol. In: Proceedings of the 7th ACM Conference on Embedded Networked Sensor Systems (SenSys) (2009)Google Scholar
  8. 8.
    Gupta, P., Kumar, P.: Critical power for asymptotic connectivity in wireless networks. In: Stochastic Analysis, Control, Optimization and Applications (1998)Google Scholar
  9. 9.
    He, L., Cheng, P., Gu, Y., Pan, J., Zhu, T., Liu, C.: Mobile-to-mobile energy replenishment in mission-critical robotic sensor networks. In: Proceedings of the 33rd IEEE International Conference on Computer Communications (INFOCOM) (2014)Google Scholar
  10. 10.
    Li, J., Wang, C., Ye, F., Yang, Y.: Netwrap: An NDN based real time wireless recharging framework for wireless sensor networks. In: Proceedings of the 10th IEEE International Conference on Mobile Ad-Hoc and Sensor Systems (MASS), pp. 173–181 (2013)Google Scholar
  11. 11.
    Peng, Y., Li, Z., Zhang, W., Qiao, D.: Prolonging sensor network lifetime through wireless charging. In: Proceedings of the 31st IEEE Real-Time Systems Symposium (RTSS) (2010)Google Scholar
  12. 12.
    Penrose, M.: Random Geometric Graphs. Oxford University Press (2003)Google Scholar
  13. 13.
    Shi, Y., Xie, L., Hou, Y.T., Sherali, H.D.: On renewable sensor networks with wireless energy transfer. In: Proceedings of the 30th IEEE International Conference on Computer Communications (INFOCOM) (2011)Google Scholar
  14. 14.
    Tanenbaum, A.: Modern Operating Systems, 3rd edn. Prentice Hall (2007)Google Scholar
  15. 15.
    Wang, C., Li, J., Ye, F., Yang, Y.: Multi-vehicle coordination for wireless energy replenishment in sensor networks. In: Proceedings of the 27th IEEE International Parallel & Distributed Processing Symposium (IPDPS) (2013)Google Scholar
  16. 16.
    Wang, C., Li, J., Ye, F., Yang, Y.: Recharging schedules for wireless sensor networks with vehicle movement costs and capacity constraints. In: Proceedings of the 11th IEEE International Conference on Sensing, Communication, and Networking (SECON), pp. 468–476. IEEE (2014)Google Scholar
  17. 17.
    Xie, L., Shi, Y., Hou, Y.T., Lou, W., Sherali, H.D., Midkiff, S.F.: Bundling mobile base station and wireless energy transfer: Modeling and optimization. In: Proceedings of the 32nd IEEE International Conference on Computer Communications (INFOCOM) (2013)Google Scholar
  18. 18.
    Zhang, S., Wu, J., Lu, S.: Collaborative mobile charging for sensor networks. In: Proceedings of the 9th IEEE International Conference on Mobile Ad-Hoc and Sensor Systems (MASS) (2012)Google Scholar

Copyright information

© Springer International Publishing AG 2016

Authors and Affiliations

  • Adelina Madhja
    • 1
    Email author
  • Sotiris Nikoletseas
    • 1
  • Theofanis P. Raptis
    • 1
    • 2
  1. 1.Department of Computer Engineering and InformaticsUniversity of Patras and Computer Technology Institute and Press “Diophantus” (CTI)PatrasGreece
  2. 2.Institute of Informatics and TelematicsNational Research CouncilPisaItaly

Personalised recommendations