Advertisement

Tandem Networks with Intermittent Energy

  • Yasin Murat Kadioglu
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 935)

Abstract

Energy harvesting may be needed to operate digital devices in locations where connecting them to the power grid and changing batteries is difficult. However, energy harvesting is often intermittent resulting in a random flow of energy into the device. It is then necessary to analyse systems where both the workload, and the energy supply, must be represented by random processes. Thus, in this paper, we consider a multi-hop tandem network where each hop receives energy locally in a random process, and packets arrive at each of the nodes and then flow through the multi-hop connection to the sink. We present a product-form solution for this N-hop tandem network when both energy is represented by discrete entities, and data is in the form of discrete packets.

Keywords

Tandem networks Energy packet network Renewable energy 

References

  1. 1.
    Gelenbe, E., Caseau, Y.: The impact of information technology on energy consumption and carbon emissions. Ubiquity 2015(June), 1 (2015)CrossRefGoogle Scholar
  2. 2.
    Rodoplu, V., Meng, T.H.: Bits-per-joule capacity of energy-limited wireless networks. IEEE Trans. Wireless Commun. 6(3) (2007)CrossRefGoogle Scholar
  3. 3.
    Gelenbe, E.: Energy packet networks: ICT based energy allocation and storage. In: Rodrigues, J.J.P.C., Zhou, L., Chen, M., Kailas, A. (eds.) GreeNets 2011. LNICST, vol. 51, pp. 186–195. Springer, Heidelberg (2012).  https://doi.org/10.1007/978-3-642-33368-2_16CrossRefGoogle Scholar
  4. 4.
    Gelenbe, E.: Synchronising energy harvesting and data packets in a wireless sensor. Energies 8(1), 356–369 (2015)CrossRefGoogle Scholar
  5. 5.
    Kadioglu, Y.M.: Finite capacity energy packet networks. Probab. Eng. Inf. Sci. 31(4), 477–504 (2017)MathSciNetCrossRefGoogle Scholar
  6. 6.
    Kadioglu, Y.M., Gelenbe, E.: Packet transmission with k energy packets in an energy harvesting sensor. In: Proceedings of the 2nd International Workshop on Energy-Aware Simulation, p. 1. ACM (2016)Google Scholar
  7. 7.
    Kadioglu,Y.M., Gelenbe, E.: Wireless sensor with data and energy packets. In: 2017 IEEE International Conference on Communications Workshops (ICC Workshops), pp. 564–569. IEEE (2017)Google Scholar
  8. 8.
    Gelenbe, E., Marin, A.: Interconnected wireless sensors with energy harvesting. In: Gribaudo, M., Manini, D., Remke, A. (eds.) ASMTA 2015. LNCS, vol. 9081, pp. 87–99. Springer, Cham (2015).  https://doi.org/10.1007/978-3-319-18579-8_7CrossRefGoogle Scholar
  9. 9.
    Dallery, Y., Gershwin, S.B.: Manufacturing flow line systems: a review of models and analytical results. Queueing Syst. 12(1–2), 3–94 (1992)CrossRefGoogle Scholar
  10. 10.
    Ramaswami, S.: Optical Networks: A practical Perspective, 2nd edn. Academic Press (2002)Google Scholar
  11. 11.
    Balsamo, S., Harrison, P.G., Marin, A.: Methodological construction of product-form stochastic petri nets for performance evaluation. J. Syst. Softw. 85(7), 1520–1539 (2012)CrossRefGoogle Scholar
  12. 12.
    Marin, A., Balsamo, S., Harrison, P.G.: Analysis of stochastic petri nets with signals. Perform. Eval. 69(11), 551–572 (2012)CrossRefGoogle Scholar
  13. 13.
    Kadioglu, Y.M., Gelenbe, E.: Product form solution for cascade networks with intermittent energy. IEEE Syst. J. (2018). Accepted for publicationGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2018

Authors and Affiliations

  1. 1.Intelligent Systems and Networks Group, Electrical and Electronic Engineering DepartmentImperial CollegeLondonUK

Personalised recommendations