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Optimal Energy Efficiency Data Dissemination Strategy Based on Optimal Stopping Theory in Mobile Network

  • Gaocai Wang
  • Ying Peng
  • Qifei Zhao
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11280)

Abstract

Data dissemination application has become popular in mobile networks, which made energy consumed by mobile terminals growing rapidly. It is becoming an important research topic to reduce energy consumption for data dissemination in mobile networks. This paper studies the energy consumption optimization problem in mobile networks with Time-Varying channel quality, when multiple sending terminals use the same channel for data dissemination. Sending terminal transmits data with a certain probability for competing channel. After getting channel successfully, the sending terminal decides whether to distribute data according to channel quality, thereby saving energy. The maximization problem of average energy efficiency for distributing data with delay demand is constructed firstly in this paper. Then this maximization problem is transformed into an optimal stopping rule problem, and the optimal myopic stopping rule is obtained. Finally, the optimal transmission rate thresholds at each period are solved by optimal stopping theory, and then the optimal energy efficiency data dissemination strategy based on optimal stopping theory is realized. Simulation results show that the strategy proposed in this paper has bigger average energy efficiency and higher average delivery than other strategies, and achieves better energy optimization effect and network performance.

Keywords

Mobile networks Data dissemination Optimal energy efficiency Optimal stopping Optimal rate 

References

  1. 1.
    Garcia-Saavedra, A., Serrano, P., Banchs, A.: Energy-efficient optimization for distributed opportunistic scheduling. IEEE Commun. Lett. 18(6), 1083–1086 (2014)CrossRefGoogle Scholar
  2. 2.
    Antonopoulos, A., Verikoukis, C.: Multi-player game theoretic MAC strategies for energy efficient data dissemination. IEEE Trans. Wirel. Commun. 13(2), 592–603 (2014)CrossRefGoogle Scholar
  3. 3.
    Chen, P.Y., Cheng, S.M., Chen, K.C.: Optimal control of epidemic information dissemination over networks. IEEE Trans. Cybern. 44(12), 2316–2328 (2014)MathSciNetCrossRefGoogle Scholar
  4. 4.
    Peng, Y., Wang, G., Huang, S., et al.: An energy consumption optimization strategy for data transmission based on optimal stopping theory in mobile networks. Chin. J. Comput. 39(6), 1162–1175 (2016). (in Chinese)MathSciNetGoogle Scholar
  5. 5.
    Peng, Y., Wang, G., Wang, N., et al.: Energy consumption optimization strategy for data transmission based on data arrival rate in mobile networks. Comput. Sci. 44(1), 117–122 (2017). (in Chinese)MathSciNetGoogle Scholar
  6. 6.
    Chen, H., Baras, J.S.: Distributed opportunistic scheduling for wireless ad-hoc networks with block-fading model. IEEE J. Sel. Areas Commun. 31(11), 2324–2337 (2013)CrossRefGoogle Scholar
  7. 7.
    Zheng, D., Ge, W.Y., Zhang, J.S.: Distributed opportunistic scheduling for ad hoc networks with random access: an optimal stopping approach. IEEE Trans. Inf. Theor. 55(1), 205–222 (2009)MathSciNetCrossRefGoogle Scholar
  8. 8.
    Yan, T., Zhang, W., Wang, G.: DOVE: data dissemination to a desired number of receivers in VANET. IEEE Trans. Veh. Technol. 63(4), 1903–1916 (2014)CrossRefGoogle Scholar
  9. 9.
    Li, J., Chen, Y., Lin, Z., et al.: Distributed caching for data dissemination in the downlink of heterogeneous networks. IEEE Trans. Commun. 63(10), 3553–3568 (2015)CrossRefGoogle Scholar
  10. 10.
    Li, Y., Zhu, X., Jin, D.: Multiple content dissemination in roadside-unit-aided vehicular opportunistic networks. IEEE Trans. Veh. Technol. 63(8), 3947–3956 (2014)CrossRefGoogle Scholar
  11. 11.
    Ferguson, T.S.: Optimal Stopping and Applications. http://www.math.ucla.edu/~tom/Stopping/Contents.html. Accessed 29 June 2018

Copyright information

© Springer Nature Switzerland AG 2018

Authors and Affiliations

  1. 1.Guangxi UniversityNanningChina

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