Nothing Special   »   [go: up one dir, main page]

Skip to main content

Advertisement

Log in

An energy-aware deadline-constrained message delivery in delay-tolerant networks

  • Published:
Wireless Networks Aims and scope Submit manuscript

Abstract

In order to understand the message dissemination performance in delay-tolerant networks, much analysis work has been proposed in literature. However, existing work shares a common simplification that the pairwise inter-meeting time between any two mobile nodes is exponentially distributed. Not mention the fact that such assumption is only an approximation, it cannot be applied by network planners to directly control the mobile nodes for any network optimization, e.g., energy efficiency. It is quite significant to study the relationship between the network performance with the parameters that can be adjusted directly to tackle the limitations of current exponential distribution assumption based analysis. Therefore, in this paper, we are motivated to jointly consider the transmission range and messages residence time to stochastically analyze deadline-constrained message delivery ratio utilizing a controlled epidemic routing. The message propagation is considered as an age-structure process and described by a susceptible–infectious–recovered model, which is then analyzed using delay differential equations. Since both the transmission range and the message residence time are related to the mobile nodes’ energy consumption, we further apply our analysis framework to investigate the tradeoff between the energy consumption and the achievable message delivery ratio. The correctness and accuracy of our analysis are validated by extensive simulations.

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

Access this article

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8

Similar content being viewed by others

References

  1. Daly, M. E. M. (2007). Social network analysis for routing in disconnected delay-tolerant MANETs. In Proceedings of the 8th ACM International Symposium on Mobile Ad Hoc Networking and Computing (Mobihoc ’07) (pp. 32–40). ACM.

  2. Zhang, X., Neglia, G., Kurose, J., & Towsley, D. (2007). Performance modeling of epidemic routing. Computer Networks, 51(10), 2867–2891.

    Article  MATH  Google Scholar 

  3. Lin, Y., Li, B., & Liang, B. (2008). Stochastic analysis of network coding in epidemic routing. IEEE Journal on Selected Areas in Communications, 26(5), 794–808.

    Article  Google Scholar 

  4. Islam, M., Akon, M., Abdrabou, A., & Shen, X. (2011, December). Modeling epidemic data diffusion for wireless mobile networks. In Proceedings of the 54th Annual IEEE Global Telecommunications Conference (GLOBECOM ’11) (pp. 1–5).

  5. Khouzani, M., Eshghi, S., Sarkar, S., Shroff, N., & Venkatesh, S. (2012). Optimal energy-aware epidemic routing in DTNs. In Proceedings of the 13th ACM International Symposium on Mobile Ad Hoc Networking and Computing (Mobihoc ’12) (pp. 175–182). ACM.

  6. Zeng, D., Cong, L., Huang, H., Guo, S., & Yao, H. (2012). Deadline-constrained content distribution in vehicular delay tolerant networks. In Proceedings of the 8th International Wireless Communications and Mobile Computing Conference (IWCMC ’12) (pp. 994–999). IEEE.

  7. Zou, Z., Soldati, P., Zhang, H., & Johansson, M. (2012). Energy-efficient deadline-constrained maximum reliability forwarding in lossy networks. IEEE Transactions on Wireless Communications, 11(10), 3474–3483.

    Article  Google Scholar 

  8. Abdulla, M., & Simon, R. (2008). Controlled epidemic routing for multicasting in delay tolerant networks. In IEEE International Symposium on Modeling, Analysis and Simulation of Computers and Telecommunication Systems (MASCOTS ’08) (pp. 1–10). IEEE.

  9. Zhang, Z., Mao, G., & Anderson, B. (2011). On the information propagation in mobile ad-hoc networks using epidemic routing. In Proceedings of the 54th Annual IEEE Global Telecommunications Conference (GLOBECOM ’11) (pp. 1–6).

  10. Groenevelt, R., Nain, P., & Koole, G. (2005). The message delay in mobile ad hoc networks. Performance Evaluation, 62(1), 210–228.

    Article  Google Scholar 

  11. Britton, T. (2010). Stochastic epidemic models: A survey. Mathematical Biosciences, 225(1), 24–35.

    Article  MathSciNet  MATH  Google Scholar 

  12. Zhang, Z., Mao, G., & Anderson, B. (2012). On information dissemination in infrastructure-based mobile ad-hoc networks. In Proceedings of IEEE Wireless Communications and Networking Conference (WCNC ’12) (pp. 1743–1748). IEEE.

  13. Erneux, T. (2009). Applied delay differential equations. In: Surveys and tutorials in the applied mathematical sciences (Vol. 3). New York: Springer.

  14. Bortz, D. (2012). Eigenvalues for two-lag linear delay differential equations. arXiv, preprintarXiv:1206.6364.

  15. Nelson, P. W., & Perelson, A. S. (2002). Mathematical analysis of delay differential equation models of HIV-1 infection. Mathematical Biosciences, 179(1), 73–94.

    Article  MathSciNet  MATH  Google Scholar 

  16. Forde, J. (2005). Delay differential equation models in mathematical biology. Ph.D. dissertation, The University of Michigan.

  17. Wu, K., & Ding, X. (2012). Impulsive stabilization of delay difference equations and its application in Nicholson’s blowflies model. Advances in Difference Equations, 2012(1), 1–11.

    Article  MATH  Google Scholar 

  18. Keung, G., Li, B., Zhang, Q., & Yang, H.-D. (2011, December). The target tracking in mobile sensor networks. In Proceedings of the 54th Annual IEEE Global Telecommunications Conference (GLOBECOM ’11) (pp. 1–5).

  19. Zeng, D., Guo, S., Li, Z., & Lu, S. (2010). Performance evaluation of network coding in disruption tolerant networks. In Proceedings of the Second Asia-Pacific Symposium on Internetware (p. 12). ACM.

  20. Zeng, D., Guo, S., Jin, H., & Leung, V. (2012, June). Dynamic segmented network coding for reliable data dissemination in delay tolerant networks. In Proceedings of the 2012 IEEE International Conference on Communications (ICC ’12). IEEE.

  21. Zeng, D., Guo, S., Jin, H., & Leung, V. (2011, December). Segmented network coding for stream-like applications in delay tolerant networks. In Proceedings of the 2011 IEEE Global Telecommunications Conference (GLOBECOM ’11) (pp. 1–5). IEEE.

  22. Li, Z., Zeng, D., Guo, S., Lu, S., Chen, D., & Zhuang, W. (2012). On the throughput of feedbackless segmented network coding in delay tolerant networks. Wireless Communications Letters, IEEE, 1(2), 93–96.

    Article  Google Scholar 

  23. Shebli, F., Dayoub, I., & Rouvaen, J. (2007). Minimizing energy consumption within wireless sensors network. Ubiquitous Computing and Communication Journal (UBICC), Special Issue on Ubiquitous Sensor Networks, 2, 19–24.

    Google Scholar 

  24. Murali, P., Challa, A., Kasyap, M., & Hota, C. (2010). A generalized energy consumption model for wireless sensor networks. In Proceedings of International Conference on Computational Intelligence and Communication Networks (CICN ’10) (pp. 210–213). IEEE.

  25. Wang, Q., Hempstead, M., & Yang, W. (2006). A realistic power consumption model for wireless sensor network devices. In Proceedings of the 3rd Annual IEEE Communications Society on Sensor and Ad Hoc Communications and Networks (SECON ’06) (Vol. 1, pp. 286–295). IEEE.

  26. Wang, Q., & Yang, W. (2007). Energy consumption model for power management in wireless sensor networks. In Proceedings of the 4th Annual IEEE Communications Society Conference on Sensor, Mesh and Ad Hoc Communications and Networks (SECON’07) (pp. 142–151). IEEE.

  27. Yang, K., Wu, Y., & Zhou, H. (2010). Research of optimal energy consumption model in wireless sensor network. In Proceedings of the 2nd International Conference on Computer Engineering and Technology (ICCET ’10) (Vol. 7, pp. 421–424). IEEE.

  28. Zhu, J., Qiao, C., & Wang, X. (2006). On accurate energy consumption models for wireless ad hoc networks. Wireless Communications, IEEE Transactions on, 5(11), 3077–3086.

    Article  Google Scholar 

  29. Huang, H., Zeng, D., Guo, S., Yao, H., & Miyazaki, T. (2013). Stochastic analysis on epidemic dissemination of lifetime-controlled messages in DTNs. In 2013 9th International Wireless Communications and Mobile Computing Conference (IWCMC ’13) (pp. 1578–1583). IEEE.

  30. Camp, T., Boleng, J., & Davies, V. (2002). A survey of mobility models for ad hoc network research. Wireless Communications and Mobile Computing, 2(5), 483–502.

    Article  Google Scholar 

  31. Das Sarma, A., Molla, A., & Pandurangan, G. (2012). Near-optimal random walk sampling in distributed networks. In Proceedings of the 31st Annual Conference of the IEEE Computer and Communications (INFOCOM ’12) (pp. 2906–2910). IEEE.

  32. Jun, J., Fu, W., & Agrawal, D. (2011). Average delay analysis of opportunistic single copy delivery in manhattan area using biased random walk. In Proceedings of the 30th Annual Conference of the IEEE Computer and Communications Workshops (INFOCOM WKSHPS ’11) (pp. 566–571). IEEE.

  33. Zeng, Y., Cao, J., Zhang, S., Guo, S., & Xie, L. (2010). Random-walk based approach to detect clone attacks in wireless sensor networks. IEEE Journal on Selected Areas in Communications, 28(5), 677–691.

    Article  Google Scholar 

  34. Cai, L., & Lu, Y. (2004). Dynamic power management using data buffers. In Proceedings of the Conference on Design, Automation and Test in Europe (Vol. 1, p. 10526). IEEE Computer Society.

  35. Li, L., Kadayif, I., Tsai, Y.-F., Vijaykrishnan, N., Kandemir, M., Irwin, M. J., et al. (2002). Leakage energy management in cache hierarchies. In Proceedings 2002 International Conference on Parallel Architectures and Compilation Techniques. (PACT ’02) (pp. 131–140). IEEE.

  36. Dropsho, S., Kursun, V., Albonesi, D. H., Dwarkadas, S., & Friedman, E. G. (2002). Managing static leakage energy in microprocessor functional units. In Proceedings of 35th Annual IEEE/ACM International Symposium on Microarchitecture (MICRO ’02) (pp. 321–332). IEEE.

  37. Gayasen, A., Tsai, Y., Vijaykrishnan, N., Kandemir, M., Irwin, M., & Tuan, T. (2004). Reducing leakage energy in FPGAs using region-constrained placement. In Proceedings of the 12th International Symposium on ACM/SIGDA Field Programmable Gate Arrays, (FPGA ’04) (pp. 51–58). ACM.

  38. Stauffer, D., & Aharony, A. (1994). Introduction to percolation theory. Boca Raton: CRC Press.

    Google Scholar 

Download references

Acknowledgments

This research was supported in part by the NSF of China (Grant No.61272470); the Fundamental Research Funds for the Central Universities, China University of Geosciences (Wuhan) (Grant No. CUG140615, CUG120114).

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Deze Zeng.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Yao, H., Huang, H., Zeng, D. et al. An energy-aware deadline-constrained message delivery in delay-tolerant networks. Wireless Netw 20, 1981–1993 (2014). https://doi.org/10.1007/s11276-014-0720-3

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11276-014-0720-3

Keywords

Navigation