Open Access
Issue
MATEC Web Conf.
Volume 232, 2018
2018 2nd International Conference on Electronic Information Technology and Computer Engineering (EITCE 2018)
Article Number 01036
Number of page(s) 5
Section Network Security System, Neural Network and Data Information
DOI https://doi.org/10.1051/matecconf/201823201036
Published online 19 November 2018
  1. Wu, Y., S. Deng, and H. Huang, Performance analysis of hop‐limited epidemic routing in DTN with limited forwarding times. International Journal of Communication Systems, 2015. 28(15): p. 2035-2050. [CrossRef] [Google Scholar]
  2. Lau, G., et al., Context-aware RAON middleware for opportunistic network. Pervasive & Mobile Computing, 2017. 41. [CrossRef] [Google Scholar]
  3. Dede, J., et al., Simulating Opportunistic Networks: Survey and Future Directions. IEEE Communications Surveys & Tutorials, 2017. [Google Scholar]
  4. Cuka, M., et al., Implementation and performance evaluation of two fuzzy-based systems for selection of IoT devices in opportunistic networks. Journal of Ambient Intelligence and Humanized Computing, 2018: p. 1-11. [Google Scholar]
  5. Kaur, S., A Review of Energy Consumption on DTN Routing Protocols. [Google Scholar]
  6. Dou, Y., F. Zeng, and W. Li. Energy-Efficient Contact Detection Model in Mobile Opportunistic Networks. in International Conference on Wireless Algorithms, Systems, and Applications. 2017. Springer. [Google Scholar]
  7. Choi, B.J. and X. Shen, Adaptive Asynchronous Sleep Scheduling Protocols for Delay Tolerant Networks. 2011: IEEE Educational Activities Department. 1283-1296. [Google Scholar]
  8. Chumchu, P., An extension to IEEE 802.11 power save mode for NS-3. 2015: p. 799-804. [Google Scholar]
  9. Zeng, F., et al., Efficient Listening and Sleeping Scheduling Mechanism Based on Self-Similarity for Duty Cycle Opportunistic Mobile Networks. Information, 2017. 8(3): p. 87. [CrossRef] [Google Scholar]
  10. Li, Y., et al. Optimal Opportunistic Forwarding Policies for Energy-Constrained Delay Tolerant Networks. in IEEE International Conference on Communications. 2010. [Google Scholar]
  11. Li, Y., et al. Performance Evaluation of Routing Schemes for Energy-Constrained Delay Tolerant Networks. in IEEE International Conference on Communications. 2012. [Google Scholar]
  12. Tan, D.N., et al. Mobile charging and data gathering in multiple sink Wireless Sensor Networks: How and why. in International Conference on System Science and Engineering. 2017. [Google Scholar]
  13. Keränen, A., J. Ott, and T. Kärkkäinen. The ONE simulator for DTN protocol evaluation. in International Conference on Simulation TOOLS and Techniques. 2009. [Google Scholar]
  14. Luo, G., et al., Exploiting intercontact time for routing in delay tolerant networks. European Transactions on Telecommunications, 2013. 24(6): p. 589–599. [CrossRef] [Google Scholar]
  15. Bonomi, S., et al. FAROES: Fairness And Reliability using Overlay Expenseless Set-out for duty-cycle optimization in WSN. 2011. [Google Scholar]
  16. Aliouat, Z. and Z. Aliouat. Improved WSN Life Time Duration through Adaptive Clustering, Duty Cycling and Sink Mobility. in International Conference on Information Management and Engineering. 2016. [Google Scholar]
  17. Ringwald, M. and K. Romer. Practical time synchronization for Bluetooth Scatternets. in International Conference on Broadband Communications, Networks and Systems, 2007. Broadnets. 2007. [Google Scholar]
  18. Wâhslén, J., I. Orhan, and T. Lindh. Local Time Synchronization in Bluetooth Piconets for Data Fusion Using Mobile Phones. in International Conference on Body Sensor Networks. 2011. [Google Scholar]

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