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Erlang Based Buffer Management and Routing in Opportunistic Networks

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Abstract

In opportunistic networks the network’s topology is not connected due to the intermittent links. Thus, to deliver messages there is not a route between the source and destination node. To solve this problem in opportunistic networks, the routing and forwarding are carried out concurrently. In this approach, which is called store, carry-forward, the selection of the next node for message forwarding is based on the appropriateness of the next node to deliver the message. One of the most appropriate message routing and forwarding algorithms for opportunistic networks is spray and wait algorithm. The selection of the node encountered as the next relay and the number of tokens sent to the next node depend on factors such as the probability of message delivery, buffer status (the probability of message deletion), and the delivery time of the message. In most studies carried out, one of these factors has been effective in selecting the next node. In some others the number of tokens sent to relay node has followed a fixed function. This has resulted in the reduction of the ratio of delivery and it has increased delays. In this paper the proposed algorithm has considered the probability of message delivery, buffer status, and message delivery time concurrently in selecting the relay node and in allocation the tokens sent to the node. The results of simulation have shown that the proposed algorithm has improved the delivery ratio and the delay in delivering messages with a trivial overhead.

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References

  1. 1.

    Lersteau, C., Rossi, A., & Sevaux, M. (2016). Robust scheduling of wireless sensor networks for target tracking under uncertainty. European Journal of Operational Research,252(2), 407–417.

  2. 2.

    Huang, C.-M., Lan, K.-C., & Tsai, C.-Z. (2008). A survey of opportunistic networks. In 22nd international conference on advanced information networking and applications-workshops. AINAW 2008. New York: IEEE.

  3. 3.

    Liu, H., Yang, H., Wang, Y., Wang, B., & Gu, Y. (2015). CAR: Coding-aware opportunistic routing for unicast traffic in wireless mesh networks. Journal of Network and Systems Management,23(4), 1104–1124.

  4. 4.

    Keskin, M. E. (2017). A column generation heuristic for optimal wireless sensor network design with mobile sinks. European Journal of Operational Research,260(1), 291–304.

  5. 5.

    Wei, X., Wang, T., Tang, C., & Fan, J. (2016). Collaborative mobile jammer tracking in multi-hop wireless network. Future Generation Computer Systems,78, 1027–1039.

  6. 6.

    Vahdat, A., & Becker, D. (2000). Epidemic routing for partially connected ad hoc networks. Technical report CS-200006. Duke University.

  7. 7.

    Xie, L. F., Chong, P. H. J., & Guan, Y. L. (2013). Routing strategy in disconnected mobile ad hoc networks with group mobility. EURASIP Journal on Wireless Communications and Networking,2013(1), 1–12.

  8. 8.

    Psounis, K., & Raghavendra, C. S. (2004). Multiple-copy routing in intermittently connected mobile networks. Technical report CENG-2004-12, USC.

  9. 9.

    Spyropoulos, T., Psounis, K., & Raghavendra, C. S. (2005). Spray and wait: An efficient routing scheme for intermittently connected mobile networks. In Proceedings of the 2005 ACM SIGCOMM workshop on delay-tolerant networking. New York: ACM.

  10. 10.

    Shu, J., et al. (2010). RET: A random and encounter time based forwarding mechanism for opportunistic network. In 2010 3rd international symposium on information processing (ISIP). New York: IEEE.

  11. 11.

    Nelson, S. C., Bakht, M., & Kravets, R. (2009). Encounter-based routing in DTNs. In INFOCOM 2009, IEEE. New York: IEEE.

  12. 12.

    Dubois-Ferriere, H., Grossglauser, M., & Vetterli, M. (2003). Age matters: Efficient route discovery in mobile ad hoc networks using encounter ages. In Proceedings of the 4th ACM international symposium on mobile ad hoc networking and computing. New York: ACM.

  13. 13.

    Zhang, J., & Luo, G. (2012). Adaptive spraying for routing in delay tolerant networks. Wireless Personal Communications,66(1), 217–233.

  14. 14.

    Wang, K., & Guo, H. (2014). An improved routing algorithm based on social link awareness in delay tolerant networks. Wireless Personal Communications,75(1), 397–414.

  15. 15.

    Lindgren, A., Doria, A., & Schelén, O. (2003). Probabilistic routing in intermittently connected networks. ACM SIGMOBILE Mobile Computing and Communications Review,7(3), 19–20.

  16. 16.

    Kim, E.-H., et al. (2014). Probability-based spray and wait protocol in delay tolerant networks. In 2014 international conference on information networking (ICOIN). New York: IEEE.

  17. 17.

    Prodhan, A. T., et al. (2011). TTL based routing in opportunistic networks. Journal of Network and Computer Applications,34(5), 1660–1670.

  18. 18.

    Iqbal, S. M. A., & Chowdhury, A. K. (2012). Adaptation of spray phase to improve the binary spray and wait routing in delay tolerant networks. In 2012 15th international conference on computer and information technology (ICCIT).

  19. 19.

    Pan, D., et al. (2012). Buffer management and hybrid probability choice routing for packet delivery in opportunistic networks. Mathematical Problems in Engineering. https://doi.org/10.1155/2012/817528

  20. 20.

    Lee, C., & Kim, K. I. (2014). A deadline aware DTN approach based on epidemic routing. In 2014 IEEE 13th international symposium on network computing and applications (NCA). New York: IEEE.

  21. 21.

    Mergenci, C., & Korpeoglu, I. (2015). Routing in delay tolerant networks with periodic connections. EURASIP Journal on Wireless Communications and Networking,2015(1), 1–19.

  22. 22.

    Burgess, J., et al. (2006). MaxProp: Routing for vehicle-based disruption-tolerant networks. In INFOCOM.

  23. 23.

    Tibor, M., & Baroå, I. (2012). Packet loss probability estimation using Erlang B and M/G/1/K models in modern VoIP networks. IU-Journal of Electrical and Electronics Engineering.,12(2), 1483–1491.

  24. 24.

    Diagnostic Strategies. (2003). Traffic modeling and resource allocation in call centers. Needham, MA.

  25. 25.

    Keränen, A., Ott, J., & Kärkkäinen, T. (2009). The ONE simulator for DTN protocol evaluation. In Proceedings of the 2nd international conference on simulation tools and techniques. ICST (Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering).

  26. 26.

    Derakhshanfard, N., Sabaei, M., & Rahmani, A. M. (2017). CPTR: Conditional probability tree based routing in opportunistic networks. Wireless Networks, 23(1), 43–50.

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Correspondence to Nahideh Derakhshanfard.

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Derakhshanfard, N. Erlang Based Buffer Management and Routing in Opportunistic Networks. Wireless Pers Commun 110, 2165–2177 (2020). https://doi.org/10.1007/s11277-019-06835-8

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Keywords

  • Opportunistic network
  • Spray and wait
  • TTL based routing
  • Encounter time
  • Buffer management
  • Drop probability