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Mobility-based sinknode-aided routing in disaster network under the background of big data

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Abstract

Most routing protocols of delay and disruption tolerant Networking have become popular in disasters areas. However, the nodes’ mobility is limited due to the special requires in disaster scenario. In this paper, a novel mobility-based sinknode-aided routing scheme is proposed with a view to using the scheduled mobility model. Then, the extensive simulations on real traces are conducted in comparison with several existing approaches, including MaxProp, Prophet and so on. Finally, the results show the competitive performance of mobility-based sinknode-aided routing in disaster network, which proves the proposed MSR performs better than the other three existing routing schemes in some way. Therefore, the mobility patterns proposed will definitely play an important role in routing in disaster network.

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References

  1. Kim, Y.P., Nakano, K., Miyakita, K., et al.: A routing protocol for considering the time variant mobility model in delay tolerant network. Ieice Trans. Inf. Syst. 95(2), 451–461 (2012)

    Article  Google Scholar 

  2. Batheja, J., Parashar, M.: A framework for adaptive cluster computing using javaspaces. Cluster Comput. 6(3), 201–213 (2003)

    Article  Google Scholar 

  3. MartíN-Campillo, A., Crowcroft, J., Yoneki, E., Martí, R.: Evaluating opportunistic networks in disaster scenarios. J. Netw. Comput. Appl. 36, 870–880 (2013)

    Article  Google Scholar 

  4. Cassel, G., Eriksson, H., Sandström, B.: Mass-casualties and health care following the release of toxic chemicals or radioactive materials. Int. J. Environ. Res. Public Health 8, 4521 (2011)

    Article  Google Scholar 

  5. Sakanushi, K., Hieda, T., Shiraishi, T., et al.: Electronic triage system for continuously monitoring casualties at disaster scenes. J. Ambient Intell. Hum. Comput. 4(5), 547–558 (2013)

    Article  Google Scholar 

  6. MartíN-Campillo, A., Crowcroft, J., Yoneki, E., Martí, R.: Evaluating opportunistic networks in disaster scenarios. J. Netw. Comput. Appl. 2013(36), 870–880 (2013)

    Article  Google Scholar 

  7. Ye, Q., Cheng, L., Chuah, M.C., Davison, B.D.: Performance comparison of different multicast routing strategies in disruption tolerant networks. Comput. Commun. 32, 1731–1741 (2009)

    Article  Google Scholar 

  8. Wittie, M.P., Harras, K.A., Almeroth, K.C., Belding, E.M.: On the implications of routing metric staleness in delay tolerant networks. Comput. Commun. 32, 1699–1709 (2009)

    Article  Google Scholar 

  9. Martí, R., Robles, S., Martín-Campillo, A., Cucurull, J.: Providing early resource allocation during emergencies: the mobile triage tag. J. Netw. Comput. Appl. 32, 1167–1182 (2009)

    Article  Google Scholar 

  10. Rizk, R., Nashaat, H.: Smart prediction for seamless mobility in F-HMIPv6 based on location based services. Ksii Trans. Internet Inf. Syst. 9(12), 5028–5057 (2016)

    Google Scholar 

  11. Brown, C., Nicosia, V., Scellato, S., et al.: Social and place-focused communities in location-based online social networks. Phys. Condens. Matter 86(6), 1–10 (2013)

    Google Scholar 

  12. Wei, K., Zeng, D., Guo, S., et al.: On social delay-tolerant networking: aggregation, tie detection, and routing. IEEE Trans. Parallel Distrib. Syst. 25(6), 1563–1573 (2014)

    Article  Google Scholar 

  13. Cabaniss, R., Vulli, S.S., Madria, S.: Social group detection based routing in delay tolerant networks. Wirel. Netw. 19(8), 1979–1993 (2013)

    Article  Google Scholar 

  14. Eaglea, N., Pentlandb, A.S., Lazerc, D.: Inferring friendship network structure by using mobile phone data. PNAS 106, 15274–15278 (2009)

    Article  Google Scholar 

  15. Eagle, N., Pentland, A.S.: Eigenbehaviors: identifying structure in routine. Behav. Ecol. Sociobiol. 63, 1057–1066 (2009)

    Article  Google Scholar 

  16. Tang, L., Liu, H.: Community Detection and Mining in Social Media, pp. 11–15. China machine press, Beijing (2013)

    Google Scholar 

  17. Backstrom, L., Dwork, C., Kleinberg, J.: Wherefore art thou R3579X? Commun. ACM 54(12), 181–190 (2011)

    Article  Google Scholar 

  18. Watkins, J., Kitner, K.R., Mehta, Dina: Mobile and smartphone use in urban and rural India. Continuum 26(5), 685–697 (2012)

    Article  Google Scholar 

  19. Ye, J., Xu, Z., Ding, Y.: Secure outsourcing of modular exponentiations in cloud and cluster computing. Cluster Comput. 19(2), 811–820 (2016)

    Article  Google Scholar 

  20. Lindgren, A., Doria, A., Schelén, O.: Probabilistic routing in intermittently connected networks. ACM SIGMOBILE Mob. Comput. Commun. Rev. 7, 19–20 (2003)

    Article  Google Scholar 

  21. Aschenbruck, N., Gerhards-Padilla, E., Martini, P.: Modeling mobility in disaster area scenarios. Perform. Eval. 66(12), 773–790 (2009)

    Article  Google Scholar 

  22. Su, C.J.: A binary relation inference network for constrained optimization. Dissertation, University of British Columbia, Vancouver (1992)

  23. Wang, J.: A recurrent neural network for solving the shortest path problem. IEEE Trans. Circuits Syst. I 43, 482–486 (1996)

    Article  Google Scholar 

  24. Schurgot, M.R., Comaniciu, C., Jaffres-Runser, K.: Beyond traditional DTN routing: social networks for opportunistic communication. IEEE Commun. Mag. 50, 155–162 (2012)

    Article  Google Scholar 

  25. Henmi, K., Koyama, A.: An enhanced spray and wait DTN routing protocol based on node mobility and maximum number of replications. Int. J. Adapt. Innov. Syst. 2(1), 3–14 (2014)

    Article  Google Scholar 

  26. Hui, P., Crowcroft, J., Yoneki, E.: BUBBLE rap: social-based forwarding in delay-tolerant networks. IEEE Trans. Mob. Comput. 10(11), 1576–1589 (2011)

    Article  Google Scholar 

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Acknowledgements

The authors declare that there is no conflict of interests regarding the publication of this article. Research was sponsored by the National Natural Science Foundation of China under Grant Number 61272412; Jilin province science and technology development plan Item Number 20120303.

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Authors and Affiliations

  1. College of Computer Science and Technology, Jilin University, Changchun, 130012, Jilin, China

    Chuang Ma & Yongjian Yang

  2. Syracuse University, New York, NY, 13244, USA

    C. Ma

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  1. Chuang Ma
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  2. Yongjian Yang
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Correspondence to Chuang Ma.

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Ma, C., Yang, Y. & Ma, C. Mobility-based sinknode-aided routing in disaster network under the background of big data. Cluster Comput 22 (Suppl 5), 11583–11590 (2019). https://doi.org/10.1007/s10586-017-1423-1

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