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New Trends in Mobility Modelling and Handover Prediction

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Wireless Networking for Moving Objects

Abstract

A wireless network may include fixed nodes and mobile nodes that change the location during data transmission. The node mobility influences heavily the operation of a wireless network, as the signal propagation conditions depend on the location of the nodes and may cause dramatic changes in the data transmission rates and packet error rates. Because the network performance is influenced by the location and signal propagation conditions between network nodes, accurate representation of the user mobility in the wireless network analysis is a crucial element in both simulation and numerical or analytical modelling. This chapter discusses mobility models used in simulating network behaviour. Further, the handover optimization and prediction are discussed, along with alternative methods of radio signal propagation changes caused by client mobility.

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References

  1. Ali, T., Saquib, M., Sengupta, C.: Vertical handover analysis for voice over WLAN/cellular network. In: Proceedings of the IEEE International Conference on Communications, pp. 1–5 (2010)

    Google Scholar 

  2. Atkinson, R.P.D., Rhodes, C.J., Macdonald, D.W., Anderson, R.M.: Scale-free dynamics in the movement patterns of jackals. OIKOS 98(1), 134–140 (2002)

    Article  Google Scholar 

  3. Bai, F., Helmy, A.: A survey of mobility models. Wireless Adhoc Networks, vol. 206. University of Southern California, USA (2004)

    Google Scholar 

  4. Barabási, A.L.: The origin of bursts and heavy tails in human dynamics. Nature 435, 207–211 (2005)

    Article  Google Scholar 

  5. Bettstetter, C.: Mobility modelling in wireless networks: categorization, smooth movement, and border effects. ACM SIGMOBILE Mob. Comput. Commun. Rev. 5(3), 55–66 (2001)

    Article  Google Scholar 

  6. Bettstetter, C., Hartenstein, H., Perez-Costa, X.: Stochastic properties of the random waypoint mobility model. ACM/Kluwer Wirel. Netw. (Special Issue on Modelling and Analysis of Mobile Networks) 10(5), 555–567 (2004)

    Google Scholar 

  7. Bettstetter, C., Wagner, C.: The spatial node distribution of the random waypoint mobility model. In: Proceedings of WMAN, Ulm, pp. 41–58 (2002)

    Google Scholar 

  8. Birand, B., Zafer, M., Zussman, G., Lee, K.-W.: Dynamic graph properties of mobile networks under Lévy walk mobility. In: IEEE 8th International Conference on Mobile Adhoc and Sensor Systems, MASS 2011, Valencia, Spain, 17–22 October 2011, pp. 292–301 (2011)

    Google Scholar 

  9. Boldrini, C., Passarella, A.: HCMM: modelling spatial and temporal properties of human mobility driven by users’ social relationships. Elsevier Comput. Commun. 33, 1056–1074 (2010)

    Article  Google Scholar 

  10. Borrel, V., Legendre, F., de Amorim, M.D.: Simps: using sociology for personal mobility. IEEE/ACM Trans. Netw. 17, 831–842 (2009)

    Article  Google Scholar 

  11. Brockmann, D., Hufnagel, L., Geisel, T.: The scaling laws of human travel. Nature 439, 462–465 (2006)

    Article  Google Scholar 

  12. Cai, X., Chen, L., Sofia, R.: A dynamic and user-centric network selection in heterogeneous wireless networks. In: IEEE International Performance, Computing, and Communications Conference, 2007, IPCCC (2007)

    Google Scholar 

  13. Camp, T., Boleng, J., Davies, V.: A survey of mobility models for ad hoc network research. ACM Comput. Surv. (CSUR) 37(2), 164–194 (2005). ACM, New York, NY, USA

    Article  Google Scholar 

  14. Chaoming, S., et al.: Limits of predictability in human mobility. Science 327, 1018–1021 (2010)

    Article  MATH  MathSciNet  Google Scholar 

  15. Chatzimisios, P., Vitsas, V., Boucouvalas, A.C.: Throughput and delay analysis of IEEE 802.11 protocol. In: Proceedings of 2002 IEEE 5th International Workshop on Networked Appliances, 2002, Liverpool, pp. 168–174. IEEE (2002)

    Google Scholar 

  16. CRAWDAD - A Community Resource for Archiving Wireless Data at Darthmouth. http://crawdad.org/. Accessed Nov 2012

  17. Gonzalez, M.C., Hidalgo, C.A., Barabási, A.L.: Understanding individual human mobility patterns. Nature 453, 779–782 (2008)

    Article  Google Scholar 

  18. Gorawski, M., Marks, P., Gorawski, M.: Collecting data streams from a distributed radio-based measurement system. In: Haritsa, J.R., Kotagiri, R., Pudi, V. (eds.) DASFAA 2008. LNCS, vol. 4947, pp. 702–705. Springer, Heidelberg (2008)

    Chapter  Google Scholar 

  19. Gorawski, M., Grochla, K.: The real-life mobility model: RLMM. In: Proceedings of FGCT 2013, London, pp. 12–14 (2013)

    Google Scholar 

  20. Einstein, A.: Investigations on the Theory of the Brownian Movement. Dover Publications Inc., New York (1956)

    MATH  Google Scholar 

  21. Hossmann, T., Spyropoulos, T., Legendre, F.: A complex network analysis of human mobility. In: IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS), 10–15 April 2011, pp. 876–881 (2011)

    Google Scholar 

  22. Humphries, N.E., Weimerskirch, H., Queiroza, N., Southall, E.J., Sims, D.W.: Foraging success of biological Lévy flights recorded in situ. In: Proceedings of the National Academy of Sciences of the U.S.A. (2012)

    Google Scholar 

  23. Hyttiä, E., Lassila, P., Virtamo, J.: Spatial node distribution of the random waypoint mobility model with applications. IEEE Trans. Mob. Comput. 5(6), 680–694 (2006)

    Article  Google Scholar 

  24. Iraqi, Y., Baoutaba, R.: Handoff and call dropping probabilities in wireless cellular networks. In: Proceedings of IEEE International Conference on Wireless Networks, Communications and Mobile Computing, vol. 1, pp. 209–213 (2005)

    Google Scholar 

  25. Isaacman, S., Becker, R., Cáceres, R., Martonosi, M., Rowland, J., Varshavsky, A., Willinger, W.: Human mobility modeling at metropolitan scales. In: Proceedings of the 10th International Conference on Mobile Systems, Applications, and Services (MobiSys’12), pp. 239–252. ACM, New York (2012)

    Google Scholar 

  26. Joshi, T., Mukherjee, A., Agrawal, D.P.: Exploiting mobility patterns to reduce reauthentication overheads in infrastructure WLAN networks. In: Proceedings of IEEE Canadian Conference on Electrical and Computer Engineering, pp. 1423–1426 (2006)

    Google Scholar 

  27. Karim, L., Mahmoud, Q.H.: A hybrid mobility model based on social cultural and language diversity. In: 9th IEEE International Conference CollaborateCom (2013)

    Google Scholar 

  28. Kim, T.S., Kwon, J.K., Sung, D.K.: Mobility modelling and traffic analysis in three-dimensional high-rise-building environments. IEEE Trans. Veh. Technol. 49(5), 1633–1640 (2000)

    Article  Google Scholar 

  29. Kurkowski, S., Camp, T., Colagrosso, M.: MANET simulation studies: the incredibles. SIGMOBILE Mob. Comput. Commun. Rev. 9(4), 50–61 (2005)

    Article  Google Scholar 

  30. Lee, K., Kim, S.J., Rhee, I., Chong, S.: SLAW: self-similar least-action human walk. IEEE/ACM Trans. Netw. 20(2), 515–529 (2012)

    Article  Google Scholar 

  31. Michaelis, S., Wietfeld, C.: Comparison of user mobility pattern prediction algorithms to increase handover trigger accuracy. In: Proceedings of IEEE Vehicular Technology Conference, vol. 2, pp. 952–956 (2006)

    Google Scholar 

  32. Musolesi, M., Hailes, S., Mascolo, C.: An ad hoc mobility model founded on social network theory. MSWiM 2004, 20–24 (2004)

    Article  Google Scholar 

  33. Musolesi, M., Mascolo, C.: A community based mobility model for ad hoc network research. In: Proceedings of the 2nd International Workshop on Multi-Hop Ad Hoc Networks: From Theory to Reality (REALMAN ’06), pp. 31–38. ACM Press (2006)

    Google Scholar 

  34. Prasad, P.S., Agrawal, P.: Movement prediction in wireless networks using mobility traces. In: Proceedings of the 7th IEEE Conference on Consumer Communications and Networking Conference, pp. 1–5 (2010)

    Google Scholar 

  35. Ramos-Fernandez, G., Morales, J.L., Miramontes, O., Cocho, G., Larralde, H., Ayala-Orozco, B.: Lévy walk patterns in the foraging movements of spider monkeys (ateles geof-froyi). Behav. Ecol. Sociobiol. 273, 1743–1750 (2004)

    Google Scholar 

  36. Rhee, I., Lee, K., Hong, S., Kim, S.J., Chong, S.: Demystifying the Lévy-walk nature of human walks. Technical report, CS Department, NCSU, Raleigh, NC (2008). http://netsrv.csc.ncsu.edu/export/Demystifying_Levy_Walk_Patterns.pdf

  37. Rhee, I., Shin, M., Hong, S., Lee, K., Chong, S.: On the Lévy-walk nature of human mobility: do humans walk like monkeys? IEEE/ACM Trans. Netw. (TON) 19(3), 630–643 (2011)

    Article  Google Scholar 

  38. Rojas, A., Branch, P., Armitage, G.: Validation of the random waypoint mobility model through a real world mobility trace. In: Proceedings of IEEE Region 10 TENCON, pp. 1–6 (2005)

    Google Scholar 

  39. Romano, P.: The range vs. rate dilemma of WLANs (2004). http://www.eetimes.com/document.asp?doc_id=1271995

  40. Roy, R.R.: Handbook of Mobile Ad Hoc Networks for Mobility Models. LXIV, 1st edn, 1104 p. Springer, Boston (2011)

    Google Scholar 

  41. Sgora, A., Vergados, D.: Handoff prioritization and decision schemes in wireless cellular networks: a survey. IEEE Commun. Surv. Tutor. 11(4), 57–77 (2009)

    Article  Google Scholar 

  42. Sims, D.W., et al.: Scaling laws of marine predator search behaviour. Nature 451, 1098–1102 (2008)

    Article  Google Scholar 

  43. Soh, W.S., Kim, H.S.: QoS provisioning in cellular networks based on mobility prediction techniques. IEEE Commun. Mag. 41(1), 86–92 (2003)

    Article  Google Scholar 

  44. Sricharan, M.S., Vaidehi, V.: A pragmatic analysis of user mobility patterns in macrocellular wireless networks. Elsevier Pervasive Mob. Comput. 4(5), 616–632 (2008)

    Article  Google Scholar 

  45. Tong, C., Niu, J.W., Qu, G.Z., Long, X., Gao, X.P.: Complex networks properties analysis for mobile ad hoc networks. IET Commun. 6(4), 370–380 (2012)

    Article  MathSciNet  Google Scholar 

  46. Tong, L., Bahl, P., Chlamtac, I.: Mobility modelling, location tracking and trajectory prediction in wireless ATM networks. IEEE J. Sel. Areas Commun. 16(6), 922–936 (1998)

    Article  Google Scholar 

  47. Yoon, J., Liu, M., Noble, B.: Random waypoint model considered harmful. In: Proceedings of INFOCOM 2003, San Francisco, April 2003

    Google Scholar 

  48. Zola, E., Barcelo-Arroyo, F.: Probability of handoff to neighbor cells for random waypoint mobility and non-ideal conditions. In: Proceedings of IEEE 2nd Baltic Congress on Future Internet Communications (BCFIC’12), pp. 162–169 (2012)

    Google Scholar 

  49. Zola, E., Barcelo-Arroyo, R., Martín-Escalona, I.: Forecasting the next handoff for users moving with the random waypoint mobility model. EURASIP J. Wirel. Commun. Netw. 2013, 16 (2013)

    Article  Google Scholar 

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Acknowledgement

This work was partially supported by the grant of the Polish National Centre for Research and Development, No. LIDER/10/194/L-3/11.

We thank the team of the User-centric Mobility Management project funded by Fundação para a Ciência e Tecnologia, (UMM, http://copelabs.ulusofona.pt/~umm), reference PTDC/EEA-TEL/105709/2008.

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Correspondence to Krzysztof Grochla .

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Barcelo-Arroyo, F. et al. (2014). New Trends in Mobility Modelling and Handover Prediction. In: Ganchev, I., Curado, M., Kassler, A. (eds) Wireless Networking for Moving Objects. Lecture Notes in Computer Science(), vol 8611. Springer, Cham. https://doi.org/10.1007/978-3-319-10834-6_6

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  • DOI: https://doi.org/10.1007/978-3-319-10834-6_6

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