Building of a Competent Mobility Model for Ad Hoc Wireless Networks

  • Arvind Kumar Shukla
  • C. K. Jha
  • Vimal Kumar Mishra
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 258)

Abstract

Mobility is a natural character of Ad Hoc networks. A realistic simulation of user movement in Ad Hoc Network is very important to the network performance. Therefore, by using a realistic mobility model, which is an important aspect in enhancing the self-confidence in the simulation result of the network. Although, each node’s movement is random, there are still some underlying disciplines in their mobility. By predicting the mobility of user that truly depicts nodes mobility in an Ad Hoc Network, is the first step of mobility management. In this manuscript an attempt has been made by proposing a new mobility model called restriction models for generating unusual mobility scenarios for Ad Hoc networks such as campus scenario. The propose algorithm performance has been evaluated using network simulator (ns2.35) for dynamic source routing (DSR). The results are compared with other mobility model such as Random way point. The results shows that our proposed algorithm has outperform the available mobility model for campus scenario.

Keywords

Ad Hoc network Mobility models Mobility patterns ns 2.35 Performance parameters Boonmotion 2.0 

References

  1. 1.
    Rhee, I., Shin, M., Hong, S., Lee, K., Chong, S.: On the levy-walk nature of human mobility. In: Proceedings of the IEEE INFOCOM (2008)Google Scholar
  2. 2.
    Zhao, M., Mason, L., Wang, W.: Empirical study on human mobility for mobile wireless networks. In: Proceedings of the IEEE Military Communications Conference (MILCOM 2008), pp. 1–7 (2008)Google Scholar
  3. 3.
    Li, F., Wu, J.: Mobility reduces uncertainty in manets. In: Proceedings of the IEEE INFOCOM (2007)Google Scholar
  4. 4.
    Jardosh, A., Belding-Royer, E.M., Almeroth, K., Suri, S.: Towards realistic mobility models for mobile ad hoc networks. In: Proceedings of the 9th Annual ACM/IEEE International Conference on Mobile Computing and Networking (MobiCom’03), San Diego, September 2003Google Scholar
  5. 5.
    Rhee, I., Shin, M., Hong, S., Lee, K., Chong, S.: On the levy-walk nature of human mobility: do humans walk like monkeys? Technical report, CSC, NCSU (2007)Google Scholar
  6. 6.
    Grossglauser, M., Vetterli, M.: Locating nodes with EASE: mobility diffusion of last encounters in Ad Hoc networks. In: Proceedings of the IEEE Infocom (2003)Google Scholar
  7. 7.
    Hsu, W., Helmy, A.: Impact: Investigation of Mobile-User Patterns Across University Campuses Using WLAN Trace Analysis. Tech. rep., USC, Los Angeles (2005)Google Scholar
  8. 8.
    Balazinska, M., Castro, P.: Characterizing mobility and network usage in a corporate wireless local-area network. Paper presented at the 1st international conference on mobile systems, applications, and services (MobiSys), San Francisco, May 2003Google Scholar
  9. 9.
    Garmin website. In http://www.garmin.com/
  10. 10.
    Bai, F., Helmy, A.: A survey of mobility modeling and analysis in wireless adhoc networks. In: Wireless Ad Hoc and Sensor Networks. Springer (2006), ISBN: 978-0-387-25483-8Google Scholar
  11. 11.
    Bettstetter, C., Resta, G., Santi, P.: The node distribution of the random waypoint mobility model for wireless ad hoc networks. IEEE Trans. Mob. Comput. 2(3), 257–269 (2003)Google Scholar
  12. 12.
    Karagiannis, T., Faloutsos, M., Molle, M.: Long-range dependence: ten years of internet traffic modeling. IEEE Internet Comput. 8(5), 57–64 (2004) (special issue in ‘‘measuring the internet’’)Google Scholar
  13. 13.
    Pawlikowski, K., Jeong, H.-D.J., Lee, J.-S.R.: On credibility of simulation studies of telecommunication networks. IEEE Commun. Mag. 40(1), 132–139 (2002)Google Scholar
  14. 14.
    Camp, T., Boleng, J., Davies, V.: A survey of mobility models for ad hoc, network research. Wirel. Commun. Mob. Comput. 2(5), 483–502 (2002). special issue on mobile ad hoc networking: research, trends, and applicationsCrossRefGoogle Scholar
  15. 15.
    La, R.: Distributional convergence of inter-meeting times under generalized hybrid random walk mobility model. IEEE Trans. Mob. Comput. 9(9), 1201–1211 (2010)Google Scholar
  16. 16.
    Rhee, I., Shin, M., Hong, S., Lee, K.R., Kim, S.J., Chong, S.: On the levy-walk nature of human mobility. IEEE/ACM Trans. Network. 19(3), 630–643 (2011)Google Scholar
  17. 17.
    Aschenbruck, N., Gerhards-Padilla, E., Peter, M.: A survey on mobility models for performance analysis in tactical mobile networks. J. Telecommun. Inf. Technol. 2, 54–61 (2008)Google Scholar
  18. 18.
    Iyer, A., Rosenberg, C., Karnik, A.: What is the right model for wireless channel interference. IEEE Trans. Wireless Commun. 8(5), 2662–2671 (2009)Google Scholar
  19. 19.
    Jayakumar, G., Ganapathy, G.: Performance comparison of mobile ad-hoc netwrok routing protocol. Int. J. Comput. Sci. Netw. Secur. 7(11), 77–84 (2007)Google Scholar
  20. 20.
    Asma, T., Rajneesh, G.M., Sunil, T.: Comparative performance analysis of DSDV, AODV and DSR routing protocols in MANET using NS2. In: International Conference on Advances in Computer Engineering (2010)Google Scholar
  21. 21.
    Kumar, S., Sharma, SC., Suman, B.: Mobility metrics based classification & analysis of mobility model for tactical network. Int. J. Next Gener. Netw. 2(3), 39–51 (2010)Google Scholar
  22. 22.
    Liu, J., Jiang, X., Nishiyama, H., Kato, N.: On the delivery probability of two-hop relay MANETs with erasure coding. IEEE Trans. Commun. 61(4), 1314–1326 (2013)Google Scholar
  23. 23.
    Andrews, J.G., Haenggi, M., Jindal, N.: A primer on spatial modeling and analysis in wireless networks. IEEE Commun. Mag. 48(11), 156–163 (2010)Google Scholar
  24. 24.
    Kotz, D., Essien, K.: Analysis of a campus-wide wireless network. Wireless Netw. 11, 115–133 (2005)CrossRefGoogle Scholar
  25. 25.
    Hong, D., Rappaport, S.-S.: Traffic model and performance analysis for cellular mobile radio telephone systems with prioritized and non prioritized handoff procedures. IEEE Trans. Veh. Technol. 35, 77–92 (2003)Google Scholar
  26. 26.
    Su, J., Goel, A., de Lara, E.: An empirical evaluation of the student-net delay tolerant network. In: International Conference on Mobile and Ubiquitous Systems: Networking & Services (MobiQuitous), pp. 1–10 (2006)Google Scholar
  27. 27.
    Karagiannis, T., LeBoudec, J.-Y., Vojnovic, M.: Power law and exponential decay of inter contact times between mobile devices. In: Proceedings of ACM MOBICOM, pp. 183–194 (2007)Google Scholar
  28. 28.
    Medina, A., Gursun, G., Basu, P., Matta, I.: On the universal generation of mobility models. In: Proceedings of the IEEE/ACM MASCOTS 2010, Miami Beach, FL (2010)Google Scholar

Copyright information

© Springer India 2014

Authors and Affiliations

  • Arvind Kumar Shukla
    • 1
  • C. K. Jha
    • 1
  • Vimal Kumar Mishra
    • 2
  1. 1.Department of AIM and ACTBanasthali VidyapithRajasthanIndia
  2. 2.Department of Computer EngineeringGovernment Girls PolytechnicAllahabadIndia

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