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Simulation of AdHoc Networks Including Clustering and Mobility

Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10517)

Abstract

We introduce a discrete-event simulation model of an AdHoc network considering the presence of clusters and node mobility. The main goal is to study the volume of traffic in relatively large networks of sensor systems and Internet of Things considering fading and network connectivity. We also evaluate relevant parameters such as the mean CPU utilization and the mean queueing time in each node. The model is relatively general in that it combines the traffic from small devices such as sensors as well as more complex intermediate systems such as gateways and Internet nodes. It is also extensible to other types of scenarios and it allows the evaluation of the network under other performance criteria or evaluation metrics. The results show that the model yields simulation values that could be analytically validated by Jackson networks.

Keywords

Emergency services MANET VANET WSN IoT Traffic planning Network dimensioning Connectivity Clustering 

References

  1. 1.
    Amis, A.D., Prakash, R.T., Vuong, H., Huynh, D.: Max-min cluster formation in wireless ad hoc networks. In: Proceedings of Ad Hoc Infocom 2000 (2000)Google Scholar
  2. 2.
    Cai, M., Rui, L., Liu, D., Huang, H., Qiu, X.: Group mobility based clustering algorithm for mobile ad hoc networks. In: 2015 17th Asia-Pacific Network Operations and Management Symposium (APNOMS), pp. 340–343, August 2015Google Scholar
  3. 3.
    Celes, C., Silva, F., Boukerche, A., Andrade, R., Loureiro, A.: Improving VANET simulation with calibrated vehicular mobility traces. IEEE Trans. Mob. Comput. PP(99), 1 (2017)Google Scholar
  4. 4.
    Jackson, J.R.: Networks of waiting lines. Oper. Res. 5(4), 518–521 (1957)MathSciNetCrossRefGoogle Scholar
  5. 5.
    Nassef, L.: On the effects of fading and mobility in on-demand routing protocols. Egypt. Inform. J. 11, 67–74 (2010)CrossRefGoogle Scholar
  6. 6.
    Phanish, D., Coyle, E.J.: Application-based optimization of multi-level clustering in ad hoc and sensor networks. IEEE Trans. Wireless Commun. PP(99), 1 (2017)Google Scholar
  7. 7.
    Pramanik, A., Choudhury, B., Choudhury, T.S., Arif, W., Mehedi, J.: Simulative study of random waypoint mobility model for mobile ad hoc networks. In: IEEE Proceedings Global Conference on Communication Technologies (GCCT 2015), pp. 112–116 (2015)Google Scholar
  8. 8.
    Ren, M., Khoukhi, L., Labiod, H., Zhang, J., Veque, V.: A new mobility-based clustering algorithm for vehicular ad hoc networks (VANETs). In: 2016 IEEE/IFIP Network Operations and Management Symposium, NOMS 2016, pp. 1203–1208, April 2016Google Scholar

Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  1. 1.School of TechnologyUniversity of Campinas (UNICAMP)LimeiraBrazil

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