Abstract
Knowledge of traffic load evolution in time is essential to properly configure and dimension a mobile network. Moreover, it is a key parameter to indicate the network performance and quality of service. In this paper, we use interarrival time (time between arrivals), waiting time, and service time parameters to investigate outgoing and incoming traffic of an international voice traffic carrier. Both types of traffic are analyzed for the previously mentioned parameters by taking into account short and long-distance international call scenarios. The obtained results follow the expected Poisson and Exponential distributions for these parameters. In addition, the traffic load of neighboring countries shows a long-term stability and consistency.
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Sultan, K., Ali, H., Zhang, Z.: Call detail records driven anomaly detection and traffic prediction in mobile cellular networks. IEEE Access 6, 41728–41737 (2018). https://doi.org/10.1109/ACCESS.2018.2859756
Zonoozi, M.M., Dassanayake, P., Faulkner, M.: Teletraffic modelling of cellular mobile networks. In: Proceedings of Vehicular Technology Conference (VTC 1996), vol. 2, 1274–1277. IEEE Press, Atlanta (1996). https://doi.org/10.1109/VETEC.1996.501517
Rico-Paez, A., Cruz-Perez, F.A., Hernandez-Valdez, G.: Teletraffic analysis formulation based on channel holding time statistics. In: IEEE International Conference on Wireless and Mobile Computing, Networking and Communications, pp. 326–330. IEEE Press, Marrakech (2009). https://doi.org/10.1109/WiMob.2009.62
Fan, L., Zhao, Z., Qi, Ch., Li, R., Zhang, H.: A revisiting to queueing theory for mobile instant messaging with keep-alive mechanism in cellular networks. In: IEEE International Conference on Communications (ICC), 1–6. IEEE Press, Paris (2017). https://doi.org/10.1109/ICC.2017.7996707
Mehr, K.A., Nobar, S.Kh., Niya, J.M.: Inter-arrival time distribution of IEEE 802.15.4 under saturated traffic condition. In: 23rd Iranian Conference on Electrical Engineering, pp. 2164–7054. IEEE Press, Tehran (2015). https://doi.org/10.1109/IranianCEE.2015.7146211
Mark, B.L., Ephraim, Y.: On modeling network congestion using continuous-time bivariate Markov chains. In: 45th Annual Conference on Information Sciences and Systems, pp. 1–6. IEEE Press, Baltimore (2011). https://doi.org/10.1109/CISS.2011.5766118
Castellanos-Lopez, S.L., Cruz-Perez, F.A., Hernandez-Valdez, G., Miranda-Tello, J.R.: Performance analysis of mobile cellular networks with MMPP call arrival patterns. In: 9th IFIP International Conference on New Technologies, Mobility and Security (NTMS), pp. 2157–4960. IEEE Press, Paris (2018). https://doi.org/10.1109/NTMS.2018.8328711
Stenico, J.W.G., Lee, L.L., Vieira, F.H.T.: Queuing modeling applied to admission control of network traffic flows considering multifractal characteristics. IEEE Latin Am. Trans. 11, 749–758 (2013). https://doi.org/10.1109/TLA.2013.6533964
Pattavina, A., Parini, A.: Modeling voice call inter-arrival and holding time distributions in mobile networks. In: ITC19/Performance Challenges for Efficient Next Generation Networks, pp. 729–738 (2005)
Nagy, L., Tombal, J., Novotny, V.: Proposal of a queueing model for simulation of advanced telecommunication services over IMS architecture. In: 36th International Conference on Telecommunications and Signal Processing (TSP), pp. 326–330. IEEE Press, Rome (2013). https://doi.org/10.1109/TSP.2013.6613945
Ferrante, G.C., Quek, T.Q.S., Win, M.Z.: Timing capacity of queues with random arrival and modified service times. In: IEEE International Symposium on Information Theory (ISIT), pp. 370–374. IEEE Press, Barcelona (2016). https://doi.org/10.1109/ISIT.2016.7541323
Błaszczyszyn, B., Karray, M.K., Keeler, H.P.: Using Poisson processes to model lattice cellular networks. In: Proceedings IEEE INFOCOM, pp. 773–781. IEEE Press, Turin (2013). https://doi.org/10.1109/INFCOM.2013.6566864
Jun, L., Tingting, L., Gang, C., Hua, Y., Zhenming, L.: Mining and modelling the dynamic patterns of service providers in cellular data network based on big data analysis. China Commun. 10, 25–36 (2013). https://doi.org/10.1109/CC.2013.6723876
Stallings, W.: Data and Computer Communications, 8th edn., Chap. 10, pp. 307–308 (2007)
Forouzan, B.A.: TCP/IP Protocol Suite, 4th edn., Chap. 25, pp. 748–751 (2010)
Hartpence, B.: Packet Guide to Voice over IP, Chap. 3, pp. 70–75 (2013)
Tunnicliffe, G.W., Murch, A.R., Sathyendran, A., Smith, P.J.: Analysis of traffic distribution in cellular networks. In: VTC 1998. 48th IEEE Vehicular Technology Conference. Pathway to Global Wireless Revolution (Cat. No. 98CH36151), vol. 3, pp. 1984–1988. IEEE Press, Ottawa (1998). https://doi.org/10.1109/VETEC.1998.686103
Schay, G.: Introduction to Probability with Statistical Applications, Chap. 6, pp. 183–184 (2007)
Cooper, R.B.: Introduction to Queueing Theory, 2nd edn., Chap. 2, pp. 50–56 (1981)
Ross, Sh.M.: Introduction to Probability and Statistics for Engineers and Scientists, 4th edn., Chap. 5, pp. 176–182 (2009)
Aziz, Z., Bestak, R.: Analysis of call detail records of international voice traffic in mobile networks. In: Tenth International Conference on Ubiquitous and Future Networks (ICUFN), pp. 475–480. IEEE Press, Prague (2017). https://doi.org/10.1109/ICUFN.2018.8436669
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This research work was supported by the Grant Agency of the Czech Technical University in Prague, grant no. SGS18/181/OHK3/3T/13.
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Aziz, Z., Bestak, R. (2019). Mobile Voice Traffic Load Characteristics. In: Gaj, P., Sawicki, M., Kwiecień, A. (eds) Computer Networks. CN 2019. Communications in Computer and Information Science, vol 1039. Springer, Cham. https://doi.org/10.1007/978-3-030-21952-9_15
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DOI: https://doi.org/10.1007/978-3-030-21952-9_15
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