Advertisement

How to Quantify Trust in Your Network Emulator?

  • Domenico Capriglione
  • Gianni CerroEmail author
  • Luigi Ferrigno
  • Gianfranco Miele
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10866)

Abstract

Network emulators are used in many contexts of communication networks for the design and the development of network management and routing strategies as well as for the tuning of multimedia services as Voice Over IP, video streaming, TV on-demand, to cite a few. These devices are generally used for modifying, in a controlled way, data traffic flows by changing, in real time, several critical parameters as delay, packet loss percentage, throughput, and so on. Due to very attractive features as high versatility and configurability and low cost, the solutions based on general purpose hardware platforms and free/open-source software are the most ones adopted in the practice for implementing network emulators. Nevertheless, in such architectures the complex interaction of software and hardware sections should affect the accuracy and repeatability of such systems in correctly emulating the desired network behaviors. Consequently, a suitable pre-characterization stage of such kind of network emulators should be performed before they are used. In this framework, the paper describes a methodological approach for designing suitable test-bed and measurement procedure able to reliably characterize the performance of such systems. The final aim of the research activity is to provide a suitable uncertainty model and a confidence level for the parameters provided by network emulators, which can drive the final users in more reliably analyzing the experimental results coming from their test campaigns and which involve the network emulators.

Keywords

Network emulators Delay Packet loss Network measurements Metrological performance 

References

  1. 1.
    Coyle, C.L., Vaughn, H.: Social networking: communication revolution or evolution? Bell Labs Tech. J. 13, 13–17 (2008).  https://doi.org/10.1002/bltj.20298CrossRefGoogle Scholar
  2. 2.
    Angrisani, L., Narduzzi, C.: Testing communication and computer networks: an overview. IEEE Instrum. Meas. Mag. 11(5), 12–24 (2008).  https://doi.org/10.1109/MIM.2008.4630738CrossRefGoogle Scholar
  3. 3.
    Ayele, E.D., Meratnia, N., Havinga, P.J.M.: Towards a new opportunistic IoT network architecture for wildlife monitoring system. In: 9th IFIP International Conference on New Technologies, Mobility and Security (NTMS), Paris, France, pp. 1–5 (2018).  https://doi.org/10.1109/NTMS.2018.8328721
  4. 4.
    Lucas-Estañ, M.C., Raptis, T.P., Sepulcre, M., Passarella, A., Regueiro, C., Lazaro, O.: A software defined hierarchical communication and data management architecture for Industry 4.0. In: 14th Annual Conference on Wireless On-demand Network Systems and Services (WONS), Isola 2000, France, pp. 37–44 (2018).  https://doi.org/10.23919/WONS.2018.8311660
  5. 5.
    Abdallah, S., Elhajj, I.H., Chehab A., Kayssi, A.: A network management framework for SDN. In: 9th IFIP International Conference on New Technologies, Mobility and Security (NTMS), Paris, France, pp. 1–4 (2018).  https://doi.org/10.1109/NTMS.2018.8328672
  6. 6.
    Koshimura, R., Ito, Y.: Development of Web-QoE evaluation system for wireless LAN with combination of simulator and network emulator. In: IEEE 2nd Global Conference on Consumer Electronics (GCCE), Tokyo, pp. 431–432 (2013).  https://doi.org/10.1109/GCCE.2013.6664879
  7. 7.
    Holt, C., Kong, A., Leger, A.S., Bennett, D.: Communications network emulation for smart grid test-bed. In: IEEE Power and Energy Society General Meeting (PESGM), Boston, MA, pp. 1–5 (2016).  https://doi.org/10.1109/PESGM.2016.7741999
  8. 8.
    Lal, C., Laxmi V., Gaur, M.S.: Video streaming over MANETs: testing and analysis using real-time emulation. In: 19th Asia-Pacific Conference on Communications (APCC), Denpasar, pp. 190–195 (2013).  https://doi.org/10.1109/APCC.2013.6765940
  9. 9.
    Angrisani, L., Capriglione, D., Cerro, G., Ferrigno, L., Miele, G.: Experimental analysis of software network emulators in packet delay emulation. In: IEEE International Workshop on Measurement and Networking (M&N), Naples, pp. 1–6 (2017).  https://doi.org/10.1109/IWMN.2017.8078382
  10. 10.
    Beuran, R.: Introduction to Network Emulation. Pan Stanford Publishing Pte. Ltd .(2013). ISBN: 9789814364096Google Scholar
  11. 11.
    Hemminger, S.: Network Emulation with NetEm (2005). Inlinux.conf.au
  12. 12.
    Hoßfeld, T., Fiedler, M.: The unexpected QoE killer: when the network emulator misshapes traffic and QoE. In: Seventh International Workshop on Quality of Multimedia Experience (QoMEX), Pylos-Nestoras, pp. 1–6 (2015).  https://doi.org/10.1109/QoMEX.2015.7148093
  13. 13.
    Beshay, J.D., Francini, A., Prakash, R.: On the fidelity of single-machine network emulation in linux. In: IEEE 23rd International Symposium on Modeling, Analysis, and Simulation of Computer and Telecommunication Systems, Atlanta, GA, pp. 19–22 (2015)Google Scholar
  14. 14.
    Betta, G., Capriglione, D., Ferrigno, L., Laracca, M.: A Measurement driven approach to design an efficient test methodology for PLT network QoS performance parameters assessment. Meas. Sci. Technol. (2009).  https://doi.org/10.1088/0957-0233/20/10/105101CrossRefGoogle Scholar
  15. 15.
    Angrisani, L., Botta, A., Miele, G., Pescapé, A., Vadursi, M.: Experiment-driven modeling of open-source internet traffic generators. IEEE Trans. Instrum. Meas. 63(11), 2529–2538 (2014).  https://doi.org/10.1109/TIM.2014.2348633CrossRefGoogle Scholar
  16. 16.
    Angrisani, L., Capriglione, D., Ferrigno, L., Miele, G.: Internet Protocol Packet Delay Variation measurements in communication networks: how to evaluate measurement uncertainty? Measurement 46(7), 2099–2109 (2013).  https://doi.org/10.1016/j.measurement.2013.03.007CrossRefGoogle Scholar
  17. 17.
    Angrisani, L., Capriglione, D., Ferrigno, L., Miele, G.: A methodological approach for estimating protocol analyzer instrumental measurement uncertainty in packet jitter evaluation. IEEE Trans. Instrum. Meas. 61(5), 1405–1416 (2012).  https://doi.org/10.1109/TIM.2012.2186478CrossRefGoogle Scholar
  18. 18.
    Angrisani, L., Capriglione, D., Ferrigno, L., Miele, G.: An internet protocol packet delay variation estimator for reliable quality assessment of video-streaming services. IEEE Trans. Instrum. Meas. 62(5), 914–923 (2013).  https://doi.org/10.1109/TIM.2013.2245051CrossRefGoogle Scholar
  19. 19.
    Carbone, M., Rizzo, L.: DummyNet revisited. SIGCOMM Comput. Commun. 40(2), 12–20 (2010).  https://doi.org/10.1145/1764873.1764876CrossRefGoogle Scholar
  20. 20.
    Botta, A., Dainotti, A., Pescapé, A.: A tool for the generation of realistic network workload for emerging networking scenarios. Comput. Netw. 56(15), 3531–3547 (2012).  https://doi.org/10.1016/j.comnet.2012.02.019CrossRefGoogle Scholar
  21. 21.
    JCGM: Evaluation of measurement data—guide to the expression of uncertainty in measurement. JCGM 100 (2008)Google Scholar

Copyright information

© IFIP International Federation for Information Processing 2018

Authors and Affiliations

  1. 1.DIINUniversity of SalernoFiscianoItaly
  2. 2.DIEIUniversity of Cassino and Southern LazioCassinoItaly

Personalised recommendations