Performance Limitations of Parsing Libraries: State-of-the-Art and Future Perspectives

  • Antonino Manlio D’Agostino
  • Aleksandr OmetovEmail author
  • Alexander Pyattaev
  • Sergey Andreev
  • Giuseppe Araniti
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11118)


The acceleration of mobile data traffic and the shortage of available spectral resources create new challenges for the next-generation (5G) networks. One of the potential solutions is network offloading that opens a possibility for unlicensed spectrum utilization. Heterogeneous networking between cellular and WLAN systems allows mobile users to adaptively utilize the licensed (LTE) and unlicensed (IEEE 802.11) radio technologies simultaneously. At the same time, softwarized frameworks can be employed not only inside the network controllers but also at the end nodes. To operate with the corresponding policies and interpret them efficiently, a signaling processor has to be developed and equipped with a fast packet parsing mechanism. In this scenario, the reaction time becomes a crucial factor, and this paper provides an overview of the existing parsing libraries (Scapy and dpkt) as well as proposes a flexible parsing tool that is capable of reducing the latency incurred by analyzing packets in a softwarized network.


SDN Parsing dpkt Scapy Performance evaluation 



The publication has been prepared with the support of the “RUDN University Program 5-100.”


  1. 1.
    VNI Cisco: Global mobile data traffic forecast 2016–2021. White Paper (2018)Google Scholar
  2. 2.
    Mäkitalo, N., Ometov, A., Kannisto, J., Andreev, S., Koucheryavy, Y., Mikkonen, T.: Safe and secure execution at the network edge: a framework for coordinating cloud, fog, and edge. IEEE Softw. 35(1), 30–37 (2018)CrossRefGoogle Scholar
  3. 3.
    Karakus, M., Durresi, A.: A survey: control plane scalability issues and approaches in Software-Defined Networking (SDN). Comput. Netw. 112, 279–293 (2017)CrossRefGoogle Scholar
  4. 4.
    Florea, R., Ometov, A., Surak, A., Andreev, S., Koucheryavy, Y.: Networking solutions for integrated heterogeneous wireless ecosystem. In: Cloud Computing, p. 103 (2017)Google Scholar
  5. 5.
    Xia, W., Wen, Y., Foh, C.H., Niyato, D., Xie, H.: A survey on software-defined networking. IEEE Commun. Surv. Tutorials 17(1), 27–51 (2015). Scholar
  6. 6.
    Ordonez-Lucena, J., Ameigeiras, P., Lopez, D., Ramos-Munoz, J.J., Lorca, J., Folgueira, J.: Network slicing for 5G with SDN/NFV: concepts, architectures, and challenges. IEEE Commun. Mag. 55(5), 80–87 (2017)CrossRefGoogle Scholar
  7. 7.
    Volkov, A., Khakimov, A., Muthanna, A., Kirichek, R., Vladyko, A., Koucheryavy, A.: Interaction of the IoT traffic generated by a smart city segment with SDN core network. In: Koucheryavy, Y., Mamatas, L., Matta, I., Ometov, A., Papadimitriou, P. (eds.) WWIC 2017. LNCS, vol. 10372, pp. 115–126. Springer, Cham (2017). Scholar
  8. 8.
    Laselva, D., Lopez-Perez, D., Rinne, M., Henttonen, T.: 3GPP LTE-WLAN aggregation technologies: functionalities and performance comparison. IEEE Commun. Mag. 56(3), 195–203 (2018)CrossRefGoogle Scholar
  9. 9.
    Ometov, A.: Short-range communications within emerging wireless networks and architectures: a survey. In: Proceedings of 14th Conference of Open Innovations Association (FRUCT), pp. 83–89. IEEE (2013)Google Scholar
  10. 10.
    Galinina, O., et al.: Capturing spatial randomness of heterogeneous cellular/WLAN deployments with dynamic traffic. IEEE J. Sel. Areas Commun. 32(6), 1083–1099 (2014)CrossRefGoogle Scholar
  11. 11.
    Ometov, A., Masek, P., Urama, J., Hosek, J., Andreev, S., Koucheryavy, Y.: Implementing secure network-assisted D2D framework in live 3GPP LTE deployment. In: Proceedings of International Conference on Communications Workshops (ICC), pp. 749–754. IEEE (2016)Google Scholar
  12. 12.
    Andreev, S., et al.: Exploring synergy between communications, caching, and computing in 5G-grade deployments. IEEE Commun. Mag. 54(8), 60–69 (2016)MathSciNetCrossRefGoogle Scholar
  13. 13.
    Feamster, N., Rexford, J., Zegura, E.: The road to SDN: an intellectual history of programmable networks. ACM SIGCOMM Comput. Commun. Rev. 44(2), 87–98 (2014)CrossRefGoogle Scholar
  14. 14.
    Volkov, A., Muhathanna, A., Pirmagomedov, R., Kirichek, R.: SDN approach to control internet of thing medical applications traffic. In: Vishnevskiy, V.M., Samouylov, K.E., Kozyrev, D.V. (eds.) DCCN 2017. CCIS, vol. 700, pp. 467–476. Springer, Cham (2017). Scholar
  15. 15.
    Grebeshkov, A., Gaidamaka, Y., Zaripova, E., Pshenichnikov, A.: Modeling of vertical handover from 3GPP LTE to cognitive wireless regional area network. In: Proceedings of 9th International Congress on Ultra Modern Telecommunications and Control Systems and Workshops (ICUMT), pp. 1–6. IEEE (2017)Google Scholar
  16. 16.
    Määttanen, H.L., Masini, G., Bergström, M., Ratilainen, A., Dudda, T.: LTE-WLAN aggregation (LWA) in 3GPP Release 13 & Release 14. In: Proceedings of Conference on Standards for Communications and Networking (CSCN), pp. 220–226. IEEE (2017)Google Scholar
  17. 17.
    Shen, X.: Device-to-device communication in 5G cellular networks. IEEE Netw. 29(2), 2–3 (2015). Scholar
  18. 18.
    Pyattaev, A., Johnsson, K., Surak, A., Florea, R., Andreev, S., Koucheryavy, Y.: Network-assisted D2D communications: implementing a technology prototype for cellular traffic offloading. In: Proceedings of Wireless Communications and Networking Conference (WCNC), pp. 3266–3271. IEEE (2014)Google Scholar
  19. 19.
    Gerasimenko, M., Moltchanov, D., Florea, R., Himayat, N., Andreev, S., Koucheryavy, Y.: Prioritized centrally-controlled resource allocation in integrated multi-RAT HetNets. In: Proceedings of 81st Vehicular Technology Conference (VTC Spring), pp. 1–7. IEEE (2015)Google Scholar
  20. 20.
    Pontarelli, S., Bruschi, V., Bonola, M., Bianchi, G.: On offloading programmable SDN controller tasks to the embedded microcontroller of stateful SDN dataplanes. In: Proceedings of IEEE Conference on Network Softwarization (NetSoft), pp. 1–4, July 2017.
  21. 21.
    Pontarelli, S., Bonola, M., Bianchi, G.: Smashing SDN “built-in” actions: programmable data plane packet manipulation in hardware. In: Proceedings of IEEE Conference on Network Softwarization (NetSoft), pp. 1–9, July 2017.

Copyright information

© Springer Nature Switzerland AG 2018

Authors and Affiliations

  1. 1.University Mediterranea of Reggio CalabriaReggio CalabriaItaly
  2. 2.Tampere University of TechnologyTampereFinland
  3. 3.Peoples’ Friendship University of Russia (RUDN University)MoscowRussia

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