Skip to main content

Development and Research of Active Queue Management Method on Interfaces of Telecommunication Networks Routers

  • Chapter
  • First Online:
  • 255 Accesses

Part of the book series: Lecture Notes on Data Engineering and Communications Technologies ((LNDECT,volume 69))

Abstract

The paper presents the results of the development and further research of the method of active queue management at the interfaces of telecommunication networks routers. The research was conducted as part of a full-scale experiment based on the laboratory of Cisco Systems. To evaluate the effectiveness of the proposed method of active queue management, we compared the results of its work (according to the main indicators of quality of service) with technological solutions of congestion management mechanism—WFQ and congestion avoidance mechanism—WRED, which were automatically configured on the router interfaces. In particular, the obtained results were compared with the average packet delay and the packet loss probability. Such characteristics of flows and queues as a bandwidth of the router interface; the number of packet flows arriving at its input, the value of their classes and intensities; the number of queues formed on the interface, and their classification were changing. The D-ITG package was used as a load testing package for generating and further analyzing network traffic. The results of the research confirmed the effectiveness of the proposed method in terms of improving the average packet delay—from 12–17 to 22–25% for high-priority flows (EF, AF41-43), and from 8–12 to 16–19%—low priority flows (AF11-13). Using the active queue management method allowed to reduce the chance of packet loss by 7–12% for high-priority flows (EF, AF41-43), and by 10–17%—low priority flows (AF11-13). Also, according to the results of the laboratory experiment, recommendations were developed on the practical application of the proposed solutions in modern and promising telecommunication networks (TCNs). It was found that the algorithmic implementation in practice of the proposed models and methods can be the basis for promising queue management mechanisms and interface bandwidth in order to improve the quality of service in telecommunication networks as a whole. It was also established that the recommended area of the practical application of the proposed method of active queue management is a high-load area (over 80–85%) and congestion of interfaces of telecommunication network routers, especially in conditions of increased dynamics of their state change.

This is a preview of subscription content, log in via an institution.

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   109.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   139.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

References

  1. Rao DS (2012) Queue management and quality of service (QoS) in the internet: a novel approach for flow protection for providing better than best-effort service in the internet. LAP LAMBERT Academic Publishing

    Google Scholar 

  2. Tan L (2017) Resource allocation and performance optimization in communication networks and the internet. CRC Press

    Google Scholar 

  3. White R, Banks E (2018) Computer networking problems and solutions: an innovative approach to building resilient, modern networks, 1st edn. Addison-Wesley Professional

    Google Scholar 

  4. Smelyakov K, Chupryna A, Hvozdiev M, Sandrkin D, Martovytskyi V (2019) Comparative efficiency analysis of gradational correction models of highly lighted image. In: 2019 IEEE international scientific-practical conference problems of infocommunications, science and technology (PIC S&T). Kyiv, Ukraine, pp 8–11. https://doi.org/10.1109/PICST47496.2019.9061356

  5. Tipper D (2014) Resilient network design: challenges and future directions. Telecommun Syst 56(1):5–16. https://doi.org/10.1007/s11235-013-9815-x

    Article  Google Scholar 

  6. Muscariello L, Carofiglio G, Papalini M (2018) System and method to facilitate robust traffic load balancing and remote adaptive active queue management in an information-centric networking environment: U.S. Patent Application No. 15/658,628

    Google Scholar 

  7. Lemeshko OV, Ali AS, Semenyaka MV (2012) Results of the dynamic flow-based queue balancing model research. In: 2012 IEEE international conference on modern problem of radio engineering, telecommunications and computer science, Lviv-Slavske, Ukraine, pp 318–319

    Google Scholar 

  8. Lebedenko T, Simonenko A, Fouad Abdul Razzaq Arif A (2016) Queue management model on the network routers using optimal flows aggregation. In: 2016 IEEE 13th international conference modern problems of radio engineering, telecommunications, and computer science (TCSET), Lviv, Ukraine, pp 605–608. https://doi.org/10.1109/TCSET.2016.7452129

  9. Lemeshko O, Lebedenko T, Yeremenko O, Simonenko O (2018) Mathematical model of queue management with flows aggregation and bandwidth allocation. In: International conference on theory and applications of fuzzy systems and soft computing, Springer, Cham, pp 165–176. https://doi.org/10.1007/978-3-319-91008-6_17

  10. Lebedenko T (2019) Method of scheduling and active queues management on routers interfaces of telecommunication networks. Innov Technolo Sci Solut Ind 2(8):54–61. https://doi.org/10.30837/2522-9818.2019.8.054

    Article  Google Scholar 

  11. Irazabal M, Lopez-Aguilera E, Demirkol I (2019) Active queue management as quality of service enabler for 5G networks. In: 2019 IEEE European conference on networks and communications (EuCNC’2019), Valencia, Spain, pp 421–426. https://doi.org/10.1109/EuCNC.2019.8802027

  12. Lemeshko O, Lebedenko T, Al-Dulaimi A (2019) Improvement of the method of balanced queue management on the routers interfaces of the telecommunication networks. In: 2019 IEEE 3rd international conference advanced information and communication technologies (AICT), Lviv, Ukraine, pp 170–175. https://doi.org/10.1109/AIACT.2019.8847749

  13. Chitra K, Padamavathi G (2010) Classification and performance of AQM-based schemes for congestion avoidance. Int J Comput Sci Inf Secur 8(1):331–340

    Google Scholar 

  14. Lemeshko O, Lebedenko T, Nevzorova O, Snihurov A, Mersni A, Al-Dulaimi A (2019) Development of the balanced queue management scheme with optimal aggregation of flows and bandwidth allocation. In: 2019 IEEE the15th international conference the experience of designing and application of CAD system in microelectronic (CADSM), Polyana-Svalyava, Ukraine, pp 1–4. https://doi.org/10.1109/CADSM.2019.8779246

  15. Okokpujie KO, Chukwu EC, Noma-Osaghae E, Okokpujie IP (2018) novel active queue management scheme for routers in wireless networks. Int J Commun Antenna Propag (IRECAP) 8(1):53–61. https://doi.org/10.15866/irecap.v8i1.13408

  16. Lebedenko T, Kholodkova A, Al-Dulaimi A (2018) Linear-quadratic model of optimal queue management on interface of telecommunication network router. In: 2018 IEEE international conference on information and telecommunication technologies and radio electronics (UkrMiCo), Odessa, Ukraine, pp 1–4. https://doi.org/10.1109/UkrMiCo43733.2018.9047602

  17. Rao SS (2019) Engineering optimization: theory and practice, 5th edn. Wiley

    Google Scholar 

  18. Lemeshko O, Semenyaka M, Simonenko O (2013) Researching and designing of the dynamic adaptive queue balancing method on telecommunication network routers. In: 2013 IEEE 12th international conference on the experience of designing and application of cad systems in microelectronics (CADSM), Polyana Svalyava, Ukraine, pp 204–207

    Google Scholar 

  19. An architectural framework for support of quality of service in packet networks, ITU-T Recommendation Y.1291. ITU-T (2004)

    Google Scholar 

  20. Network performance objectives for IP-based services. ITU-T Recommendation Y. 1541. ITU-T (2011)

    Google Scholar 

  21. Ramachendra GA, Reshma B, Ali ahammed GF (2014) Performance comparison of ModRED AQM with round robin scheduling. Int J Adv Res Comput Eng Technol 3(7):2560–2566

    Google Scholar 

  22. Yeremenko O, Lebedenko T, Mersni A (2018) Features of dynamic modeling of routers operation modes in simulink. In: 2018 IEEE fifth international scientific-practical conference problems of infocommunications. Science and Technology (PIC S&T), Kharkiv, Ukraine, pp 520–524. https://doi.org/10.1109/INFOCOMMST.2018.8632061

  23. Fei Z, Xing C, Li N (2015) QoE-driven resource allocation for mobile ip services in wireless network. Sci China Inf Sci 58(1):1–10. https://doi.org/10.1007/s11432-014-5163-z

    Article  MATH  Google Scholar 

  24. Avallone S, Guadagno S, Emma D, Pescapè A, Ventre G (2004) D-ITG distributed internet traffic generator. In: 2004 IEEE first international conference quantitative evaluation of systems (QEST’2004), Enschede, The Netherlands, pp 316–317

    Google Scholar 

  25. Kolahi S, Narayan S, Nguyen DDT, Sunarto Y (2011) Performance monitoring of various network traffic generators. In: the13th international conference computer modelling and simulation (UKSim-AMSS), Cambridge, United Kingdom, pp 501–506. https://doi.org/10.1109/UKSIM.2011.102

  26. Stallings W (2016) Foundations of modern networking: SDN, NFV, QoE, IoT, and Cloud, 1st edn. Pearson Education Inc.

    Google Scholar 

  27. Varma S (2015) Internet congestion control. Morgan Kaufmann

    Google Scholar 

  28. Haghighi A, Mishev D (2016) Delayed and network queues. Wiley

    Google Scholar 

  29. Yeremenko O, Lebedenko T, Vavenko T, Semenyaka M (2015) Investigation of queue utilization on network routers by the use of dynamic models. In: 2015 IEEE second international scientific-practical conference problems of infocommunications science and technology (PIC S&T), Kharkiv, Ukraine, pp 46–49. https://doi.org/10.1109/INFOCOMMST.2015.7357265

  30. Ramakrishna BB, Prashant A, Shrinivasa DMD (2012) A survey on new load based active queue management mechanisms. Int J Sci Eng Res 3(10):1–4

    Google Scholar 

  31. Romanov O, Mankivskyi V (2019) Optimal traffic distribution based on the sectoral model of loading network elements. In: 2019 IEEE international scientific-practical conference problems of infocommunications, science and technology (PIC S&T), Kyiv, Ukraine, pp 683–688. https://doi.org/10.1109/PICST47496.2019.9061296

  32. John J, Balan R (2017) Priority queuing technique promoting deadline sensitive data transfers in router based heterogeneous networks. Int J Appl Eng Res 12(15):4899–4903

    Google Scholar 

  33. Romanov O, Nesterenko M, Mankivsky V (2016) Application of the regression model of the coefficient of use of channels for forming the plan of load distribution in the network. In: Bulletin of NTUU “KPI”. Radio Engineering Series, Radio apparatus construction, No 67, pp 34–42

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Oleksandr Lemeshko .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2021 The Author(s), under exclusive license to Springer Nature Switzerland AG

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Lemeshko, O., Lebedenko, T., Holoveshko, M. (2021). Development and Research of Active Queue Management Method on Interfaces of Telecommunication Networks Routers. In: Ageyev, D., Radivilova, T., Kryvinska, N. (eds) Data-Centric Business and Applications. Lecture Notes on Data Engineering and Communications Technologies, vol 69. Springer, Cham. https://doi.org/10.1007/978-3-030-71892-3_1

Download citation

Publish with us

Policies and ethics