Skip to main content
SpringerLink
Log in

Approximate Method for Estimating Characteristics of Joint Service of Real-Time Traffic and Elastic Data Traffic in Multiservice Access Nodes

  • STOCHASTIC SYSTEMS
  • Published:
Automation and Remote Control Aims and scope Submit manuscript

Abstract

A mathematical model of joint servicing of priority real-time traffic and elastic data traffic in multiservice access nodes has been constructed and studied. Definitions of quality indicators for joint servicing of incoming requests for information services are provided. A system of statistical equilibrium equations is formed and its use for calculating the exact values of the introduced characteristics is considered. A method for approximate calculation of characteristics is proposed, based on the construction of a system of simplified equilibrium equations. It has been established that the obtained estimates of customer service indicators are asymptotically accurate in the region of large and small losses. The use of the developed method is shown to solve the problem of estimating the volume of traffic offloaded in an overload situation to other access nodes or to other frequency ranges in order to achieve values of specified QoS indicators and to solve the problem of planning the volume of required transmission resource of a multiservice access node.

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

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1.
Fig. 2.
Fig. 3.
Fig. 4.
Fig. 5.
Fig. 6.
Fig. 7.
Fig. 8.
Fig. 9.
Fig. 10.

Notes

  1. We will use lowercase letters to denote the normalized values of the probabilities of states and characteristics and uppercase letters to denote their non-normalized values.

  2. Worst case scenario for servicing elastic data.

REFERENCES

  1. Study on Scenarios and Requirements for Next Generation Access Technologies, 3GPP Technical Report (TR) 138.913 version 15.0.0 Release 15. 2018.

  2. Network Slice Selection Services, 3GPP Technical Specification (TS) 129.531 version 15.5.0. Release 15. 2019.

  3. Evans, J. and Filsfils, C., Deploying IP and MPLS QOS for Multiservice Networks. Theory and Practice, Morgan Kaufmann Publishers, Elsevier, 2007.

    Google Scholar 

  4. Ross, K.W., Multiservice Loss Models for Broadband Telecommunication Networks. London: Springer, 1995.

    Book  Google Scholar 

  5. Iversen, V.B., Teletraffic Engineering and Network Planning, Technical University of Denmark, May 2010.

  6. Broadband Network Traffic. Performance Evaluation and Design of Broadband Multiservice Networks. Final Report of Action COST 242, James Roberts, Ed., Lecture Notes in Computer Sciences, Springer, 1996.

  7. Stepanov, S.N., Osnovy Teletrafika Mul’tiservisnykh Setei (The Foundation of Multiservice Network Teletraffic), Moscow: Eqo-Trends, 2010.

  8. Bonald, T. and Feuillet, M., Network Performance Analysis, United Kingdom, London: Wiley, 2011.

    Book  Google Scholar 

  9. Basharin, G.P., Gaidamaka, Yu.V., and Samouylov, K.E., Mathematical Theory of Teletraffic and Its Application to the Analysis of Multiservice Communication of Next Generation Networks, Autom. Control Comput. Sci., 2013, vol. 47, no. 2, pp. 62–69.

    Article  Google Scholar 

  10. Stepanov, S.N., Teoriya teletrafika: kontseptsii, modeli, prilozheniya (Teletraffic Theory: Concepts, Models, Applications), Moscow: Goryachaya Liniya–Telekom, 2015.

  11. Stepanov, S.N. and Stepanov, M.S., Planning Transmission Resource at Joint Servicing of the Multiservice Real Time and Elastic Data Traffics, Autom. Remote Control, 2017, vol. 78, no. 11, pp. 2004–2015.

    Article  MathSciNet  Google Scholar 

  12. Shorgin, S., Samouylov, K., Gaidamaka, Y., Chukarin, A., Buturlin, I., and Begishev, V., Modeling Radio Resource Allocation Scheme with Fixed Transmission Zones for Multiservice M2M Communications in Wireless IoT Infrastructure, Lecture Notes Comput. Sci., Springer, Cham., 2015, vol. 9012, pp. 473–483.

    Google Scholar 

  13. Begishev, V., Petrov, V., Samuylov, A., Moltchanov, D., Andreev, S., Koucheryavy, Y., and Samouylov, K., Resource Allocation and Sharing for Heterogeneous Data Collection over Conventional 3GPP LTE and Emerging NB-IoT Technologies, IT Comput. Commun., 2018, vol. 120, no. 2, pp. 93–101.

    Article  Google Scholar 

  14. Naumov, V., Gaidamaka, Yu., Yarkina, N., and Samouylov, K., Matrix and Analytical Methods for Performance Analysis ofTelecommunication Systems, Springer Nature, Switzerland, 2021.

    Google Scholar 

  15. Kallos, G.A., Vassilakis, V.G., Moscholios, I.D., and Logothetis, M.D., Performance Modelling of W-CDMA Networks Supporting Elastic and Adaptive Traffic, Proc. of 4 Int. Working Conference on Performance Modelling and Evaluation of Heterogeneous Networks (HET-NETs’06), Ilkley, 2006.

  16. Gudkova, I.A. and Samouylov, K.E., Modelling a Radio Admission Control Scheme for Video Telephony Service in Wireless Networks, Lecture Notes Comput. Sci., 2012, vol. 7469, pp. 208–215.

    Article  Google Scholar 

  17. Bonald, T. and Virtamo, J., A Recursive Formula for Multirate Systems with Elastic Traffic, IEEE Communicat. Lett., 2005, vol. 9, no. 8, pp. 753–755.

    Article  Google Scholar 

  18. Stepanov, S.N. and Stepanov, M.S., Planning the Resource of Information Transmission for Connection Lines of Multiservice Hierarchical Access Networks, Autom. Remote Control, 2018, vol., 79. no. 8, pp. 1422–1433.

    Article  MathSciNet  Google Scholar 

  19. Stepanov, S.N. and Stepanov, M.S., Efficient Algorithm for Evaluating the Required Volume of Resource in Wireless Communication Systems under Joint Servicing of Heterogeneous Traffic for the Internet of Things, Autom. Remote Control, 2019, vol., 80, no. 11, pp. 2017–2032.

    Article  MathSciNet  Google Scholar 

  20. Stepanov, S.N. and Stepanov, M.S., Methods for Estimating the Required Volume of Resource for Multiservice Access Nodes, Autom. Remote Control, 2020, vol., 81, no. 12, pp. 2244–2261.

    Article  MathSciNet  Google Scholar 

  21. Stepanov, S.N., Markov Models with Retrials: The Calculation of Stationary Performance Measures Based on the Concept of Truncation, Math. Comput. Model, 1999, no. 30, pp. 207–228.

  22. Stepanov, S. and Stepanov, M., Estimation of the Performance Measures of a Group of Servers Taking into Account Blocking and Call Repetition Before and After Server Occupation, Mathematics, 2021, vol. 9, no. 21, p. 2811https://doi.org/10.3390/math9212811

  23. Fortet, R., and Grandjean, Ch., Congestion in a Loss System When Some Calls Want Several Devices Simultaneously, Electr. Communicat., 1964, vol. 39, no. 4, pp. 513–526.

    Google Scholar 

  24. Kaufman, J.S., Blocking in a Shared Resource Environment, IEEE Transact. Communicat., 1981, vol. 29, no. 1, pp. 1474–1481.

    Google Scholar 

  25. Chen, J., Chang, Z., Guo, X., Li, R., Han, Z., and Hamalainen, T., Resource Allocation and Computation Offloading for Multi-Access Edge Computing with Fronthaul and Backhaul Constraints, IEEE Transactions on Vehicular Technology, 2021, vol. 70, no. 8, pp. 8037–8049.

    Article  Google Scholar 

  26. Stepanov, S.N., Andrabi, U.M., Stepanov, M.S. and Ndayikunda, J., Reservation Based Joint Servicing of Real Time and Batched Traffic in Inter Satellite Link, Proc. of 2020 Systems of Signals Generating and Processing in the Field of on Board Communications, Moscow, Russia, 2020, pp. 1–5. https://doi.org/10.1109/IEEECONF48371.2020.9078542

  27. Volkov, A.O., Korobkina, A.V. and Stepanov, S.N., Development of Model and Algorithms for Servicing Real-Time and Data Traffic in a Cloud Computing System, Proc. of 2022 Systems of Signals Generating and Processing in the Field of on Board Communications, Moscow, Russia, 2022, pp. 1–6.https://doi.org/10.1109/IEEECONF53456.2022.9744289

Download references

Author information

Authors and Affiliations

  1. Moscow Technical University of Communications and Informatics, Moscow, Russia

    S. N. Stepanov & M. S. Stepanov

Authors
  1. S. N. Stepanov
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. M. S. Stepanov
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding authors

Correspondence to S. N. Stepanov or M. S. Stepanov.

Additional information

This paper was recommended for publication by A.I. Lyakhov, a member of the Editorial Board

Publisher’s Note.

Pleiades Publishing remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Stepanov, S.N., Stepanov, M.S. Approximate Method for Estimating Characteristics of Joint Service of Real-Time Traffic and Elastic Data Traffic in Multiservice Access Nodes. Autom Remote Control 84, 1191–1207 (2023). https://doi.org/10.1134/S0005117923110073

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1134/S0005117923110073

Keywords:

Search

Navigation