Network traffic management based on differentiated and integrated services

DOI: 10.31673/2412-4338.2020.046068

Abstract

The problem of traffic control and management for the purpose of forecasting and prevention of congestion of a telecommunication network is considered. The definition of the concept of traffic policy is given. The solution of traffic control problems is based on the application of a policy that allows the harmonious distribution of information flow. A promising way to prevent congestion is the management of traffic parameters ‒ policing and shaping, i.e the management of statistical characteristics of traffic. The necessity of using probabilistic and statistical methods of traffic control, based on correlation and regression analysis, is substantiated. The concept of end-to-end network diagnostics is considered. End-to-end management includes network management as a whole, congestion management and traffic parameters management.
Further development of traffic policy is the use of differentiated and integrated services. The method involves the dynamic allocation of bandwidth of transmission channels between users based on their priorities. This approach avoids periodic local congestion of routes that have been identified as optimal at the current stage. The algorithm involves the selection of routes according to the criterion of equable loading of transmission lines. To implement a policy of traffic with differentiated services, it is necessary to solve the problem of flow distribution between locally optimal or quasi-optimal routes in real time.
The process model of the total flow formation due to the imposition of separate flows from different sources is considered. It is shown that, under the conditions of maintaining the balance of network flows the intensities of flows to nodes with limited buffer memory exceed the corresponding intensity of the network with unlimited memory. This saves storage and reduces packet delays due to latency in switching buffers.

Keywords: traffic policy, congestion control, differentiated and integrated services, end-to-end management, flow distribution, packet buffer, flow balance, routing.

References
1. Tanenbaum A. S., and Wetherall D. J. (2011). Computer Networks. 5th ed. Prentice Hall, Cloth. 960 p.
2. Shuangyin Ren, Quanyou Feng, Yu Wang, and Wenhua Dou. (2017). A Service Curve of Hierarchical Token Bucket Queue Discipline on Soft-Ware Defined Networks Based on Deterministic Network Calculus: An Analysis and Simulation. Journal of Advances in Computer Networks. V.5, No.1. P. 8-12.
3. Rodionov S.S., and Udovikin. (1979). Identification of disturbing influences at the input of the receiving device. Kiev: Znaniye. 36 p.
4. Wilson E. (2002). Monitoring and Analysis of Networks. Troubleshooting Methods. Moscow: Lori. 363 p.
5. Savchenko A.S. (2011). Conceptual Model of a Large Corporate Network Management Systemю. Problems of Informatization and Management. Kyiv: NAU. No. 2(34). P. 120-128.
6. Chang Shu, and Nick A. Vinogradov. (2010). The Method of Adaptive Shaping of the Traffic Flows of Calculating Networks. Proceedings the Fourth Congress “Aviation in the XXI Century”, (Safety in Aviation and Space Technologies), Kiev, National aviation university, 2010, Sept. 21-23. V.1. – P. 18.13 – 18.16.
7. Danyluk A., Provost F.J., Carr B. (2002). Telecommunication Network Diagnosis. In Handbook of Data Mining and Knowledge Discovery. Oxford University Press. 1064 p.
8. Policing and Shaping Overview. Cisco IOS Quality of Service Solutions Configuration Guide QC-222.
https://www.cisco.com/c/en/us/td/docs/ios/12_2/qos/configuration/guide/fqos_c/qcfpolsh.pdf
9. Comparing Traffic Policing and Traffic Shaping for Bandwidth Limiting. https://www.cisco.com/c/en/us/support/docs/quality-of-service-qos/qos-policing/19645-policevsshape.html
10. Kozelkova E.S., Toroshanko Ya.I., and Kharlai L.A. (2016). Data flow control in digital telecommunication networks with heterogeneous traffic. Bulletin of the National University "Lvivska Politechnika". Series "Radioelectronics and Telecommunications". No. 849. P. 210-217.
11. Giambene G. (2014). Queuing Theory and Telecommunications: Networks and Applications: 2nd edition. Springer NY. 512 p.
12. Stallings W. (2016). Foundations of Modern Networking: SDN, NFV, QoE, IoT, and Cloud. Pearson Education, Inc., Old Tappan, New Jersey. 538 p.
13. Mykytyshyn A.H., Mytnyk M.M., and P.D. Stukhliak (2017). Telecommunication Systems and Networks. Ternopil: Ternopil National Technical University of Ivan Puliui. 384 p.
14. Cui Y., Xiao S., Liao C., Stojmenovic I., and Li M. (2013). Data Centers as Software Defined Networks: Traffic Redundancy Elimination with Wireless Cards at Routers. IEEE Journal on Selected Areas in Communications. V.31, No.12. P. 1-15.
15. Kolmogorov A.N., and S.V. Fomin S.V. (1981). Elements of the theory of functions and functional analysis. Moscow: Nauka, 1981. 543 p.
16. Vinogradov N.A., and Zembitskaya A.S. (2004). Analysis and calculation of characteristics of data traffic passing in converged networks. Problems of the systemic approach to the economy. Kiev: NAU. Issue 9. P.18-26.