USING TIME SCALES WHILE APPROXIMATING THE LENGTH OF COMPUTER NETWORKS
AbstractThe subject of the research is to predict the queue length for the communication device of a high-speed computer network with non-Gaussian traffic. The goal of this article is to examine the probabilities of the application of time scales used to study the organization of queues of modern high-speed computer networks. The following methods were used: the fractal analysis, scaling methods, methods of approximation. The following results were achieved: the results of the time scale selection for constructing adequate models of modern traffic were presented. The use of such models, in particular, enables studying the dynamics of the queues of active network devices, which is important for planning and distributing the network load. The use of statistical characteristics of traffic on a small number of time scales enables expanding theoretical concepts for critical time scales, which makes this approach applicable to any traffic process including the long-term traffic. In addition, the issues of describing the behaviour of queue tails for modern high-speed computer networks are considered and the properties of the proposed model approximations are determined. The analysis of the independent Gaussian model of a wavelet domain and the multifractal wavelet model showed the advantage of the first one for the fractal traffic and a slight discrepancy in the results for traffic close to the Gaussian one. Conclusions. Various approaches to the selection of time scales used in the study of the organization of queues of modern high-speed data networks were studied. The effect of the necessary accuracy and computational power required for calculating the maximum approximation were analyzed and it was established that exponential time scales are optimal for the fractal traffic. The impact of the tails of distributions in different time scales on the process of queue organization was also shown. It was noted that in the context of non-Gaussian traffic scenarios, the correlation structure (both short-term and long-term ones) does not describe the queues behaviour adequately enough.
Crovella, M., Bestavros, А. (1997), "Self-similarity in World Wide Web trafﬁc: evidence and possible causes", IEEE/ACM Transactions on Networking, vol. 5, Р. 835–846.
Kuchuk, G., Kharchenko, V., Kovalenko, A. and Ruchkov, E. (2016), “Approaches to selection of combinatorial algorithm for optimization in network traffic control of safety-critical systems”, East-West Design & Test Symposium (EWDTS), P. 1–6. Doi: https://doi.org/10.1109/EWDTS.2016.7807655.
Willinger, W., Taqqu, M. S., Sherman, R., Wilson, D. V. (1991), "Self-Similarity Through High-Variability: Statistical Analysis of Ethernet LAN Traffic at the Source Level", ACM SIGCOMM’91, Р. 149–157.
Leland, W., Taqqu, М., Willinger, W. (1997), "On the self-similar nature of IP-trafic", IEEE/ACM Transactions on Networking, No. 3, P. 423–431.
Kuchuk, G. A., Mozhayev, A. A., Pashchenko, R. E. and other. (2006), Fractal analysis of processes, structures and signals: Collective monograph [Fraktal’nyy analiz protsessov, struktur i signalov: Kollektivnaya monografiya], Kharkiv : EkoPerspektiva, 360 p.
Kuchuk, G. A., Kovalenko, A. A., Mozhaev, A. A. (2010), "An Approach to Development of Complex Metric for Multiservice Network Security Assessment", Statistical Methods of Signal and Data Processing (SMSDP – 2010): Proceedings of Int. Conf., NAU, RED, IEEE Ukraine section joint SP, Kyiv, P. 158–160.
Kovalenko, А., Kuchuk, H. (2018), "Methods for synthesis of informational and technical structures of critical application object’s control system", Advanced Information Systems, Vol. 2, No. 1, P. 4–9. Doi: https://doi.org/10. 20998/2522-9052.2018.1.04.
Papagiannaki, K., Moon, S., Fraleigh, С., Tobagi, F., Diot, C. (2002), "Analysis of measured single-hop delay from an operational backbone network", Proc. IEEE INFOCOM, Р. 535–544.
Kuchuk, G. А. (2013), "Method of corporate multiservice networkcoherent fragment informative structure synthesis", Scientific Works of Kharkiv National Air Force University, No. 2 (35), P. 97–102.
Fraleigh, С., Tobagi, F., Diot, C. (2003), Provisioning IP backbone networks to support latency sensitive traffic, Proc. IEEE INFOCOM. Р. 375–385.
Norros, I. (1994), "A storage model with self-similar input", Queueing Syst, vol. 16, Р. 387–396.
Kosenko, V. (2017), "Mathematical model of optimal distribution of applied problems of safety-critical systems over the nodes of the information and telecommunication network", Advanced Information Systems, Vol. 1, No. 2, P. 4–9. Doi: https://doi.org/10. 20998/2522-9052.2017.2.01.
Ruban, I., Kuchuk, H., Kovalenko, A. (2017), “Redistribution of base stations load in mobile communication networks”, Innovative Technologies and Scientific Solutions for Industries, No. 1 (1), P. 75–81. Doi: https://doi.org/10.30837/2522-9818.2017.1.075
Neidhardt, A. L., Wang, J. L. (1998), "The concept of relevant time scales and its application to queueing analysis of self-similar traffic", Proc. ACM SIGMETRICS, Р. 222–232.
Kosenko, V. V. (2017), “Principles and structure of the methodology of risk-adaptive management of parameters of information and telecommunication networks of critical application systems”, Innovative Technologies and Scientific Solutions for Industries, No. 1 (1), P. 75–81. Doi: https://doi.org/10.30837/2522-9818.2017.1.046
Kuchuk, G., Kovalenko, A., Kharchenko, V., Shamraev, A. (2017), "Resource-oriented approaches to implementation of traffic control technologies in safety-critical I&C systems", Green IT Engineering: Components Network and Systems Implementation, Springer International Publishing, Vol. 105, P. 313–338.
Erramilli, A., Narayan, O., Neidhardt, A., Sanjee, I. (2000), "Performance impacts of multi-scaling in wide area TCP/IP traffic", Proc. IEEE INFOCOM, Р. 352–359.
Debicki, K., Rolski, T.(2002), "A note on transient Gaussian fluid models", Queueing Syst, vol. 41, Р. 321–342.
Abstract views: 298 PDF Downloads: 40
Our journal abides by the Creative Commons copyright rights and permissions for open access journals.
Authors who publish with this journal agree to the following terms:
Authors hold the copyright without restrictions and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License (CC BY-NC-SA 4.0) that allows others to share the work with an acknowledgment of the work's authorship and initial publication in this journal.
Authors are able to enter into separate, additional contractual arrangements for the non-commercial and non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgment of its initial publication in this journal.
Authors are permitted and encouraged to post their published work online (e.g., in institutional repositories or on their website) as it can lead to productive exchanges, as well as earlier and greater citation of published work.