Nonlinear Analysis for Automation Purposes in Computer Networks

Milan Milivojević – Academy of Technical and Art Applied Studies Belgrade (ATUSS) – Department ICT College for Vocational Studies, Zdravka Čelara, 16, 11000, Belgrade, Republic of Serbia

Milan Pavlović – Academy of Technical and Art Applied Studies Belgrade (ATUSS) – Department ICT College for Vocational Studies, Zdravka Čelara, 16, 11000, Belgrade, Republic of Serbia

Marija Zajeganović – Academy of Technical and Art Applied Studies Belgrade (ATUSS) – Department ICT College for Vocational Studies, Zdravka Čelara, 16, 11000, Belgrade, Republic of Serbia

Abstract: Automated network management processes have become more common in recent years. The main goal of automation is to efficiently configure a computer network. This is especially true when software and hardware prob­lems require a rapid response. In this context, selecting appropriate features to serve as inputs for machine learning algorithms is important. It is important to choose the most appropriate features that can help in the event of a network disruption, such as a component failure that requires network equipment to be reconfigured or emerging security threats. One of the key metrics that provides insight into the state of a computer network is round-trip time (RTT). The sequence of RTT data serves as a fundamental basis for extracting relevant features. While linear analysis provides basic features, the complex nature of these processes requires more advanced analytical methods. Nonlinear time series analysis naturally becomes necessary. Features extracted using these methods provide a much more accurate assessment of the network’s state. This paper presents the application of fractal analysis for feature extraction to assess network conditions and automate network configuration processes. Fractal analysis, a well-established nonlinear method, is widely recognized in the literature. This paper explores the potential of applying fractal analysis to time series containing RTT data. Simulations were performed using the GNS3 network simulator and the Python programming language.

8th International Scientific Conference on Recent Advances in Information Technology, Tourism, Economics, Management and Agriculture – ITEMA 2024 – Conference Proceedings, Hybrid (Zayed University, Dubai, UAE), October 24, 2024

ITEMA Conference Proceedings published by: Association of Economists and Managers of the Balkans – Belgrade, Serbia

ITEMA conference partners: Faculty of Economics and Business, University of Maribor, Slovenia; Faculty of Organization and Informatics, University of Zagreb, Varaždin; Faculty of Geography, University of Belgrade, Serbia; Institute of Marketing, Poznan University of Economics and Business, Poland; Faculty of Agriculture, Banat’s University of Agricultural Sciences and Veterinary Medicine ”King Michael I of Romania”, Romania

ITEMA Conference 2024 Conference Proceedings: ISBN 978-86-80194-89-9, ISSN 2683-5991, DOI: https://doi.org/10.31410/ITEMA.2024

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