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Behavioral Study of Software-Defined Network Parameters Using Exploratory Data Analysis and Regression-Based Sensitivity Analysis

Author

Listed:
  • Mobayode O. Akinsolu

    (Faculty of Arts, Science and Technology, Wrexham Glyndŵr University, Wrexham LL11 2AW, UK)

  • Abimbola O. Sangodoyin

    (School of Mathematics and Computer Science, University of Wolverhampton, Wolverhampton WV1 1LY, UK)

  • Uyoata E. Uyoata

    (Department of Electrical and Electronics Engineering, Modibbo Adama University, Yola P.M.B. 2076, Nigeria)

Abstract

To provide a low-cost methodical way for inference-driven insight into the assessment of SDN operations, a behavioral study of key network parameters that predicate the proper functioning and performance of software-defined networks (SDNs) is presented to characterize their alterations or variations, given various emulated SDN scenarios. It is standard practice to use simulation environments to investigate the performance characteristics of SDNs, quantitatively and qualitatively; hence, the use of emulated scenarios to typify the investigated SDN in this paper. The key parameters studied analytically are the jitter, response time and throughput of the SDN. These network parameters provide the most vital metrics in SDN operations according to literature, and they have been behaviorally studied in the following popular SDN states: normal operating condition without any incidents on the SDN, hypertext transfer protocol (HTTP) flooding, transmission control protocol (TCP) flooding, and user datagram protocol (UDP) flooding, when the SDN is subjected to a distributed denial-of-service (DDoS) attack. The behavioral study is implemented primarily via univariate and multivariate exploratory data analysis (EDA) to characterize and visualize the variations of the SDN parameters for each of the emulated scenarios, and linear regression-based analysis to draw inferences on the sensitivity of the SDN parameters to the emulated scenarios. Experimental results indicate that the SDN performance metrics (i.e., jitter, latency and throughput) vary as the SDN scenario changes given a DDoS attack on the SDN, and they are all sensitive to the respective attack scenarios with some level of interactions between them.

Suggested Citation

  • Mobayode O. Akinsolu & Abimbola O. Sangodoyin & Uyoata E. Uyoata, 2022. "Behavioral Study of Software-Defined Network Parameters Using Exploratory Data Analysis and Regression-Based Sensitivity Analysis," Mathematics, MDPI, vol. 10(14), pages 1-24, July.
    • Handle: RePEc:gam:jmathe:v:10:y:2022:i:14:p:2536-:d:868152
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    References listed on IDEAS

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    1. John Luke Gallup, 2019. "Added-variable plots with confidence intervals," Stata Journal, StataCorp LP, vol. 19(4), pages 598-614, December.
    2. John Luke Gallup, 2019. "Added-variable plots with confidence intervals," Stata Journal, StataCorp LP, vol. 19(3), pages 598-614, September.
    3. Joost R. Ginkel, 2020. "Standardized Regression Coefficients and Newly Proposed Estimators for $${R}^{{2}}$$R2 in Multiply Imputed Data," Psychometrika, Springer;The Psychometric Society, vol. 85(1), pages 185-205, March.
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    Cited by:

    1. Wancheng Xie & Andrew Chapman & Taihua Yan, 2023. "Do Environmental Regulations Facilitate a Low-Carbon Transformation in China’s Resource-Based Cities?," IJERPH, MDPI, vol. 20(5), pages 1-23, March.

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