IDEAS home Printed from https://ideas.repec.org/a/gam/jmathe/v10y2022i14p2536-d868152.html
   My bibliography  Save this article

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
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-7390/10/14/2536/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2227-7390/10/14/2536/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    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.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Steffen Westermann & Scott J. Niblock & Jennifer L. Harrison & Michael A. Kortt, 2020. "Financial Advice Seeking: A Review of the Barriers and Benefits," Economic Papers, The Economic Society of Australia, vol. 39(4), pages 367-388, December.
    2. Gábor Pintér & Chaojun Wang & Junyuan Zou, 2021. "Size Discount and Size Penalty Trading Costs in Bond Markets," Discussion Papers 2114, Centre for Macroeconomics (CFM).
    3. Bierman, Alex & Upenieks, Laura & Glavin, Paul & Schieman, Scott, 2021. "Accumulation of economic hardship and health during the COVID-19 pandemic: Social causation or selection?," Social Science & Medicine, Elsevier, vol. 275(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jmathe:v:10:y:2022:i:14:p:2536-:d:868152. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.