Modeling Internet Traffic Packet Length Using Probdistid: a Case Study
Modeling Internet Traffic Packet Length Using Probdistid: a Case Study
Autori:
Izdanje: Sinteza 2023 - International Scientific Conference on Information Technology and Data Related Research
DOI: 10.15308/Sinteza-2023-172-177
Oblast: Advanced Technologies and Applications Session
Stranice: 172-177
Apstrakt:
n this study, we apply the ProbDistID tool, a user-friendly tool based on nonlinear regression, designed for fitting probability distributions and estimating their parameters, to model internet traffic packet length using a real-world internet traffic dataset. The tool requires no a priori knowledge of input data, making it suitable for real-time fitting recognition and for data mining tasks. Our primary objectives in this case study are to identify distributions that offer the best fit for internet traffic datasets. We utilized our tool to fit and estimate parameters for eight cumulative density functions (CDFs). The fitting results are presented using utilized several model selection methods and goodness-of-fit tests to determine the most appropriate distri- bution model. The case study indicate that the Generalized Extreme Value (GEV) and Pareto distributions provide the most accurate fit. Our findings are presented graphically and in tabular form, demonstrating the effectiveness of ProbDistID and its potential applicability across various fields, including data mining tasks.
Ključne reči: Data Mining, Internet Traffic, Nonlinear Regression, Cumulative Distribution Function, Model Selection
Priložene datoteke:
- US - SINTEZA - 2023 - RAD 25 - 172-177 ( veličina: 392,19 KB, broj pregleda: 167 )
Kategorije objave:
Radovi na konferenciji Sinteza 2023, Beograd, Srbija
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BibTeX format
@article{article, author = {D. Miljković, S. Ilić, B. Jakšić, P. Milić and S. Pitulić}, title = {Modeling Internet Traffic Packet Length Using Probdistid: a Case Study}, journal = {Sinteza 2023 - International Scientific Conference on Information Technology and Data Related Research}, year = 2023, pages = {172-177}, doi = {10.15308/Sinteza-2023-172-177} }
RT Conference Proceedings A1 Dragiša Miljković A1 Siniša Ilić A1 Branimir Jakšić A1 Petar Milić A1 Stefan Pitulić T1 Modeling Internet Traffic Packet Length Using Probdistid: a Case Study AD Univerzitet Singidunum, Beograd, Beograd, Srbija YR 2023 NO doi: 10.15308/Sinteza-2023-172-177
D. Miljković, S. Ilić, B. Jakšić, P. Milić and S. Pitulić, Modeling Internet Traffic Packet Length Using Probdistid: a Case Study, Univerzitet Singidunum, Beograd, 2023, doi:10.15308/Sinteza-2023-172-177