BANDWIDTH MODELING ON SMART CAMPUS BASED ON ENGINEERING METHOD – STATISTICS

  • Ewi Ismaredah (1*) Universitas Islam Negeri Sultan Syarif Kasim
  • Hasdi Radiles (2) Universitas Islam Negeri Sultan Syarif Kasim

  • (*) Corresponding Author
Keywords: Internet traffic generation, Traffic Shaping, Bandwidth allocation, statistical-engineering method

Abstract

The importance of generating internet traffic as one of the basic considerations in bandwidth allocation policies between faculties is increasing due to the number of students who complain about connection services on campus. This study proposes internet traffic generation based on the statistical - engineering method. The population is calculated based on class capacity in each faculty, as the main alibi of student attendance on campus where traffic arrivals are generated based on the arrival model through information on possible scheduling variations. Although internet services have different characteristics, they are physically determined by the bitrate and idle mode in the traffic time series. The results show recommendations in three application bitrate categories, namely 200kbps, 400kbps, and 800kbps Traffic Shaping.

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References

Adeyemi, O. J., Popoola, S. I., Atayero, A. A., Afolayan, D. G., Ariyo, M., & Adetiba, E. (2018). Exploration of daily Internet data traffic generated in a smart university campus. Data in Brief, 20, 30–52. https://doi.org/10.1016/j.dib.2018.07.039

Alam, T., Alharbi, Y. M., Abusallama, F. A., & Hakeem, A. O. (2020). Smart Campus Mobile Application Toward the Development of Smart Cities. International Journal of Applied Sciences and Smart Technologies, 2(1), 75–88. https://doi.org/10.2139/ssrn.3638973

Anggrawan, A., Satria, C., & Husain, H. (2018). Smart Campus: Model Baru Enterprise Architecture STMIK Bumigora Mataram dalam Manajement Tata Kelola TIK Berbasis TOGAF ADM. Jurnal Mantik Penusa, 2(2), 127–136. https://e-jurnal.pelitanusantara.ac.id/index.php/mantik/article/view/476

Feng, S., Wong, Y. K., Wong, L. Y., & Hossain, L. (2019). The Internet and Facebook Usage on Academic Distraction of College Students. Computers and Education, 134, 41–49. https://doi.org/10.1016/j.compedu.2019.02.005

Herianto, H., & Vega, H. (2021). Implementasi Neural Network Untuk Membangun Model Prediksi Kebutuhan Bandwidth Dan Spesifikasi. Jurnal Sains & Teknologi Fakultas Teknik, 11(3), 56–64. http://repository.unsada.ac.id/2361/1/06-Herianto- Jurnal-Implementasi Neural Network Untuk Membangun Model Prediksi Kebutuhan Bandwidth Dan Spesifikasi.pdf

Herwin, H., & Andesa, K. (2021). Penerapan Manajemen Bandwidth Berdasarkan PPPoE Pada Pondok Pesantren Miftahul Huda. SATIN-Sains Dan Teknologi Informasi, 7(2), 121–128. http://register.stmik-amik-riau.ac.id/index.php/satin/article/view/778

Mahmood, I., Quair-tul-ain, Nasir, H. A., Javed, F., & Aguado, J. A. (2020). A hierarchical multi-resolution agent-based modeling and simulation framework for household electricity demand profile. Simulation, 96(8), 655–678. https://doi.org/10.1177/0037549720923401

Markelov, O., Nguyen Duc, V., & Bogachev, M. (2017). Statistical modeling of the Internet traffic dynamics: To which extent do we need long-term correlations? Physica A: Statistical Mechanics and Its Applications, 485(1), 48–60.

Marnerides, A. K., Pezaros, D. P., & Hutchison, D. (2018). Internet traffic characterisation: Third-order statistics & higher-order spectra for precise traffic modelling. Computer Networks, 134, 183–201. https://doi.org/10.1016/j.comnet.2018.01.050

Shiraki, H., Nakamura, S., Ashina, S., & Honjo, K. (2016). Estimating the hourly electricity profile of Japanese households – Coupling of engineering and statistical methods. Energy, 114(1), 478–491. https://doi.org/10.1016/j.energy.2016.08.019

Sihotang, J. I. (2019). Pemodelan Background Traffic Pada Jaringan Berkapasitas Terbatas. TeIKa, 9(1), 53–62. https://jurnal.unai.edu/index.php/teika/article/view/785

Singichetti, B., Conklin, J. L., Hassmiller Lich, K., Sabounchi, N. S., & Naumann, R. B. (2021). Congestion Pricing Policies and Safety Implications: a Scoping Review. Journal of Urban Health, 98(6), 754–771. https://doi.org/10.1007/s11524-021-00578-3

Tampubolon, J. A., Suhada, S., Safii, M., Poningsih, P., & Efendi, B. (2022). Optimasi Bandwidth Menggunakan Metode Peer Connection pada Dinas Lingkungan Hidup Pematangsiantar. Jurnal Ilmu Komputer Dan Teknologi, 2(2), 27–32. https://doi.org/10.35960/ikomti.v2i2.705

Wohn, D. Y., & Ahmadi, M. (2019). Motivations and habits of micro-news consumption on mobile social media. Telematics and Informatics, 44, 101262. https://doi.org/10.1016/j.tele.2019.101262

Yadav, S. K., & Akhter, Y. (2021). Statistical Modeling for the Prediction of Infectious Disease Dissemination With Special Reference to COVID-19 Spread. Frontiers in Public Health, 9(June), 1–27. https://doi.org/10.3389/fpubh.2021.645405

Published
2022-06-20
How to Cite
Ismaredah, E., & Radiles, H. (2022). BANDWIDTH MODELING ON SMART CAMPUS BASED ON ENGINEERING METHOD – STATISTICS. Jurnal Riset Informatika, 4(3), 269-276. https://doi.org/10.34288/jri.v4i3.386
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