Comparative analysis of software defined network performance and conventional based on latency parameters
DOI:
10.33395/sinkron.v7i2.11424Abstract
Software Defined Network (SDN) offers convenience in managing network devices by simply setting the software control plane so as to reduce the complexity of network configuration. However, the ease of management offered is not always accompanied by an increase in network performance when compared to conventional network architectures. This study will perform a performance comparison analysis between networks with SDN architecture (OpenFlow) and conventional architecture. The research methods applied are: topology implementation on Mininet, network simulation and data collection, data analysis, and comparative analysis. Network performance testing is carried out based on latency parameters that are simulated in one subnet using the Mininet emulator. From the results of the latency test, it is found that the average latency on the SDN network is 0.119ms, while the average latency on the conventional network is 0.09588ms. Based on these results, it can be concluded that the network topology that has better performance based on latency parameters is a conventional network topology with an average latency value of 0.09588ms.
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References
Anam, K., & Adrian, R. (2017). Analisis Performa Jaringan Software Defined Network Berdasarkan Penggunaan Cost Pada Protokol Ruting Open Shortest Path First. CiITEE, 1–8.
Banjar, A., Pupatwibul, P., Braun, R., & Moulton, B. (2014). Analysing the performance of the OpenFlow standard for software-defined networking using the OMNeT++ network simulator. https://doi.org/10.1109/APCASE.2014.6924467
Eissa, H. A., Bozed, K. A., & Younis, H. (2019). Software Defined Networking. 2019 19th International Conference on Sciences and Techniques of Automatic Control and Computer Engineering (STA), 620–625. https://doi.org/10.1109/STA.2019.8717234
ETSI. (2018). Achieving the lowest latency for delay-sensitive traffic. Retrieved April 15, 2022, from etsi.org website: https://www.etsi.org/newsroom/blogs/entry/achieving-the-lowest-latency-for-delay-sensitive-traffic
Gallenmüller, S., Naab, J., Adam, I., & Carle, G. (2020). 5G QoS: Impact of Security Functions on Latency. NOMS 2020 - 2020 IEEE/IFIP Network Operations and Management Symposium, 1–9. https://doi.org/10.1109/NOMS47738.2020.9110422
Haleplidis, E., Pentikousis, K., Denazis, S., Salim, J., Meyer, D., & Koufopavlou, O. (2015). RFC 7426: Software-Defined Networking (SDN): Layers and Architecture Terminology. IRTF.
Hernandez, L., Jimenez, G., Pranolo, A., & Rios, C. U. (2019). Comparative Performance Analysis Between Software-Defined Networks and Conventional IP Networks. 2019 5th International Conference on Science in Information Technology (ICSITech), 235–240. https://doi.org/10.1109/ICSITech46713.2019.8987493
Heryanto, A., & Afrilia. (2016). Software Defined Network Menggunakan Simulator. Kntia, (33), 5–8. Retrieved from https://www.seminar.ilkom.unsri.ac.id/index.php/kntia/article/view/1142
IEEE. (2017). Overview of RFC7426: SDN Layers and Architecture Terminology. Retrieved from sdn.ieee.org website: https://sdn.ieee.org/newsletter/september-2017/overview-of-rfc7426-sdn-layers-and-architecture-terminology
Iskandar, I., & Hidayat, A. (2015). Analisa Quality of Service (QoS) Jaringan Internet Kampus (Studi Kasus: UIN Suska Riau). Jurnal CoreIT, 1(2), 67–76.
Nugroho, H., Irfan, M., & Faruq, A. (2019). Software Defined Networks: a Comparative Study and Quality of Services Evaluation. Scientific Journal of Informatics, 6, 181–192. https://doi.org/10.15294/sji.v6i2.20585
Ummah, I. (2016). Perancangan Simulasi Jaringan Virtual Berbasis Software-Define Networking. Indonesian Journal on Computing (Indo-JC), 1(1), 95–106. https://doi.org/10.21108/indojc.2016.1.1.20
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Copyright (c) 2022 Raja Pahlevi Harahap, Deci Irmayani, Rahma Muti’ah
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