Perancangan dan Implementasi Sistem Multi-Access Edge Computing dengan Use Case Face Mask Detection pada Open RAN SmartLab Politeknik Negeri Jakarta

Authors

  • Akita Hasna Mayanti Politeknik Negeri Jakarta
  • Raviadin Nugroho Politeknik Negeri Jakarta
  • Asri Wulandari Politeknik Negeri Jakarta
  • Alfin Hikmaturokhman Institut Teknologi Telkom Purwokerto https://orcid.org/0000-0001-7643-9149

DOI:

https://doi.org/10.61769/telematika.v18i2.619

Keywords:

Open RAN, use case, latency, akses-jamak komputasi tepi, deteksi masker wajah, virtualisasi jaringan, multi-access edge computing, face mask detection, network virtualization

Abstract

Multi-access edge computing (MEC) telah muncul sebagai topik hangat dalam beberapa tahun terakhir yang bertepatan dengan kemajuan teknologi jaringan 5G. MEC yang dirancang memanfaatkan infrastruktur jaringan pada SmartLab Politeknik Negeri Jakarta. MEC dibangun dengan tujuan untuk mengurangi latency dan mempercepat transfer data antara perangkat dan server untuk mendukung proses pembelajaran pada SmartLab Politeknik Negeri Jakarta. Sistem ini dibangun dengan menggunakan jaringan Open RAN dan server sebagai platform MEC untuk memproses konten dengan komputasi tepi terdistribusi yang berjalan di atas infrastruktur virtualisasi dan terletak di tepi jaringan. Use case face mask detection secara real-time diakses ketika use case sedang running. Pengujian dilakukan dengan menentukan skenario implementasi dan membandingkan downlink, uplink, dan latency sebagai parameter perbandingan multi-access edge computing. Keberhasilan use case face mask detection pada infrastruktur MEC juga dilihat. Setelah menjalankan skenario pengujian, didapatkan hasil bahwa multi-access edge computing memiliki nilai maksimal untuk downlink sebesar 21,70 Mbps, nilai uplink maksimal 22,70 Mbps, dan nilai latency maksimal sebesar 15 ms. Selain itu, implementasi use case face mask detection pada skenario pengujian berhasil dijalankan pada infrastuktur MEC.

 

Multi-access edge computing (MEC) has emerged as a hot topic in recent years which coincides with the advancement of 5G network technology. The designed MEC utilizes the network infrastructure in the SmartLab of Politeknik Negeri Jakarta. MEC is built to reduce latency and accelerate data transfer between devices and servers to support the learning process at SmartLab Politeknik Negeri Jakarta. The system uses an Open RAN network and server as an MEC platform to process content with distributed edge computing running on top of virtualization infrastructure and located at the network edge. The face mask detection use case is accessed in real time when the use case is running. Tests were conducted by defining implementation scenarios and comparing downlink, uplink, and latency as multi-access edge computing comparison parameters. The success of the face mask detection use case on the MEC infrastructure is also examined. After running the test scenario, it was found that multi-access edge computing has a maximum value for downlink of 21.70 Mbps, a maximum uplink value of 22.70 Mbps, and a maximum latency value of 15 ms. In addition, the face mask detection use case implementation in the test scenario was successfully run on the MEC infrastructure.

Author Biographies

Akita Hasna Mayanti, Politeknik Negeri Jakarta

Prodi Broadband Multimedia, Jurusan Teknik Elektro

Raviadin Nugroho, Politeknik Negeri Jakarta

Prodi Broadband Multimedia, Jurusan Teknik Elektro

Asri Wulandari, Politeknik Negeri Jakarta

Prodi Broadband Multimedia, Jurusan Teknik Elektro

Alfin Hikmaturokhman, Institut Teknologi Telkom Purwokerto

Prodi Teknik Telekomunikasi

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Published

2024-01-19

Issue

Section

Articles