<![CDATA[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.]]>
Copyrights © 2023
