Adaptive Rule Engine for Anomaly Detection in 5G Mobile Edge Computing

Abstract

Mobile Edge Computing received significant attention in recent years. MEC can effectively reduce the data transmission pressure from end to cloud, while meeting the requirements of low latency and high bandwidth in 5G scenarios, and has wide application prospects in industrial and medical fields. In this paper, we propose to adopt the deployment of computing resources in the telecom operator's C-RAN (Centralized Radio Access Network) to form a landing solution for MEC. At the same time, it is combined with smart street light equipped with 5G base stations to form the IoT front-end of the C-RAN network for data collection. Finally, an adaptive rule engine is used to routinely monitor data and detect data anomalies in a timely manner. The anomaly monitoring solution can meet the rapid response capability to anomalies in 5G communication.