研究目的
To describe the implementation of data analysis for GPON frames transmitted over passive optical networks, addressing the lack of accessible analysis tools due to high costs and licensing issues.
研究成果
The system effectively analyzes GPON traffic, detecting abnormalities and processes defined in the G.984 recommendation. However, optimization is needed for JSON creation with large datasets.
研究不足
The critical part of data processing in Python, creating JSON format for the website, becomes time-consuming with an increasing count of frames in the database.
1：Experimental Design and Method Selection:
The system captures GPON frames using an FPGA card, stores them in a Microsoft SQL database, and analyzes them using Python scripts.
2：Sample Selection and Data Sources:
Traffic from a passive optical network is captured, focusing on communication between OLT and ONUs.
3：List of Experimental Equipment and Materials:
FPGA card, Microsoft SQL server, Python programming language.
4：Experimental Procedures and Operational Workflow:
Frames are captured, stored, and analyzed for abnormalities based on ITU-T G.984 recommendations.
5：Data Analysis Methods:
Python scripts compare frames against standards to detect abnormalities, with results presented in HTML tables.
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