README.md



LMS using Machine Learning Base Station Selection and Edge Contents Caching

머신러닝 기반 최적 기지국 선택기법과 엣지 콘텐츠 캐싱을 활용한 LMS 
2020-1 Capstone Design2 Project 
https://github.com/yhye97/lms 


Motivation:

LMS that provides effective mobile traffic distribution and increase contents delivery speed


Assumptions:


Students access LMS according to their School's Timetable
Students access LMS near their school
Base Stations have MEC(Mobile Edge Computing) Server


Requirement:


Dataset: 
Telecom Italia Big Data Challenge set (https://dandelion.eu/datamine/open-big-data/)  
(Grid 1,2,3 == BS 1,2,3) 


Background:


Mobile Traffic Prediction & BS Selection Algorithm: 
Python 3.5 
Jupyter Notebook 
Keras 
WEB:
Express Framework 
Back-end : Node JS 
Front-end: HTML/CSS/JS 

AWS: 


EC2 instance: LMS Web Server, Controller 
S3: Contents Storage 
RDS : Database 
CloudFront: CDN Service 
Edge Location: Base Station