Author: Yichong Liang, Ping Zhang
Email: yichongliang@mines.edu, pingzhang@mines.edu
Supervised by Dr. Qi Han
This project aims to harness the power of machine learning to predict bandwidth requirements and dynamically allocate resources based on the behavior patterns and usage trends of family members.
Week 1: Setup & Preliminaries (Oct 22)
Project Onboarding: Understand project scope and finalize the deliverables.
Network Assessment: Survey the existing home network architecture and device connectivity.
Data Collection Setup: Implement tools to capture content access logs and real-time network traffic.
Week 2: Data Accumulation & Initial Analysis (Oct 29)
Collect Historical Data: Gather past data on content requests and network bandwidth usage.
Real-time Data Collection: Begin collecting real-time data on user behavior and network traffic.
Preliminary Analysis: Explore initial trends, patterns, and potential challenges in the data.
Week 3: Model Design & Training (Nov 5)
Data Preprocessing: Clean, normalize, and partition the data into training and validation sets.
Model Selection: Experiment with different ML algorithms suitable for bandwidth prediction.
Model Training: Train the chosen algorithm using the training set.
Week 4: Model Validation & Integration (Nov 12)
Model Testing: Evaluate the model's performance on the validation set.
Optimization: Fine-tune the model based on validation results.
System Integration: Incorporate the trained model into the network management system for bandwidth allocation.
Week 5: Prototype Testing & Feedback (Nov 19)
Deploy Test Version: Roll out a prototype of the system in a controlled environment.
Monitor Performance: Track key metrics such as bandwidth usage efficiency and latency.
Gather Feedback: Collect preliminary feedback from users on the perceived network performance.
Week 6: Refinement & Documentation (Nov 26)
Iterative Improvement: Make necessary adjustments based on feedback and test results.
Final Deployment: Launch the enhanced bandwidth allocation system for regular use.
Documentation: Draft a comprehensive guide detailing the system's functionality, user guidelines, and maintenance procedures.