Goal and Outcomes
This course aims to introduce the students to state-of-the-art technologies and architecture. We will introduce the students to modern networking research and guide them to investigate novel ideas in the area via semester-long lectures, practical sessions, and projects. We will also look at industry trends and discuss some innovations that have recently been developed. The course material will be drawn from research papers, industry white papers, and technical reports.
Syllabus (Tentative)
- Introduction to Edge architectures
o Course overview
o Basic notations
- Edge Networking
o SDN Fundamentals and architecture
o NFV Fundamentals and architecture
- IoT Quality of Service
o Impacts of network design
o FAIR Principles
- Resource management in the Edge I
o Resource allocation and scheduling
o Resource availability and volatility
- Resource management in the Edge II
o Resource Provisioning
o Server collaboration
- Workload management in the Edge
o Workload/task placement
o Load balancing and offloading
- Edge Data Analytics
o Large-scale Data Analytics systems
o AI Hardware’s accelerators
- Edge Intelligence I
o AI on Edge of the network
o Distributed Machine Learning
- Edge Intelligence II
o Lightweight ML (e.g.,TensorFlow Lite)
o ML on edge devices (Edge Impulse)
- Data Privacy in Edge
o Centralized vs. Distributed architecture security
o Security by design towards Federated Learning
- Federated Learning I
o Federated Learning architectures
o Federated Learning open-source frameworks (TensorFlow Federated, FedML, FEDn, FLOWER)
- Federated Learning II
o Federated Learning algorithms with FedAvg
o Vertical and Horizontal Data Partitioning
- Federated Learning III
o Federated Learning communication efficiency
o Weight of weight for FL, Client Contribution
- New trends in Edge architectures
o Microservice architectures, IoT registry,
o Blockchain technology
- Course project work and presentations
o Title and abstraction
o Evaluation I and discussion
o Evaluation II and Presentation
Practical sessions can be found here!!
- There will be guest lectures (TBA)