Course Outline
The course begins by establishing the foundational principles of 6G and edge computing.
- Overview of 6G technology and its development roadmap
- Core concepts of edge computing and various deployment models
- The 6G–Edge–Cloud continuum and paradigms of distributed computing
Next, we examine the architecture of the intelligent edge.
- Essential components of edge systems, including compute, storage, and networking
- Integration strategies for IoT sensors, gateways, and 6G connectivity
- Managing edge orchestration and service lifecycle
We then delve into the specific capabilities and enabling technologies of 6G.
- Utilizing terahertz spectrum for low-latency communications
- Implementing AI-native network management and intent-driven orchestration
- Applying network slicing and dynamic resource allocation for edge workloads
The curriculum explores data handling and AI integration at the edge.
- Techniques for federated learning and distributed AI processing
- Designing real-time analytics and event-driven architectures
- Addressing data governance and privacy within multi-domain edge systems
Attention turns to collaboration models between the edge and the cloud.
- Strategies for hybrid and multi-cloud integration
- Optimizing latency through offloading and caching techniques
- Leveraging APIs, microservices, and container-based deployment
Security and trust are central to distributed edge networks.
- Implementing identity, authentication, and zero-trust frameworks
- Safeguarding data integrity and encryption using trusted execution environments (TEEs)
- Ensuring resilience and disaster recovery across distributed nodes
We review practical use cases and industry applications.
- Applications in industrial automation and smart factories
- Infrastructure for autonomous vehicles and mobility
- Solutions for healthcare, logistics, and environmental monitoring
- Delivering AR/VR and immersive media experiences at the edge
The course also covers the operational and business implications.
- Understanding Edge-as-a-Service and emerging ecosystem models
- Optimizing costs and managing the infrastructure lifecycle
- Assessing skill requirements and workforce transformation for 6G-edge convergence
A hands-on workshop focuses on designing a 6G-ready edge architecture.
- Mapping workloads and latency-sensitive services
- Defining network topologies and resource allocation strategies
- Drafting a proof-of-concept deployment and evaluation plan
The session concludes with a summary and next steps.
Requirements
- Proficiency in cloud and networking fundamentals
- Familiarity with IoT and distributed systems concepts
- Basic understanding of edge or hybrid infrastructure design
Target Audience
- IT architects exploring the convergence of edge computing and next-generation networks
- Enterprise infrastructure planners and solution designers
- Cloud and IoT professionals preparing for the evolution of 6G
Testimonials (1)
That we can cover advance topic and work with real-life example
