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Course Outline
Foundations of 6G and Edge Computing
- Overview of 6G technology and its development roadmap.
- Core principles of edge computing and various deployment models.
- The 6G–Edge–Cloud continuum and distributed computing paradigms.
Architecture of the Intelligent Edge
- Essential components of edge systems, including compute, storage, and networking.
- Integration strategies for IoT sensors, gateways, and 6G connectivity.
- Edge orchestration mechanisms and service management practices.
6G Capabilities and Enabling Technologies
- Terahertz spectrum utilization and low-latency communication protocols.
- AI-native network management and intent-driven orchestration.
- Network slicing and dynamic resource allocation for edge workloads.
Data and AI at the Edge
- Federated learning approaches and distributed AI processing.
- Real-time analytics capabilities and event-driven architecture patterns.
- Data governance and privacy considerations in multi-domain edge systems.
Edge–Cloud Collaboration Models
- Hybrid and multi-cloud integration strategies.
- Techniques for offloading, caching, and latency optimization.
- Utilization of APIs, microservices, and container-based deployments.
Security and Trust in Distributed Edge Networks
- Identity management, authentication, and zero-trust security frameworks.
- Data integrity, encryption standards, and trusted execution environments (TEEs).
- Resilience strategies and disaster recovery across distributed nodes.
Use Cases and Industry Applications
- Industrial automation and smart factory implementations.
- Autonomous vehicles and advanced mobility infrastructure.
- Applications in healthcare, logistics, and environmental monitoring.
- Delivering AR/VR and immersive media experiences via the edge.
Operational and Business Implications
- Edge-as-a-Service models and emerging ecosystem dynamics.
- Cost optimization strategies and lifecycle management.
- Skill requirements and workforce transformation for 6G-edge convergence.
Workshop: Designing a 6G-Ready Edge Architecture
- Mapping workloads and identifying latency-sensitive services.
- Defining network topologies and resource allocation plans.
- Drafting a proof-of-concept deployment and evaluation strategy.
Summary and Next Steps
Requirements
- A solid grasp of cloud computing and networking fundamentals.
- Working knowledge of IoT and distributed system concepts.
- Foundational understanding of edge or hybrid infrastructure design.
Intended Audience
- IT architects investigating the intersection of edge computing and next-generation networks.
- Enterprise infrastructure planners and solution designers.
- Cloud and IoT professionals preparing for the 6G evolution.
21 Hours
Testimonials (1)
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