Chapter 3: Architecture and Components of Edge Computing
Abstract
This chapter provides a comprehensive overview of edge computing architecture, categorizing its components into on-premises edge, network edge, and data center edge, each representing a unique deployment approach. Through collaboration with cloud and peripheral devices, edge computing enables powerful data processing, caching, storage, and efficient content delivery. The chapter also examines four collaborative models within edge computing: edge-to-edge, edge-to-device, edge-tocloud, and cloud-edge-device, each enhancing interoperability across various layers. Finally, the chapter emphasizes the importance of network integration in supporting smooth data flow and communication in distributed systems, highlighting how strategic model selection can optimize system performance.
📝 Practice Questions
1. Discuss the different grades/layers of edge infrastructure. How do these layers contribute to the overall efficiency and scalability of an edge computing system?
2. Compare and contrast mobile edge computing (MEC) and multi-access edge computing (MEC).
3. Explain the role of gateways in an edge computing architecture.
4. What are collaborative edge computing models, and in what scenarios are they most beneficial?
5. What factors should be considered when choosing the right edge computing model for a specific application? Provide examples to support your explanation.
📘 Course Projects
1. Set up a small edge computing network and demonstrate communication between edge devices and servers.
2. Design a multilayer edge computing architecture tailored to a specific application, such as smart cities, autonomous vehicles, or smart homes, and explain how each layer contributes to the overall architecture and meets the application's requirements.
3. Build a demo system for cloud-edge-device collaboration, with the functions of deviceside data collection, edge-side preprocessing data, and cloud batch data processing.
4. Implement a system for managing and monitoring edge devices using KubeEdge.
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2. Yun Chao Hu et al. "Mobile edge computing—A key technology towards 5G". In: ETSI White Paper 11. 11 (2015), pp. 1–16 | Paper.
3. Heiko Koziolek and Nafise Eskandani. "Lightweight Kubernetes distributions: A performance comparison of MicroK8s, k3s, k0s, and MicroShift". In: Proceedings of the 2023 ACM/SPEC International Conference on Performance Engineering. 2023, pp. 17–29 | Paper.
4. Fang Liu et al. "A survey on edge computing systems and tools". In: Proceedings of the IEEE. 107. 8 (2019), pp. 1537–1562 | Paper.
