Summary

In this chapter, we learned the fundamentals of edge computing and discussed the benefits that can be derived from it. Although it certainly requires more understanding of its setup and has its own set of challenges based on the decentralized network it needs to abide by, it provides a cost-effective way for large workloads to be performed while ensuring that they do not get congested when they are directed toward a centralized hub, as with most solutions. We looked at an exercise where an edge device in the form of an ESP32 device was built to retrieve information from a DHT11 sensor and used for both obtaining data and running an ML model on it, seeing how powerful edge computing can be. Toward the end, we also did a practical on creating a simple network for edge computing and further learned about strategies that can be used to optimize edge networks, evaluate them, and make appropriate design decisions based on them, while also applying the knowledge that we have learned...