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Real-World Edge Computing

Real-World Edge Computing

By : Robert High, Sanjeev Gupta
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Real-World Edge Computing

Real-World Edge Computing

By: Robert High, Sanjeev Gupta

Overview of this book

Edge computing holds vast potential to revolutionize industries, yet its implementation poses unique challenges. Written by industry veterans Rob High and Sanjeev Gupta, this comprehensive guide bridges the gap between theory and practice. Distilling expertise from their combined decades of experience in edge computing and hybrid cloud mesh solutions, this book equips software developers and DevOps teams with the knowledge and skills needed to deploy edge solutions at scale in production environments. It also explores foundational standards and introduces key factors that may impede the scaling of edge solutions. While edge computing draws from the successes of cloud computing, crucial distinctions separate the two. High and Gupta elucidate these distinctions, helping you grasp the nuanced dynamics of edge-computing ecosystems. With a focus on leveraging Open Horizon to overcome pitfalls and optimize performance, this book will help you confidently navigate the intricacies of constructing and deploying resilient edge solutions in real-world production settings. By the end of this book, you’ll have acquired a deep understanding of essential success factors for building and deploying robust edge solutions in real-world production settings, leveraging Open Horizon for scalable edge deployments.
Table of Contents (24 chapters)
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Free Chapter
1
Part 1: Managing the Edge
7
Part 2: Working on the Edge
13
Part 3: Advancing the Edge System
17
Part 4: Edge Management in Practice

Technical requirements

As with the previous chapters, verify the current setup of the AIO Management Hub and the Edge agent on your Edge node as per the instructions in Chapter 7’s Technical requirements section.

If you happen to be using a standalone Edge device node such as an Intel NUC, you may attach a USB video camera. Using Raspberry Pi, Nvidia Jetson/Xavier or any other similar devices are also good alternatives.

As depicted in Figure 14.1, the video stream can come from an MP4 file, an RTSP stream, or both. Although not required, it would be helpful to familiarize yourself with the concept of an RTSP stream and a VLC player if you are planning to use an RTSP stream in your example.

In this example, we will be using TensorFlow Lite as an ML model. Using PyTorch, OpenVINO, YOLO, and so on are also options.

Additionally, this application uses OpenCV, an open source software (OSS), to perform various image-processing tasks, and this example is written in Python...

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