Book Image

Intelligent Workloads at the Edge

By : Indraneel Mitra, Ryan Burke
Book Image

Intelligent Workloads at the Edge

By: Indraneel Mitra, Ryan Burke

Overview of this book

The Internet of Things (IoT) has transformed how people think about and interact with the world. The ubiquitous deployment of sensors around us makes it possible to study the world at any level of accuracy and enable data-driven decision-making anywhere. Data analytics and machine learning (ML) powered by elastic cloud computing have accelerated our ability to understand and analyze the huge amount of data generated by IoT. Now, edge computing has brought information technologies closer to the data source to lower latency and reduce costs. This book will teach you how to combine the technologies of edge computing, data analytics, and ML to deliver next-generation cyber-physical outcomes. You’ll begin by discovering how to create software applications that run on edge devices with AWS IoT Greengrass. As you advance, you’ll learn how to process and stream IoT data from the edge to the cloud and use it to train ML models using Amazon SageMaker. The book also shows you how to train these models and run them at the edge for optimized performance, cost savings, and data compliance. By the end of this IoT book, you’ll be able to scope your own IoT workloads, bring the power of ML to the edge, and operate those workloads in a production setting.
Table of Contents (17 chapters)
1
Section 1: Introduction and Prerequisites
3
Section 2: Building Blocks
10
Section 3: Scaling It Up
13
Section 4: Bring It All Together

Chapter 2

  1. The use of isolated services is the best practice for organizing code in edge ML solutions. Monolithic applications may sometimes be the right choice, depending on project requirements.
  2. A benefit of decoupling services in edge architecture is limiting the behavioral scope of what those services do. A simple single-purpose service is easier to write, maintain, and reuse.
  3. A benefit of isolating your code and dependencies from other services is the assurance that you won't have any dependency conflicts between your services.
  4. A key trade-off when evaluating wired and wireless networking is power consumption. Wireless communication needs more power to transmit and receive messages. If the overall solution is wireless, this usually means reliance upon a local battery source for power.
  5. A smart home device that uses both a sensor and an actuator is a motorized garage door. These devices use a break beam sensor to detect whether anything is in the path of...