Making Sense of Edge Computing
Cody Bumgardner, Caylin Hickey
  • MEAP began April 2020
  • Publication in Summer 2021 (estimated)
  • ISBN 9781617297595
  • 350 pages (estimated)
  • printed in black & white

Much needed text that covers important edge computing topics in an approachable and systemized manner.

Milorad Imbra
Edge computing systems run essential data processing tasks on the devices that make up their network, reducing laggy data transfers and expensive cloud infrastructure. Edge systems can be complex, so it’s essential to have the big picture as you explore this innovative technology. Making Sense of Edge Computing gives you an easy-to-grok technical overview, covering what sets edge computing apart from other systems, and how to get started on edge projects from personal scale IoT to geographically distributed systems demanding real-time data processing.

About the Technology

In edge systems, individual devices gather and process their own data, delivering huge benefits for speed, legal adherence, and cost-efficiency. A self-driving car saves vital seconds by running its own pedestrian image recognition. A CCTV system preserves privacy with a de-identification program before transferring footage. A smart watch calculates fitness stats on its own circuits instead of incurring costs in the cloud. Edge systems are in demand from an ever-growing set of applications, and it’s important to understand the benefits and impacts this model can have on your work.

About the book

Making Sense of Edge Computing is a technical overview of edge computing systems offering accessible examples and clear explanations. You’ll start with what sets edge computing apart from other distributed systems. Then, you’ll dive into the various components of these systems, including the entity relationships, networks, and so forth, you’ll need to model your problem. You’ll learn about testing the performance of edge components, picking the right stack for your projects, and how to develop custom features. Finally, you’ll get a chance to test your skills by exploring three large-scale edge computing projects: an agent-based IoT system, a privacy-preserving app, and a geographically distributed system with a huge number of agents and vast volumes of data.

What's inside

  • Identify problems that can be solved by edge computing
  • Design edge-focused infrastructures
  • Develop and implement dynamic edge-enabled pipelines
  • Monitor and measure KPIs in distributed edge applications
  • Agent-based computing and autonomic systems
  • Popular edge computing frameworks from AWS, Google, and Azure

About the reader

For technology professionals familiar with distributed systems and cloud computing.

About the authors

Dr. Cody Bumgardener has over twenty years of experience working with the communications, distributed systems, and streaming complex event processing technology that make up edge computing. His research focuses on the applied use of edge computing, distributed inference, and AI in large-scale real-time systems. Caylin Hickey has over a decade’s experience in data analytics, cloud computing, distributed systems, and edge computing. He is pursuing his PhD in computer science at the University of Kentucky.

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