Introducing New eBook: Essentials of Edge Computing

Devices that collect and process data “at the edge” of the network are quickly becoming a requirement for the next era of the IoT.

Consumers and organizations are already benefitting from a growing number of smart, connected internet of things (IoT) devices to improve lives and drive greater efficiencies, safety and convenience. The near-zero latencies demanded by real-time applications such as industrial robotics and connected vehicles cannot be achieved across wide area networks. At the same time, the enormous volumes of data generated by IoT applications consume significant amounts of costly network bandwidth and data center storage. And as increasing volumes of sensitive data are transported to and from the cloud, security becomes a growing concern. All of this is putting the traditional cloud computing model under pressure. It’s becoming obvious that moving all of the increasing amount of data generated by sensors from the end-user location to the cloud and back is no longer viable.

A better approach is to complement the cloud by performing more of this processing at the user location—at the edge. The edge operates on “instant data” generated in real-time and processed by the IoT devices themselves. The smallest microcontrollers and microprocessors can now run machine learning (ML) in the device, thereby reducing latencies associated with cloud computing. Even with no connection, your smart door lock, for example, unlocks when it recognizes your face because the machine learning runs on an edge device where your personal images are stored. And your private data, including your comings and goings, can stay at the edge without leaving your home.

The Road to the Edge

The edge has great potential to change how we interact with our world in a more productive, safe and efficient way. From a technology perspective, what do you need to have? What are the components of a well-architected edge computing system? How do you achieve optimal security, energy efficiency, connectivity and machine learning intelligence?

I worked with more than 30 experts at NXP to answer these questions and we shared our insights in Essentials of Edge Computing. Wide-ranging topics are covered in this 200+ page ebook, including hardware and software architectures, security, machine learning, connectivity, device life-cycle management, energy efficiency and optimization, HMI and development tools. Use cases are detailed for local voice, 5G for Industry 4.0, wearables, time-sensitive networking and intelligent connected vehicles. You can download it at no cost today.