According to Gartner, by year-end 2023, more than 50% of big enterprises will deploy at least 6 edge computing use cases installed for IoT, versus less than 1% in 2019.
In the past, many technical experts speculated that the Internet of Things (IoT) would be entirely driven on the cloud. Their hypothesis proved to be accurate for the consumer-connected IoT; however, to build and design enterprise-scale IoT solutions, one of the key basics is to achieve a balance between the use of cloud and edge computing.
Unlike the cloud-based solutions, a blended solution is a hybrid base of small devices and sensors that aggregate their connectivity to central hubs and edge computers. It is too costly and energy-inefficient to connect every sensor to the cloud directly. This alleviates the network latency, raises scalability, and improves the access to information to make an organization more agile and more capable of deriving insightful conclusions faster.
In this article, we will explore the recommendations Perry Lea suggests to attain a holistic and expert review of implementing cloud and edge computing to build commercial IoT systems, and how the second edition of his renowned book, IoT and Edge Computing for Architects, Second Edition, will enable you to achieve that goal.
Edge Computing in IoT
Edge computing isn’t new. Embedded systems running remote devices have existed since the 1970s. In today’s world, edge computing is considered a natural extension of cloud computing, or a necessity in resolving the challenges that come with IoT-cloud systems.
Edge Computing for the Internet of Things (IoT) enables data processing closer to the end device resulting in enhanced IoT deployments. It also leads to improved efficiency of data transport and lower latency. Edge computers come in all shapes and sizes, from datacenter blades to small hardened computers that can sit in a school bus or emergency vehicle. They all reside close to where the data is being generated — hence close to IoT devices.
Advantages of Edge Computing in IoT
Resolves Network Latency
There are numerous safety-critical IoT applications that require a mandatory quick response to ensure safety. The approach to sending a request to the cloud and waiting for a response is likely to have unfortunate consequences. Shifting the sensor data’s processing to an edge gateway alleviates network latency and successfully achieves the expected response time.
Edge computing allows digital products to continue functioning even when they are not connected to the network by providing them with the ability to have local computation and local storage.
High Computational Efficiency
Edge computing offers faster computational efficiency to process small data sets. An edge gateway can be deployed with machine learning models to facilitate the processing.
Sensors and actuators generate a high volume of telemetry data which is not relevant for an IoT application. Edge computing reduces the network expenditure of data transmission by filtering and processing the data before sending it to the cloud.
Keeping in mind the prominence of edge computing, the book delves deeply into the topic. The first edition was focused on IoT, but edge systems are prevalent and a good understanding of their use cases, design, and frameworks is now a must in order to become an eminent IoT application developer.
In addition, this new second edition is a definitive guide and instruction manual for new technologies, including 5G communications and technology; the new Bluetooth 5.1; MQTT 5 for edge to cloud secure and efficient communication; EdgeX and OpenFog computing frameworks; Ambient computing and synthetic sensing and dozens of new real-world use cases for IoT and edge computing.
Encapsulating Enterprise IoT Application Development
Readers of this book will have a holistic and expert review of everything from the edge to the cloud and back. This book covers everything from sensors to near-range and long-range telecommunications, edge computer architecture, edge to cloud data analytics and deep learning, and of course, security.
It is intended to give readers a view of building real commercial and enterprise IoT and edge systems. It crosses multiple domains such as radio communications, embedded design, networking protocols, sensor physics, energy and power electronics, cloud and fog software frameworks, cloud computing, and analytics.
Potential Security Risks
Security is treated holistically in this book, from the sensor to the cloud and back. It covers security all the way from a device level to a communication level. Further, the specific security aspects pertaining to each topic are covered within each relevant chapter itself.
This new edition also expands its discussion to historic and global threats to IoT systems that have succeeded. The book dissects those attacks, how they spread, and the measures that are taken to tackle them. Additionally, the book also explores all phases of security from device hardening to software mitigation, and network encryption standards.
In short, IoT and Edge Computing for Architects, Second Edition provides a complete package of executable insights and real-world scenarios that will help the reader to gain comprehensive knowledge of edge computing and become proficient in building efficient enterprise-scale IoT applications.