Fog/Edge Computing: Opportunities, Case Studies, Challenges — An Introduction
The convergence of the Internet of Things (IoT), fifth-generation (5G), and artificial intelligence (AI) technologies is providing industries such as manufacturing, healthcare, telecommunications, and finance, as well as many others, the means to collect and generate data faster than ever before. Until recently, this data was usually sent to the cloud for processing and storage. But with the staggering increase in the amount of data being collected, the need to process and analyze this data faster to capture and act on valuable customer and operational insight in real or near real time is more critical than ever.
Fog and edge computing address these challenges by pushing intelligence and processing capabilities closer to where the data originates, yielding the ability to perform real-time analytics for actionable insights. Reducing the amount of data being sent to the cloud and between sensors means minimized latency as well as lowered time, energy, and bandwidth expenditures.
Fog and edge computing together offer many advantages. Although the technologies may seem similar — and there is much confusion about the terminology — the general consensus is that their difference lies in where the intelligence and computing power are placed. Fog computing extends cloud computing and intelligence to the edge of an enterprise’s network. It brings computing, storage, control, and networking functions closer to the point of data generation along the cloud-to-thing continuum, at the network level, and processes data in a fog node or IoT gateway. Another aspect of fog computing is determining whether the data will be processed at the network level or in the cloud data center.
Edge computing places the intelligence, processing power, and communications, as much as possible, in the devices themselves, to carry out analysis where the data is generated. Connected devices such as sensors, controllers, smartphones, autonomous cars, or other intelligent devices collect and analyze the data themselves or send it to a server or laptop for analysis.
In This Issue
This issue of Cutter Business Technology Journal offers perspectives from seven authors on fog/edge computing to bring some sunlight to the challenges, benefits, and possible uses of these emerging technologies.
First up in this issue, Cutter Consortium Senior Consultant Claude Baudoin sets the stage with his take on the current trends presented at the Fog World Congress late last year. Baudoin discusses fog versus edge, the growing fog market, the industry sectors benefitting from — or poised to benefit from — fog/edge, and the issues posed by security and privacy, competing standards, and future directions.
Ken Hatano, in our second article, offers a case study of how fog computing “can reduce waste, improve product quality and consistency, and create a digital twin of difficult-to-replicate processes,” using the hypothetical example of a craft brewery. Fog helps optimize operations in food and beverage manufacturing and is a key enabling factor in smart factories, allowing systems in those factories to connect with external systems, while mitigating connectivity and security concerns.
Next, Frank Michaud and John K. Zao take an in-depth look at the role of fog computing — specifically fog architecture — in cybersecurity protection for today’s “connected-everything/data-everywhere” systems. The authors explain fog node–centric security, provide some real-world examples, and delve into physical security of the fog nodes, end-to-end security within the device-fog-cloud continuum, and security monitoring and management among the hardware/software entities present in the continuum.
This issue’s second case study, by Charles C. Byers and Katalin K. Bartfai-Walcott, addresses the criteria for operating unmanned aerial vehicles, or “aerial drones,” in a fog architecture. The use of drones in supply chain delivery offers faster, more cost-effective delivery but also poses myriad concerns, ranging from collision to security risks, as well as regulatory concerns. Specific attributes of the fog computing architecture — secure operations, autonomous capabilities, and system availability — benefit aerial drones. The authors examine two types of drone delivery — individual drones and drones working together (“hives”) — to show how fog computing facilitates drone operations and helps overcome challenges.
Finally, Cutter Consortium Senior Consultant Curt Hall closes out the issue with with a close look at edge computing. He discusses the Industrial Internet along with the IoT applications and domains that are most likely to benefit from edge computing. Hall also provides several examples of companies that have already developed edge computing applications and describes the rationale for and operation of each.
It may be foggy along the coastal edge, but the forecast is for clearer skies ahead. We trust the articles in this issue help clear the air in your understanding of computing at the perimeters of your network and provide you with some insights into taking advantage of these emerging technologies.
More: Articles Like This
- Fog/Edge Computing: Opportunities, Case Studies, Challenges — Opening Statement
- Fog/Edge Computing: Opportunities, Case Studies, Challenges
- Fog Computing: Securing the Intelligent Edge in Next-Generation Networks
- Flying Through the Fog: Aerial Drones in Supply Chain Delivery
- Fog Computing: A New Space Between Data and the Cloud