What is fog computing? What about security in fog nodes? What are the fundamental elements to a fog computing architecture? Are there any online courses available?
Got questions? Get answers in our resource hub, where we’ve compiled a centralized library to help you learn more about fog computing through white papers, webinars, research link, blog and online education materials.
Fog computing is a system-level horizontal architecture that distributes resources and services of computing, storage, control and networking anywhere along the continuum from Cloud to Things. It is a:
Fog Computing – Indepth look at fog computing’s opportunities and challenges to form a distributed and virtualized platform.
The Energy Fog – A new paradigm on how electric vehicles, blockchain, and fog computing will re-power the planet. White paper by Shaun Varga & Ross Laurie
Fog vs. Edge – Nebbiolo Technologies explains the commonalities and differences between Fog and Edge.
Fog and IoT: An Overview of Research Opportunities by Dr. Mung Chiang, Princeton University; and Dr. Tao Zhang, Cisco System
From Cloud to Fog and The Internet of Things by Michael Enescu, Co-founder at Energy Adaptive Networks
Fog Computing and Its Role in the Internet of Things by Flavio Bonomi et al
Fog Networks by Mung Chiang, OpenFog Consortium Board Member and Arthur LeGrande Doty Professor of Electrical Engineering at Princeton University
Fog Networking: An Overview on Research Opportunities by Mung Chiang, OpenFog Consortium Board Member and Arthur LeGrand Doty Professor of Electrical Engineering at Princeton University
OpenFog Consortium members include the leading thinkers and technical experts on fog, edge and distributed computing. To request a speaker for a keynote, panel or breakout session speaker for your event, please submit your request.
Gain insights into advanced research on fog computing from universities, research centers and industry organizations. This content was formerly located at fogresearch.org.
To contribute to these pages, please contact us at email@example.com.
Video Short: Introduction to fog computing in 2 minutes
Video Short: Disrupting the food chain between IoT and cloud
Video Short: Drones in fog
Video Short: Why you need fog computing
What is fog computing and why it matters (on demand replay of April 2017 IoT Central event)
Out of the Fog: Viewpoints from Founding Members (5-7 minute videos):
Enterprise IoT Summit 2017: Panel discussion on Enterprise IoT: How to Get Started – Moderator – Analyst Mike Krell, Moor Insights with Rhonda Dirvin, OpenFog Board member and Director of Vertical Industries, ARM (video, 47 minutes)
IEEE Future Directions: Convergence through the Cloud-to-Things Continuum – Keynote by Dr. Tao Zhang, OpenFog Board Member and Distinguished Engineer, Cisco (video, 10 minutes)
The Emerging Era of Fog Computing and its Impact on Consumer Electrics – ICCE keynote by Dr. Tao Zhang, OpenFog Board Member and Distinguished Engineer, Cisco (video, 49 minutes)
Fog-based use cases are essential to the work of the OpenFog Consortium. They provide invaluable insight into the spectrum of vertical markets and applications served by fog computing and networking, and they also drive requirements for next iterations of the OpenFog architecture and testbeds. This page contains links to representative use cases created by OpenFog workgroups and members that help to define the functions of an open and interoperable fog architecture, fog implementations and deployments.
Each of these use cases highlights one or more representative fog attributes such as latency, network bandwidth, reliability, security, programmability and scalability.
These use cases are published to provide system architects with a technical foundation to plan and design fog implementations, plus extract high-level requirements tailored to specific vertical industries. We encourage you to browse through this library – including those outside your industry or interest area – as each use case highlights less obvious aspects of fog that could prove valuable to your work. We appreciate comments on these use cases, which can be sent to firstname.lastname@example.org.
Thank you for your interest in fog computing and in our work.
Today’s smart buildings are beginning to leverage the Industrial Internet for improved business outcomes, such as better energy efficiency, sustainable technology, improved occupant satisfaction and lower operational costs. When coupled with 5G and other building communications, fog computing can provide local processing and storage as well as optimize network usage that enhance the value of smart building applications. This use case reviews and explains how fog computing & networking can make buildings more secure and operationally efficient. Download the use case.
High-Scale Package Drone Delivery
The concept of using drones—also known as flying robots and unmanned aerial vehicles (UAVs)—is gaining a lot of attention. Drone fleets can reduce costs, congestion and environmental impact to a degree that no one would have imagined possible. Yet there are also challenges to deployment: Network bandwidth and availability, drone hub management, regulatory considerations and more. This use case examines the advantages, requirements and restrictions of drone package delivery in a fog computing environment. Download the use case.
Real-time Subsurface Imaging
Subsurface imaging and monitoring in real time is crucial for understanding subsurface structures and dynamics that may pose risks or opportunities for oil/gas exploration and production, civil infrastructure, etc., while minimizing environmental impact. This use case examines a new approach to real-time subsurface imaging through a mesh network of fog nodes. Download the use case.
Traffic congestion is such a severe and growing problem that it has the potential to paralyze major cities, choking off growth and prosperity. Some cities are taking what commuters may consider drastic and expensive measures, like expanding toll roads or restricting the number of license plates issued.
The open architecture of fog computing gives municipalities a new weapon in the fight against traffic congestion. Fog has the flexibility to leverage traffic-related big data, which enables municipalities to take measures to alleviate congestion by connecting and analyzing previously unconnected infrastructure devices, roadside sensors, and on-board vehicles devices, in order to redirect traffic based on real-time data. Review the OpenFog Use Case – Traffic Congestion
Surveillance and security cameras are being deployed worldwide in record numbers in order to ensure the security and safety of materials, people, and places. These surveillance devices are generating massive amounts of data, with a single camera generating in excess of one terabyte of data per day. Systems of surveillance devices generate data that must be analyzed in real time in order to ensure public safety. Traditional cloud-based models to analyze the data are no longer adequate due to latency challenges, network availability and the cost to transmit data to the cloud and back. This use case explores the use of fog computing in surveillance scenarios. Download the use case.
These vertical market use cases, created by OpenFog members and contributors, showcase how fog works in industry. They were designed to provide architects with a resource that has enough detail to plan and design a fog implementation and extract high-level requirements. Please fill out the form below for access to all of these use case studies.
Subsurface imaging and monitoring in real time is crucial for understanding subsurface structures and dynamics that may pose risks or opportunities for oil, gas and geothermal exploration and production. This use case describes an architecture for integrating IoT sensor networks with fog computing and geophysical imaging technology. Fog’s scalability enables real-time computation in remote field locations, including support for complex compute algorithms.
Today’s smart buildings are leveraging the IoT for improved business outcomes, such as better energy efficiency, improved occupant experience, and lower operational costs. They require distributed fog architectures because they typically contain thousands of sensors measuring various building operating parameters such as: temperature, humidity, occupancy, energy usage, keycard readers, parking space occupancy, fire, smoke, flood, security, elevators, and air quality. This use case demonstrates how fog nodes at the room level, floor level, building level and cloud level can be hierarchically architected for efficient real-time processing, enabling dozens of new applications.
Autonomous Driving, which involves hundreds and hundreds of simultaneous data processes and connections, can’t be accomplished without fog. Fog establishes trustworthiness of communications between low-level sensors while enabling high-bandwidth real-time processing. This use case validates how fog architectures for autonomous cars enable significantly greater scalability than any other architecture. Fog interoperability enables on-board equipment to communicate at a variety of hierarchies while providing standard interfaces that will provide a foundation for the fog ecosystem.
With its real-time communications and analytics requirements for data from thousands of low-level sensors, today’s hospital patient monitoring requires the scalability and agility of fog. Fog’s distributed architecture and hierarchical structure are necessary for moment-to-moment healthcare operations. This use case describes an architecture based on a virtual compute environment residing on a series of fog nodes that supports the flexible deployment of applications and streamlines the integration of healthcare systems.