Posted on 10/25/2017

Fog Computing: A New Paradigm for the Industrial IoT

Morris Novello

We’ve all heard of cloud computing, but is the cloud right for every business? In this blog post, we will explore the many opportunities and applications of fog computing. Fog computing extends and complements the cloud computing paradigm to the edge of the network, thus enabling a new breed of applications and services. Defining characteristics of fog technology include:

  • Low latency and location awareness
  • Wide-spread geographical distribution
  • Mobility
  • Distributed deployment of nodes
  • Access via wireline and wireless connection
  • Strong presence of streaming and real-time applications
  • Heterogeneity of systems

Fog computing can be the appropriate platform for a number of critical Internet of Things (IoT) services and applications, namely, connected vehicle, smart grid, Industry 4.0 manufacturing, smart cities, and many other verticals.

The cloud computing model is an efficient alternative to owning and managing data centers for customers facing web applications and batch processing. Several factors contribute to the economy of scale of mega data centers: higher predictability of massive aggregation, which allows higher utilization without degrading performance; convenient location that takes advantage of inexpensive power; and lower OPEX achieved through the deployment of homogeneous compute, storage, and networking components.

This model becomes a problem for latency-sensitive applications, which require nodes in the vicinity to meet their delay requirements. An emerging wave of Internet deployments, most notably the IoTs, requires mobility support and geo-distribution in addition to location awareness and low latency.

Fog computing seamlessly extends cloud computing into edge for secure control and management of domain specific hardware, software, and standard compute, storage and network functions within the operational technologies domain and enable secure rich data processing applications across IT-OT domains.

Characterization of Fog Computing

Fog computing is a highly virtualized platform that provides compute, storage and networking services between end devices and traditional cloud computing data centers, typically, but not exclusively located at the edge of network.

The image below presents the idealized information and computing architecture supporting the future IoT applications, and illustrates the role of fog computing.

The main concepts of fog computing distilled from the above definition are that fog computing:

  • Extends cloud into fog domain at the edge and performs cloud functions in a single continuum.
  • Applies its principles horizontally across different types of domains, i.e., IoT verticals like industrial automation, smart cities, oil and gas, transportation of men, material and goods, agriculture etc., to promote a consistent architecture, sharing of technology, resources and data across these domains.
  • Interconnects different IoT verticals for resource sharing, data sharing and service sharing for productivity, efficiency and other business factors improvement.
  • Enables secure control and management of multiple fog domain instances called the Fog Federation, comprising of edge devices, computes, networking, storage, and services in a distributed and consistent manner.
  • Empowers end-to-end security from the cloud to the edge devices across IT domain, DMZ domains, and the OT domains.
  • Bring the required data collection, processing and analysis closer to the data sources at the edge enabling both edge and fog analytics. Fog analytics is the analysis of data from multiple interoperating edge devices for anomaly detection, failure prediction, and optimization of the eco-system.

To support the above use cases, a new platform (pictured below) is needed to meet these requirements, bringing cloud-inspired (IT) computing, storage, and networking functions closer to the data-producing sources; integrating real-time contro/apps, safety capabilities required in the OT domain and security to connect IIoT devices; becoming the key enabler of a real convergence between IT and OT technologies.

Nebbiolo Technologies Fog Computing Platform

Furthermore, fog computing complements the cloud computing architecture enabling a new breed of applications and services, and that there is a fruitful interplay between the cloud and the fog, particularly when it comes to data management and analytics at the edge of the network.

Use Cases

In this section, we demonstrate the role the fog plays in two scenarios: Connected vehicle and smart grid.

Connected Vehicle (CV)

The modern automobile is a computing-rich electronic system on wheels (pictured below), with more than 100 computers per vehicle, and it will become much more powerful in the not too distant future. This trend is motivated by a number of converging requirements and developments, including the need for connectivity of automobiles to sources of travel information and entertainment, the need for vehicle-to-vehicle and vehicle-to-infrastructure exchanges for accident prevention, the move towards more dynamic and modern vehicle maintenance, the need to rationalize the electronic vehicle control architecture by reducing control system weight and cost of software development, the evolution towards electric vehicles, and, most importantly, the need to assist or even replace drivers.

The evolution of thought at the origin of fog computing was in many ways motivated by the critical requirements foreseen in the automotive and intelligent transportation sectors, which have contributed to crystallize fog computing at the convergence of the most advanced embedded system virtualization and of modern real-time, deterministic and safety-aware computing and networking.

Smart Grid

While fog nodes provide localization, therefore enabling low latency and context awareness, the cloud provides global centralization. Many applications require both fog localization, and cloud globalization, particularly for analytics and big data. Here we consider smart grid, which data hierarchies help illustrate further this interplay.

Fog collectors at the edge ingest the data generated by grid sensors and devices. Some of this data relates to protection and control loops that require real-time processing (from milliseconds to sub seconds), see image below.

This first tier of the Fog (pictured below), designed for machine-to-machine (M2M) interaction, collects, process the data, and issues control commands to the actuators. It also filters the data to be consumed locally, and sends the rest to the higher tiers. The second and third tier deal with visualization and reporting (human-to- machine interactions), as well as systems and processes (M2M). The time scales of these interactions, all part of the fog, range from seconds to minutes (real-time analytics), and even days (transactional analytics). As a result of this, the fog must support several types of storage, from ephemeral at the lowest tier to semi-permanent at the highest tier. We also note that the higher the tier, the wider the geographical coverage, and the longer the time scale.

The ultimate, global coverage is provided by the cloud, which is used as repository for data that that has a permanence of months and years, and which is the bases for business intelligence analytics. This is the typical HMI environment of reports and dashboards the display key performance indicators.


We have outlined the vision and defined key characteristics of fog computing, a platform to deliver a rich portfolio of new services and applications at the edge of the network. The motivating examples throughout the discussion range from conceptual visions to existing point solution prototypes. We envision the fog to be a unifying platform, rich enough to deliver this new breed of emerging services and enable the development of new applications.

About the Author

Morris Novello | Nebbiolo Technologies Inc.

Morris Novello is senior director of marketing at Nebbiolo Technologies. His interests focus on market segmentation, use cases definition, go-to-market strategy, thought leadership and sales enablement. Prior to joining Nebbiolo, Novello led the vRealize Product Marketing team at VMware and spent 7 years at Microsoft, where he led Azure marketing for the public sector. Novello also built the SQL Server go-to-market messaging and value proposition for Mid-Market and Enterprise segments. Before this role, he was with Intel for four years, most recently as Product Manager for Xeon processors responsible for the EMEA market. Novello attended the University of Padova in Italy earning a BSc. and MSc. in Electrical Engineering and he was a visiting scholar at MIT Sloan School of Management during his MBA degree.


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