Size and Impact of Fog Computing Market AND IMPACT OF FOG COMPUTING MARKET CORIHT 2017 451 RESEARCH...

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Size and Impact of Fog Computing MarketO C TO B E R 20 1 7

The OpenFog Consortium contracted with 451 Research to research the scope and size of the

global Fog computing market. This report presents the results of that research, which is based

on primary interviews with OpenFog Consortium member stakeholders, subject-matter experts in

target vertical markets, extensive use of the proprietary 451 Research Global IoT market model

(GIMM), Voice of the Enterprise (VotE): IoT and Voice of the Connected User Landscape (VoCUL)

syndicated quantitative services, the 451 Research Market Monitor; and the company’s financial

M&A KnowledgeBase.

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Table of ContentsKey Findings 4

Executive Summary 4Figure 1: Size of Fog computing market opportunity by vertical market, 2019 and 2022 4

Introduction 5

Methodology 5

Defining the Fog Opportunity 7Figure 2: Growth of Fog opportunity by vertical market 7

Figure 3: Growth of Fog as a service 8

Agriculture 8

Datacenter 8

Energy and Utilities 9

Figure 4: Historical and projected transmission investment, North America only 9

Healthcare 10

Industrial 10

Military 10

Retail 10

Smart Buildings 11

Smart Cities 11

Smart Homes 11

Transportation 11

Wearables 12

Appendix A: Fog Market Forecast 12Figure 5: Fog computing revenue by vertical market 12

Figure 6: Fog computing revenue by component 13

Appendix B: Key Forecast Assumptions, Considerations and Dependencies 14



Key Findings � The global Fog market opportunity has the potential to reach more than $18bn worldwide by 2022. � The largest worldwide potential markets for Fog computing are in energy/utilities and transportation,

followed by the healthcare and industrial markets. � Key market transitions, such as large public/private investments in energy infrastructure moderniza-

tion, demographic shifts and governmental mandates in trucking (within transportation) and health-care, and increased automation of manufacturing contributed to the growth rate across each market.

� Initially, hardware will have the largest percentage of overall Fog revenue (51.6%), followed by Fog ap-plications (19.9%) and then services (15.7%). Over time, we forecast that standardization plus the incor-poration of Fog functions ‘as a feature’ into existing hardware driving this hardware component down to 42% of the total market, with the primary ‘upside’ benefactors being Fog applications and services.

Executive SummaryThe Fog computing market opportunity will exceed $18bn by 2022; however, it is dependent on a number of precursor conditions to occur before the technology can fully emerge, including capable hardware, operating system support, Fog node applications, security and management services, as well as the emergence of service providers of Fog services (Fog as a service/FaaS). The market also requires business models and a liability structure that allow manufacturers of endpoints (cargo ships, fitness trackers, portable endoscopes) to ‘sandbox’ Fog node capability within their environments without potentially impairing device functionality or incurring liability.

Figure 1: Size of Fog computing market opportunity by vertical market, 2019 and 2022

Source: 451 Research OpenFog project analysis

16%

14%

14%

4%5%

23%

10%

4%

3%3%

4%

2022

Transportation Industrial Healthcare Datacenters Retail Utilities

Agriculture Smart Buildings Smart Cities Smart Homes Wearables

18%

13%

15%

5%

3%

21%

12%

4%3%

2%

4%

2019

$18.2bn$3.7bn



While Fog computing is distinctly new technology, the forecast is that there will be aspects of Fog that become features of existing devices and software, working in tandem with stand-alone, single-purpose Fog nodes. Thus, the Fog market op-portunity will become more diffused over time as Fog becomes a feature and capability of all distributed IoT analytics and not a separate overlay system. The market size above reflects this by including Fog within existing systems (manufacturing robots, diagnostic ultrasound devices, aircraft avionics units), as well as forecasting new device types such as gateways and single-purpose Fog nodes within a datacenter. It does not include ‘drag along’ revenue for items such as upgrades to carrier infrastructure for increased bandwidth required for Fog applications.

1. Military soldier wearables are included in the wearable market forecast; military vehicles and equipment are included in the transportation market forecast; and smart governmental buildings are included in the smart buildings forecast.

IntroductionSizing the Fog market opportunity begins with a clear definition of what constitutes Fog – what is included and what is excluded. This begins on one ‘end’ with edge devices (in this context, we define edge devices as those devices where sensor data originates, such as vehicles, manufacturing equipment and ‘smart’ medical devices) that have the requisite compute hardware, operating system, application software and connectivity to participate in the distributed analytics Fog. It extends from the edge to ‘near edge’ functions, such as local datacenters and other compute assets, multi-access-edge (MEC) ca-pabilities within an enterprise or operator radio access network, intermediate computing and storage capabilities within hosting service providers, interconnects and colocation facilities, and ultimately to cloud service providers. These locations have integrated or host ‘Fog nodes,’ which are devices capable of participating in the overall distributed analytics system.

Fog nodes are a subset of all endpoints (trucks, manufacturing robots, monitored refrigeration units, etc.) and even a subset of all ‘connected’ endpoints because not all endpoints have the required hardware capabilities, and not all endpoint manu-facturers have/will support Fog node capability. We have modeled Fog node adoption in applications and use cases where distributed and hierarchical multi-step analysis is likely to occur, dependent on overall endpoint adoption and availability data from our Global IoT Market Model. The market-size estimates within this document are based on what we believe to be conservative assumptions in each vertical market for adoption; however, some markets have built in ‘step functions’ where rapid adoption occurs, such as when a large quantity of aircraft is cycled out of service for a technology refresh, or as US military personnel equipment is routinely reevaluated and refreshed every 18-24 months. Details about each vertical market with key drivers are below.

MethodologyThe conclusions and recommendations in this report are based primarily on adoption assumptions developed from conver-sations with industry stakeholders across enterprises and the vendor community, applied to the IoT endpoints and verticals captured in the 451 Research GIMM. In addition, the model was informed by data from other 451 Research assets, including VotE: IoT, VoCUL and Market Monitor.

The 451 Research Global IoT Market Model deconstructs the Internet of Things into specific, actionable components. GIMM integrates more than 1,000 endpoint types across 12 vertical markets, from precision agriculture to manufacturing, and from military aircraft to consumer fitness bands, into a unified lens to focus on key applications and country-level and re-gional geographic opportunities. The model includes device type breakdowns, forecasted bandwidth, data volumes and location (edge, multi-access edge, datacenters, cloud), as well as inflection points in adoption by vertical.

Verticals include:

�� Agriculture (farming, forestry, livestock, fisheries, agricultural equipment)

�� Datacenters (IoT-specific growth, as well as IoT applications within the datacenter)

�� Energy and utilities (electricity, oil, gas, water infrastructure)

�� Health (hospitals and medical equipment, telehealth, wearables)

�� Industrial (manufacturing, construction, mining)

�� Military (battlefield equipment and soldiers, vehicles and aircraft)1



�� Retail (interactive displays, inventory management, point of sale)

�� Smart buildings (access control and surveillance, employee tracking, HVAC, elevators)

�� Smart cities (lighting, waste management, traffic and congestion optimization)

�� Smart homes (thermostats, appliances, cameras, speakers)

�� Transportation (fleet telematics, civilian and commercial aircraft, ships)

�� Wearables (fitness trackers, smartwatches, augmented and virtual reality equipment) 2

VotE: IoT provides actionable data and insight to understand the key dynamics driving the enterprise IoT ecosystem. It combines 451 Research’s industry-leading analysis with an extensive network of over 50,000 senior IT professionals to track the disruption occurring in the market and exposes the major opportunities for enterprises, IT vendors, suppliers and inves-tors. Delivered quarterly, VotE: IoT analyzes the ways in which IoT is disrupting how businesses operate and the products they sell.

VoCUL identifies and tracks the market impact of disruptive and emerging changes in technology end-user buying behav-ior and preferences through quarterly monitoring from multiple survey groups. VoCUL combines 15+ years of accurately predicting trends on consumer and business technology buying plans from our managed, leading indicator survey panel with topical deep dives and segmentation capabilities from our US population representative surveys.

Market Monitor & Forecast data exploits 451 Research’s deep insight into both startups and established technology ven-dors. More than 100 analysts work closely with the Market Monitor team to collect data and set revenue estimates. As a result, when clients pair Market Monitor & Forecast numbers with our in-depth qualitative research, they receive a deep and unified view of some of the most disruptive segments of the current technology marketplace. The Market Monitor & Forecast product family offers market-size, share and forecast data for key emerging segments of the enterprise technol-ogy marketplace. Our analyst team builds out revenue estimates for each vendor in the segment, and performs global and regional market sizing in some areas.

Reports such as this one represent a holistic perspective on key emerging markets in the enterprise IT space. These markets evolve quickly, though, so 451 Research offers additional services that provide critical marketplace updates. These updated reports and perspectives are presented on a daily basis via the company’s core intelligence service, 451 Research Market Insight. Forward-looking M&A analysis and perspectives on strategic acquisitions and the liquidity environment for tech-nology companies are also updated regularly via Market Insight, which is backed by the industry-leading 451 Research M&A KnowledgeBase.

Emerging technologies and markets are covered in 451 Research channels, including Cloud Transformation; Customer Ex-perience & Commerce; Data Platforms & Analytics; Datacenters & Critical Infrastructure; Development, DevOps and IT Ops; European Services; Information Security; Internet of Things; Managed Services & Hosting; Multi-Tenant Datacenters; Net-working; Storage; Systems & Software Infrastructure; and Workforce Productivity & Compliance. Beyond that, 451 Research has a robust set of quantitative insights covered in products such as Voice of the Enterprise, Voice of the Connected User Landscape, Market Monitor, the M&A KnowledgeBase and the Datacenter KnowledgeBase.

All of these 451 Research services, which are accessible via the Web, provide critical and timely analysis specifically focused on the business of enterprise IT innovation. For more information about 451 Research, please go to: www.451research.com.

2 . The examples in each vertical are representative but not exhaustive. The 451 Research GIMM includes more than 1,000 connected device types.



Defining the Fog Opportunity451 Research estimates the conservative market opportunity for Fog computing to be $18.2bn by 2022, growing from $1.032bn in 2018 as products and standards emerge and each vertical market adopts at its own pace. The key verticals contributing to the market are energy and utilities ($3.84bn), transportation ($3.296bn) and healthcare ($2.737bn).

Figure 2: Growth of Fog opportunity by vertical market

Source: 451 Research OpenFog project analysis

$582

$3,296

$524

$2,305

$503

$2,737

$162

$856

$178

$509

$851

$3,840

$362

$2,118

$160

$693

$128

$629

$99

$413

$158

$778

2019 2022

WEARABLES

SMART HOMES

SMART CITIES

SMART BUILDINGS

AGRICULTURE

UTILITIES

RETAIL

DATACENTERS

HEALTHCARE

INDUSTRIAL

TRANSPORTATION

$18.2bn

$3.7bn



This market forecast captures both Fog as a service (FaaS), where the vendor leases an outcome (hardware/software/ser-vices) to the end customer, and Fog as a product,’ where the vendor sells Fog-enabled products and services to the cli-ent. Both of these business models are included in the overall Fog market forecast because the hardware, OS, application software, security and orchestration components are required to operate a Fog node regardless of whether managed by a vendor or enterprise/end user. 451 Research anticipates that adoption of the FaaS model will initially trail product-oriented approaches among early adopters, but that FaaS will grow to represent more than one-third of all deployments by 2022 as the outcome-based lease model grows in familiarity and popularity.

Figure 3: Growth of Fog as a serviceSource: 451 Research OpenFog project analysis

Vertical Market 2018 2019 2020 2021 2022 18-22 CAGR

Product $862 $2,933 $6,012 $8,819 $11,810 92%

Y/Y Growth -- 240.1% 105.0% 46.7% 33.9%

Segment Share 83.6% 79.1% 74.0% 69.5% 65.0%

Cloud $170 $773 $2,116 $3,875 $6,365 147%

Y/Y Growth -- 355.7% 173.6% 83.1% 64.2%

Segment Share 16.4% 20.9% 26.0% 30.5% 35.0%

Total $1,032 $3,706 $8,128 $12,694 $18,175 105%

Y/Y Growth 0.0% 259.1% 119.3% 56.2% 43.2%

The initial Fog market forecast is dominated by hardware components (51%), followed by application software (Fog-en-abled analytics – 19.9%) and ongoing Fog services (15.7%). 451 Research forecasts that Fog-specific hardware will decrease as a percentage of the total Fog market over time – from 51% to 42% – as standardization and commodification become prevalent, with application software and Fog services capturing that ‘wallet share’ of overall Fog spending. Also worth noting is that there is variation in the mix of hardware and software components and services application by application, and vertical market by vertical market. This is primarily based on whether Fog node capability is incorporated into specific-function hardware (e.g., cloud-assisted navigation ‘sandboxed’ within autonomous vehicle onboard computers) or general-purpose hardware (e.g., Fog node application hosted on standard datacenter servers).

AG R I C U LT U R EThe agricultural forecast component of the Fog market forecast includes aquaculture, livestock, forestry, farming and agri-cultural equipment. The largest component of the forecast was the adoption of IoT technologies such as inexpensive sen-sors and machine learning for precision agriculture, primarily in equipment such as tractors, seeders and similar modern farming equipment. Recent M&A activity in this space includes the acquisition of computer vision and machine-learning startup Blue River Technology by Deere & Company for $305m in September. Fog node capability is forecasted to primarily be feature functionality that is hosted on agricultural equipment onboard control and navigation systems, and on aftermar-ket/retrofitted gateways on ‘brownfield’ equipment. Fog computing is a natural complement to precision agriculture where latency plays a key role in seeding and fertilizing.

DATAC E N T E RDatacenters are leading in the adoption of IoT technologies, according to the 451 Research VotE: Internet of Things survey responses. The leading IoT application cited by respondents to the 2017 IoT Workloads and Key Projects survey was data-center IT equipment (42.6%), with an additional 26.6% of respondents identifying datacenter facility equipment as a key IoT use case. While interest is high in IoT for datacenter projects, that doesn’t equate to high revenue for the sector for IoT-only projects, or for Fog specifically.



In addition to datacenter adoption of IoT and Fog computing for internal use (within the datacenter), Fog computing will drive demand for additional datacenter capacity as analytics workloads are shifted from the edge to datacenter (near edge), enterprise and carrier multi-access edge, colocation and hosting, and the cloud. The forecast model includes what we believe to be a conservative incremental forecast for datacenter capacity (both on-premises and off-premises) directly at-tributable to Fog; however, this component of the overall Fog market could potentially be considerably larger than forecast depending on the Fog applications developed.

This additional capacity includes compute/storage/networking as it directly applies to Fog computing in on-premises data-centers, and off-premises in network operator infrastructure, hosting/interconnect, and public and private cloud providers. This was derived via a combination of the 451 Research VotE: Cloud Transformation quantitative survey and the Global IoT Market Model.

E N E RGY A N D U T I L I T I ESThe energy and utilities sector presents the largest market for Fog computing of any of the vertical markets analyzed, with the potential opportunity to reach $3.84bn by 2022. This vertical includes a vast array of energy infrastructure components, including nuclear power plants, offshore oil platforms, high-voltage electricity transmission towers, and residential natural gas and water meters. The global energy industry is undergoing major transformation under pressure from distributed generation (solar, wind), electric grid bidirectionality, effective energy storage, water conservation, and massive public/private investment in replacing the aging and inefficient electricity transmission and distribution infrastructure worldwide.

Figure 4: Historical and projected transmission investment, North America only (Billions $)Source: Edison Electric Institute, 2015

Fog computing has natural synergies with the energy industry, where latency-sensitive infrastructure compo-nents (generation plants, oil rigs, long-haul transmission lines) are frequently remote from primarily urban host-ing and cloud computing assets. Surprisingly, although highly regulated, the electricity, water and gas critical infrastructure industries have not been shy in their adoption of cloud computing and big-data analytics to squeeze efficiencies out of existing infrastructure assets. Utility respondents to the 451 Research VotE: IoT Work-loads and Key Projects 2017 survey identified off-premises computing resources as the first point of data analyt-ics in 11.8% of applications.

$10.2

$11.9

$14.8

$16.9

$19.5 $20.1$21.5

$22.5$21.0

$18.5

2010 2011 2012 2013 2014 2015 2016 2017 2018 2019

ACTUAL PROJECTED



H E A LT H CA R E

3. Source: Infrastructure Consortium for Africa, United Nations Development Program. “Africa Energy Atlas (2017).”4. Source: European Commission (2014). “Population Aging in Europe: Facts, Implications, and Policies.”

The healthcare industry presents the third-largest potential opportunity for Fog computing, with an estimated $2.74bn potential opportunity in 2022. In the US, the reimbursements model has shifted from one of ‘fee for service’ to one of outcome-based reimbursements. This is evident in the key driver for IoT projects among healthcare industry respondents to 451 Research VoTE: IoT Workloads and Key Projects 2017, which was reducing risk (60.9%). In sub-Saharan Africa, only 34% of hospitals and 28% of health facilities have reliable electricity access,3 creating opportunities for store-and-forward, localized Fog computing until WAN connectivity is restored. In Asia, the demands on healthcare infrastructure will balloon as the share of population aged 65 and over skyrockets from 8.1% in 2016 to 20.5% in 2050. Europe already faces these same demographic challenges, with one-quarter of the population of Europe to be 60 years or older by 2020.4

As with energy and utilities, the healthcare sector is a mix of latency-sensitive real-time applications (literally, ‘life and death’ applications) and post-hoc, non-latency-sensitive applications for analysis of large volumes of device telemetry data. In addition, healthcare will drive the ‘where-ness’ of data analytics based on geography and nation-state regula-tion. One parameter in Fog computing is geographic placement of workloads and analytics to adhere to these healthcare data-sovereignty requirements.

I N D U ST R I A LThe industrial vertical includes manufacturing in its many forms, construction, mining and the supporting industries for the above. While the industrial sector is the largest vertical market for IoT deployments, 451 Research analysis identifies it as the fourth-largest Fog computing opportunity. This is due to a number of factors, including the rate at which large manufactur-ing equipment is depreciated and replaced (with new, Fog-enabled hardware), the speed of innovation in the construction sector and macroeconomic challenges for the mining industry.

There are broad variances in technology adoption within the different forms of manufacturing (e.g., high tech robotic man-ufacturing of electronics vs. pet food manufacturing), as well as within construction and even mining, which ranges from very little automation to very advanced open-pit mines with autonomous mining vehicles and drones. Therefore, given the sheer scale and diversity of the industrial sector and geographic differences, this vertical was the most complicated in terms of forecasting demand.

Factored into the industrial Fog forecast were both ‘greenfield’ (new equipment) sales, which incorporate Fog capability at the point of manufacture, and brownfield sales, the retrofitting of existing manufacturing, construction and mining equipment with additional technology to improve yield and uptime. The brownfield opportunity is critical, given the long depreciation cycles (20-30 years) of some large capital equipment purchases.

M I L I TA RYThe military presents a considerable opportunity for Fog computing technologies, driven by two key factors: the cost of devices (high) and the rate of adoption (large increments). For this forecast, military is not broken out as a separate market opportunity, but the more than 250 distinct military node types are incorporated within transportation (tanks, artillery and personnel carriers, military watercraft, military aircraft), buildings, datacenters and wearables (combat soldier equipment). In addition, the average ‘Fog node per endpoint’ count is higher in military than in any other vertical, given the criticality of combat aircraft and watercraft individual systems (draught and submerged pressure sensors in watercraft, weapons plat-forms and flight control systems in aircraft).

R E TA I LRetail is a broad industry sector and includes wholesale warehouses, as well as large and small retail establishments (gaso-line stations, electronics and appliance stores, restaurants). The retail sector, while historically lagging in adopting new technologies when compared with other industries, has strong demand for new technology and the IoT. Retail industry respondents to the 451 Research VotE: IoT Workloads and Key Projects 2017 survey identified both the need to optimize operations (66.7%) and the need to enhance customer targeting (60%) as key drivers for new technology deployments. This, in turn, has contributed to the rollout of new technologies including Bluetooth Low Energy (BLE) beacons to track customer movement around physical locations, omni-channel marketing by tying mobile devices to online behavior, in-ventory tracking using RFID and shelf displays with demand-based pricing, and interactive displays to engage customers



for a ‘stickier’ in-store experience. The recent EMV (Europay, Mastercard and Visa) ‘liability shift’ to chip and pin payment systems has created an episodic opportunity for point-of-sale (PoS) vendors and resulted in the widespread ‘rip and replace’ of legacy PoS systems.

S M A RT B U I L D I N G SBuilding control, security and management systems constitutes another legacy market in the midst of transition. New ‘smart buildings’ that use pervasive sensor data to adjust HVAC, window tint and lighting are becoming more prevalent in Asia and Europe, and the incentives to be certified as Leadership in Energy and Environmental Design (LEED) ‘green’ buildings continue to increase for developers and building owners in the form of government incentive programs and lower opera-tional costs. Security and surveillance was the second-most prevalent IoT application identified in the 451 Research VotE: IoT Workloads and Key Projects survey; an average of 52% of respondents identified the application as a target area to be enabled by IoT. Worth noting is that government and education scored highest regarding demand for IoT-enabled security and surveillance technology adoption.

The Fog market forecast for smart buildings includes surveillance and security (cameras, access control), as well as elevators, lighting fixtures, HVAC control processors and other building management systems.

S M A RT C I T I ESThere is no common definition for the term ‘smart city.’ Definitions range from basic public broadband connectivity to more elaborate, interconnected systems such as the Emirate of Dubai’s smart city project, in which 1,000 government services go smart by 2017. In addition to modeling existing global smart city projects and announced initiatives, 451 Research has forecasted further country-by-country, region-by-region adoption of smart street and traffic lighting, environmental sen-sors, waste bins, smart parking and surveillance, among many other factors. Transportation, energy and buildings are not included in the smart city market sizing, but are included in other respective verticals. Worth noting is that government re-spondents to the 451 Research VotE: Internet of Things Workloads and Key Projects 2017 survey had the smallest quantity of off-site data storage and analytics (19.6%) of any of the 10 vertical markets encompassed in the survey, making government a potentially challenging market for initial Fog adoption, thus the comparatively small smart city Fog opportunity forecast.

S M A RT H O M ESSmart home technology, previously the domain of enthusiasts and hobbyists, has reached the mainstream. The 451 Re-search VoCUL 2017 US Consumer Representative Survey of Smart Home Device Ownership and Buying Trends indicates that 29.6% of all respondents already own smart home devices, including thermostats, appliances and ‘smart speakers’ such as Google Home and Amazon Echo. Consumers are struggling with interoperability between the multitude of device types, and 74.6% of respondents identified themselves as ‘very concerned’ or ‘somewhat concerned’ about the safety and security of their internet-connected smart home devices.

As is the case in smart buildings, Fog can play a role in the consumer smart home market in access control (smart ga-rage doors, door locks, motion sensors, cameras), as well as in environmental monitoring applications (thermostat/HVAC, flood/freeze sensors, smoke/CO2 detectors). 451 Research identified fewer opportunities for Fog in primarily entertainment-related applications such as smart speakers, which typically stream content over the internet, other than in content delivery network/caching applications of Fog at intermediate points within the internet. The price pressure on consumer devices – that is also occurring in wearables (below) will drive revenue forecasts for Fog capability down, making it a less-attractive market for technology vendors to initially target.

T RA N S P O RTAT I O NThe transportation sector is the second-largest potential market for Fog computing with the potential to reach $3.29bn by 2022. Transportation is a key market for the characteristics of Fog, given the intermittent connectivity and mobility of the assets. The 160+ transportation device endpoints incorporated in the forecast range from assets on the ground (commer-cial trucks, consumer automobiles, public transport), water transportation (ships), rail and aircraft (consumer, commercial, military aircraft).

There are three major market transitions underway in transportation that will contribute to the adoption of technology and potential Fog capabilities. These are connectivity (connected car/plane/rail), telematics (fleet trucking route optimization, condition-based maintenance), and autonomy (advanced driver-assistance systems, autonomous vehicles) across all sec-tors. These trends are not mutually exclusive, and all will contribute to increased volumes of data generation and analysis.



W E A RA B L ESThe final vertical market included in the Fog market forecast is wearables. This includes a range of devices from fitness track-ers and smartwatches to augmented and virtual reality wearables, as well as more sophisticated military soldier wearables. The military wearable component of the wearable forecast represents the majority (70%+) of the forecasted $778m op-portunity in 2022, with consumer wearables constituting the remainder. This is primarily due to pricing pressure in the con-sumer space, which is also present in the smart homes vertical. Disruptive developments in augmented reality technology that would radically increase adoption could drive this forecast up beyond anticipated levels, as could increased adoption of ‘enterprise wearables,’ but the consumer smartwatch and fitness tracker market segments alone will not meaningfully con-tribute to demand for Fog technologies and applications. The 451 Research VoCUL: Wearable Device Ownership and Buying Plans Q3 2017 survey respondents indicated that there is fair existing penetration of these devices, with 17% of respondents indicating that they already own a smartwatch, and 18% indicating existing ownership of a health and fitness monitor.

Appendix A: Fog Market ForecastFigure 5: Fog computing revenue by vertical market ($m)


Transportation $132 $582 $1,251 $2,141 $3,296 123.4%

Y/Y Growth -- 339.9% 115.1% 71.1% 53.9%

Industrial $150 $524 $1,079 $1,672 $2,305 97.9%

Y/Y Growth -- 248.5% 105.9% 55.0% 37.9%

Healthcare $117 $503 $985 $1,680 $2,737 120.1%

Y/Y Growth -- 330.8% 96.1% 70.5% 62.9%

Datacenters $82 $162 $322 $531 $856 79.7%

Y/Y Growth -- 97.7% 98.2% 65.3% 61.1%

Retail $74 $178 $278 $387 $509 61.8%

Y/Y Growth -- 139.2% 56.1% 39.4% 31.5%

Utilities $238 $851 $2,008 $2,836 $3,840 100.4%

Y/Y Growth -- 257.1% 136.1% 41.2% 35.4%

Agriculture $97 $362 $1,100 $1,606 $2,118 116.3%

Y/Y Growth -- 273.8% 204.3% 46.0% 31.9%

Smart Buildings $36 $160 $311 $514 $693 110.1%

Y/Y Growth -- 349.1% 94.7% 65.3% 34.9%

Smart Cities $26 $128 $279 $431 $629 120.8%

Y/Y Growth -- 384.8% 117.3% 54.3% 46.1%

Smart Homes $47 $99 $165 $267 $413 72.4%

Y/Y Growth -- 112.6% 66.3% 62.0% 54.4%

Wearables $33 $158 $350 $629 $778 120.8%

Y/Y Growth -- 383.1% 121.5% 79.5% 23.8%

Total $1,032 $3,706 $8,128 $12,694 $18,175 104.9%

Y/Y Growth -- 259.1% 119.3% 56.2% 43.2%Source: 451 Research OpenFog project analysis



Figure 6: Fog computing revenue by component ($m)


18-22 Share Δ

Hardware Components $533 $1,824 $3,809 $5,643 $7,659 94.7% -9.5%

Y/Y Growth -- 242.4% 108.9% 48.1% 35.7%

Share of Fog Market 51.6% 49.2% 46.9% 44.5% 42.1%

OS Components $49 $188 $426 $693 $1,035 113.9% 0.9%

Y/Y Growth -- 280.7% 126.7% 62.5% 49.3%


Fog Applications/Platforms $205 $741 $1,649 $2,659 $3,903 108.8% 1.6%

Y/Y Growth -- 260.8% 122.5% 61.3% 46.8%


Security $44 $173 $397 $649 $964 116.7% 1.1%

Y/Y Growth -- 295.5% 129.7% 63.5% 48.5%


Management $39 $153 $361 $602 $909 120.2% 1.3%

Y/Y Growth -- 296.2% 135.7% 66.8% 51.0%


Fog Services $162 $627 $1,486 $2,448 $3,705 118.6% 4.7%

Y/Y Growth -- 286.5% 137.0% 64.7% 51.3%


Total $1,032 $3,706 $8,128 $12,694 $18,175 104.9% --

Y/Y Growth -- 259.1% 119.3% 56.2% 43.2%Source: 451 Research OpenFog project analysisIt is worth reiterating that Fog as a service, Fog application services and Fog support services are different from one another. For the sake of clarity, in this model, we define these as follows:

� Fog as a service: A product offering from a vendor that sells an outcome to the client, where the client pays monthly/quarterly/annually for a particular outcome and service-level agreement, and the hardware/software/etc. that is required to achieve this outcome is likely owned by the vendor and leased to the end user as part of the ‘as a service.’

� Fog application services: These are enabling applications that are designed ‘a priori’ as distributed computing and ana-lytics functions within, and potentially outside of, a customer environment. These would include multitier analysis of machine data within control-loop latencies (<10ms) graduating up to aggregation and, ultimately, non-latency-sensitive post-hoc analysis of large datasets.

� Fog support services (annotated as ‘Fog services’ in the model) capture the ongoing maintenance and support services for customers that pursue an ‘as a product’ (vs. an ‘as a service’) purchase model, where the end user owns the hardware/software/etc. in a Fog environment and pays for annual service and support on same.



Appendix B: Key Forecast Assumptions, Considerations and DependenciesThe following have been included in the market-sizing forecast.

� Intelligent endpoints – growth over time of Fog node capability in key market verticals including manufacturing equip-ment, automotive, utility meters, medical equipment, drones, robots, wearables.

� Gateways and special function distributed compute boxes that will function as Fog nodes for non-robust endpoints, including dedicated gateways and access points for Fog functions.

� Aggregation devices such as micro-modular datacenters on-premises or at a central IT location that will participate as Fog nodes.

� Network operator components such as compute devices in the radio access network as part of 4G LTE or 5G networks leveraging MEC.

� Specialized compute service providers such as interconnects and hosting service providers that will participate in the Fog things-to-cloud continuum as aggregation points.

� Cloud service providers that have or will implement Fog capabilities.

More specifically, the following have been included as part of the market-sizing estimates.

� Hardware components (100% of dedicated Fog nodes, or partial attach rate for multi-function devices that also include Fog node capability such as intelligent robots, automotive head-end units, etc.).

� Operating system components for the hardware above.

� Fog node applications/platforms that will be sold separately for execution on endpoints, gateways, dedicated devices or general-purpose computing environments.

� Separate security and orchestration/management for HW/OS software above.

� Dedicated (or fractional for multi-use devices) MEC used as Fog nodes (HW/SW/OS/security/orchestration).

� Interconnect/hosting participating Fog node services (HW/SW/OS/security/orchestration).

� Cloud provided participating Fog node services (HW/SW/OS/security/orchestration).

Excluded from the estimates and market sizing are professional services for installation and ongoing maintenance of Fog, ‘drag along’ upgrades to carrier infrastructure other than dedicated Fog nodes, and network transport costs incurred in carrying Fog traffic. Additional demands for bandwidth for Fog traffic that would pull through additional networking infra-structure have also excluded from this forecast.

The assumptions inherent in a model of this magnitude are multilayered because they include assumptions and data from multiple 451 quantitative survey instruments. We began with more than 1,000 endpoint types, with breakdowns of each in hardware, operating system software, application software (in this case, Fog applications), security, management (orches-tration) and support services. In addition, we modeled the data generated by each device type, as well as made assump-tions on a device-by-device basis of how much of the overall device cost could be attributed to Fog-specific capabilities. We also modeled the distribution between hardware and software and on-premises vs. off-premises, leveraging data from two years of IoT adoption trend data from the 451 Research VotE: Internet of Things.

Finally, the percentage of open vs. non-open Fog deployments is not broken out from the broader Fog address-able market because there will inevitably be proprietary single-vendor approaches to Fog computing that will fail or succeed depending on the value proposition provided by interoperability between Fog components in contrast to proprietary approaches.

Size and Impact of Fog Computing Market AND IMPACT OF FOG COMPUTING MARKET CORIHT 2017 451 RESEARCH...

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