By 2020, IoT Connectivity Revenues Might be 10% of Total

Internet of Things deployments and revenue are growing, and have been since at least 2015, according to BCG. Communications services (network access) might represent about 10 percent of total IoT revenues in 2020. 

That is why it makes sense for connectivity providers to look for additional roles within the ecosystem. 

source: BCG

The verticals with the most spending in 2020, according to BCG, are manufacturing, transportation and utilities. 

source: BCG

source: BCG

Smart City Spending Lead by Smart Grids, Traffic, Transit, Surveillance, Lighting

The top priorities for smart cities initiatives are smart grids, followed by data-driven public safety and intelligent transportation, as global spending on smart cities initiatives reaches $189.5 billion in 2023, according to researchers at IDC. 

Together, smart grids, advanced public transit, visual surveillance, outdoor lighting and intelligent traffic management will account for more than half of all smart cities spending throughout the 2019-2023 forecast, IDC predicts.

source: IDC

The use cases that will see the fastest spending growth over the five-year forecast are vehicle-to-everything (V2X) connectivity, digital twin, and officer wearables.

Singapore will remain the top investor in smart cities initiatives, driven by the Virtual Singapore project, IDC says. New York City will have the second largest spending total this year, followed by Tokyo and London. 

Beijing and Shanghai were essentially tied for the number number five position and spending in all these cities is expected to surpass the $1 billion mark in 2020.

On a regional basis, the United States, Western Europe, and China will account for more than 70 percent of all smart cities spending throughout the forecast. Japan and the Middle East and Africa (MEA) will experience the fastest growth in smart cities spending with CAGRs of around 21 percent, IDC says. .

Telco Role in Edge Computing LIkely Highest in Hybrid Scenario

Potential connectivity service provider roles in edge computing vary by chosen role, but also by the value of edge analytics. 

It is fair to note that the advantage of edge computing in some cases hinges on how much analytics contributes to the value of sensor data, in real time or near real time. In essence, the broad choices are processing at the edge, in the cloud (at a remote location) or using a hybrid approach. 

By definition, edge analytics adds value when the analytics are necessary for real-world processes that are very dynamic. On the other hand, remote processing might make more sense when learning does not have very-dynamic implications, and when the amount of raw data transmitted to the remote data centers is reasonable. 

The hybrid approach (some local analytics, some remote analytics) makes sense in scenarios where decisions and response time are optimized, but network data load also is reduced. 

In other words, even if analytics run many times faster at the far edge, there can be latency when the amount of raw data to be crunched is very high (analysis of video feeds, for example), as well as transmission cost implications. 

But analytics location also is controlled by the application setting. Engine performance of a motorcycle perhaps cannot easily be conducted anywhere but at a remote location. But data might be collected and then transmitted in non real time using store and forward. 

On the other hand, data related to road hazards or mechanical condition of the brakes might have to be displayed and processed locally to have any immediate value. 

Local analytics might also make sense if the edge device has the ability to handle the amount of local processing, and if the device already is fully paid for, thus avoiding recurring transmission costs. 

Longer-term analytics might then be performed by cloud data centers that have gotten the records non real time. 

Telcos and other connectivity service providers arguably have the greatest value in edge computing when hybrid computing is optimal. The edge processing centers might offer small value when the edge devices can process real time data themselves.

Likewise, edge computing for analytics provides small value when data can be processed remotely, in non real time, by cloud data centers. Arguably, the highest value is provided by edge computing facilities when end user devices do not have the ability to process in real time but when near real time analytics are valuable. 

Connectivity service providers can, in principle, choose from various business roles and revenue models of varying risk and value proposition. The lowest risk approaches tend to have lowest value, the highest risk approaches the highest value, as elsewhere in the information technology ecosystem. 

Service providers can choose to create and operate dedicated edge hosting facilities, where the telco owns and manages edge-located compute/storage resources that are connected to the telco network. The customer  runs its software or applications. This is similar to a colocation or hosting revenue model. 

In other cases, the edge computing provider might choose to operate edge infrastructure or platform “as a service.” This is the edge version of the AWS cloud computing model. 

Also, a connectivity provider can choose to operate as a system integrator, providing turnkey information systems that require an edge computing component. 

Connectivity providers might choose to develop their own edge-computing-based solutions for enterprises or other organizations,  

Finally, some connectivity providers might develop end-to-end consumer retail applications based on edge computing support, such as virtual reality for live sports events, for example. 

No matter which approaches are chosen, attempting to have a greater role in edge computing, beyond supplying connectivity, will make sense for larger service providers. Arguably, even the lowest-value edge computing role has more value than the connectivity role alone.

Communications Will Represent 10% of IoT Market Revenue in 2020

Internet of Things deployments and revenue are growing, and have been since at least 2015, according to BCG. Communications services (network access) might represent about 10 percent of total IoT revenues in 2020. 

That is why it makes sense for connectivity providers to look for additional roles within the ecosystem. 

source: BCG

The verticals with the most spending in 2020, according to BCG, are manufacturing, transportation and utilities. 

source: BCG

source: BCG

As IoT Grows, So Do Digital Twins

A digital twin is a software replica of a living or non-living physical entity, and seems to be growing in importance now that internet of things sensors are able to provide enough data to create real-time virtual duplicates of machines and processes. 

Twins can provide a complete digital footprint of products from cradle to grave, allowing companies to detect physical issues sooner, predict outcomes more accurately, and build better products by maintaining a complete feedback loop from design to retirement.

source: GE

Among the stated benefits are:

• Lower spending on asset repair and maintenance
• Predictive rather than responsive business decisions
• Improved regulatory and industrial standard compliance
• Better tracking of efficiency and productivity

source: DocSend

What is Digital Twin? How does it work?

Digital twins--virtual represenations of real-world machines and processes--become more important as internet of things beomes more important. 

IoT Connectivity Market Shares

Opinions differ about the relative market shares of mobile service provider IoT access services built on licensed spectrum, compared to low power wide area networks using unlicensed spectrum. 

Separately, there is the role to be played by private networks owned and operated directly by enterprises. Private LTE, for example, is viewed as an important platform for some automative factory applications.

source: Mobile Experts

The easy answer at this point is that a number of platforms will have sizable share in the wide area marketplace, while local connection technologies are expected to rely on unlicensed spectrum and short-range access networks. 

There are, to be sure, some present cost differences. LPWA using unlicensed spectrum has had a cost advantage in terms of network costs and arguably for sensors as well. Those sorts of cost advantages tend to narrow with volume, though. 

source: Sierra Wireless

source: Sierra Wireless

source: Sierra Wireless

China Hyperscale Data Center Spending Drops 37%

A sharp decline in capital spending by hyperscale data centers in China lead to a decline of  global capex of two percent in the second quarter of 2019, according to Synergy Research.

source: Synergy Research

IoT Platform Markets Still Highly Fragmented

Someone asked me recently where the “picks and shovels” plays were in internet of things as IoT drives edge computing. The problem right now is that enabling technologies, tools and platforms are highly fragmented. 

One recent analysis found just a handful of firms selling IoT platforms have annual revenue of more than $10 million. 

source: IoT Analytics

And much of that revenue is essentially relabeled current revenue that could be considered “IoT.” 

source: IoT Analytics

Enterprise Software Spending Grows, Hardware Shrinking

Software is not only the largest category of US tech budgets; it is also the fastest-growing, with increases of 10 percent in 2019 and eight percent in 2020, according to Forrester Research.

The main cause of this growth is the U.S. shift to cloud software, especially mult-tenant software as a service. Demand for front-office sales, marketing, and customer service software is especially strong, Forrester says.

Demand is also rising for back-office software for finance, human relations, purchasing, risk management, and core transaction systems. 

The combination of rising spending on cloud and slowing revenues will put pressure on the other categories of computer equipment, communications equipment, and telecommunications services, Forrester also notes.

Communications equipment spending growth will slow to under three percent in 2019 and under 1.5 percent in 2020. And spending on voice and data wireless and wired telecom services will expand by around one percent each year.

“We do expect a slowing U.S. economy will lead to U.S. tech budget growth decreasing from almost six percent in 2017 and 2018 to five percent in 2019 and four percent in 2020, the firm predicts.

source: Forrester Research

5G IoT Monetization

John Abraham, Analysys Mason analyst, discusses "monetization" of new services, often internet of things related, on 5G networks.

Where is the Edge?

It still remains unclear where the “edge” is for “edge computing. Sometimes it is on the device; sometimes on a premises; sometimes elsewhere in the metro area. Latency-sensitive applications are believed to be the use cases driving various forms of edge computing. 

Such use cases drive thinking that there is a role for service provider edge computing, in some instances. As has been the case for content delivery networks, there is value in placing content or processing closer to the places where content is consumed, or decisions must be made. 

The idea is to put processing someplace in the network closer to the end user devices and apps, but not at remote cloud data centers. Athonet, for example, uses the term “Servicing Gateway Local Break Out” (SGW-LBO) to describe the way some traffic can be directed to local computing facilities rather than across the network to cloud data centers.

source: Athonet

Business Model for Network Slicing: Retail or Wholesale?

The business model for 5G network slicing could, in principle, take two different paths. It could be a way for service providers to create customized private networks for their customers. It might also become a wholesale product used by customers to create and control their own services, sort of on the model of enterprises buying computing instances and storage from Amazon Web Service. 

The former path will likely be the preferred model, as it tends to preserve more of the value of the connectivity role. The latter role will appeal to potential competitors who want to use network slicing the way they have purchased wholesale services to create mobile virtual network operator businesses, with the added ability, using network slicing, to customize experience. 

According to 3GPP  [TR23.501], “a network slice is defined as an end to end logical communication network, within a Public Land Mobile Network (PLMN) and includes the Core Network (CN) Control Plane, User Plane Network Functions and 5G Access Network (AN).”

The 3GPP sees a network slice as controlled by the network services provider, and used to create customized and virtualized services for customers. 

Others, including the IETF, see a broader application where end-to-end network slicing can be used by mobile networks and others.

The former view is a standard view of how telecom networks create services and features sold to customers. The latter view might be more akin to the way enterprises buy capabilities from Amazon Web Services. The former is more closed; the latter is more open. 

source: Ericsson

At a practical level, implementing the former means retail tariffs are created. The latter view implies that wholesale access is possible. 

Service providers will tend to resist the latter, as it further extends the “dumb pipe” business model, allowing wholesale customers to use connectivity features to create their own services, as do AWS cloud customers. In principle, they would rather create vertical market solutions with higher value on behalf of enterprise customers, or at the very least be the creators of customized connectivity solutions for those customers. 

When Will Quantum Changes Next Happen in Computing?

At what point do quantitative improvements in computing or communications networks lead to qualitative changes? And what is more important--advances in computing speed or communications network speed? 

Looking only at mobile networks, we have seen two orders of magnitude increases in end user device speeds, in each successive generation, from 2G to 4G, for example. That should not change with 5G, either. 

source: Speedtest

In a broad sense, the emergence of the internet, cloud computing and edge computing are examples of qualitative changes produced by all the quantitative changes. Eventually, faster speeds and more bandwidth, resulting in lower application latency, plus lower prices, enable new use cases. 

Perhaps these changes are easier to see on mobile platforms, as the generational differences in platform are easier to describe. 

source: Nielsen Group

Only analog voice was possible in the first mobile generation. Low-speed data and texting became possible in 2G. Mobile internet became widespread in the 3G era. Mobile consumption of video became possible in the 4G era. What use cases will characterize the 5G era are not yet clear. But it seems reasonable to assume that some characteristic new use cases will develop as a result of quantitative improvements in network performance and cost. 

source: GlobalData

What might now be clear, though, is that 5G will be among the instances where improvements in communications networks provide the quantitative changes that result in qualitative developments. Edge device processors and capabilities will improve. But the decisive changes will come from new capabilities in the communications networks.

AWS Revenue Up 37%; Azure Up 19%

Amazon.com Inc. and Microsoft Corp., reported year-over-year growth of 37.3 percent and 18.6 percent in their respective cloud-related segments for the first half of 2019, according to S&P Global. 

While Microsoft's intelligent cloud segment reported the larger top-line figure, with $11.39 billion in revenue versus $8.38 billion from Amazon's web services segment, Microsoft includes results from its server products and enterprise services as well as its primary cloud product Azure in the intelligence cloud total.

Google Cloud is about an $8 billion annual run rate as of June 2019, the ratings firm says.

Azure revenue grew 64 percent year over year during the most-recent quarter. Some of that growth is due to technology that extends Azure services to the edge of the network for a hybrid cloud offering

source: S&P Global

AI, VR Create Need for Edge Computing, 5G Access

Edge computing--including mobile edge computing or infrastructure edge computing-- is seen as a fundamental building block for some types of consumer applications. Latency is a key issue. Apps such virtual reality or augmented reality, used in consumer settings, will require ultra-fast processing and response. 

The other issue is the need to move huge amounts of data, which in turn raises the issue of bandwidth cost. Edge computing is one solution, putting the processing nodes very close to the app end users. 

Mobile 5G networks then come into play as the connectivity solutions, largely because untethered and ambient operation will often be the preferred or only mode of use. 

source: Qualcomm

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