1.
EDGE COMPUTING
M&A Trend Analysis and the Acquired Patent Capabilities
October 2019

2.
TABLE OF CONTENTS
Introduction............5
Rise of Edge Computing Solutions............6
Edge Computing Use Cases............7
Key Drivers of Edge Computing............9
Need to Invest in Edge Computing............10
1
2
3
Mergers and Acquisitions in Edge Computing:
Trends between 2015 – 2019............12
Year wise Analysis............13
Geography Analysis............13
Acquirer Landscape............14
Technology Breakdown............14
Acquisition Trend #1 Data Center............16
Acquisition Trend #2 SD-WAN............18
Acquisition Trend #3 Artificial Intelligence (AI)............20
Acquisition Trend #4 Security............22
Acquisition Trend #5 Analytics............23
Acquisition Trend #6 Multi-access Edge Computing(MEC)............24
Acquisition Trend #7 Interoperability Solutions............25
Acquisition Trend #8 Embedded Technologies............26
Acquisition Trend #9 Other Capabilities............27
Patent Capabilities of the
Target Companies............30
Methodology............30
The Acquired Technology Landscape............31
Breakdown of Key Technology Areas............32

3.
4
Patent Coverage of Acquired
Target Companies............34
Technology Distribution of Top 5 Assignees............35
Patent Coverage of Other Assignees............38
Patent Analysis: Concluding Remarks............40
Insights and Recommendations..................42
Time to Market Strategies............42
ROI on the High Value Deals............42
Growing Interest in New Technology Areas............43
Support for Multi-cloud and Hybrid Architectures............43
Opportunities in Edge Computing............44
Integration of Blockchain Technologies with the Edge
Computing Architecture............44
AI-based Solutions not on the Radar of Acquiring Companies............44
5G............ 45
Appendix
Detailed Overview of Deals..................47
References..................58
TABLE OF CONTENTS
5
6

4.
Edge Computing: M&A Trend Analysis
Cloud computing has traditionally been the go-to strategy for most telecom operators,
enterprise IT and Internet of Things (IoT) solution providers, industry 4.0 operators, and other
service providers in a connected environment. With the accelerated growth in the adoption of
IoT devices, it is becoming increasingly difficult for centralized cloud architectures to handle
dynamic loads leading to network traffic, bandwidth and latency issues, and lack of efficient
and reliable data processing. This is driving the growth of edge computing.
INTRODUCTION
5

5.
Figure 1: Computing Architectures from Chips to Cloud
RISE OF EDGE COMPUTING SOLUTIONS
Edge computing is not a new concept. It has
evolved in the last few years and has been
the most prominent trend of the IoT
ecosystem. Discussions related to IoT always
start with the level of readiness for the global
proliferation of connected devices and end at
the need for decentralized solutions that can
eliminate several challenges. The evolution
has now reached a point where several
industries have already started adopting
edge computing architectures and
technologies for various business cases.
Therefore, it is critical to discuss the latest
developments in the space and gauge the
degree of shift that is happening between
cloud and edge computing
environments.
Edge computing indicates moving computing
resources closer to the edge of the network
where the data is generated – sensors,
vehicles, robots, cameras, mobile phones,
wearable devices, etc. However, the
definitions change based on the use cases
and the amount of computation happening
at the cloud, edge data centers, edge devices,
or directly on the device. Figure 1 represents
the computing architectures from a
centralized cloud to sensors and chips.
Centralized cloud infrastructure includes data
centers located at several global locations.
Although these facilities are distant from the
IncreasingProcessingPower
Edge Sensors/Chips
ReducingLatency
Centralized
Cloud
Edge Computing: M&A Trend Analysis
Edge Infrastructure
Edge Devices
6

6.
network edge (source of data generation),
they offer high capacity computation power
and optimum networking resources. As we
move closer to the edge of the network, from
the cloud to edge data centers to devices, the
computation capacity gradually decreases
and is lowest on the semiconductor chips.
However, this trend is changing, with
breakthrough innovations that are happening
in the semiconductor domain for increasing
the computation power of edge devices.
EDGE COMPUTING USE CASES
About latency, on-device computing
solutions offer the fastest results by
employing the latest AI technologies,
processors and related architectures, and
analytics. Many industry participants are
undertaking large investments for building a
strategy for edge computing with some of the
companies aiming latencies as low as 5
milliseconds for time- and
bandwidth-sensitive applications.(1)
Industries are recognizing the benefits of
edge computing and are exploring suitable
use cases that would help them garner
maximum benefits. Most of them are
deploying immersive technologies,
autonomous solutions, and other IoT
technologies that demand for near real time
latency for efficient outcomes. Industrial IoT
(IIoT) is expected to benefit the most, given
the amount of data generation and
computation involved in manufacturing
environments. To cite an instance, edge
analytics has proved to be a game changer
for a manufacturing plant that deploys AI for
computation -intensive tasks such as
predictive maintenance of expensive
machinery and quality control.
Autonomous vehicle is another use case
where innovative processors undertake
maximum computation of data from
multitude of sensors locally and send only
limited information to the cloud, which is also
preferably an edge data center in the vicinity.
Retailers can leverage latency-sensitive
immersive technologies for improving
customer experience and boosting
personalization in brick and mortar as well
as for offering smart online services. Figure 2
highlights the latency and bandwidth
requirements of various IoT use cases.
Edge computing architectures are expected
to drive smart city use cases including
security and video surveillance, drones for
smart monitoring applications, mobility and
transportation, smart grids, etc. Healthcare
applications like remote surgeries and
tactile internet are the most demanding use
cases in a connected environment that
require a latency of approximately one
millisecond with high bandwidth
throughput. These medical practices will
become prevalent with the evolution of
mobile edge computing fueled by next
generation 5G technologies.
Edge Computing: M&A Trend Analysis7

7.
KEY DRIVERS OF EDGE COMPUTING
Deemphasizing the cloud’s role in connected
environments is expected to lead to
autonomous solutions that have the potential
to transform the IoT landscape at a business
as well as a consumer level. Edge computing
promises the decentralized architectures
that are vital for improving performance,
enhancing security, and efficiency of IoT
applications. Figure 3 discloses the key
drivers of edge computing.
Near real time
processing and analysis
in milliseconds
Distributed
computing enables
optimized bandwidth
utilization
End user has
increased control
on their data
Commercialization of 5G
will boost the growth
of edge computing
Innovative networking technolgies
employed in the decentralized
architecture increase uptime
Adaptable and modular
architectures eliminate the
scalability issues that were
traditionally associated
with centralized solutions
Cost-effective computing
resources, software-defined
solutions, and reduced
data transmission costs
Increase operational efficiencies
at different levels from sensors
to data transmission
Figure 3: Key Drivers of Edge Computing
Source: Netscribes' Secondary Research
LatencyEfficiency
ReducedCost
Scalability
Reliability 5G
Privacy
Bandwidth
Edge Computing: M&A Trend Analysis
Key Drivers
9

8.
Edge Computing: M&A Trend Analysis
NEED TO INVEST IN EDGE COMPUTING
Edge computing technologies are disrupting
the cloud computing space. Companies are
transforming their business models to attain
edge computing capabilities necessary for
offering end to end services. Startups with
innovative networking technologies and
software-defined architectures are aiming to
increase the flexibility required for hybrid
network architectures. Emerging technologies
like AI and neuromorphic computing are
changing data processing and
decision-making. Data center architectures
are being redefined with easily available off
the shelf, cost-effective and efficient solutions
in the market. The upcoming 5G networks are
going to fuel the expansion of edge
infrastructure for high speed communication.
Edge Computing: M&A Trend Analysis
Edge computing is an inevitable trend that
will transform the IoT landscape into a
hyperconnected environment where the
restrictions related to latency and
computation capacity will be eliminated. It
is important for the incumbents to keep up
the pace of innovations to stay ahead of
the competition. Also, companies from
other industries will also cash-in the
opportunity at hand.
The recent years have witnessed a wave of
mergers and acquisitions in the space of
edge computing for IoT, with the increase
in M&A activity representing the industry’s
conundrum of cloud, edge, and hybrid
architectures, and the race to achieve
considerable market share.
10

9.
11

10.
MERGERS AND ACQUISITIONS IN
EDGE COMPUTING:
Companies across sectors are assessing the impact of edge computation and are
accelerating acquisition strategies in the domain to unlock new IoT business opportunities.
The increased momentum of the M&A activity is key evidence of how organizations are
focusing on edge strategy to reap major benefits as massive number of connected devices
proliferates. According to the M&A analysis, the transactions in the edge computing domain
can be outlined into five major categories as shown in Table 1.
Type of Deal Intent Description Example
Tuck-in
Acquisitions
Capability Addition Large company acquiring smaller
companies to acquire capabilities
like technology, patents, skills,
customers, etc., focusing on the
integration of gained capabilities
into the acquirer’s operating model.
Veea acquired
Virtuosys;
Microsoft acquired
Express Logic
Business Line
Expansion
Largely Complementary Buying company to get into a new
line of business and build a new
business model
Munich Re
acquired relayr
Vertical
Integration
Stack Expansion Acquiring a company which is a
supplier to the buyer or a
downstream service provider
within the value chain
Xilinx buying
Deephi
Consolidation Scaling up Acquiring a competitor to
increase market share and for
expanding existing services
Equinix buying
Metronode
Roll-ups Platform Strategy Private equity and venture capital
firms buying multiple companies
to create platforms
Zephyrtel buying
Vasona Networks
Table 1: M&A Framework for Edge Computing
TRENDS BETWEEN 2015 – 2019
Edge Computing: M&A Trend Analysis12

11.
Edge Computing: M&A Trend Analysis
Edge Computing: M&A Trend Analysis
YEAR WISE ANALYSIS
0
5
10
15
20
25
2015 2016 2017 2018 2019
Edge Computing: Yearly M&A Trend
GEOGRAPHY ANALYSIS
Figure 5 provides an overview of the
edge computing transactions
globally. The target companies
spanned geographies with
US-based target companies
attracting maximum acquirers to
make strategic advancements in
edge computing. The US registered
more than 70% of the transactions,
that will form a route for enabling the
edge computing use cases with
changing consumer and business
expectations. The high number of US
deals is proof of the technology
adoption in the US market before
any other region.
US dominates with a total of 44 deals
in the edge computing market
Other countries including
South Africa, England, Canada,
and Israel had one deal each.
European and Asian countries
are distant followers with
4 and 3 deals respectively.
Geographical Distribution of the Deals
Figure 5: M&A Across Geographies
Source: Netscribes' Secondary Research
Since 2015, M&A activity in the edge
computing domain has been
growing with the rise in IoT use cases
and the need to deploy computing
systems at the edge.
Figure 4 suggests that the
transaction count started increasing
in 2017 when the companies realized
the need to shift their cloud
capabilities to the edge. In 2018, the
maximum number of deals were
struck in the edge computing space,
a trend that can be seen as
strengthening in 2019.
Figure 4: Yearly Trend Analysis
Source: Netscribes' Secondary Research
30
NumberofDeals
Years
13

12.
2
2
3
3
3
4
4
4
5
7
9
13
Edge Computing: M&A Trend Analysis
ACQUIRER LANDSCAPE
The leading buyers in the edge computing
space include software providers, data
center services providers, and
semiconductor companies. A majority of
the buyers with an existing software
portfolio in communication and networking
technologies, enterprise applications,
analytics, and IoT platforms, are focused on
acquiring complementary capabilities. And
while most semiconductor companies are
focusing on developing a portfolio of
on-device intelligence technologies by
acquiring AI innovators, some are entering
a race for driving data center
interconnectivity.
Type of Buyers in the Edge Computing Market
TECHNOLOGY BREAKDOWN
Acquiring companies entered the edge
computing market for bringing data
centers closer to the users, as a part of their
overall edge computing strategy. A majority
of the data center providers started buying
colocation facilities within a region,
increasing their infrastructure presence as
a measure for handling different types of
workloads. While many other micro data
center and cabinet innovators continued to
grab attention with their modular designs,
data center interconnectivity technologies
continued to attract large sums in
investment. *Others include technology areas including operating system, RISC
IP, enterprise middleware, cloud native, microservices, sensor
modules, networking, connectivity, and blockchain
M&A Activity:
Technology Distribution
in the Edge
Computing Space
24%
17%
14%
12%
8%
7%
7%
5%
3% 3%
14

13.
Edge Computing: M&A Trend Analysis
AI and security companies are next on the list.
The trend is only expected to strengthen, with
the data center, AI, and security companies
combined accounting for half of all M&A
activity in the edge computing market.
Data center, AI, and security-focused M&A
activity is spread throughout the five-year
period, with the majority of them taking place
over 2018 and 2019. Over a 2-year period, the
deal count has been significant, and the
transactions have been done to acquire
different technology capabilities.
Network virtualization has emerged as a key
trend that is driving communication
technologies and IoT networks. Apart from
SD-WAN companies, other entities working
on virtualization technologies including cloud
native and microservices architectures are
also on the radar of buyers.
The year 2018 witnessed M&A activities
across technology domains such as AI, MEC,
analytics, data center, SD-WAN, embedded
technology, mesh IoT, security, blockchain,
edge modules, and IoT managed services for
edge computing applications.
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
TechnologyCoverageintheTrend
Years
2015 2016 2017 2018 2019
Breakdown of Technologies Over Years
1
1
1
2
2
2
1
3
1
2
1
3
5
1
5
2
2
1
5
2
1
2
1
1
1
1
2
5
1
1
15

14.
DATA CENTER
ACQUISITION TREND #1
2016 2017 2018
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Majority of the deals in the edge
computing market are related to data
centers with the aim of expanding
geographical presence and
developing micro data centers
Data Center Focused Acquisition Trend for Edge Computing
Source: Netscribes’ Secondary Research
Since data centers and edge computing must
be in synergy for ensuring better outcomes,
almost all the buyers in this category are
focusing on expanding their geographical data
center footprint while preparing for the age of
edge computing.
Going ahead, data centers will not be
represented by the size of facilities but their
proximity to the end user. Therefore, micro data
centers are rapidly gaining traction owing to
their modular size, cost-effective design, and
the ability to handle a variety of workloads
within an IoT network.
Compass Datacenters, Scalematrix, and
EdgeConnex are some major acquiring
companies that are focusing on micro data
centers. Compass Datacenters has acquired
two companies (EdgePoint System, BitBox) for
building a portfolio of data centers that can
support workloads from the core to the edge of
Edge Computing: M&A Trend Analysis16

15.
Data Center Interconnect
Technologies
Data center interconnect technologies
feature prominently among the high value
deals in the edge computing space. To cite
an instance, Mellanox, a provider of smart
network interface cards (NICs), switches,
and ethernet and InfiniBand interconnect
solutions for edge and hyperscale data
centers, has been acquired by Nvidia. The
acquisition will enable Nvidia to integrate
Mellanox's accelerated networking
technologies with Nvidia EGX, a computing
platform developed for AI at the edge.
Intel has acquired Barefoot Networks, a
provider of P-4 programmable Tofino
ethernet switches for interconnecting data
centers from various cloud service
providers. This acquisition enables Intel to
strengthen its cloud networking and
infrastructure portfolio with integration of
high-speed data center interconnects, P4
compilers, driver software, switch silicon
development, network telemetry, and
computational networking.
Data center interconnect technologies are
a vital tool for developing offloading
routines for certain processing procedures
that would otherwise run on switches and
adapters of the data centers. Also, these
approaches allow containerized
applications to run on the switch itself
without putting too much load. Both
Mellanox and Barefoot Networks promote
the offload models with flexible data
center switching and interconnect
technologies that are key to the dynamic
landscape of hyperscale cloud
architectures. Such acquisitions will
become more relevant in the telecom and
IoT market once the MEC architectures for
5G and edge computing come into play.
the network. EdgePoint System offers a fully
integrated edge data center solution per
customer requirements, while BitBox monitors
and maintains edge computing facilities for its
customers.
The acquisition of Colo Atl, a data center
provider in Atlanta may not be significant in
terms of pure-play data centers, but is a
landmark deal for communication service
providers looking to prepare for the future of
edge computing. With this acquisition,
American Tower has expanded in the data
center space with carrier-neutral, colocation
services for edge computing applications. Colo
Atl's portfolio will augment American Tower’s
wireless infrastructure to prepare for the future
of integration between data centers, telecom
towers, and antennas.
The number of such acquisitions is only likely to
grow, especially with the rise in the number of
startups developing micro data centers, with
self-contained, plug-and-play features that
can be leveraged for deployments at various
locations in an existing wireless network.
Edge Computing: M&A Trend Analysis17

16.
The M&A trend in the above sections indicate
the technologies, skills, product portfolio and
geographic footprint gained through the
deals. Another factor that is critical for filling a
technological gap in the acquirer’s portfolio is
the acquisition of patent portfolio of the
target companies. Patent acquisition leads to
evolution in business strategies and paves
the path for exploring new revenue
Note: Target companies acquired for data centers are considered beyond the ambit of this
analysis. Also, the patent portfolio analysis of Aruba Networks was out of the scope of this study.
opportunities. IP acquisition is valuable for
technology companies for innovating in the
edge computing space with a goal to develop
next generation solutions. Therefore, an
assessment of the patent capabilities
acquired in the M&A deals has been
conducted to understand the IP value
creation with the deals.
Edge Computing: M&A Trend Analysis
PATENT CAPABILITIES OF THE
TARGET COMPANIES
Patent analysis of the acquired companies was conducted to understand the IP secured
through the M&A transactions in the edge computing domain. The research activities
covered in the approach include:
• An assignee-based search to analyze the patent portfolio of the companies.
Inventor-based search strategies were not included in the scope of the study
• Patent categorization to understand the technology distribution of the patent portfolio
of the different companies
• Patent publications that have been re-assigned to the buyer have been considered
under the target company’s name for standardization.
• Only unique patent publications were considered from a family of patents
METHODOLOGY
30

17.
THE ACQUIRED TECHNOLOGY
LANDSCAPE
An analysis of patent portfolios of target companies in the edge computing domain provides
an insight into the various types of technologies that are gaining traction. The study highlights
that most of the acquired patent capabilities were in the field of microprocessors due to the
deal between -----------------------------------------------------------------------
-------------------------------------------. Similarly, wireless communication and mesh
networking space also indicates patent portfolios from individual target companies,
----------------------- respectively. Furthermore, AI and security related patent capabilities
are spread across multiple buyers for various focus areas.
Acquired
Technology
Landscape
43
26
19
16
14
13
11
8
7
6
6
5
5
5 2
Edge Computing: M&A Trend Analysis31

18.
PATENT COVERAGE OF ACQUIRED
TARGET COMPANIES
XXXX
XXXX
XXXX xxxx xxxx
xxxx xxxx
xxxxxxxx
xxxx xxxx xxxx
xxxxxxxx
xxxx
xxxx
Virtuosys
xxxx xxxx xxxx
xxxxxxxx
xxxx
57
30
23
14
8
5
5 2 2
2
3
4
13
4
23
2 2 2
1 1
1 1
The top 5 patent assignees including -----------------------------------------------------
---------- have maximum number (in double digits) of relevant patent publications in the edge
computing space. The patent focus areas of these acquired companies include ---------------
-------------------------------------------------.
Edge Computing: M&A Trend Analysis34

19.
Edge Computing: M&A Trend Analysis
TECHNOLOGY DISTRIBUTION OF
TOP FIVE ASSIGNEES
Patent Portfolio of
xxxx
Patent Portfolio of Beijing
xxxx
Patent Portfolio
of xxxx
Patent Portfolio
of xxxx
Patent Portfolio of
xxxx
Instruction Set Architecture
14 7
23
42
1 1 1
4
4
313
5
17
Processors
Computer Vision
Artificial Intelligence
Artificial intelligence
35

20.
MIPS Technologies has a patent portfolio
covering various solutions and architectures
for ensuring high-performance, low-power
consumption, and efficient operation of
electronic devices. ------------------------
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---------------------.
Instruction Set Architectures (ISA) for
hardware virtualization forms --------------
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-------------------------------------- are
based on the principles of virtualization and
SIMD. These architectures work in combination
with---------------------------------enha-
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----------, and interrupt vectors and
predictors for automated handling.
Deephi’s patent portfolio focuses on neural
networks, deep learning, and computer vision
techniques with an intent to address--------
-----------------------------------------
-----------------------------------------
-----------------------------------------
-----------------------------------------
-----------------------------------------
-----------------------------------------
------------------- for machine intelligence
applications. Another highlight from the
company’s patent filing coverage is the
Edge Computing: M&A Trend Analysis
Deephi’s patent portfolio focuses on neural
36

21.
exploration of ----------------------------
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monitoring methods of deep learning
processors.
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Edge Computing: M&A Trend Analysis
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PATENT COVERAGE OF OTHER ASSIGNEES
Description
Assignees Description of the Patent Portfolio
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Daho Networks’ patent portfolio focuses on network virtualization techniques related to
optical fiber signaling and routing. The patent publications disclose control systems for
externally managing software-defined network components and dynamically adjusting WAN
topologies of leased optical circuits. The solutions including out-of-band switching, logic
fiber wavelength division multiplexing and virtual channel controlling are deployed to ensure
reliability and scalability of the network.
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Edge Computing: M&A Trend Analysis
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Assignees Description of the Patent Portfolio
Edge Computing: M&A Trend Analysis
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24.
PATENT ANALYSIS:
CONCLUDING REMARKS
The overall patent analysis of the target
companies highlights that acquired IP
capabilities -------------------------------
------------------------------------------
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------------------------------------------
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--------. Global patent filings also provide the
acquirers an opportunity to explore new
geographies for business. ------------------
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--------.
Edge Computing: M&A Trend Analysis

25.
41Reinforcement Learning: Defining Next-Generation Artificial Intelligence Applications41

26.
Notable acquisitions related to data centers
have been financially on the higher side as
compared to the other deals. -------------
----------------------------------------
----------------------------------------
----------------------------------------
----------------------------------------
----------------------------------------
----------------------------------------
----------------------------------------
----------------------------------------
----------------------. The transaction is
expected to complete in the third quarter of
2019. Since xxxx has raised a total of USD 155
million, the valuation of the company is
expected to be on a higher side as well.
Moreover, both these deals are at a nascent
stage for the companies to appropriately
define ROI.
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------------------------------------.
The last five years have witnessed the increased
activity of innovations in the edge computing
space. Hundreds of startups have come into the
picture with billions of dollars being invested in
the new developments. Naturally, the
collaborations between the technology and
industry participants increase at every step of
innovation. Many are taking the inorganic route
to achieve the capabilities required for getting
ready for the age of edge computing. Some of
these companies already have a portfolio in
place and are augmenting it with
complementary capabilities. Other companies
with traditional solutions and services are
entering a new target market with the
acquisition of innovative entities in the domain.
TIME TO MARKET STRATEGIES
Edge computing is evolving in stages. While it is still time for real world implementation of an
autonomous on-chip or on-device computing solution, the transformation of edge data center
architectures is already happening at a considerable pace. Therefore, participants are --------
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will reap them early benefits.
ROI ON THE HIGH VALUE DEALS
Edge Computing: M&A Trend Analysis
INSIGHTS AND RECOMMENDATIONS
42

27.
GROWING INTEREST IN NEW
TECHNOLOGY AREAS
Accelerated growth has been observed in two technology areas that offer promising
perspectives for the age of the hyperconnected world.
-------------------------------------
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-----------------.
xxxx xxxx
SUPPORT FOR XXXXXXXXXXX
AND XXXXXXXXXXXXXXXXXXXX
Most of the M&A participants are exploring the
route of ---------------------------------
-----------------------------------------
-----------------------------------------
-----------------------------------------
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--------- to cover the complete spectrum of
IoT services and solutions. They are
leveraging new ---------------------------
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-----------------------------------------
-----------------------------------------
-----------------------------------------
-----------------------------------------
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------------ prominent futureproofing
strategies that is taking prominence for IoT
networking infrastructure.
Edge Computing: M&A Trend Analysis43

28.
OPPORTUNITIES IN EDGE COMPUTING
Integration of xxxx with the Edge
Computing Architecture
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xxxx Solutions not on the Radar of Acquiring Companies
xxxx
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xxxx
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Edge Computing: M&A Trend Analysis44

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Edge Computing: M&A Trend Analysis
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loads/2015/01/Understanding-5G-Perspectives-on-future-technological-advancements-in-mobile.pdf
3. https://software.intel.com/en-us/neural-compute-stick
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6. http://investor.equinix.com/static-files/21b9703b-c299-4e65-a49d-58a5c3673257
7. https://ieeexplore.ieee.org/document/8761664
8. https://ieeexplore.ieee.org/document/8436042
9. https://acadpubl.eu/jsi/2018-119-10/articles/10a/47.pdf
10. https://www.vmware.com/company/news/updates/vmware-announces-intent-to-acquire-uhana.html
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