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Edge Computing Market - Growth, Trends, COVID-19 Impact, and Forecasts (2022 - 2027)

Edge Computing Market - Growth, Trends, COVID-19 Impact, and Forecasts (2022 - 2027)

  • March 2022
  • 184 pages
  • ID: 6062848
  • Format: PDF
  • Mordor Intelligence LLP


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The global edge computing market was valued at USD 5242.90 million in 2021, and it is expected to reach a value of USD 43,459.40 million by 2027, registering a CAGR of 44.90% over the forecast period.

Key Highlights
Enterprises across industries are beginning to drive new levels of performance and productivity by deploying different technological innovations, like sensors and other data-producing and collecting devices, along with analysis tools. Traditionally, data management and analysis are performed in the cloud or data centers. However, the scenario seems to be changing with the increasing penetration of network-related technologies and initiatives, such as smart manufacturing and smart cities.
Although the adoption is presently not common, over the forecast period, some large enterprises, especially across industries, such as telecom and manufacturing, are expected to use edge computing, especially in relation to IoT.
As enterprises are embracing these new technologies, the need to analyze important data in near real-time became more critical to take full benefit of the adopted technologies. The need became vital across many industries, including manufacturing, healthcare, telecommunications, and finance. Moreover, the explosion of data (according to SharesPost, more than 150 zettabytes (150 trillion gigabytes) of data is estimated to be generated by 2025) has been pushing the need further and made factors, like network latency, very critical.
Furthermore, the development of processing-intensive applications involving artificial intelligence, IoT, and machine learning (ML), which work on larger data sets and perform massive algorithmic parallelism on models (to improve business operations), has promoted the demand for localized compute, data storage, and network resources. Therefore, along with IoT and IIoT, the adoption of AI and ML is also driving the growth of edge computing.
Distributing data across a large network containing numerous devices and data centers operating from enterprise locations can create problems with network visibility and control, with each device representing another potential endpoint, especially in the IoT network framework. Other devices that use edge have similar problems, and loopholes in edge security can provide hackers easy access to the core network.
The COVID-19 pandemic accelerated a global digital transformation that was already underway. The progress that might have taken more than five years has leaped forward significantly in a year.

Key Market Trends

Industrial Sector to Account For the Largest Market Share

One of the most prominent edge computing use cases is in the industrial manufacturing sector, where new technologies could potentially lead to massive productivity gains. Edge computing facilitates localized processing, which helps reduce latency issues and enables smart and intelligent manufacturing through predictive analytics. With the increase in IoT deployment, manufacturing companies have been rapidly adopting edge computing to enhance interoperability among IoT devices, reduce unforeseen downtime issues, and improve production efficiency.
Edge computing framework significantly reduces the complexity of interconnected systems, making it easier to collect and analyze data in real-time. It can also allow devices to gather critical information in remote sites where network connectivity is inconsistent or not cost-effective. Edge devices can be IoT-enabled machines, gateways, sensors, or single-board computers.
Data can be gathered and analyzed locally, with only critical information being transmitted back to the central network when connections are possible. The combination of edge computing and industrial IoT devices would make it easier to streamline industrial processes, optimize supply chains, and create the “smart” factory.
Edge computing forms the framework of the machine learning (ML) network that makes automatic manufacturing driven by robotics possible. According to IFR, the operational stock of industrial robots was around 3 million units in 2020. Considering an increase in the use of artificial intelligence, automation software will be providing a way for companies to produce more products without increasing production costs or wages.
Robots gathering and transmitting data through an edge network using IoT devices can identify irregularities and eliminate inefficiencies much more quickly than they could through the cloud-based architecture. The distributed nature of such a system also makes it much more robust, ensuring better levels of uptime productivity.
Industrial manufacturing is witnessing a revolution, owing to the potential of edge computing. Combined with a new generation of smart IoT edge devices, edge computing applications would completely transform manufacturing in the coming decades to drive better efficiency and productivity while also controlling costs. This is expected to impact the market’s growth positively over the forecast period.

North America Accounts For the Largest Market Share

The United States is expected to be the first market to adopt 5G widely, and the country has the highest ROI in the telecom industry. Due to regulatory concerns, the US government has delayed the auction of the 5G spectrum, due to which edge computing did not grow at the pace that was expected.
Enterprises across industries have expressed interest in edge computing, and the adoption has begun in the past few years. For instance, Dropbox, file storage, and sharing company have developed its edge network to deliver better connectivity and faster file access for its customers. The company shifted to edge computing to enhance its service capabilities to customers, especially outside of the United States. Post the transition to the edge; the company reported that some users had seen sync speeds by as much as 300%.
Autonomous cars are already in use across the United States. For instance, Google’s Waymo reached its 20-million-mile mark of fully autonomous driving on public roads by January 2020. Currently, most fully autonomous vehicles are in their testing phase.
In March 2022, Federal vehicle safety regulators cleared the way for the production and deployment of driverless vehicles that do not include manual controls such as steering wheels or pedals.
Canada is known to be an early adopter of new technologies. Most new technologies at present are data intensive. They create, process, and transfer large amounts of data, due to which the current infrastructure, consisting of data centers and the cloud, is inching toward its maximum capacity.
With the amount of new data generated and used at present, these infrastructures won’t support the needs of their customers. Of all the parameters involved, latency will be the most crucial factor for the business.
In June 2021, Bell Canada signed a contract with Amazon Web Services (AWS) to deploy cloud connectivity edge computing and storage solutions. It is Canada’s first operator to adopt multi-access edge computing (MEC) on 5G networks.

Competitive Landscape

The competitive rivalry in the Edge Computing Market among the existing players is high and increasing, considering the inflow of new entrants. Currently, the market is dominated by cloud-based IoT vendors, such as Dell, Microsoft, Amazon, Google, etc. Companies like GE, which have the expertise of delivering edge computing solutions across different industries, including aerospace or manufacturing, also have significant market positions. Acquisitions, partnerships with industry participants, and new product/service rollouts have been the key competitive strategies exhibited by the vendors in the market. Some of the recent developments in the market are:

March 2022 - FogHorn collaborated with IBM to provide a secured and open next-generation hybrid cloud platform with advanced, closed-loop system control capabilities and edge-powered artificial intelligence (AI). By bringing together edge and cloud capabilities, FogHorn and IBM plan to help customers rapidly process, deploy, analyze, store, and train critical data from the edge to the cloud and enhance their business processes.
February 2022 - Microsoft and AT&T collaborated for the development of AT&T Private 5G Edge. The companies aim to develop simple, smart, and flexible Private 5G Networks for schools, businesses, and organizations.

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