Edge Computing Market

[129 Pages Report] MarketsandMarkets forecasts the global edge computing market to grow from USD 1.17 Billion in 2016 to 6.72 Billion by 2022. The global managed services market will grow at a Compound Annual Growth Rate (CAGR) of 35.4% during the forecast period. The forecast period has been considered from 2017 to 2022, while 2016 is considered as the base year for estimating the market size.

Objectives of the Study:

The main objective of this report is to define, describe, and forecast the edge computing market on the basis of segments which include component, application, organization size, vertical, and region. The report provides detailed information regarding the major factors influencing the growth of the market (drivers, restraints, opportunities, and industry-specific challenges). The report forecasts the market size with respect to 5 main regions, namely, North America, Europe, Asia Pacific (APAC), the Middle East and Africa (MEA), and Latin America. The report profiles key players and comprehensively analyzes their core competencies. This report also tracks and analyzes competitive developments such as mergers and acquisitions, new product developments, and Research and Development (R&D) activities in the market.

The research methodology used to estimate and forecast the edge computing market begins with the collection and analysis of data on key vendor product offerings and business strategies from secondary sources, such as IT service providers, technology providers, press releases, investor presentations of companies, white papers, technology journals, certified publications, and articles from recognized authors, directories, and databases. The vendor offerings have also been taken into consideration to determine the market segmentation. The bottom-up procedure was employed to arrive at the total market size of the market from the revenue of the key market hardware, platform, solution, and service providers. After arriving at the overall market size, the total edge computing market was split into several segments and subsegments, which were then verified through primary research by conducting extensive interviews with key people, such as Chief Executive Officers (CEOs), Vice Presidents (VPs), directors, and executives.

To know about the assumptions considered for the study, download the pdf brochure

Industry Ecosystem

The edge computing market ecosystem comprises hardware and software vendors such as Nokia Networks (Finland), Huawei (China), Juniper Networks (US), Dell (US), Cisco Systems (US), HPE (US), SixSq Sàrl (Switzerland), FogHorn Systems (US), Vasona Networks (US), MachineShop Inc. (US), Saguna Networks (Israel), Vapor IO (US), Xiotech (US), Mirror Image (US), Aricent (US), and ADLINK Technology (US).

Key Target Audience

• Edge computing solution and service providers
• System integrators
• Application developers
• Hardware vendors
• Consulting firms
• Research organizations
• Resellers and distributors

Scope of the Edge Computing Market Report

The research report categorizes the edge computing market to forecast the revenues and analyze the trends in each of the following sub-markets:

Edge Computing Market by Component

• Hardware
• Platform
• Solutions
• Services
  • Consulting Services
  • System Integration and Testing
  • Technical Support

Edge Computing Market by Application

• Smart Cities
• Location Services
• Analytics
• Environmental Monitoring
• Optimized Local Content
• Data Caching
• Augmented Reality
• Others (Asset Tracking and Video Surveillance)

Edge Computing Market by Organization Size

• SMEs
• Large Enterprises

Edge Computing Market by Vertical

• Manufacturing
• Healthcare
• Transportation
• Government and Public
• Media and Entertainment
• Energy and Utilities
• Telecom and IT
• Retail
• Others (Hospitality, BFSI, and Education)

Edge Computing Market by Region

• North America
• Europe
• Middle East and Africa (MEA)
• Asia Pacific (APAC)
• Latin America

Available Customizations

With the given market data, MarketsandMarkets offers customizations as per the company’s specific needs. The following customization options are available for the report:

Product Analysis

• Product matrix which gives a detailed comparison of the product portfolio of each company

Geographic Analysis

• Further breakdown of the North American edge computing market into countries
• Further breakdown of the European market into countries
• Further breakdown of the APAC market into countries
• Further breakdown of the MEA market into countries
• Further breakdown of the Latin American edge computing market into countries

Company Information

• Detailed analysis and profiling of additional edge computing market players

Growing load on cloud infrastructure and significant increase in number of intelligent application to drive global edge computing market to USD 6.72 billion by 2022

Edge computing assists real-time applications in processing and analysing data collected from various sensors and connected devices, at the edge of the network. It helps in reducing latency and thereby, provides a faster response to the critical applications. The data transmitted from the sensors and devices is stored and processed on the edge of the network, close to the devices, instead of transferring it to the cloud or data centres located miles away from the connected devices. Furthermore, edge computing reduces the bandwidth concerns experienced on the cloud.

Wide range of applications in different industries, advent of IoT and 5G network, increase in number of intelligent applications and growing load on cloud infrastructure are likely to fuel the growth of edge computing market.

The retail segment is likely to be the fastest growing vertical in terms of adoption of edge computing during the forecast period. The retail vertical is undergoing a significant transformation owing to the technological advancements in place. The emergence of IoT is further contributing to the digital transformation in the vertical and changing the traditional retail practices. The introduction of electronic Point-of-Sale (PoS) system in the retail vertical marks the beginning of an evolution in the vertical. The vertical is now focusing on providing tailored offerings to customers to enhance their experience and increase the value. For instance, Bluetooth beacons track the customers near the store to communicate and notify them about the tailored offerings to enhance the customer experience and target the potential customers. Furthermore, digital shopping carts, social shopping tools, in-store videos, and digital signage are becoming common in the stores. Augmented reality and virtual reality technologies are said to be further transforming the retail vertical with Oculus goggles, smart mirrors, and smart shelves applications that target the potential customers and enhance the experience and value to have a competitive advantage in the market. This transformation is achieved with a combination of the internet, IoT transmitters, sensors, cameras, and beacons. High volumes of data would be generated from these smart applications. Storing and computing this data in the cloud increases the latency and the operational costs associated with the cloud. The edge computing solution empowers the retailers by collecting, storing, and computing this data at the edge of the network rather than in the cloud or data centre. With the edge computing solution, retailers have gained a high scalability and network flexibility, required to grow at the rate the vertical requires.

Advent of the 5G network across major economies is major opportunity for the global edge computing market

In The advent of the 5G network is expected to introduce new possibilities for high-end applications to further reduce the network latency. The evolution of the 5G network will encourage edge computing initiatives that will support advanced applications. For instance, applications, such as AR/VR, will benefit from advancements in the network technology, as the evolution of the 5G network will facilitate such applications with faster computing power. The emergence of 5G networks across different applications is expected to significantly increase the data transferred to the data centres, thereby augmenting the need for intermediary servers or edge networks.

Edge Computing Market Dynamics

The edge computing market is expected to grow from USD 1.47 Billion in 2017 to USD 6.72 Billion by 2022, at a CAGR of 35.4%, considering the tremendous growth in data generated from multiple sources across different applications. Furthermore, the rise in real-time applications has contributed to the growth of edge computing market. Moreover, increasing load on cloud infrastructure has encouraged enterprises to adopt and implement edge computing solutions.

The small and medium enterprises (SMEs) segment is expected to grow at a higher CAGR during the forecast period. SMEs have been majorly dependent on data centers to process and analyze their data. However, budget constraints have been a major obstacle for SMEs to adopt data center services. Transferring and processing the data over the cloud increases the operational cost. Edge computing facilitates SMEs to collect, process, and store data at the edge of the network closer to the source. This further reduces the operational costs of managing and storing data for SMEs, thus encouraging SMEs to adopt edge computing solutions and services.

The augmented reality application is likely to gain traction in the edge computing application segment. Augmented reality is one of the trending application that is expected to gain demand in the coming years across different industries such as retail, manufacturing, media and entertainment, and healthcare and life sciences. Augmented reality applications require high computing power in order to avoid delays. Edge computing plays a vital role in providing high computing power to augmented reality applications.

The edge computing solutions and services are being increasingly adopted across various industry verticals, which have led to the growth of the edge computing market globally. The consumer goods and retail sector is expected to grow at the highest rate from 2017 to 2022.

North America is expected to hold the largest market share and dominate the edge computing market from 2017 to 2022. The region also has a high concentration of telecom and IT and manufacturing industries that largely contribute to the adoption of edge computing solutions and services. However, the APAC region is considered to provide high growth opportunities for edge computing vendors. This can be majorly attributed to the rapid technological development and government initiatives to promote digitization across industries with an objective to optimize resources and increase profitability in the developing countries.

The major solution and service providers in the edge computing market include Nokia Networks (Finland), Huawei (China), Juniper Networks (US), Dell (US), Cisco Systems (US), HPE (US), SixSq Sàrl (Switzerland), FogHorn Systems (US), Vasona Networks (US), MachineShop Inc. (US), Saguna Networks (Israel), Vapor IO (US), Xiotech (US), Mirror Image (US), Aricent (US), and ADLINK Technology (US). These players have adopted various strategies, such as new product launches, product upgradations, and partnerships with technology companies to cater to the needs of the edge computing users.

The global edge computing market is expected to witness healthy growth considering the tremendous growth in data generated at multiple sources across different applications. Furthermore, the rise in real-time applications has contributed to the growth of market. Moreover, increasing load on cloud infrastructure has encouraged enterprises to adopt and implement edge computing solutions.

The edge computing market report categorizes the edge computing applications into 8 categories, namely, smart cities, location services, analytics, environmental monitoring, optimized local content, data caching, augmented reality, and others, which include asset tracking and video surveillance. All these applications have their own significance. Furthermore, the presence of edge computing at the edge of operators' networks enables a large number of new features to be developed in the industry, which helps them monetize the services.

Edge computing applications improve the response time, operational efficiency, and network utilization while enhancing the user experience and reducing overall network cost.

Smart Cities

The evolution of 5G and IoT is expected to increase the number of connected devices drastically. With this technological advancement in place, smart applications are developed to rely on man-to-machine and machine-to-machine communication. The smart cities application is expected to be gaining momentum with the focus on making the urban areas citizen-friendly and connected technologically. Smart cities comprise a multitude of applications, such as smart transportation, smart lighting, smart utilities, and smart citizen services. The real-time applications take place through the man-to-machine and machine-to-machine communication. These applications require a very low latency and high bandwidth due to the enormous data generated from sensors, devices, and IoT components. The processing and monitoring of such large amounts of data in the cloud make it difficult to cope with the low latency challenge. The edge computing solution brings the computing capabilities at the edge of the network, thereby increasing the efficiency and compatibility. The high volumes of data generated by sensors, devices, and IoT components are collected, stored, and computed at the extreme point of the network, which handles the high bandwidth requirements with low latency, to improve the efficiency and productivity.

Location Services

Location-based services make use of real-time geographical data from devices to provide information, entertainment, and security. In other words, location-based services recommend a variety of services linked to a particular place. Furthermore, to improve the Quality of Experience (QoE) for the usefulness of the recommended service, the user’s behavior log and preference can be collected in the user’s mobile terminal, and then be delivered to the location-based service application. The edge computing solution makes it feasible to collect, store, and compute the data generated from the devices at the edge to reduce the response time and avoid unnecessary traffic to the cloud. For instance, if a user is nearby a mall, then discount coupons can be recommended to him/her for shopping. Henceforth, it would provide an opportunity to deliver higher value to consumers as well as the vendors.

Similarly, if some content needs to be blocked at certain geographies owing to the compliance, regulations, and licensing restrictions, it can be prevented by accessing it from that location. For example, the library of content for on-demand services by Netflix may vary depending on the region or a service may not be available in a particular region or country.

Analytics

Analytics is used across enterprises to improve the customer experience and efficiency. With edge computing, data analytics happens at the edge of the network, enabling decision makers to act on the insights at a faster pace. Edge computing offers benefit to enterprises, as the amount of data sent to the cloud decreases significantly and reduces the cloud computing costs, further. Moreover, in the manufacturing or power production industry, the data analytics at the edge helps make quick and efficient decisions that can be used to prevent failure, prevent product defects, and optimize the productivity.

Environmental Monitoring

Edge computing plays a crucial role in monitoring the places that are out of human reach or difficult to reach. Furthermore, it facilitates the continuous monitoring of remote locations to understand the unusual patterns. For example, sensor network and Closed-Circuit Television (CCTV) help in monitoring remote locations, and in case of intrusion, they communicate the observations to a base station, which resides at the edge of the sensor network and acts as a gateway to analyze the data. Upon computing the response, the network sends alert signals to the control station to notify the intrusion. Some of the instances include CCTV surveillance and environmental monitoring to detect wildfires, tsunamis, earthquakes, and other natural disasters. In the traditional system, the raw observation data is transmitted to a centralized data center for processing, which would increase the response time. On the other hand, with the deployment of the edge computing technology, the edge nodes can easily process the raw observation and provide useful analysis, thereby reducing the overall response time and bandwidth usage.

Optimized Local Content

The proliferation of smartphones and the global web-based services have resulted in a significant increase in the use of mobile broadband services. The display and graphic processing technologies are evolving rapidly, and high-resolution videos can be played on-the-go on the handheld devices. Furthermore, with the presence of social media, the content is accessed several times from the same region, at about the same time. The edge computing solution stores locally, the most popular content consumed in the geographical area, and once requested, it can provide the content from the local cache. In this scenario, there is no need to transfer the content over the core network, thereby leading to significant savings in the backhaul capacity. Thus, with the help of edge computing, the content can be distributed optimally among users at high speed and quality, which may enable everyone to access it.

Data Caching

Data caching is one of the applications that store the frequently accessed data, so that it can be retrieved back from memory rather than generating the data again. Storing this data at the edge of the network reduces the latency and increases the efficiency, as the data is stored and processed near the source. Edge computing facilitates storage and computing of large volumes of data, so that it can be accessed by the users as per their needs. For instance, Orbitz, one of the leading global online travel services, uses data caching to store frequently accessed data, which improved the company’s productivity and reduced the licensing, maintenance, and operations costs.

Augmented Reality

Edge computing offers broad opportunities in augmented reality to empower enterprises across different verticals. Augmented reality requires a very low latency for its successful implementation to accomplish the desired tasks. Edge computing provides ultra-low latency and reduces the traffic on the cloud to ensure increased efficiency and productivity. For instance, implementation of augmented reality in gaming requires very less response time to enhance the user gaming experience.

Others

Others include asset tracking and video surveillance applications. In the recent years, video surveillance is being extended from the operations room to mobile devices, enabling the security personnel to access any feed, at any time and location. The edge computing solution is used for analyzing raw video streams from surveillance cameras connected to the network, and for forwarding the relevant incidents to the city command center. Edge computing is expected to provide exceptional performance and quality, while at the same time, provide savings in the backhaul capacity by being able to provide content as close to the edge as possible. The biggest gains can likely be achieved in a scenario with a dense population of consumers in a small geographical area.

Asset tracking systems generate large amounts of data across different verticals, such as manufacturing, retail, and transportation and logistics. It becomes difficult for business systems to manage and compute this bundled data, which eventually leads to increased latency and efficiency. Edge computing is likely to play a vital role in this application by processing and computing the data at the edge, instead of sending it to the data centers that are located far away from the data source.

Key questions

• Which are the substitute solutions and how big is the threat from them?
• Which are the top use cases where edge computing can be implemented for revenue generation while leveraging new technologies like artificial intelligence and analytics?
• What are the potential opportunities in the adjacent markets, such edge analytics and mobile edge computing?
• What should be your go-to-market strategy to expand the reach into developing countries across APAC, MEA, and Latin America?

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