The term 'Edge Computing' refers to computing that pushes intelligence, data processing, analytics, and communication capabilities down to where the data originates, that is, at network gateways or directly at endpoints. The aim is to reduce latency, ensure highly efficient networks and operations, as well as service delivery and an improved user experience. By extending computing closer to the data source, edge computing enables latency-sensitive computing, offers greater business agility through better control and faster insights, lowers operating expenses, and results in more efficient network bandwidth support. Key characteristics of edge computing include:
  • Computing power in the network or 'on-premises'
  • Proximity 
  • Real-time data processing 
  • Wide geo-distribution
There have been 3 major computing revolutions in industrial applications—mainframe, client server, and cloud computing. Taking up where these paradigms left off, edge computing is establishing itself as a foundational technology for industrial enterprises with its shorter latencies, robust security, responsive data collection, and lower costs. It is extremely relevant in the current hyper-connected industrial environment, as its solution-agnostic nature enables its use across a range of applications, including autonomous assets, remote asset monitoring, data extraction from stranded assets, autonomous robotics, autonomous vehicles, smart factories, oilfield operations management, machine monitoring and smart campuses.

The multi-access edge computing (MEC) market is still at nascent stage, with telecom operators and cloud providers conducting trials and, in certain cases, agreements to launch commercial offerings. The recent launch of 5G technology with much lower latency and higher capacity, coupled with MEC, brings computing power closer to customers, driving new applications and experiences. Operators are now deploying smaller data centers in the network edge, closer to customers, optimizing applications performance. However, telecom operators cannot implement and manage MEC alone. They must establish partnerships and an application ecosystem to seize this growth opportunity. Thus, operators are partnering with cloud providers such as Amazon Web Services (AWS), Microsoft Azure, Google Cloud, and IBM Cloud to improve the performance of existing mission-critical applications, and enable new applications over wireless networks.

This market influences growth opportunities in a variety of areas, for both consumer and enterprise use cases, where the low-latency requirements for connectivity are essential for applications and user experience. For consumers, there are innovative applications such as 5G gaming and augmented reality (AR), virtual reality (VR), and ultra-high-definition (UDH) streaming. For enterprises, telecom operators are deploying private wireless networks to enable Manufacturing 4.0, automated mining, precision agriculture, Industrial Internet of Things (IIoT), and other compelling use cases. Frost & Sullivan anticipates that approximately 90% of industrial enterprises will utilize edge computing by 2022, and a majority of the data will be processed in the edge even before 5G coverage reaches higher levels and use cases mature. The geographic coverage of this Frost & Sullivan MEC study is global, and the study period is from 2019 to 2024.