What is multi-access edge computing?

What is multi-access edge computing?

Multi-Access Edge Computing (MEC) moves the computing of traffic and services from a centralized cloud to the edge of the network and closer to the customer. Instead of sending all data to a cloud for processing, the network edge analyzes, processes, and stores the data. Collecting and processing data closer to the customer reduces latency and brings real-time performance to high-bandwidth applications.

 

 

MEC Characteristics

  • Proximity
  • Ultra-low latency
  • High bandwidth
  • Virtualization

MEC also offers cloud-computing capabilities and an IT service environment at the edge of the network. You typically implement MEC with data centers that are distributed at the edge. Applications at the edge require a high bandwidth and low latency environment. To achieve that service providers create distributed data centers, or distributed clouds. The resources that make up a cloud can reside anywhere—from a centralized datacenter to a cell site, a central office, an aggregation site, a metro data center, or on the customer premises. The MEC platform enables distributed edge computing by processing content at the edge using either a server or a CPE.

A software-defined access layer could also be used as an extension of a distributed cloud. Most edge computing initiatives are being developed using open source hardware and software that leverage cloud and virtualization paradigms, including SDN and NFV.

A software-defined access layer could also be used as an extension of a distributed cloud. Most edge computing initiatives are being developed using open source hardware and software that leverage cloud and virtualization paradigms, including SDN and NFV.

Key Drivers for MEC

Key drivers for edge computing include the Internet of things (IoT), today’s 4G networks, and next-generation 5G networks. Exponential growth in traffic, especially video, and the explosion of connected devices mean that network infrastructures will need to scale effectively to deliver higher volumes of data. MEC brings the flexibility and agility of the cloud closer to the customer to meet these demands.

Edge access networks are also evolving to include converged residential, business, and mobile networks and virtualization.

BI Intelligence expects more than 5.6 billion enterprise and government IoT devices worldwide will utilize edge computing solutions in 2020, up from less than 1 billion in 2016.
Edge Computing in the IoT, BI Intelligence October 2016
IDC predicted that 43% of the data created by IoT devices worldwide will be stored, processed, analyzed, and acted on at the edge (instead of in the cloud or a remote data center) by 2019.
Cloud 2.0: New Services, Challenges, and Opportunities, IDC February 2017

How is MEC Used?

Some common MEC use cases are:

  • Data and video analytics
  • Location tracking services
  • Internet-of-Things (IoT)
  • Augmented reality
  • Local hosting of content, such as videos

An IoT example is a connected car constantly sensing driving patterns, road conditions and other vehicle movements to provide safety guidance to the driver. Most of the predictive and prescriptive insights need to be provided on time. That means, sensor data needs to be collected, processed and analyzed at the edge to provide low latency insights to the driver.