April 15, 2019
Definitions matter in telecom. With the name change from Mobile Edge Computing to Multi-Access Edge Computing, and now perhaps just Edge Computing, with some use cases that do not seem to involve the wide area network or even the access network at all, does anyone really know what MEC is and does it matter?
At its most basic level, mobile edge computing or multi-access edge computing or just edge computing distributes cloud services compute and storage resources throughout the network to reduce delays and latency, distributes services to support new use cases and revenue opportunities and decreases service deployment costs. MEC does this by merging IT, content, connectivity and location to place compute, storage, orchestration and application resources closer to the users.
The problem comes when you look at where the placement happens and for what applications. Is it a function such as autonomous driving or gaming and virtual reality? Do you architect MEC services on the basis of latency bands? Or on the basis of location such as cell site, pre-aggregation, aggregation, regional and central data centers? The upshot is that MEC means many things to different people, companies and organizations.
The clarity challenge
One of the considerable challenges with understanding edge computing is agreeing to a common definition with your suppliers and partners. Nearly every MEC solution definition starts with "And here is what we mean by the edge." Here is a sample of edge compute definitions by different organizations.
Edge Definition (Source: websites or white papers)
Multi-access edge computing offers application developers and content providers cloud-computing capabilities and an IT service environment at the edge of the network. This environment is characterized by ultra-low latency and high bandwidth as well as real-time access to radio network information that can be leveraged by applications.
References the ETSI WP defining MEC.
Edge computing is the practice of processing data near the edge of your network, where the data is being generated, instead of in a centralized data-processing center.
Wikipedia defines edge computing as "pushing the frontier of computing applications, data and services away from centralized nodes to the logical extremes of a network. It enables analytics and data gathering to occur at the source of the data."
The most mature view of edge computing is that it is offering application developers and service providers cloud computing capabilities, as well as an IT service environment at the edge of a network.
We think that you put the compute closer to the eyeballs and devices, and you start to use more specialized (vs. generic) hardware to drive down cost while increasing performance.
By circumventing the need to access the cloud to make decisions, edge computing provides real-time local data analysis to devices, which can include everything from remote mining equipment and autonomous vehicles to digital billboards, wearable health appliances and more.
MEC processes data close to where it is generated and consumed. This enables the network to deliver the ultra-low latency required by business-critical applications and to support interactive user experiences in busy venues. By processing data locally, MEC applications can also significantly reduce data transfer costs.
Edge compute is about providing execution resources with the adequate connectivity at close proximity to the data sources. From a cost perspective centralization is preferred for computing. But from a technical perspective distribution is normally an advantage. The edge is the sweet spot where the two perspectives meet, which means the location of the edge depends on the use case. Even within a single use case, there might be multiple locations for the edge.
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