Edge computing continues to receive a lot of discussion. With companies in every sector recognizing the limitations of supporting the connectivity needs of smartphones, tablets, laptops, smart homes, factories, and people, many have begun using technologies via distributed IT infrastructure to move storage and computing closer to users and devices. What hasn’t been done is to identify edge ecosystem and infrastructure needs.

This is the first in a four-part series of posts identifying the main archetypes for edge applications and the technology required to support them. Vertiv edge experts, in conjunction with an independent third-party research firm, identified 24 use cases considered to have the greatest impact on businesses and end users, based on projected growth, criticality and financial influence. The full report is available here.

The experts analyzed these use cases for common characteristics such as bandwidth, latency, availability, and security. From that analysis, four edge archetypes were defined, the first being Data Intensive.

The Data Intensive Archetype encompasses use cases where the amount of data is so large that layers of storage and computing are required between the endpoint and the cloud to reduce bandwidth costs or latency.

Examples include smart cities, smart factories, smart homes/buildings, high-definition content distribution, high-performance computing, restricted connectivity, virtual reality, and oil and gas digitization. The most widely used example is high-definition content delivery, where major content providers actively partner with colocation providers to expand delivery networks to bring data-intensive streaming video closer to users to reduce costs and latency.

Another prime example of the Data Intensive Archetype is the use of IoT networks to create smart homes, buildings, factories, and cities. Despite IoT still being in its early stages, organizations are already struggling to manage the volume of data being generated.

In this case, the challenge is the opposite of the one presented by high-definition content delivery. Rather than moving data closer to users, these applications must manage the huge amounts of data generated by devices and systems at the source. This will require the evolution of an edge-to-core network model.

IoT and the Industrial Internet of Things (IIoT) represent a mesh of sensors that generate huge volumes of data each hour. This data supports a “sense-infer-react” loop that enables visibility into and control of everything from home appliances to industrial equipment. Only a subset of this data is transmitted to a local, regional or cloud data center for further processing, which means massive amounts of compute will be required at the extremity of the edge to enable devices and systems to make decisions and act on the data provided by sensors.

The bottom line for those working with the Data Intensive Archetype is that all of these use cases have a need to move large volumes of data to users where it can be consumed, or from devices and systems where it is generated to a central repository. This will require an expansion in the number of urban and local hubs available to support regional cloud or enterprise data centers.

Next archetype: Human-Latency Sensitive