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Edge computing archetypes – and their needs

In its new report, Defining Four Edge Archetypes and their Technology Requirements, Vertiv, formerly Emerson Network Power, identifies four edge computing archetypes. They are:

Data Intensive – where volume, cost or bandwidth issues make the transfer of data over the network directly to the cloud or from the cloud to point-of-use impractical. Examples include smart cities, smart factories, smart homes/buildings, high-performance computing, virtual reality and high-definition content distribution where content providers such as Amazon and Netflix actively partner with colocation providers to expand delivery networks to bring data-intensive streaming video closer to users to reduce costs and latency.

Human-Latency Sensitive – where services are optimised for human consumption and speed is a priority, with any delay in data delivery negatively impacting the user experience and potentially reducing a retailer’s sales and profitability. Examples include smart retail, augmented reality, website optimisation and natural language processing.

Machine-to-Machine Latency Sensitive – in which speed is, once again, the defining characteristic but, because machines are able to process data much faster than humans, the consequences for slow delivery are higher than in the HumanLatency Archetype. For example, delays in commodities and stock trading, where prices fluctuate in fractions of a second, could turn gains into losses. Other examples include the smart grid, smart security, real-time analytics, low-latency content distribution and defence force simulation.

Life Critical – where speed and reliability are vital for human health and safety. Examples include smart transportation, digital health, connected/autonomous cars, autonomous robots and drones.

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