It is hard right now to know whether internet of things apps and services, enabled largely--but not exclusively--by 5G, are going to be as important as expected. But it is reasonable to argue that artificially-intelligent systems of all sorts will have a computing support requirement that would be difficult to handle on a traditional cloud compute platform.
A single autonomous vehicle, for example, could have hundreds of central processing units. Beyond that, the sheer amount of unstructured data being produced is growing exponentially. In fact, some believe artificial intelligence represents the next wave of growth for cloud computing overall.
In addition, 5G is a platform that could enable mobile service providers “moving up the stack” in enterprise and some consumer services.
Edge computing, in other words, required by many proposed new apps, the most-frequently-mentioned being autonomous vehicles, which will require such low latency that cloud computing has to be done at the edge of the network. The issue, perhaps, is how many other new apps then could benefit from an edge computing network.
"Software gives us this capability to actually play in a different space than the connectivity
space for the consumer and the enterprise," said Ed Chan, Verizon SVP.
The assumption is that many new apps will require those interactions to be nearly real-time, requiring mobile edge computing. MEC is about packing the edge with computing power, like "making the cloud as if it's in your back pocket," Chan said.
Many of the apps benefitting from edge computing might be a bit prosaic. Real-time video at stadiums might provide one example. Even high-end metropolitan-area networks often have capacity to support about 100 Gbps, supporting uploads of 1080p streams from only 12,000 users at YouTube’s recommended upload rate of 8.5 Mbps. A million concurrent uploads would require 8.5 terabytes per second.
Some have predicted that, by 2018, some 40 percent of IoT-created data will be stored, processed, analyzed, and acted upon close to, or at the edge, of a network, according to IDC.
Some even argue that analyzing data from offshore oil rigs, or managing automated parking systems or smart lighting, could require edge computing.
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