The reason for having edge computing in the first place is an inherent asymmetry. In the case of classic edge computing it is an asymmetry in the balance between nearness to sensors and computational power.
For example, the computer attached to a surveillance camera has a high quality connection to a sensor (in this case, a video camera), but a relatively small amount of computational power. On the other hand, the central server network to which that computer is connected has an enormous computational capacity, but a relatively poor connection to the sensor.
And so the two subsystems split up the work of surveillance: The local computer can do initial movement analysis and image compression — tasks that both require relatively little compute power. Then it hands that selected and compressed result to the central network, which has the resources to perform more sophisticated tasks such as comparing a suspicious face against a huge database.
But in the coming few years the inexorable march of Moore’s Law is about to enable a refinement of this paradigm. As people start to wear computational devices in the form of eyewear in their daily lives, different opportunities and constraints will soon arise.
This new paradigm won’t replace existing edge computing. Rather, a second edge will emerge, one which will complement and enhance the one that already exists.
More tomorrow.