Edge-computing will go hand-in-hand with the rollout of 5G, while the architecture needed for the efficient delivery of 5G services will also rely on a cloudlet-based approach.
The past decade has seen massive growth in centralized computing, with data processing flowing to the cloud to take advantage of low-cost dedicated data centres. However, the volume of data that will be needed to drive the next wave of applications is beginning to force a change in direction.
Currently, just 10% of enterprise-generated data is created and processed outside centralized data centres this figure is predicted to reach 50% by 2022 (Gartner). This necessary reversal is driven by the shift towards hyper-connected cyber-physical systems, enabled by the arrival of technologies such as 5G wireless communications and a new wave of application-focused computing hardware.
The automotive industry provides a microcosm of the coming sectoral change. Car manufacturers have realized that maintaining data in centralized servers will reach a limit. Today, the intelligence in automated driver assistance systems (ADAS) is largely self-contained, with scenes captured by the built-in cameras and radar systems processed purely within the vehicle. Only a tiny proportion of this data is relayed to the carmaker’s servers where it may be used to update databases to help with predictive maintenance and collect statistics on the performance of the ADAS software.
Every mile an ADAS-equipped car travels generates gigabytes of data, but bandwidth and processing limitations hinder usage. This information is processed once and then discarded, being too dense to send to centralized cloud servers. Systems much closer to the vehicle could make use of high-speed, cost-effective wireless networks, to capture the data and use it to make informed decisions.
In a simple case, transmissions from passing vehicles could use V2X to relay data to roadside beacons about road surface conditions. These beacons themselves may be isolated with only a low-speed connection to the cloud. Rather than discard much of the data before delivery and processing in the cloud, the beacons could use their own local compute capability to learn about road conditions and send that information to vehicles passing in the other direction.
Other sectors that are likely to need edge computing are battery powered robots, autonomous factory machines, land surveyor drones and Augmented Reality/Virtual Reality systems.