Edge computing essential to supporting 5G use cases
For business and consumers, new use cases and applications dependent on low-latency network connectivity are driving computing power to the edge of the network. For AT&T, edge computing is a key part of supporting new technologies, including the IoT, software-defined networking, blockchain, artificial intelligence and 5G.
AT&T Vice President of Intelligent Edge said the aforementioned technologies are all “essential to the future of the customer experience and back-end business operations–require massive amounts of near real-time computation. Edge-to-edge intelligence is poised to help make this computation possible, and make seamless user experiences a reality.”
Goodell likened the move of compute to the network edge as making “it feel like every device is a supercomputer. Digital processes become lightning fast. Critical data is processed [at] the edge of the network, right on the device. Secondary systems and less urgent data are sent to the cloud and processed there. With SDN, organizations have more flexibility to define rules on where and how data is processed to optimize application performance and user experience.”
The idea of combining edge services with cloud-based services reflects the mix and importance of data being produced by IP-connected IoT devices. Consider an automated mining operation–connected equipment stream huge volumes of operational data and telemetry. Some of that data, an alarm warning of an impending equipment failure, needs to be processed near-instantaneously at the edge in order to quickly initiate a fix to the alarm. Conversely, other data from the machines that doesn’t impact immediate operations, can be kicked back to a cloud service for analysis and storage. For the mine operator, this mix maximizes operational efficiency while cutting down on data transport costs.
The integration of edge and cloud decision making is encompassed by the term fog computing, which speaks to the architecture that enables interoperable edge and cloud devices and services.
At the Fog World Congress event in November, 2017, Alicia Abella, AT&T VP of Advanced Technology Realization, noted the key role of edge computing in support of AR/VR-type applications, autonomous driving and smart city projects.
“In order to achieve some of the latency requirements of these services, you’re going to need to be closer to the edge,” she said. “Especially when looking at say the autonomous vehicle where you have mission critical safety requirements. When we think about the edge, we’re looking at being able to serve these low latency requirements for the application.”
She listed a number of benefits to operators that can be derived from edge computing:
- A reduction of backhaul traffic;
- Cost reduction by decomposing and disaggregating access function;
- Optimization of central office infrastructure;
- Improve network reliability by distributing content between the edge and centralized data centers;
- And deliver innovative services not possible without edge computing.
“We are busy thinking about and putting together what that edge compute architecture would look like,” Abella said. “It’s being driven by the need for low latency.” In terms of where, physically, edge compute power is located “depends on the use case. We have to be flexible when defining this edge compute architecture. There’s a lot of variables and a lot of constraints. We’re actually looking at optimization methods.”
