At a recent conference, several leading Tier 1 operators shared compelling business cases demonstrating how edge-generated data can deliver significant benefits to customers. These benefits include improved productivity, quality, safety and real-time decision-making. The scenarios they presented illustrate what lies ahead as we move closer to an era where connected equipment, quality control systems and real-time decision support become commonplace.
One scenario involves the use of tablet computers on the sidelines in sports. Coaches now use video replays to make critical adjustments that perfect their game and help them compete to win. Today’s networks transmit data back to a central point, which then pushes the videos to the coaches’ tablets. However, multiple coaches moving between weaker and stronger signals and streaming replays can experience slow video loads, turning a productivity tool into a potential hindrance.
Network performance problems are certainly not unique to sports. In many industries, the demands of processing growing data streams — often in locations far from centralized data centers — are straining existing networks to their limits. CSPs (Communications Service Providers) that are adopting a cloud-native network architecture and offering compute power closer to where data is generated are positioning themselves to deliver a competitive advantage to their customers. These capabilities support real-time decision-making and provide greater agility as businesses optimize their performance with edge -generated data.
Increased automation, increased value
In another example, manufacturers often rely on recorded visual inspections to maintain production, quality control and workplace safety. In these environments, cameras generate hundreds of simultaneous video feeds while sensors facilitate machine-to-machine connectivity, resulting in significant data generated at the edge — and a significant opportunity to deliver increased value through automation.
Enhanced quality control
One food factory they discussed requires precise product quantity deliveries, no more and no less. Today, this precision necessitates significant staffing to inspect production processes and perform quality control. Processing data more quickly at the edge will allow the factory to detect anomalies and stop the production line, reducing potential losses from production errors, equipment downtime, and in some cases, preventing workplace injuries.
Continuous production
In another factory scenario, robots roam the floor performing highly choreographed tasks. If the signal is lost, the robots stop moving to avoid collisions with other equipment or workers. A human must then reposition the robots, causing delays and lost productivity. Having compute power closer to data will enable robots to continue operating and keep production on course.
The common thread
These examples share a common thread: compute power deployed at the network’s edge.
CSPs can improve their service offerings and create new opportunities for innovation and growth by deploying a cloud-native horizontal network architecture that optimizes the performance of traditional network services while also hosting new, revenue-generating enterprise applications. As part of this new network architecture, compute and storage capabilities expand towards the edge and far-edge, getting closer to where data is generated.
Now is the time for CSPs to accelerate their network transformation strategies to take advantage of the opportunities at the edge. By 2027, IDC estimates that 62% of enterprise data will be processed at the edge. Those CSPs who are working now to support edge computing in their networks are positioning themselves to deliver competitive advantages to their customers with unprecedented agility while creating new growth opportunities. And it is not too late for those CSPs who are behind on network transformation to accelerate their efforts and catch up.
Table of Contents
