nEdge (network coding at the edge) enables low-delay communication, fast processing, and enhanced security for applications and devices connected via a private 5G network in an enterprise. Instead of providing these services in a cloud, nEdge provides the services on-premises, making the processing, data storage, and data flow faster, better, and more economical.
What is nEdge?
nEdge stands for network coding at the edge. nEdge — a 5G-compliant technology — is a key enabler of 5G applications. nEdge provides low-delay communication services, low-latency processing, and increased security and privacy for data communication and data storage. Enterprises can integrate nEdge with their private 5G network to leverage the benefits of 5G along with nEdge.
By leveraging 5G along with network coding, nEdge provides the following benefits:
- Alleviates security & privacy concerns of (private) data transferred through communication networks and stored in (untrusted) clouds
- Latency concerns in wireless communications (e.g., in AR/MR streaming or broadcasting) and local content distribution
- Provides low latency, high bandwidth, security, and localized service needs
- Reduces costs by reducing traffic flow via EPC/5G core and internet transit
- Virtualized edge computing design enhances network communication and IT computing capability
CU Coding’s nEdge technology can be an enabler for multiple applications and solutions. Some of these are as follows:
- Low latency broadcast of AR/MR stream of a local event in a local area, stadium, mall, etc.
- Real-time incident detection (e.g., of accidents, available parking lots, and fire breakouts)
- Geo-location services for pets in pet-friendly zones, pedestrians, etc.
- Detection of wild animals in villages
- Wireless 5G CCTV for indoor and outdoor monitoring for enterprises
- Monitoring of an area using a 5G-LiDAR (i.e., enabling security without compromising on privacy)
- Building automation using a private 5G network in an enterprise
- Enabling local monitoring and control of devices (without using internet or WAN) connected wirelessly through a private 5G network in an enterprise (e.g., 5G printers, 5G CCTV control and monitoring).
What technology is used?
The key technologies nEdge makes use of are multiaccess edge computing (MEC), network coding, and AI processing. Using these technologies nEdge acts as an enabler for applications requiring low-latency and high QoS.
More specifically, network coding technology in nEdge enables storing of network coded data in a distributed cloud for the upstream traffic. Network coding operation is applied to the upcoming traffic (show in grey colored circles) at nEdge and network coded traffic (shown in dark blue circles) is generated. The network coded traffic is distributed to multiple data centers. Storing of network coded data instead of the original data in the cloud provides increased fault tolerance, enhanced security, and privacy (even when data is stored on untrusted clouds). The downlink data coming from the clouds can be network decoded at the nEdge as well before it is distributed to the users via a 5G network. Network coded data can also be directly distributed to the users and the users can perform network decoding. This methodology is beneficial for broadcast and multicast, e.g., in AR and MR streaming.
The MEC technology provides a local breakout point to the traffic generated locally. What this means is that the MEC platform (nEdge) enables the traffic to leave the 5G network immediately without going through the core network. This helps in reducing costs for the operator as well as for the enterprises employing private 5G. As we can see in the figure, the MEC platform is placed closer to the end-user (i.e., between the base station and the core network). The traffic can hence directly leave the 5G network and can be routed to a private cloud, public cloud, etc.
Since nEdge is located on-premises and is much closer to the end-user in comparison with the cloud, applications requiring low-latency can be run on nEdge. We provide an AI processing server on nEdge. Applications that need to be run and processed locally can leverage the nEdge AI processor. The traffic generated by the end-users is consumed locally at the nEdge and returned to the end-users or the enterprise for control/monitoring. This framework not only helps the enterprises in saving the data processing cost at the cloud but also the data communication costs to/from the clouds.