UPF
A core network element of the 5G core network user plane, responsible for packet forwarding, PDR/FAR/QER rule matching, tunnel encapsulation, QoS enforcement and traffic statistics. A programmable UPF allows custom processing logic to be inserted into the data plane.
Timeline (last 90 days)
In the 5G core network architecture, the control plane is responsible for session management, policy, and mobility, while the user plane is responsible for actual packet forwarding; the UPF is the core network element of the user plane, undertaking rule matching such as PDR/FAR/QER, tunnel encapsulation, QoS enforcement, and traffic statistics.
A programmable UPF allows custom processing logic to be inserted into the data plane (such as based on P4 or eBPF), which is the landing point for IoD's implementation of in-band tensor context.
The research team evaluated IoD on a testbed based on a programmable user plane function (UPF), using a partitionable visual AI workload.
There is still a distance from the testbed to live networks, and the deployment density of programmable UPFs, the standardization progress of cross-vendor APIs, and the overhead of inference context under real congestion scenarios are all questions IoD needs to continue answering.
All Facts (5)
UPF 50+意味着仅允许1/50的紫外线穿透面料
55%UnverifiedIn the 5G core network architecture, the control plane is responsible for session management, policy, and mobility, while the user plane is responsible for actual packet forwarding; the UPF is the core network element of the user plane, undertaking rule matching such as PDR/FAR/QER, tunnel encapsulation, QoS enforcement, and traffic statistics.
50%UnverifiedA programmable UPF allows custom processing logic to be inserted into the data plane (such as based on P4 or eBPF), which is the landing point for IoD's implementation of in-band tensor context.
50%UnverifiedThere is still a distance from the testbed to live networks, and the deployment density of programmable UPFs, the standardization progress of cross-vendor APIs, and the overhead of inference context under real congestion scenarios are all questions IoD needs to continue answering.
50%UnverifiedThe research team evaluated IoD on a testbed based on a programmable user plane function (UPF), using a partitionable visual AI workload.
50%