@techreport{eckert-detnet-glbf-03, number = {draft-eckert-detnet-glbf-03}, type = {Internet-Draft}, institution = {Internet Engineering Task Force}, publisher = {Internet Engineering Task Force}, note = {Work in Progress}, url = {https://datatracker.ietf.org/doc/draft-eckert-detnet-glbf/03/}, author = {Toerless Eckert and Alexander Clemm and Stewart Bryant and Stefan Hommes}, title = {{Deterministic Networking (DetNet) Data Plane - guaranteed Latency Based Forwarding (gLBF) for bounded latency with low jitter and asynchronous forwarding in Deterministic Networks}}, pagetotal = 39, year = 2024, month = jul, day = 5, abstract = {This memo proposes a mechanism called "guaranteed Latency Based Forwarding" (gLBF) as part of DetNet for hop-by-hop packet forwarding with per-hop deterministically bounded latency and minimal jitter. gLBF is intended to be useful across a wide range of networks and applications with need for high-precision deterministic networking services, including in-car networks or networks used for industrial automation across on factory floors, all the way to ++100Gbps country-wide networks. Contrary to other mechanisms, gLBF does not require network wide clock synchronization, nor does it need to maintain per-flow state at network nodes, avoiding drawbacks of other known methods while leveraging their advantages. Specifically, gLBF uses the queuing model and calculus of Urgency Based Scheduling (UBS, {[}UBS{]}), which is used by TSN Asynchronous Traffic Shaping {[}TSN-ATS{]}. gLBF is intended to be a plug-in replacement for TSN-ATN or as a parallel mechanism beside TSN-ATS because it allows to keeping the same controller-plane design which is selecting paths for TSN-ATS, sizing TSN-ATS queues, calculating latencies and admitting flows to calculated paths for calculated latencies. In addition to reducing the jitter compared to TSN-ATS by additional buffering (dampening) in the network, gLBF also eliminates the need for per-flow, per-hop state maintenance required by TSN-ATS. This avoids the need to signal per-flow state to every hop from the controller-plane and associated scaling problems. It also reduces implementation cost for high-speed networking hardware due to the avoidance of additional high-speed speed read/write memory access to retrieve, process and update per-flow state variables for a large number of flows.}, }