Towards Large-Scale Deterministic IP Networks

Abstract

Deterministic performance is a key enabler for 5G networking. In this context, we present a highly scalable Large-scale Deterministic Network (LDN) architecture providing end-to-end latency and bounded jitter guarantees in IP networks. At the data plane, flows are first shaped at ingress gateways using gate-control queues, achieving a very fine granularity compared to existing state of the art solutions. Inside the network, traffic is scheduled using an asynchronous cyclic queuing mechanism that can be implemented in real devices as it requires only 3 FIFO queues. The data plane relies on standard IP routing and a quasi-static mapping table to deterministically aggregate and forward packets over cycles with a low complexity in $O(1)$. For the control plane, we present an advanced column generation algorithm to quickly take admission control decisions in large-scale networks. For a set of flows, it determines acceptance and selects the best shaping and routing policy. Through a proof-of-concept implementation and simulations, we show that our LDN architecture can guarantee end-to-end latency and bounded jitter. We also demonstrate that our advanced control plane algorithm brings an improvement up to 40% in terms of accepted traffic over classical routing.