Dynamic QoS-Aware Traffic Planning for Time-Triggered Flows in the Real-Time Data Plane
2022
Many networked applications, e.g., in the domain of cyber-physical systems, require strict service guarantees for time-triggered traffic flows, usually in the form of jitter and latency bounds. It is a notoriously hard problem to compute a network-wide traffic plan, i.e., a set of routes and transmission schedules, that satisfies these requirements, and dynamic changes in the flow set add even more challenges. Existing traffic-planning methods are ill-suited for dynamic scenarios because they either suffer from high computational cost, can result in low network utilization, or provide no explicit guarantees when transitioning to a new traffic plan that incorporates new flows. Therefore, we present a novel approach for dynamic traffic planning of time-triggered flows. Our conflict-graph-based modeling of the traffic planning problem allows for the reconfiguration of active flows to increase the network utilization, while also providing per-flow QoS guarantees during the transition to the new traffic plan. Additionally, we introduce a novel heuristic for computing the new traffic plans. Evaluations of our prototypical implementation show that we can efficiently compute new traffic plans in scenarios with hundreds of active flows for a wide range of settings.
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