Differentiating Network Flows for Priority-Aware Scheduling of Incoming Packets in Real-Time IoT Systems

TL;DR

This paper introduces a real-time aware IP stack adaptation with early packet demultiplexing and per-flow scheduling, significantly reducing processing latency and increasing system load capacity in industrial IoT and automotive environments.

Contribution

It presents a novel IP stack modification that enables priority-aware packet processing without extra task resources, enhancing overload protection in embedded real-time systems.

Findings

Reduced low-priority packet processing time by over 86%.

Increased maximum sustainable traffic load by 7 times.

Achieved minimal overhead with simple flow mitigation techniques.

Abstract

When IP-packet processing is unconditionally carried out on behalf of an operating system kernel thread, processing systems can experience overload in high incoming traffic scenarios. This is especially worrying for embedded real-time devices controlling their physical environment in industrial IoT scenarios and automotive systems. We propose an embedded real-time aware IP stack adaption with an early demultiplexing scheme for incoming packets and subsequent per-flow aperiodic scheduling. By instrumenting existing embedded IP stacks, rigid prioritization with minimal latency is deployed without the need of further task resources. Simple mitigation techniques can be applied to individual flows, causing hardly measurable overhead while at the same time protecting the system from overload conditions. Our IP stack adaption is able to reduce the low-priority packet processing time by over 86% compared to an unmodified stack. The network subsystem can thereby remain active at a 7x higher general traffic load before disabling the receive IRQ as a last resort to assure deadlines.