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 realtime 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.Index Terms-embedded systems, real-time operating systems, embedded IP stack, internet of things, cyber-physical systems• Protection against network-induced system overloads, facilitating real-time systems. • Optimal processing latency for well-behaved High Priority flows. • Best-effort performance for Low Priority flows. The paper also introduces a prototypical implementation modifying a popular network stack and presents a set of experiments that evaluate basic performance properties.

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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 realtime 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.