AXI-REALM: Safe, Modular and Lightweight Traffic Monitoring and Regulation for Heterogeneous Mixed-Criticality Systems

2025-01-17

AI Summary

To address timing unpredictability arising from shared interconnect resources in heterogeneous mixed-criticality systems (MCS), this paper proposes a lightweight, modular, and process-agnostic AXI4 real-time extension architecture. The method introduces a novel real-time arbitration mechanism based on periodic time-window budgeting and burst fragmentation, ensuring fair traffic allocation and predictable execution. It further integrates end-to-end hardware monitoring for bandwidth and latency, alongside an automatic slave fault detection-and-reset mechanism. The open-source implementation incurs less than 2% area overhead. Experimental evaluation demonstrates a 68.2% improvement in critical-path isolation performance, a 24× reduction in slave access latency, and sustained isolation efficacy exceeding 95% even under severe bandwidth skew conditions.

Technology Category

• Machine Learning: Hardware-aware ML
• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems
• Multiagent Systems: Mechanism Design

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Web performance, measurement, and characterization
• Responsible Web: Machine-in-the-loop, human agency and autonomy
• Security and Privacy: Large-scale security measurements

Abstract

The automotive industry is transitioning from federated, homogeneous, interconnected devices to integrated, heterogeneous, mixed-criticality systems (MCS). This leads to challenges in achieving timing predictability techniques due to access contention on shared resources, which can be mitigated using hardware-based spatial and temporal isolation techniques. Focusing on the interconnect as the point of access for shared resources, we propose AXI-REALM, a lightweight, modular, technology-independent, and open-source real-time extension to AXI4 interconnects. AXI-REALM uses a budget-based mechanism enforced on periodic time windows and transfer fragmentation to provide fair arbitration, coupled with execution predictability on real-time workloads. AXI-REALM features a comprehensive bandwidth and latency monitor at both the ingress and egress of the interconnect system. Latency information is also used to detect and reset malfunctioning subordinates, preventing missed deadlines. We provide a detailed cost assessment in a 12 nm node and an end-to-end case study implementing AXI-REALM into an open-source MCS, incurring an area overhead of less than 2%. When running a mixed-criticality workload, with a time-critical application sharing the interconnect with non-critical applications, we demonstrate that the critical application can achieve up to 68.2% of the isolated performance by enforcing fairness on the interconnect traffic through burst fragmentation, thus reducing the subordinate access latency by up to 24 times. Near-ideal performance, (above 95% of the isolated performance) can be achieved by distributing the available bandwidth in favor of the critical application.

Problem

• Resource Allocation
• Predictable Usage
• Mixed Criticality Systems

Innovation

• AXI-REALM
• Resource Management
• Mixed-Criticality Systems