MCS3: A Mixed-Criticality System With Suspension-Awareness and Semi-Clairvoyance for Edge Computing

Abstract

Autonomous driving vehicles (ADVs) are transforming urban mobility with advanced sensors for real-time decision-making, promising safer and more efficient transportation. Despite recent advancements targeting accident reduction and efficiency improvement, challenges like sensor range limitations persist. Edge-assisted perception, facilitated by vehicle-to-everything (V2X) communications, addresses these limitations by sharing data among ADVs, enhancing accuracy in complex driving scenarios. However, this approach amplifies real-time computing challenges due to wireless communication-induced suspensions. This work presents a solution called MCS3 a suspension-aware mixed-criticality system (MCS) for edge-assisted computing. MCS3 addresses real-time challenges through a hardware–software co-design, introducing a MCS3-bridge for monitoring peripheral traffic with a dual-mode scheduler. MCS3 is implemented on the AMD Virtex VC709 FPGA and examined using comprehensive metrics. The experimental results show that MCS3 significantly improves the system-wide real-time performance with light overhead on both hardware and software.