AIBullisharXiv – CS AI · 4h ago3
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Green or Fast? Learning to Balance Cold Starts and Idle Carbon in Serverless Computing
Researchers developed LACE-RL, a deep reinforcement learning framework that optimizes serverless computing by balancing cold-start latency and carbon emissions. The system dynamically adjusts keep-alive durations based on real-time carbon intensity and workload patterns, achieving 51.69% fewer cold starts and 77.08% lower idle carbon emissions compared to static policies.