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Serverless Function Latency Model in Edge Computing
A statistical model of the service latency of serverless functions, with particular reference to edge computing, based on the observation of experimental latency values and adapted to produce a statistical distribution that closely approximates the real one is illustrated.
Learning to Remember: Attentive Reinforcement Learning for Edge Serverless Autoscaling
Results indicate that mitigating temporal blindness through deep attentive memory improves the reliability and stability of Kubernetes autoscaling under bursty edge workloads.