A Cloud-Edge Framework for Energy-Efficient Event-Driven Control: An Integration of Online Supervised Learning, Spiking Neural Networks and Local Plasticity Rules

arXiv:2405.02316v1 Announce Type: cross
Abstract: This paper presents a novel cloud-edge framework for addressing computational and energy constraints in complex control systems. Our approach centers around a learning-based controller using Spiking Neural Networks (SNN) on physical plants. By integrating a biologically plausible learning method with local plasticity rules, we harness the efficiency, scalability, and low latency of SNNs. This design replicates control signals from a cloud-based controller directly on the plant, reducing the need for constant plant-cloud communication. The plant …

abstract arxiv cloud computational constraints control control systems cs.ai cs.lg cs.ne cs.sy edge eess.sy energy event framework integration networks neural networks novel paper plants rules snn spiking neural networks supervised learning systems type