AERO: Adaptive Edge-Cloud Orchestration With a Sub-1K-Parameter Forecasting Model

Effective resource management in edge-cloud networks is crucial for meeting Quality of Service (QoS) requirements while minimizing operational costs. However, dynamic and fluctuating workloads pose significant challenges for accurate workload prediction and efficient resource allocation, particularl...

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Bibliografske podrobnosti

Principais autores:	Berend J. D. Gort, Godfrey M. Kibalya, Angelos Antonopoulos
Format:	Artigo
Jezik:	Inglês
Izdano:	IEEE 2025-01-01
Serija:	IEEE Transactions on Machine Learning in Communications and Networking
Teme:	Edge computing cloud-edge orchestration adaptive resource management lightweight forecasting models workload prediction dynamic periodicity detection
Online dostop:	https://ieeexplore.ieee.org/document/10935743/
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