Abstract
The novel cloud-edge collaborative computing architecture can provide more efficient and intelligent services close to users. Reliable service function chain orchestration among datacenters is critical to ensuring computing efficiency. In this study, a service orchestration model is proposed to improve the reliability while reducing cost. The solution is a federated reinforcement learning framework that shares decision-making experiences to obtain reliable and effective service orchestration results between different datacenter environments. The simulation results demonstrate that the proposed orchestration method reaches convergence faster and has a significant performance in terms of improving service reliability.
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Xiao, Z. et al. (2022). A Reliable Service Function Chain Orchestration Method Based on Federated Reinforcement Learning. In: Gao, H., Wang, X., Wei, W., Dagiuklas, T. (eds) Collaborative Computing: Networking, Applications and Worksharing. CollaborateCom 2022. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 460 . Springer, Cham. https://doi.org/10.1007/978-3-031-24383-7_10
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