Adaptive Resource Allocation in Quantum Key Distribution (QKD) for Federated Learning

08/24/2022

∙

Increasing privacy and security concerns in intelligence-native 6G networks require quantum key distribution-secured federated learning (QKD-FL), in which data owners connected via quantum channels can train an FL global model collaboratively without exposing their local datasets. To facilitate QKD-FL, the architectural design and routing management framework are essential. However, effective implementation is still lacking. To this end, we propose a hierarchical architecture for QKD-FL systems in which QKD resources (i.e., wavelengths) and routing are jointly optimized for FL applications. In particular, we focus on adaptive QKD resource allocation and routing for FL workers to minimize the deployment cost of QKD nodes under various uncertainties, including security requirements. The experimental results show that the proposed architecture and the resource allocation and routing model can reduce the deployment cost by 7.72% compared to the CO-QBN algorithm.

READ FULL TEXT

Adaptive Resource Allocation in Quantum Key Distribution (QKD) for Federated Learning

Resource Rationing for Wireless Federated Learning: Concept, Benefits, and Challenges

Privacy-preserving Intelligent Resource Allocation for Federated Edge Learning in Quantum Internet

Bandwidth Allocation for Multiple Federated Learning Services in Wireless Edge Networks

On Addressing Heterogeneity in Federated Learning for Autonomous Vehicles Connected to a Drone Orchestrator

Resource Allocation in Quantum Key Distribution (QKD) for Space-Air-Ground Integrated Networks

Towards Bridging the FL Performance-Explainability Trade-Off: A Trustworthy 6G RAN Slicing Use-Case

TEFL: Turbo Explainable Federated Learning for 6G Trustworthy Zero-Touch Network Slicing

Adaptive Resource Allocation in Quantum Key Distribution (QKD) for Federated Learning

Related Research

Resource Rationing for Wireless Federated Learning: Concept, Benefits, and Challenges

Privacy-preserving Intelligent Resource Allocation for Federated Edge Learning in Quantum Internet

Bandwidth Allocation for Multiple Federated Learning Services in Wireless Edge Networks

On Addressing Heterogeneity in Federated Learning for Autonomous Vehicles Connected to a Drone Orchestrator

Resource Allocation in Quantum Key Distribution (QKD) for Space-Air-Ground Integrated Networks

Towards Bridging the FL Performance-Explainability Trade-Off: A Trustworthy 6G RAN Slicing Use-Case

TEFL: Turbo Explainable Federated Learning for 6G Trustworthy Zero-Touch Network Slicing