
This paper introduces CONAL, a novel constraint-aware learning framework designed to optimize resource allocation in Network Function Virtualization (NFV) networks by effectively addressing the challenges of constraint management in Virtual Network Embedding (VNE).


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a-constraint-aware-learning-framework-for-efficient-resource-allocation-in-network-function-virtualization-nfv-networks


A Constraint-Aware Learning Framework for Efficient Resource Allocation in Network Function Virtualization (NFV) Networks


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A flexible and generalizable reinforcement learning framework, named FlagVNE, is proposed to effectively solve the virtual network embedding (VNE) problem by enhancing searchability and generalizability.


flexible-and-generalizable-reinforcement-learning-framework-for-efficient-virtual-network-resource-allocation


Flexible and Generalizable Reinforcement Learning Framework for Efficient Virtual Network Resource Allocation
