An Approach to Network Service Placement Reconciling Optimality and Scalability
Author:
Affiliation:
1. Advanced Connectivity Lab, IRT-BCOM, Cesson-Sévigné, France
2. University Rennes, Inria, CNRS, IRISA, Rennes, France
3. IMT Atlantique, IRISA, Adopnet, Cesson-Sévigné, France
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Electrical and Electronic Engineering,Computer Networks and Communications
Link
http://xplorestaging.ieee.org/ielx7/4275028/10274602/10147351.pdf?arnumber=10147351
Reference22 articles.
1. Learn to improve: A novel deep reinforcement learning approach for beyond 5G network slicing
2. A Deep Reinforcement Learning Approach for VNF Forwarding Graph Embedding
3. A Q-Learning-Based Approach for Deploying Dynamic Service Function Chains
4. Optimal VNF Placement via Deep Reinforcement Learning in SDN/NFV-Enabled Networks
5. Concepts of Exact QoS Routing Algorithms
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3. Guest Editors’ Introduction: Special Section on Robust and Reliable Networks of the Future;IEEE Transactions on Network and Service Management;2023-09
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