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A-DDPG: Attention Mechanism-based Deep Reinforcement Learning for NFV

2021 IEEE/ACM 29th International Symposium on Quality of Service (IWQOS)(2021)

Cited 18|Views28
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Abstract
The efficacy of Network Function Virtualization (NFV) depends critically on (1) where the virtual network functions (VNFs) are placed and (2) how the traffic is routed. Unfortunately, these aspects are not easily optimized, especially under time-varying network states with different quality of service (QoS) requirements. Given the importance of NFV, many approaches have been proposed to solve the ...
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Key words
Network function virtualization,deep reinforcement learning,placement,routing
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