Differentiated Service Based on Reinforcement Learning in Wireless Networks
作者： Malika Bourenane
DOI: 10.1007/978-3-642-32063-7_44
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摘要: In this paper, we propose a global quality of service management applied to DiffServ environments and IEEE 802.11e wireless networks. Especially, evaluate how the standard for Quality Service in Wireless Local Area networks (WLANs) can interoperate with Differentiated Services (DiffServ) architecture end-to-end IP QoS. An Architecture integration traffic conditioner is then proposed manage resources availability regulate congestion situation. This modelled as an agent based on reinforcement learning.
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