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There are two causes of network congestion: one is the lack of network resources, and the other is the irrational allocation of network resources. While traditional congestion control methods such as rate control, window mechanism, queue control, etc. can be applied to solve the congestion problem, but for the later congestion case, the fundamental solution is to make more effectively use of the network...
The problem of cognitive access of channels of primary users by a secondary user is considered. The transmissions of primary users are modeled as independent continuous-time Markovian on-off processes. A secondary cognitive user employs slotted transmissions, and it senses one of the possible channels before transmission. The objective of the cognitive user is to maximize its throughput subject to...
For the congestion problems in high-speed networks, a Q-learning model-independent flow controller is proposed. Because of the uncertainties and highly time-varying, it is not easy to accurately obtain the complete information for high-speed networks. In this case, the Q-learning, which is independent of mathematic model and prior-knowledge, has good performance. In this paper, the flow with higher...
For the congestion problems in high-speed networks, a multi-agent flow controller (MFC) based on Q-learning algorithm conjunction with the theory of Nash equilibrium is proposed. Because of the uncertainties and highly time-varying, it is not easy to accurately obtain the complete information for high-speed networks, especially for the multi-bottleneck case. The Nash Q-learning algorithm, which is...
Peer-to-peer file sharing applications, which enable peers to establish multiple TCP connections between other peers to transfer data, pose new challenge to congestion control. Since conventional congestion control only aims to make each of those connections TCP-friendly, self users can increase the number of connections to grab a large share of the bandwidth, introducing more congestion and degrading...
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