Dynamic Bandwidth Allocation with Fairness by Using Fuzzy Q-learning for MPLS-TP Ring

• Main Authors: Chen, Chun-Kuei, 陳俊魁
• Other Authors: Chang, Chung-Ju
• Format: Others
• Language: en_US
• Published: 2011
• Online Access: http://ndltd.ncl.edu.tw/handle/77830864454709672159

碩士 === 國立交通大學 === 電機學院通訊與網路科技產業專班 === 100 === The data-type traffic from mobile equipment grows rapidly day by day. While consumers want to pay less for mobile services, network operators must reduce their cost when scaling networks. Since the cost and media-usage efficiency advantages, Ethernet is extending from local area network to metropolitan area network. Beyond the attachment point as the transmitting medium, Ethernet services may operate over different kinds of packet transport networks (PTNs). MPLS-TP is one of the PTN standard. The MPLS-TP adopts all of the supporting QoS mechanisms already defined within the standards, and also brings the benefits of path-based, in-band OAM and protection mechanisms found in traditional transport technologies. This thesis is base on providing the fairness property of ring network as in previous related works. However, we make the total available bandwidth for fairness eligible traffic become dynamic in MPLT-TP ring, which is real in transport network. The fair rate scheme would be face with oscillation. So we adopt the fuzzy Q-learning algorithm in fair rate generator to enhance the performance of network. We find a signal which called rate difference take it as the reinforcement signal for fuzzy Q-learning. The simulation results reveal the purposed fuzzy Q-learning fair rate generator can make the MPLS-TP ring network with lower convergence time and higher utilization.