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Title: Intelligent adaptive bandwidth provisioning for quality of service in umts core networks
Keywords: Reinforcement Learning, adaptive bandwidth provisioning, Quality of Service, UMTS core network, Differentiated Services, 3G
Issue Date: 25-Jun-2004
Citation: HUI CHEE KIN, TIMOTHY (2004-06-25). Intelligent adaptive bandwidth provisioning for quality of service in umts core networks. ScholarBank@NUS Repository.
Abstract: The issue of bandwidth provisioning is imperative for Quality of Service (QoS) to be achieved in next-generation Universal Mobile Telecommunications System (UMTS) core networks. The standardized implementation of Differentiated Services (DiffServ) as the service model enables services with a variety of QoS requirements to be transported over the same core network. To ensure that the QoS requirements of all classes can be met efficiently, the proportion of bandwidth provisioned to each class has to be optimized. The task however is made complex by the continuously varying nature of traffic and the constant modification of routes due to the mobility of end nodes. This thesis presents a solution to the bandwidth provisioning problem in both the core backbone network and the radio access network. The solution makes use of a continuous-space, gradient-descent Reinforcement Learning (RL) algorithm to continuously adapt per-aggregate bandwidth provisions to changing conditions to achieve maximum revenue and minimum QoS violations. Extensive simulations of various traffic conditions, QoS requirements and pricing policies show that the algorithm is able to converge towards an optimal solution.
Appears in Collections:Master's Theses (Open)

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