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Stochastic utility-based flow control algorithm for services with time-varying rate requirements
Authors:Byung-Gook Kim  Jang-Won Lee
Affiliation:1. Department of Urology, Zonguldak State Hospital, Zonguldak, Turkey;2. Northern Institute for Cancer Research, School of Medicine, Newcastle University, Newcastle, United Kingdom;3. Department of Urology, Gaziosmanpasa Taksim Education and Research Hospital, Istanbul, Turkey;1. College of Business Law and Governance, James Cook University, Douglas, QLD 4811, Australia;2. School of Business, University of the Sunshine Coast, Maroochydore DC, QLD 4558, Australia;3. Shanghai Lixin University of Commerce, 2800 Wenxiang Road, Shanghai, China;1. Department of Urology, Kouseiren Takaoka Hospital, Takaoka, Toyama, Japan;2. Department of Urology, Toyama Prefectural Central Hospital, Toyama, Japan;1. Section of Endourology, Division of Urology, Hospital das Clínicas, University of Sao Paulo Medical School, Sao Paulo, Brazil;2. Glickman Urological and Kidney Institute, Cleveland Clinic, Cleveland, OH
Abstract:In this paper, we study a utility based flow control problem for a communication network. In most previous works on utility based flow control, the utility function of each user, which represents its satisfaction to the allocated data rate, is assumed to be fixed. This implies that the degree of the rate requirement of each user is assumed to be fixed over the entire duration of its session. However, in communication networks, many services are variable rate services, i.e., the degree of their rate requirement varies over time, which cannot be modeled with traditional static utility functions. To resolve this issue and appropriately model services with variable rate requirements, we propose a stochastic utility function that varies stochastically according to the variation of the degree of the rate requirement of a service. We formulate a flow control problem as a stochastic optimization problem with stochastic utility functions that aims at maximizing the average network utility while satisfying the constraint on link capacity and QoS requirement. By solving the stochastic optimization problem, we develop a distributed flow control algorithm that converges to the optimal rate allocation.
Keywords:
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