Optimization flow control—I: basic algorithm and convergence
IEEE/ACM Transactions on Networking (TON)
A game theoretic framework for bandwidth allocation and pricing in broadband networks
IEEE/ACM Transactions on Networking (TON)
Utility-based rate control in the Internet for elastic traffic
IEEE/ACM Transactions on Networking (TON)
A bandwidth sharing theory for a large number of HTTP-like connections
IEEE/ACM Transactions on Networking (TON)
Non-convex optimization and rate control for multi-class services in the Internet
IEEE/ACM Transactions on Networking (TON)
Downlink power allocation for multi-class wireless systems
IEEE/ACM Transactions on Networking (TON)
Distributed rate allocation for inelastic flows
IEEE/ACM Transactions on Networking (TON)
Utility-based end-to-end flow control for services with time-varying rate requirements
CCNC'09 Proceedings of the 6th IEEE Conference on Consumer Communications and Networking Conference
Opportunistic power scheduling for dynamic multi-server wireless systems
IEEE Transactions on Wireless Communications
Utility-Optimal Random-Access Control
IEEE Transactions on Wireless Communications
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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.