Scheduling with limited information in wireless systems
Proceedings of the tenth ACM international symposium on Mobile ad hoc networking and computing
Strategic Resource Dynamics of Manufacturing Firms
Management Science
Distributed adaptive algorithms for optimal opportunistic medium access
WiOPT'09 Proceedings of the 7th international conference on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks
Delay reduction via lagrange multipliers in stochastic network optimization
WiOPT'09 Proceedings of the 7th international conference on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks
MIMO downlink scheduling with non-perfect channel state knowledge
IEEE Transactions on Communications
How to allocate goods in an online market?
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Fast algorithms for resource allocation in wireless cellular networks
IEEE/ACM Transactions on Networking (TON)
Distributed Adaptive Algorithms for Optimal Opportunistic Medium Access
Mobile Networks and Applications
IEEE/ACM Transactions on Networking (TON)
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Computer Communications
Control of wireless networks with secrecy
IEEE/ACM Transactions on Networking (TON)
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In Stolyar (Queueing Systems 50 (2005) 401---457) a dynamic control strategy, called greedy primal-dual (GPD) algorithm, was introduced for the problem of maximizing queueing network utility subject to stability of the queues, and was proved to be (asymptotically) optimal. (The network utility is a concave function of the average rates at which the network generates several "commodities.") Underlying the control problem of Stolyar (Queueing Systems 50 (2005) 401---457) is a convex optimization problem subject to a set of linear constraints.In this paper we introduce a generalized GPD algorithm, which applies to the network control problem with additional convex (possibly non-linear) constraints on the average commodity rates. The underlying optimization problem in this case is a convex problem subject to convex constraints. We prove asymptotic optimality of the generalized GPD algorithm. We illustrate key features and applications of the algorithm on simple examples.