Fair end-to-end window-based congestion control
IEEE/ACM Transactions on Networking (TON)
A framework for opportunistic scheduling in wireless networks
Computer Networks: The International Journal of Computer and Telecommunications Networking
Optimal flow control and routing in multi-path networks
Performance Evaluation - Special issue: Internet performance and control of network systems
Proceedings of the 10th annual international conference on Mobile computing and networking
Fairness and load balancing in wireless LANs using association control
Proceedings of the 10th annual international conference on Mobile computing and networking
Stability of end-to-end algorithms for joint routing and rate control
ACM SIGCOMM Computer Communication Review
Maximizing Queueing Network Utility Subject to Stability: Greedy Primal-Dual Algorithm
Queueing Systems: Theory and Applications
A queueing analysis of max-min fairness, proportional fairness and balanced fairness
Queueing Systems: Theory and Applications
IEEE/ACM Transactions on Networking (TON)
Optimal rate allocation for energy-efficient multipath routing in wireless ad hoc networks
IEEE Transactions on Wireless Communications
User Association to Optimize Flow Level Performance in Wireless Systems with Dynamic Interference
NET-COOP '09 Proceedings of the 3rd Euro-NF Conference on Network Control and Optimization
IEEE/ACM Transactions on Networking (TON)
Practical adaptive user association policies for wireless systems with dynamic interference
IEEE/ACM Transactions on Networking (TON)
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Spatial and temporal load variations, e.g. flash overloads and traffic hot spots that persist for minutes to hours, are intrinsic features of wireless networks, and give rise to potentially huge performance repercussions. Dynamic load balancing strategies provide a natural mechanism for dealing with load fluctuations and alleviating the performance impact. In the present paper we propose a distributed shadow-price-based approach to dynamic load balancing in wireless data networks. We examine two related problem versions: (i) minimizing a convex function of the transmitter loads for given user throughput requirements; and (ii) maximizing a concave function of the user throughputs subject to constraints on the transmitter loads. As conceptual counterparts, these two formulations turn out to be amenable to a common primal-dual decomposition framework. Numerical experiments show that dynamic load balancing yields significant performance gains in terms of user throughputs and delays, even in scenarios where the long-term loads are perfectly balanced.