Optimal probabilistic allocation of customer types to servers
Proceedings of the 1995 ACM SIGMETRICS joint international conference on Measurement and modeling of computer systems
Wireless Networks - Special issue: mobile computing and networking: selected papers from MobiCom '96
Wireless Communications: Principles and Practice
Wireless Communications: Principles and Practice
The Asymptotic Workload Behavior of Two Coupled Queues
Queueing Systems: Theory and Applications
Wireless data performance in multi-cell scenarios
Proceedings of the joint international conference on Measurement and modeling of computer systems
Proceedings of the 10th annual international conference on Mobile computing and networking
Stability of Parallel Queueing Systems with Coupled Service Rates
Discrete Event Dynamic Systems
Stability of two interfering processors with load balancing
Proceedings of the 3rd International Conference on Performance Evaluation Methodologies and Tools
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
Distributed dynamic load balancing in wireless networks
ITC20'07 Proceedings of the 20th international teletraffic conference on Managing traffic performance in converged networks
Distributed α-optimal user association and cell load balancing in wireless networks
IEEE/ACM Transactions on Networking (TON)
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We study the impact of user association policies on flow-level performance in interference-limited wireless networks. Most research in this area has used static interference models (neighboring base stations are always active) and resorted to intuitive objectives such as load balancing. In this paper, we show that this can be counterproductive in the presence of dynamic interference that couples the transmission rates to users at various base stations. We propose a methodology to optimize the performance of a class of coupled systems and apply it to study the user association problem. We show that by properly inducing load asymmetries, substantial performance gains can be achieved relative to a load-balancing policy (e.g., 15 times reduction in mean delay). We present a practical, measurement based, interference-aware association policy that infers the degree of interference-induced coupling and adapts to it. Systematic simulations establish that both our optimized static and adaptive association policies substantially outperform various dynamic policies that can, in extreme cases, even be susceptible to Braess's paradox-like phenomena, i.e., an increase in the number of base stations can lead to worse performance under greedy association policies. Furthermore, these results are robust to changes in file-size distributions, large-scale propagation parameters, and spatial load distributions.