On the self-similar nature of Ethernet traffic (extended version)
IEEE/ACM Transactions on Networking (TON)
Heavy Tails and Long Range Dependence in On/Off Processes and Associated Fluid Models
Mathematics of Operations Research
Self-Similar Network Traffic and Performance Evaluation
Self-Similar Network Traffic and Performance Evaluation
Scheduling strategies and long-range dependence
Queueing Systems: Theory and Applications
Appendix: A primer on heavy-tailed distributions
Queueing Systems: Theory and Applications
Waiting-Time Asymptotics for the M/G/2 Queue with Heterogeneous Servers
Queueing Systems: Theory and Applications
The Asymptotic Workload Behavior of Two Coupled Queues
Queueing Systems: Theory and Applications
The impact of the service discipline on delay asymptotics
Performance Evaluation - Modelling techniques and tools for computer performance evaluation
Generalized processor sharing with light-tailed and heavy-tailed input
IEEE/ACM Transactions on Networking (TON)
Stable scheduling policies for fading wireless channels
IEEE/ACM Transactions on Networking (TON)
ACM SIGMETRICS Performance Evaluation Review
Surprising results on task assignment in server farms with high-variability workloads
Proceedings of the eleventh international joint conference on Measurement and modeling of computer systems
Scheduling policies for single-hop networks with heavy-tailed traffic
Allerton'09 Proceedings of the 47th annual Allerton conference on Communication, control, and computing
Dynamic server allocation to parallel queues with randomly varying connectivity
IEEE Transactions on Information Theory
Max-Weight Scheduling in Queueing Networks With Heavy-Tailed Traffic
IEEE/ACM Transactions on Networking (TON)
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We investigate the asymptotic behavior of the steady-state queue-length distribution under generalized max-weight scheduling in the presence of heavy-tailed traffic. We consider a system consisting of two parallel queues, served by a single server. One of the queues receives heavy-tailed traffic, and the other receives light-tailed traffic. We study the class of throughput-optimal max-weight-α scheduling policies and derive an exact asymptotic characterization of the steady-state queue-length distributions. In particular, we show that the tail of the light queue distribution is at least as heavy as a power-law curve, whose tail coefficient we obtain explicitly. Our asymptotic characterization also shows that the celebrated max-weight scheduling policy leads to the worst possible tail coefficient of the light queue distribution, among all nonidling policies. Motivated by the above negative result regarding the max-weight-α policy, we analyze a log-max-weight (LMW) scheduling policy. We show that the LMWpolicy guarantees an exponentially decaying light queue tail while still being throughput-optimal.