Throughput optimal scheduling in the presence of heavy-tailed traffic

We investigate the tail behavior of the steady-state queue occupancies under throughput optimal 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 traffic that is heavy-tailed (the “heavy queue”), and the other receives light-tailed traffic (the “light queue”). The queues are connected to the server through time-varying ON/OFF links. We study a generalized version of max-weight scheduling, called the max-weight-α policy, and show that the light queue occupancy distribution is heavy-tailed for arrival rates above a threshold value. We also obtain the exact ‘tail coefficient’ of the light queue occupancy distribution under max-weight-alpha scheduling. Next, we show that the policy that gives complete priority to the light queue guarantees the best possible tail behavior of both queue occupancy distributions. However, the priority policy is not throughput optimal, and can cause undesirable instability effects in the heavy queue. Finally, we propose a log-max-weight (LMW) scheduling policy. We show that in addition to being throughput optimal, the LMW policy guarantees that the light queue occupancy distribution is light-tailed, for all arrival rates that the priority policy can stabilize. Thus, the LMW scheduling policy has desirable performance on both fronts, namely throughput optimality, and the tail behavior of the light queue occupancy distribution.

[1]  Alan Scheller-Wolf,et al.  Surprising results on task assignment in server farms with high-variability workloads , 2009, SIGMETRICS '09.

[2]  Sem C. Borst,et al.  The impact of the service discipline on delay asymptotics , 2003, Perform. Evaluation.

[3]  Jean C. Walrand,et al.  Achieving 100% throughput in an input-queued switch , 1996, Proceedings of IEEE INFOCOM '96. Conference on Computer Communications.

[4]  Eytan Modiano,et al.  Dynamic power allocation and routing for time varying wireless networks , 2003, IEEE INFOCOM 2003. Twenty-second Annual Joint Conference of the IEEE Computer and Communications Societies (IEEE Cat. No.03CH37428).

[5]  Venkat Anantharam,et al.  Scheduling strategies and long-range dependence , 1999, Queueing Syst. Theory Appl..

[6]  Mihalis G. Markakis,et al.  Scheduling policies for single-hop networks with heavy-tailed traffic , 2009, 2009 47th Annual Allerton Conference on Communication, Control, and Computing (Allerton).

[7]  Krishna P. Jagannathan Asymptotic performance of queue length based network control policies , 2010 .

[8]  Leandros Tassiulas,et al.  Dynamic server allocation to parallel queues with randomly varying connectivity , 1993, IEEE Trans. Inf. Theory.

[9]  Gennady Samorodnitsky,et al.  Heavy Tails and Long Range Dependence in On/Off Processes and Associated Fluid Models , 1998, Math. Oper. Res..

[10]  Eytan Modiano,et al.  Dynamic reconfiguration and routing algorithms for IP-over-WDM networks with stochastic traffic , 2005, Proceedings IEEE 24th Annual Joint Conference of the IEEE Computer and Communications Societies..

[11]  Adam Wierman,et al.  Is Tail-Optimal Scheduling Possible? , 2012, Oper. Res..

[12]  Atilla Eryilmaz,et al.  Stable scheduling policies for fading wireless channels , 2003, IEEE International Symposium on Information Theory, 2003. Proceedings..

[13]  Walter Willinger,et al.  On the self-similar nature of Ethernet traffic , 1993, SIGCOMM '93.

[14]  Robert G. Gallager,et al.  Discrete Stochastic Processes , 1995 .

[15]  Sem C. Borst,et al.  Generalized processor sharing with light-tailed and heavy-tailed input , 2003, TNET.

[16]  Eytan Modiano,et al.  Achieving 100% throughput in reconfigurable optical networks , 2008 .

[17]  Leandros Tassiulas,et al.  Stability properties of constrained queueing systems and scheduling policies for maximum throughput in multihop radio networks , 1990, 29th IEEE Conference on Decision and Control.

[18]  Walter Willinger,et al.  Self-Similar Network Traffic and Performance Evaluation , 2000 .

[19]  R. Srikant,et al.  Stable scheduling policies for fading wireless channels , 2005, IEEE/ACM Transactions on Networking.

[20]  Eytan Modiano,et al.  Achieving 100% Throughput in Reconfigurable Optical Networks , 2006, IEEE/ACM Transactions on Networking.

[21]  A. P. Zwart,et al.  Waiting-Time Asymptotics for the M/G/2 Queue with Heterogeneous Servers , 2002, Queueing Syst. Theory Appl..

[22]  Damon Wischik,et al.  Big queues , 2004, Lecture notes in mathematics.

[23]  Eytan Modiano,et al.  Power and server allocation in a multi-beam satellite with time varying channels , 2002, Proceedings.Twenty-First Annual Joint Conference of the IEEE Computer and Communications Societies.

[24]  Sem C. Borst,et al.  Pna Probability, Networks and Algorithms the Asymptotic Workload Behavior of Two Coupled Queues , 2022 .

[25]  Leandros Tassiulas,et al.  Stability properties of constrained queueing systems and scheduling policies for maximum throughput in multihop radio networks , 1992 .

[26]  Bert Zwart,et al.  Tails in scheduling , 2007, PERV.