Bert Zwart

Exact asymptotics for fluid queues fed by multiple heavy-tailed on–off flows

We consider a fluid queue fed by multiple On–Off flows with heavy-tailed (regularly varying) On periods. Under fairly mild assumptions, we prove that the workload distribution is asymptotically equivalent to that in a reduced system. The reduced system consists of a “dominant” subset of the flows, with the original service rate subtracted by the mean rate of the other flows. We describe how a dominant set may be determined from a simple knapsack formulation. The dominant set consists of a “minimally critical” set of On–Off flows with regularly varying On periods. In case the dominant set contains just a single On–Off flow, the exact asymptotics for the reduced system follow from known results. For the case of several On–Off flows, we exploit a powerful intuitive argument to obtain the exact asymptotics. Combined with the reduced-load equivalence, the results for the reduced system provide a characterization of the tail of the workload distribution for a wide range of traffic scenarios.

Tail asymptotics for discriminatory processor-sharing queues with heavy-tailed service requirements

We derive the sojourn time asymptotics for a multi-class GI/GI/1 queue with regularly varying service requirements operating under the discriminatory processor-sharing (DPS) discipline. DPS provides a natural approach for modelling the flow-level performance of differentiated bandwidth-sharing mechanisms. Under certain assumptions, we prove that the service requirement and sojourn time of a given class have similar tail behaviour, independent of the specific values of the DPS weights. As a by-product, we obtain an extension of the tail equivalence for ordinary processor-sharing (PS) queues to non-Poisson arrivals. The results suggest that DPS offers a potential instrument for effectuating preferential treatment to high-priority classes, without inflicting excessive delays on low-priority classes. To obtain the asymptotics, we develop a novel method which only involves information of the workload process and does not require any knowledge of the steady-state queue length distribution. In particular, the proof method brings sufficient strength to extend the results to scenarios with a time-varying service capacity.

Fluid Queues with Heavy-Tailed M/G/∞ Input

We consider a fluid queue fed by several heterogeneous M/G/∞ input processes with regularly varying session lengths. Under fairly mild assumptions, we derive the exact asymptotic behavior of the stationary workload distribution. In addition, we obtain several asymptotic results for the transient workload distribution, which are applied to obtain a conditional limit theorem for the most probable time to overflow. The results are strongly inspired by the large-deviations idea that overflow is typically due to some minimal combination of extremely long concurrent sessions causing positive drift. The typical configuration of long sessions is identified through a simple integer program, paving the way for the exact computation of the asymptotic workload behavior. The calculations provide crucial insight in the typical overflow scenario.

Optimal File Splitting for Wireless Networks with Concurrent Access

The fundamental limits on channel capacity form a barrier to the sustained growth on the use of wireless networks. To cope with this, multi-path communication solutions provide a promising means to improve reliability and boost Quality of Service (QoS) in areas that are covered by a multitude of wireless access networks. Today, little is known about how to effectively exploit this potential. Motivated by this, we consider N parallel communication networks, each of which is modeled as a processor sharing (PS) queue that handles two types of traffic: foreground and background. We consider a foreground traffic stream of files, each of which is split into N fragments according to a fixed splitting rule (*** 1 ,...,*** N ), where *** *** i = 1 and *** i *** 0 is the fraction of the file that is directed to network i . Upon completion of transmission of all fragments of a file, it is re-assembled at the receiving end. The background streams use dedicated networks without being split. We study the sojourn time tail behavior of the foreground traffic. For the case of light foreground traffic and regularly varying foreground file-size distributions, we obtain a reduced-load approximation (RLA) for the sojourn times, similar to that of a single PS-queue. An important implication of the RLA is that the tail-optimal splitting rule is simply to choose *** i proportional to c i *** ρ i , where c i is the capacity of network i and ρ i is the load offered to network i by the corresponding background stream. This result provides a theoretical foundation for the effectiveness of such a simple splitting rule. Extensive simulations demonstrate that this simple rule indeed performs well, not only with respect to the tail asymptotics, but also with respect to the mean sojourn times. The simulations further support our conjecture that the same splitting rule is also tail-optimal for non-light foreground traffic. Finally, we observe near-insensitivity of the mean sojourn times with respect to the file-size distribution.

Exact queueing asymptotics for multiple heavy-tailed on-off flows

We consider a fluid queue fed by multiple on-off flows with heavy-tailed (regularly varying) on-periods. Under fairly mild assumptions, we prove that the workload distribution is asymptotically equivalent to that in a reduced system. The reduced system consists of a dominant subset of the flows, with the original service rate subtracted by the mean rate of the other flows. We describe how a dominant set may be determined from a simple knapsack formulation. We exploit a powerful intuitive argument to obtain the exact asymptotics for the reduced system. Combined with the reduced-load equivalence, the results for the reduced system provide an asymptotic characterization of the buffer behavior.

A TANDEM FLUID QUEUE WITH GRADUAL INPUT

For a two-node tandem fluid model with gradual input, we compute the joint steady-state buffer-content distribution. Our proof exploits martingale methods developed by Kella \& Whitt. For the case of finite buffers, we use an insightful sample-path argument to find a proportionality result.

Fluid models for many-server Markovian queues in a changing environment.

Abstract Motivated by service systems with time-varying customer arrivals, we consider a fluid model as a macroscopic approximation for many-server Markovian queues alternating between underloaded and overloaded intervals. Our main result is a refinement of the piecewise stationary approximation (PSA) for the stationary distribution of the fluid model. The form of the refined approximation suggests simple metrics for assessing the accuracy of PSA for underloaded and overloaded intervals respectively.

Reduced-load equivalence for Gaussian processes

We consider a fluid model fed by two Gaussian processes. We obtain necessary and sufficient conditions for the workload asymptotics to be completely determined by one of the two processes, and apply these results to the case of two fractional Brownian motions.

First-passage time asymptotics over moving boundaries for random walk bridges

textabstractWe study the asymptotic tail behavior of the first-passage time over a moving boundary for a random walk conditioned to return to zero, where the increments of the random walk have finite variance. Typically, the asymptotic tail behavior may be described through a regularly varying function with exponent -1/2, where the impact of the boundary is captured by the slowly varying function. Yet, the moving boundary may have a stronger effect when the tail is considered at a time close to the return point of the random walk bridge, leading to a possible phase transition depending on the order of the distance between zero and the moving boundary.

Fluid flow models in performance analysis

We review several developments in fluid flow models: feedback fluid models, linear stochastic fluid networks and bandwidth sharing networks. We also mention some promising new research directions.