Sojourn time asymptotics in processor sharing queues

This paper addresses the sojourn time asymptotics for a GI/GI/• queue operating under the Processor Sharing (PS) discipline with stochastically varying service rate. Our focus is on the logarithmic estimates of the tail of sojourn-time distribution, under the assumption that the jobsize distribution has a light tail. Whereas upper bounds on the decay rate can be derived under fairly general conditions, the establishment of the corresponding lower bounds requires that the service process satisfies a samplepath large-deviation principle. We show that the class of allowed service processes includes the case where the service rate is modulated by a Markov process. Finally, we extend our results to a similar system operation under the Discriminatory Processor Sharing (DPS) discipline. Our analysis relies predominantly on large-deviations techniques

Sojourn time tails in the M/D/1 Processor Sharing queue

We consider the sojourn time V in the M/D/1 processor sharing (PS) queue and show that P(V > x) is of the form Ce-[gamma]x as x becomes large. The proof involves a geometric random sum representation of V and a connection with Yule processes, which also enables us to simplify Ott's [21] derivation of the Laplace transform of V. Numerical experiments show that the approximation P(V > x) [approximate] Ce-[gamma]x is excellent even for moderate values of x

Fluid Limits for Bandwidth-Sharing Networks in Overload

Bandwidth-sharing networks as considered by Roberts and Massoulié [28] (Roberts JW, Massoulié L (1998) Bandwidth sharing and admission control for elastic traffic. Proc. ITC Specialist Seminar, Yokohama, Japan) provide a natural modeling framework for describing the dynamic flow-level interaction among elastic data transfers. Under mild assumptions, it has been established that a wide family of so-called a-fair bandwidth-sharing strategies achieve stability in such networks provided that no individual link is overloaded. In the present paper we focus on bandwidth-sharing networks where the load on one or several of the links exceeds the capacity. To characterize the overload behavior, we examine the fluid limit, which emerges when the flow dynamics are scaled in both space and time. We derive a functional equation characterizing the fluid limit, and show that any strictly positive solution must be unique, which in particular implies the convergence of the scaled number of flows to the fluid limit for nonzero initial states when the load is sufficiently high. For the case of a zero initial state and a zero-degree homogeneous rate allocation function, we show that there exists a linear solution to the fluid-limit equation, and obtain a fixed-point equation for the corresponding asymptotic growth rates. It is proved that a fixed-point solution is also a solution to a related strictly concave optimization problem, and hence exists and is unique. In addition, we establish uniqueness of fluid-model solutions for monotone rate-preserving networks (in particular tree networks)