159 research outputs found
Diffusion approximation for a processor sharing queue in heavy traffic
Consider a single server queue with renewal arrivals and i.i.d. service times
in which the server operates under a processor sharing service discipline. To
describe the evolution of this system, we use a measure valued process that
keeps track of the residual service times of all jobs in the system at any
given time. From this measure valued process, one can recover the traditional
performance processes, including queue length and workload. We show that under
mild assumptions, including standard heavy traffic assumptions, the (suitably
rescaled) measure valued processes corresponding to a sequence of processor
sharing queues converge in distribution to a measure valued diffusion process.
The limiting process is characterized as the image under an appropriate lifting
map, of a one-dimensional reflected Brownian motion. As an immediate
consequence, one obtains a diffusion approximation for the queue length process
of a processor sharing queue
Heavy traffic limit for a processor sharing queue with soft deadlines
This paper considers a GI/GI/1 processor sharing queue in which jobs have
soft deadlines. At each point in time, the collection of residual service times
and deadlines is modeled using a random counting measure on the right
half-plane. The limit of this measure valued process is obtained under
diffusion scaling and heavy traffic conditions and is characterized as a
deterministic function of the limiting queue length process. As special cases,
one obtains diffusion approximations for the lead time profile and the profile
of times in queue. One also obtains a snapshot principle for sojourn times.Comment: Published at http://dx.doi.org/10.1214/105051607000000014 in the
Annals of Applied Probability (http://www.imstat.org/aap/) by the Institute
of Mathematical Statistics (http://www.imstat.org
Invariance of fluid limits for the Shortest Remaining Processing Time and Shortest Job First policies
We consider a single-server queue with renewal arrivals and i.i.d. service
times, in which the server employs either the preemptive Shortest Remaining
Processing Time (SRPT) policy, or its non-preemptive variant, Shortest Job
First (SJF). We show that for given stochastic primitives (initial condition,
arrival and service processes), the model has the same fluid limit under either
policy. In particular, we conclude that the well-known queue length optimality
of preemptive SRPT is also achieved, asymptotically on fluid scale, by the
simpler-to-implement SJF policy. We also conclude that on fluid scale, SJF and
SRPT achieve the same performance with respect to response times of the
longest-waiting jobs in the system.Comment: 24 page
Heavy Traffic Limit for a Tandem Queue with Identical Service Times
We consider a two-node tandem queueing network in which the upstream queue is
M/G/1 and each job reuses its upstream service requirement when moving to the
downstream queue. Both servers employ the first-in-first-out policy. We
investigate the amount of work in the second queue at certain embedded arrival
time points, namely when the upstream queue has just emptied. We focus on the
case of infinite-variance service times and obtain a heavy traffic process
limit for the embedded Markov chain
Diffusion limits for shortest remaining processing time queues
We present a heavy traffic analysis for a single server queue with renewal
arrivals and generally distributed i.i.d. service times, in which the server
employs the Shortest Remaining Processing Time (SRPT) policy. Under typical
heavy traffic assumptions, we prove a diffusion limit theorem for a
measure-valued state descriptor, from which we conclude a similar theorem for
the queue length process. These results allow us to make some observations on
the queue length optimality of SRPT. In particular, they provide the sharpest
illustration of the well-known tension between queue length optimality and
quality of service for this policy.Comment: 19 pages; revised, fixed typos. To appear in Stochastic System
Critical fluid limit of a gated processor sharing queue
We consider a sequence of single-server queueing models operating under a
service policy that incorporates batches into processor sharing: arriving jobs
build up behind a gate while waiting to begin service, while jobs in front of
the gate are served according to processor sharing. When they have been
completed, the waiting jobs move in front of the gate and the cycle repeats. We
model this system with a pair of measure valued processes describing the jobs
in front of and behind the gate. Under mild asymptotically critical conditions
and a law-of-large-numbers scaling, we prove that the pair of measure-valued
processes converges in distribution to an easily described limit, which has an
interesting periodic dynamics
Clifford algebras and new singular Riemannian foliations in spheres
Using representations of Clifford algebras we construct indecomposable
singular Riemannian foliations on round spheres, most of which are
non-homogeneous. This generalizes the construction of non-homogeneous
isoparametric hypersurfaces due to by Ferus, Karcher and Munzner.Comment: 21 pages. Construction of foliations in the Cayley plane added.
Proofs simplified and presentation improved, according to referee's
suggestions. To appear in Geom. Funct. Ana
Fluid limits for networks with bandwidth sharing and general document size distributions
We consider a stochastic model of Internet congestion control, introduced by
Massouli\'{e} and Roberts [Telecommunication Systems 15 (2000) 185--201], that
represents the randomly varying number of flows in a network where bandwidth is
shared among document transfers. In contrast to an earlier work by Kelly and
Williams [Ann. Appl. Probab. 14 (2004) 1055--1083], the present paper allows
interarrival times and document sizes to be generally distributed, rather than
exponentially distributed. Furthermore, we allow a fairly general class of
bandwidth sharing policies that includes the weighted -fair policies of
Mo and Walrand [IEEE/ACM Transactions on Networking 8 (2000) 556--567], as well
as certain other utility based scheduling policies. To describe the evolution
of the system, measure valued processes are used to keep track of the residual
document sizes of all flows through the network. We propose a fluid model (or
formal functional law of large numbers approximation) associated with the
stochastic flow level model. Under mild conditions, we show that the
appropriately rescaled measure valued processes corresponding to a sequence of
such models (with fixed network structure) are tight, and that any weak limit
point of the sequence is almost surely a fluid model solution. For the special
case of weighted -fair policies, we also characterize the invariant
states of the fluid model.Comment: Published in at http://dx.doi.org/10.1214/08-AAP541 the Annals of
Applied Probability (http://www.imstat.org/aap/) by the Institute of
Mathematical Statistics (http://www.imstat.org
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