399 research outputs found
GPS queues with heterogeneous traffic classes
We consider a queue fed by a mixture of light-tailed and heavy-tailed traffic. The two traffic classes are served in accordance with the generalized processor sharing (GPS) discipline. GPS-based scheduling algorithms, such as weighted fair queueing (WFQ), have emerged as an important mechanism for achieving service differentiation in integrated networks. We derive the asymptotic workload behavior of the light-tailed class for the situation where its GPS weight is larger than its traffic intensity. The GPS mechanism ensures that the workload is bounded above by that in an isolated system with the light-tailed class served in isolation at a constant rate equal to its GPS weight. We show that the workload distribution is in fact asymptotically equivalent to that in the isolated system, multiplied with a certain pre-factor, which accounts for the interaction with the heavy-tailed class. Specifically, the pre-factor represents the probability that the heavy-tailed class is backlogged long enough for the light-tailed class to reach overflow. The results provide crucial qualitative insight in the typical overflow scenario
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
Queueing Systems with Heavy Tails
VI+227hlm.;24c
Sample-path large deviations for tandem and priority queues with Gaussian inputs
This paper considers Gaussian flows multiplexed in a queueing network. A
single node being a useful but often incomplete setting, we examine more
advanced models. We focus on a (two-node) tandem queue, fed by a large number
of Gaussian inputs. With service rates and buffer sizes at both nodes scaled
appropriately, Schilder's sample-path large-deviations theorem can be applied
to calculate the asymptotics of the overflow probability of the second queue.
More specifically, we derive a lower bound on the exponential decay rate of
this overflow probability and present an explicit condition for the lower bound
to match the exact decay rate. Examples show that this condition holds for a
broad range of frequently used Gaussian inputs. The last part of the paper
concentrates on a model for a single node, equipped with a priority scheduling
policy. We show that the analysis of the tandem queue directly carries over to
this priority queueing system.Comment: Published at http://dx.doi.org/10.1214/105051605000000133 in the
Annals of Applied Probability (http://www.imstat.org/aap/) by the Institute
of Mathematical Statistics (http://www.imstat.org
Concave Switching in Single and Multihop Networks
Switched queueing networks model wireless networks, input queued switches and
numerous other networked communications systems. For single-hop networks, we
consider a {()-switch policy} which combines the MaxWeight policies
with bandwidth sharing networks -- a further well studied model of Internet
congestion. We prove the maximum stability property for this class of
randomized policies. Thus these policies have the same first order behavior as
the MaxWeight policies. However, for multihop networks some of these
generalized polices address a number of critical weakness of the
MaxWeight/BackPressure policies.
For multihop networks with fixed routing, we consider the Proportional
Scheduler (or (1,log)-policy). In this setting, the BackPressure policy is
maximum stable, but must maintain a queue for every route-destination, which
typically grows rapidly with a network's size. However, this proportionally
fair policy only needs to maintain a queue for each outgoing link, which is
typically bounded in number. As is common with Internet routing, by maintaining
per-link queueing each node only needs to know the next hop for each packet and
not its entire route. Further, in contrast to BackPressure, the Proportional
Scheduler does not compare downstream queue lengths to determine weights, only
local link information is required. This leads to greater potential for
decomposed implementations of the policy. Through a reduction argument and an
entropy argument, we demonstrate that, whilst maintaining substantially less
queueing overhead, the Proportional Scheduler achieves maximum throughput
stability.Comment: 28 page
Self-similar traffic and network dynamics
Copyright © 2002 IEEEOne of the most significant findings of traffic measurement studies over the last decade has been the observed self-similarity in packet network traffic. Subsequent research has focused on the origins of this self-similarity, and the network engineering significance of this phenomenon. This paper reviews what is currently known about network traffic self-similarity and its significance. We then consider a matter of current research, namely, the manner in which network dynamics (specifically, the dynamics of transmission control protocol (TCP), the predominant transport protocol used in today's Internet) can affect the observed self-similarity. To this end, we first discuss some of the pitfalls associated with applying traditional performance evaluation techniques to highly-interacting, large-scale networks such as the Internet. We then present one promising approach based on chaotic maps to capture and model the dynamics of TCP-type feedback control in such networks. Not only can appropriately chosen chaotic map models capture a range of realistic source characteristics, but by coupling these to network state equations, one can study the effects of network dynamics on the observed scaling behavior. We consider several aspects of TCP feedback, and illustrate by examples that while TCP-type feedback can modify the self-similar scaling behavior of network traffic, it neither generates it nor eliminates it.Ashok Erramilli, Matthew Roughan, Darryl Veitch and Walter Willinge
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