2,593 research outputs found
BRAVO for many-server QED systems with finite buffers
This paper demonstrates the occurrence of the feature called BRAVO (Balancing
Reduces Asymptotic Variance of Output) for the departure process of a
finite-buffer Markovian many-server system in the QED (Quality and
Efficiency-Driven) heavy-traffic regime. The results are based on evaluating
the limit of a formula for the asymptotic variance of death counts in finite
birth--death processes
The effect of service time variability on maximum queue lengths in M^X/G/1 queues
We study the impact of service-time distributions on the distribution of the
maximum queue length during a busy period for the M^X/G/1 queue. The maximum
queue length is an important random variable to understand when designing the
buffer size for finite buffer (M/G/1/n) systems. We show the somewhat
surprising result that for three variations of the preemptive LCFS discipline,
the maximum queue length during a busy period is smaller when service times are
more variable (in the convex sense).Comment: 12 page
A Queueing Characterization of Information Transmission over Block Fading Rayleigh Channels in the Low SNR
Unlike the AWGN (additive white gaussian noise) channel, fading channels
suffer from random channel gains besides the additive Gaussian noise. As a
result, the instantaneous channel capacity varies randomly along time, which
makes it insufficient to characterize the transmission capability of a fading
channel using data rate only. In this paper, the transmission capability of a
buffer-aided block Rayleigh fading channel is examined by a constant rate input
data stream, and reflected by several parameters such as the average queue
length, stationary queue length distribution, packet delay and overflow
probability. Both infinite-buffer model and finite-buffer model are considered.
Taking advantage of the memoryless property of the service provided by the
channel in each block in the the low SNR (signal-to-noise ratio) regime, the
information transmission over the channel is formulated as a \textit{discrete
time discrete state} queueing problem. The obtained results show that
block fading channels are unable to support a data rate close to their ergodic
capacity, no matter how long the buffer is, even seen from the application
layer. For the finite-buffer model, the overflow probability is derived with
explicit expression, and is shown to decrease exponentially when buffer size is
increased, even when the buffer size is very small.Comment: 29 pages, 11 figures. More details on the proof of Theorem 1 and
proposition 1 can be found in "Queueing analysis for block fading Rayleigh
channels in the low SNR regime ", IEEE WCSP 2013.It has been published by
IEEE Trans. on Veh. Technol. in Feb. 201
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Cell loss dynamics and output process in a finite-buffer discrete-time queue with correlated arrivals
This paper analyzes the performance of an ATM switching node considering cell arrival correlation. An ATM switching node is modeled as a discrete-time finite-buffer queue. Cell arrivals are assumed to follow a semi-Markovian process, where the number of cell arrivals in a lot depends on the states of the underlying (M-state) Markov chain in the current and previous slots. This paper presents analyses for various characteristics of the cell loss, as well as the distribution function of the cell output process from an ATM switching node. Obtained results include the cell loss probability, the consecutive loss probability, the distribution of loss period lengths, the joint distribution of successive cell interdeparture times, and the distribution of busy and idle periods. Through the numerical results, it is shown that both the correlation and the variation of cell arrivals significantly affect the cell loss and the output process characteristics
Throughput and Latency in Finite-Buffer Line Networks
This work investigates the effect of finite buffer sizes on the throughput
capacity and packet delay of line networks with packet erasure links that have
perfect feedback. These performance measures are shown to be linked to the
stationary distribution of an underlying irreducible Markov chain that models
the system exactly. Using simple strategies, bounds on the throughput capacity
are derived. The work then presents two iterative schemes to approximate the
steady-state distribution of node occupancies by decoupling the chain to
smaller queueing blocks. These approximate solutions are used to understand the
effect of buffer sizes on throughput capacity and the distribution of packet
delay. Using the exact modeling for line networks, it is shown that the
throughput capacity is unaltered in the absence of hop-by-hop feedback provided
packet-level network coding is allowed. Finally, using simulations, it is
confirmed that the proposed framework yields accurate estimates of the
throughput capacity and delay distribution and captures the vital trends and
tradeoffs in these networks.Comment: 19 pages, 14 figures, accepted in IEEE Transactions on Information
Theor
Analysis of finite-buffer state-dependent bulk queues
<p>In this paper, we consider a general state-dependent finite-buffer bulk queue in which the rates and batch sizes of arrivals and services are allowed to depend on the number of customers in queue and service batch sizes. Such queueing systems have rich applications in manufacturing, service operations, computer and telecommunication systems. Interesting examples include batch oven processes in the aircraft and semiconductor industry; serving of passengers by elevators, shuttle buses, and ferries; and congestion control mechanisms to regulate transmission rates in packet-switched communication networks. We develop a unifying method to study the performance of this general class of finite-buffer state-dependent bulk queueing systems. For this purpose, we use semi-regenerative analysis to develop a numerically stable method for calculating the limiting probability distribution of the queue length process. Based on the limiting probabilities, we present various performance measures for evaluating admission control and batch service policies, such as the loss probability for an arriving group of customers and for individual customers within a group. We demonstrate our method by means of numerical examples.</p>
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