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63
Fitting Mixtures Of Exponentials To LongTail Distributions To Analyze Network Performance Models
, 1997
"... Traffic measurements from communication networks have shown that many quantities characterizing network performance have longtail probability distributions, i.e., with tails that decay more slowly than exponentially. File lengths, call holding times, scene lengths in MPEG video streams, and interva ..."
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Cited by 142 (13 self)
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Traffic measurements from communication networks have shown that many quantities characterizing network performance have longtail probability distributions, i.e., with tails that decay more slowly than exponentially. File lengths, call holding times, scene lengths in MPEG video streams, and intervals between connection requests in Internet traffic all have been found to have longtail distributions, being well described by distributions such as the Pareto and Weibull. It is known that longtail distributions can have a dramatic effect upon performance, e.g., longtail servicetime distributions cause longtail waitingtime distributions in queues, but it is often difficult to describe this effect in detail, because performance models with component longtail distributions tend to be difficult to analyze. We address this problem by developing an algorithm for approximating a longtail distribution by a hyperexponential distribution (a finite mixture of exponentials). We first prove tha...
Large Deviations, the Shape of the Loss Curve, and Economies of Scale in Large Multiplexers
, 1995
"... We analyse the queue Q L at a multiplexer with L inputs. We obtain a large deviation result, namely that under very general conditions lim L!1 L \Gamma1 log P[Q L ? Lb] = \GammaI (b) provided the offered load is held constant, where the shape function I is expressed in terms of the cumulant ..."
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Cited by 115 (11 self)
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We analyse the queue Q L at a multiplexer with L inputs. We obtain a large deviation result, namely that under very general conditions lim L!1 L \Gamma1 log P[Q L ? Lb] = \GammaI (b) provided the offered load is held constant, where the shape function I is expressed in terms of the cumulant generating functions of the input traffic. This provides an improvement on the usual effective bandwidth approximation P[Q L ? b] e \Gammaffib , replacing it with P[Q L ? b] e \GammaLI(b=L) . The difference I(b) \Gamma ffi b determines the economies of scale which are to be obtained in large multiplexers. If the limit = \Gamma lim t!1 t t (ffi) exists (here t is the finite time cumulant of the workload process) then lim b!1 (I(b) \Gamma ffi b) = . We apply this idea to a number of examples of arrivals processes: heterogeneous superpositions, Gaussian processes, Markovian additive processes and Poisson processes. We obtain expressions for in these cases. is zero for independent arrivals, but positive for arrivals with positive correlations. Thus economies of scale are obtainable for highly bursty traffic expected in ATM multiplexing.
Admission Control for Statistical QoS: Theory and Practice
, 1999
"... In networks that support Quality of Service (QoS), an admission control algorithm determines whether or not a new traffic flow can be admitted to the network such that all users will receive their required performance. Such an algorithm is a key component of future multiservice networks as it deter ..."
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Cited by 105 (12 self)
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In networks that support Quality of Service (QoS), an admission control algorithm determines whether or not a new traffic flow can be admitted to the network such that all users will receive their required performance. Such an algorithm is a key component of future multiservice networks as it determines the extent to which network resources are utilized and whether the promised QoS parameters are actually delivered. Our goals in this paper are threefold. First, we describe and classify a broad set of proposed admission control algorithms. Second, we evaluate the accuracy of these algorithms via experiments using both onoff sources and long traces of compressed video; we compare the admissible regions and QoS parameters predicted by our implementations of the algorithms with those obtained from tracedriven simulations. Finally, we identify the key aspects of an admission control algorithm necessary for achieving a high degree of accuracy and hence a high statistical multiplexing gain...
Decoupling bandwidths for networks: A decomposition approach to resource management for networks
 In Proceedings of INFOCOM’94, IEEE
, 1994
"... We consider large buffer asymptotics for feedforward networks of discretetime queues with deterministic service rate shared by multiple classes of streams subject to work conserving service policies. First we review the concept of effective bandwidths for traffic streams sharing a common buffer su ..."
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Cited by 57 (3 self)
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We consider large buffer asymptotics for feedforward networks of discretetime queues with deterministic service rate shared by multiple classes of streams subject to work conserving service policies. First we review the concept of effective bandwidths for traffic streams sharing a common buffer subject to subject to tail constraints on the workload distribution. Next, we obtain the effective bandwidth of the departure process from such a queue, proving that in fact the effective bandwidth of the output is at worst equal to that of the input, and depending on the service rate, strictly less than that of the input. We then define the notion of a decoupling bandwidth and the associated constraints, guaranteeing that asymptotics within the network are decoupled. These results provide a framework for call admission schemes which are sensitive to constraints on the tail distribution of the workload or approximate cell loss probabilities. Our results require relatively weak assumptions on both the traffic streams and service policies. We consider the problem of “optimal ” traffic shaping (via buffering) subject to a loss constraint. Finally, we discuss our results in the context of resource management for ATM networks. 1
Waitingtime tail probabilities in queues with longtail servicetime distributions
 QUEUEING SYSTEMS
, 1994
"... We consider the standard GI/G/1 queue with unlimited waiting room and the firstin firstout service discipline. We investigate the steadystate waitingtime tail probabilities P(W> x) when the servicetime distribution has a longtail distribution, i.e., when the servicetime distribution fails to ..."
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Cited by 55 (21 self)
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We consider the standard GI/G/1 queue with unlimited waiting room and the firstin firstout service discipline. We investigate the steadystate waitingtime tail probabilities P(W> x) when the servicetime distribution has a longtail distribution, i.e., when the servicetime distribution fails to have a finite moment generating function. We have developed algorithms for computing the waitingtime distribution by Laplace transform inversion when the Laplace transforms of the interarrivaltime and servicetime distributions are known. One algorithm, exploiting Pollaczek’s classical contourintegral representation of the Laplace transform, does not require that either of these transforms be rational. To facilitate such calculations, we introduce a convenient twoparameter family of longtail distributions on the positive half line with explicit Laplace transforms. This family is a Pareto mixture of exponential (PME) distributions. These PME distributions have monotone densities and Paretolike tails, i.e., are of order x − r for r> 1. We use this family of longtail distributions to investigate the quality of approximations based on asymptotics for P(W> x) as x → ∞. We show that the asymptotic approximations with these longtail servicetime distributions can be remarkably inaccurate for typical x values of interest. We also derive multiterm asymptotic expansions for the waitingtime tail probabilities in the M/G/1 queue. Even three terms of this expansion can be remarkably inaccurate for typical x values of interest. Thus, we evidently must rely on numerical algorithms for determining the waitingtime tail probabilities in this case. When working with servicetime data, we suggest using empirical Laplace transforms.
Buffer Overflow Asymptotics For A Buffer Handling Many Traffic Sources
 Journal of Applied Probability
, 1995
"... As a model for an ATM switch we consider the overflow frequency of a queue that is served at a constant rate and in which the arrival process is the superposition of N traffic streams. We consider an asymptotic as N !1 in which the service rate Nc and buffer size Nb also increase linearly in N . In ..."
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Cited by 54 (0 self)
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As a model for an ATM switch we consider the overflow frequency of a queue that is served at a constant rate and in which the arrival process is the superposition of N traffic streams. We consider an asymptotic as N !1 in which the service rate Nc and buffer size Nb also increase linearly in N . In this regime, the frequency of buffer overflow is approximately exp(\GammaN I(c; b)), where I(c; b) is given by the solution to an optimization problem posed in terms of timedependent logarithmic moment generating functions. Experimental results for Gaussian and Markov modulated fluid source models show that this asymptotic provides a better estimate of the frequency of buffer overflow than ones based on large buffer asymptotics. ATM SWITCHES; BUFFER OVERFLOW ASYMPTOTICS; EFFECTIVE BANDWIDTHS; LARGE DEVIATIONS; MARKOV MODULATED FLUID AMS 1991 SUBJECT CLASSIFICATION: PRIMARY 60K30, SECONDARY 60F10, 60K25, 68M20, 90B10, 90B22 1. Switches handling many bursty sources In a high speed data com...
A Network Calculus with Effective Bandwidth
, 2003
"... We present a statistical network calculus in a setting where both arrivals and service are specified interms of probabilistic bounds. We provide explicit bounds on delay, backlog, and output burstiness in a network. By formulating wellknown effective bandwidth expressions in terms of envelope func ..."
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Cited by 40 (11 self)
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We present a statistical network calculus in a setting where both arrivals and service are specified interms of probabilistic bounds. We provide explicit bounds on delay, backlog, and output burstiness in a network. By formulating wellknown effective bandwidth expressions in terms of envelope functions,we are able to apply our calculus to a wide range of traffic source models, including Fractional Brownian Motion. We present probabilistic lower bounds on the service for three scheduling algorithms: Static Priority (SP), Earliest Deadline First (EDF), and Generalized Processor Sharing (GPS).
Economies of Scale in Queues With Sources Having PowerLaw Large Deviation Scalings.
, 1995
"... We analyse the queue Q L at a multiplexer with L sources which may display longrange dependence. This includes, for example, sources modelled by fractional Brownian Motion (fBM). The workload processes W due to each source are assumed to have large deviation properties of the form P [W t =a(t) ? ..."
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Cited by 39 (10 self)
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We analyse the queue Q L at a multiplexer with L sources which may display longrange dependence. This includes, for example, sources modelled by fractional Brownian Motion (fBM). The workload processes W due to each source are assumed to have large deviation properties of the form P [W t =a(t) ? x] ß e \Gammav(t)K(x) for appropriate scaling functions a and v, and ratefunction K. Under very general conditions, lim L!1 L \Gamma1 log P [Q L ? Lb] = \GammaI (b) provided the offered load is held constant, where the shape function I is expressed in terms of the cumulant generating functions of the input traffic. For powerlaw scalings v(t) = t v , a(t) = t a (such as occur in fBM) we analyse the asymptotics of the shape function: lim b!1 b \Gammau=a i I(b) \Gamma ffi b v=a j = u for some exponent u and constant depending on the sources. This demonstrates the economies of scale available through the multiplexing of a large number of such sources, by comparison with ...
A Poisson Limit for Buffer Overflow Probabilities
 in Proceedings of IEEE INFOCOM
, 2002
"... Abstract — A key criterion in the design of highspeed networks is the probability that the buffer content exceeds a given threshold. We consider Ò independent identical traffic sources modelled as point processes, which are fed into a link with speed proportional to Ò. Under fairly general assumpti ..."
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Cited by 39 (1 self)
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Abstract — A key criterion in the design of highspeed networks is the probability that the buffer content exceeds a given threshold. We consider Ò independent identical traffic sources modelled as point processes, which are fed into a link with speed proportional to Ò. Under fairly general assumptions on the input processes we show that the steady state probability of the buffer content exceeding a threshold � � tends to the corresponding probability assuming Poisson input processes. We verify the assumptions for a large class of longrange dependent sources commonly used to model data traffic. Our results show that with superposition, significant multiplexing gains can be achieved for even smaller buffers than suggested by previous results, which consider Ç Ò buffer size. Moreover, simulations show that for realistic values of the exceedance probability and moderate utilisations, convergence to the Poisson limit takes place at reasonable values of the number of sources superposed. This is particularly relevant for highspeed networks in which the cost of highspeed memory is significant. Keywords—Longrange dependence, overflow probability, Poisson limit, heavy tails, point processes, multiplexing.