| R. Wolff. Poisson arrivals see time averages. Operations Research, 30(2):223--231, 1982. |
....and optimization than measures on lower levels) I) LLC frame blocking probability, P b and (II) LLC frame delay, # . We also give expression for steady state system utilization, U . A. LLC frame blocking probability, P The well known PASTA (Poisson Arrivals See Time Average) property [23] does not hold because of the MMPP arrival process. We can show ( 6] Section 3.2) that P b can be given as b = 1 (8) # is the average arrival rate of LLC frames and is given as and the term is the probability that an LLC frame is accepted to the MS buffer in marking ....
R. W. Wolff. Poisson arrivals see time average. Operations Research, 30:223--231, 1982.
....us assume that probing packets arrive at each link as a Poisson process . Even though this is a crude assumption, our objective here is simply to illustrate that measuring a queueing free RTT can be quite hard in loaded paths. Based on the Poisson Arrivals See Time Averages (PASTA) property [28], the probability that a probing packet will not experience any queueing at a link i is 1 # i , where # i is the fraction of time that the link i is busy, or equivalently, the utilization of link i. Consequently, the probability that a probing packet will not experience any queueing delay at ....
R. Wolff, "Poisson Arrivals See Time Averages," Operations Research, vol. 30, no. 2, pp. 223--231, 1982.
....experience. If and only if we can assume that active monitoring measures the time average of network performance and that the user traffic is Poissonian, then the performance experienced by the users and the actively measured performance will be the same. This well known property is called PASTA [25]. It is known, however, that current Internet traffic exhibits bursty properties and does not generally have Poisson arrivals [19] In that case, an average user experiences worse performance than the time average performance measured by active monitoring. b) Passive measurement is mainly used to ....
....is still assumed to be independent of the sampling process N . Now, consider the case where (V (t) a k (t) depends on N(s) s t for t 0. In this case, if N is Poisson and (t) a k (t) t#0 is jointly ergodic with N , we can verify the following by using the Poisson calculus [11] see also [25]) 0 )#C a k (0 ) N [a k (0 ) where V (0 ) lim 0 V (t) and a k (0 ) lim 0 a k (t) The corresponding estimator is given by (Tn )#C a k (T n n=1 a k (T n . 12) IV. IMPLEMENTATION Since the traffic is not fluid in practice, we have to consider the ....
R.W. Wolff. Poisson arrivals see time averages. Oper. Res., 30 (1982) 223--231.
....the stationary residual time distribution of the typical session duration. In particular this is a regularly varying distribution with infinite mean. Let S have the distribution of the stationary sojourn time of a typical session. Because Poisson arrivals see time averages (PASTA) see [4] [25], this distribution is the same as that of a marked session that, at time 0, enters the stationary system. By the nonpreemptive nature of the service discipline, this marked session will certainly have to wait for the completion of the session currently under service before it can even begin to ....
R.W. Wolff, Poisson arrivals see time averages, Oper. Res. 30 (1982) 223--231.
.... the Multi Class Case Since the arrival rate of calls of each class on each route is Poisson, the blocking probability, Q ij , of a call of class r using route (i; j) is just the fraction of time that there is no wavelength that is free on all hops along route (i; j) see the PASTA theorem in [27]) Thus, we have: ij = lim I fF ij (t) 0g dt (14) where I fF ij ( 0g = 1; if F ij ( 0 0; otherwise (15) As can be seen, the blocking probability is class independent. Next, we focus on the call blocking probabilities in the modified model. The arrival process of calls of class ....
R. W. Wolff. Poisson arrivals see time averages. Operations Research, 30(2):223--231, 1982.
....packets in set1,andset2 constitute 0.5 , 2.4 of the total packets on links out1,andout2 respectively. Although this subset results from a single input port, it will be equivalent to a pure random sampling if the matched packets on the output link are geometrically distributed and independent [11]. We first analyze the distribution of the distance between matched packets in terms of packet counts. We find that it fits a Weibull distribution . Figure 3 shows the Quantile Quantile plot The probability density function of a Weibull distribution is given by ##### 0 7803 7476 2 02 17.00 ....
R. W. Wolff, "Poisson arrivals see time average," Operations Research, vol. 30, pp. 223--231, 1982.
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R. Wolff. Poisson arrivals see time averages. Operations Research, 30(2):223--231, 1982.
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R. Wolff. Poisson arrivals see time averages. Operations Research, 30(2):223--231, 1982.
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R. Wolff, "Poisson arrivals see time averages," Opns. Res., vol. 30, pp. 223--231, 1982.
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R. Wolff, "Poisson arrivals see time averages," Operations Research, vol. 30, pp. 223--231, 1982.
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R. Wolff, "Poisson arrivals see time averages," Opns. Res., vol. 30, pp. 223--231, 1982.
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R. Wolff, "Poisson Arrivals See Time Averages," Operations Research, vol. 30, no. 2, pp. 223--231, 1982.
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R.L. Wolff, Poisson Arrivals See Time Averages, Operations Research 30, 223-231
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Ronald W. Wolff, "Poisson Arrivals See Time Averages", Operrations Research, Vol. 30, No. 2, March-April 1982.
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R. W. Wolff, "Poisson arrivals see time averages", Operations Research 30, pp. 223-231, 1982. 18
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B. Wolff, "Poisson arrivals see time averages," Operational Research, vol. 30, no. 2, pp. 223--231, Apr. 1982.
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R. Wolff, "Poisson Arrivals See Time Averages," Operations Research, 30(2):223--231, 1982.
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R. W. Wolff, "Poisson arrivals see time average," Operations Research, vol. 30, pp. 223--231, 1982.
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R. Wolff, "Poisson arrivals see time averages," Opns. Res., vol. 30, pp. 223--231, 1982.
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R.W. Wolff, (1982), Poisson arrivals see time averages. Operations Research, 30, 223--231.
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R. Wolff, "Poisson arrivals see time averages," Operations Research, vol. 30, no. 2, pp. 223--231, 1982.
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R. W. Wolff, "Poisson arrivals see time averages," Operations Res., vol. 30, no. 2, pp. 223--231, 1982.
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R. W. Wolff, "Poisson arrivals see time average," Operations Research, vol. 30, pp. 223--231, 1982.
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R. W. Wolff, "Poisson Arrivals See Time Average," Operations Research, vol. 30, pp. 223--231, 1982.
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R. Wolff, "Poisson arrivals see time averages," Operations Research, vol. 30, no. 2, pp. 223--231, 1982.
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