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On Maxima and Minima of Partial Sums of Strongly Interchangeable Random Variables

Published online by Cambridge University Press:  27 July 2009

Teunis J. Ott
Affiliation:
Belicore Morristown, New Jersey 07960
J. George Shanthikumar
Affiliation:
University of California at Berkeley, Berkeley, California 94720

Abstract

We introduce the concept of “strong interchangeability” of random vectors. Strongly interchangeable random vectors arise naturally in packetized voice channels, M/G/1 queues, symmetric queueing networks, and other standard symmetric distributions. We study some properties of strongly interchangeable random vectors. We show that if (X1, …, XN) is a strongly interchangeable random vector, then even though there is no Markov property, taboo probabilities can be used to compute the joint distribution of ŽN = min1≤nN σnk=IXk and ZN = max1≤nN σnk=1Xk. For a special instance of this problem that arises in packetized voice communication, it is shown that the resulting algorithm essentially has a complexity of order N4. When ( σnk=1Xk, n = 1,… N) is an associated random vector bound for the joint distribution of ŽN and ZN are obtained and applied to the packetized voice communication problem.

Type
Articles
Copyright
Copyright © Cambridge University Press 1990

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References

REFERENCES

Barlow, R.E. & Proschan, F. (1975). Statistical theory of reliability and life testing–Probability models. New York: Holt, Rinehart and Winston.Google Scholar
Block, H., Savits, T. & Shaked, M. (1982). Some concepts of negative dependence. Ann. Prob. 10: 765772.CrossRefGoogle Scholar
Block, H., Savits, T. & Shaked, M. (1985). A concept of negative dependence using stochastic ordering. Statist. Probab. Lett. 3: 8186.CrossRefGoogle Scholar
Efron, B. (1965). Increasing properties of Polya frequency functions. Ann. Math. Stat. 36: 272279.CrossRefGoogle Scholar
Kamae, T., Krengel, U. & O'Brien, G. (1977). Stochastic inequalities on partially ordered spaces. Ann. Prob. 5: 899912.CrossRefGoogle Scholar
Latouche, G. (1989). A study of deterministic cycles in packet queues subject to periodic traffic. Technical report, Université Libre de Bruxelles, Bruxelles, Belgium.Google Scholar
Ott, T.J. & Shanthikumar, J.G. (1989). On a buffer problem for packetized voice with an N-periodic interchangeable input process. Technical report, Bellcore, Morristown, N.J.Google Scholar
Ott, T.J. & Shanthikumar, J.G. (1989). Structural properties and stochastic bounds for a buffer problem in packetized voice transmission. Technical report, Bellcore, Morristown, N.J.Google Scholar
Ramamurthy, G. & Sengupta, B. (1989). Delay analysis of a packet voice multiplexer by the D1/D/l queue. Technical report, AT&T Bell Laboratories.Google Scholar
Shaked, M. & Shanthikumar, J.G. (1988). Parametric stochastic convexity and concavity of stochastic processes. Ann. Inst. Stat. Math. (to appear).Google Scholar
Sriram, K. & Whitt, W. (1986). Characterizing superposition arrival processes in packet multiplexers for voice and data. IEEE J. SAC. 4: 833846.Google Scholar
Tchen, A.H. (1980). Inequalities for distributions with given marginals. Ann. Prob. 8: 814827.CrossRefGoogle Scholar