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MONOTONICITY RESULTS FOR SINGLE-SERVER FINITE-CAPACITY QUEUES WITH RESPECT TO DIRECTIONALLY CONVEX ORDER

Published online by Cambridge University Press:  01 July 2004

Shigeo Shioda
Affiliation:
Urban Environment Systems, Faculty of Engineering, Chiba University, 1-33 Yayoi, Inage, Chiba 263-8522, Japan, E-mail: shioda@faculty.chiba-u.jp
Daisuke Ishii
Affiliation:
Urban Environment Systems, Faculty of Engineering, Chiba University, 1-33 Yayoi, Inage, Chiba 263-8522, Japan, E-mail: shioda@faculty.chiba-u.jp

Abstract

In this article, we investigate single-server finite-capacity queues where the partial acceptance rule is applied. In particular, we focus on the monotonicity of the amount of lost (processed) work in the queues with respect to the directionally convex order of work or interarrival processes. We first compare the queues that differ only in their work processes and show that if the work processes are directionally convex ordered, so is the amount of work lost (or processed) in the systems. Next, we compare the queues that differ only in their interarrival processes and show that if the interarrival processes are directionally convex ordered, so is the amount of work lost (or processed) in the systems. Using these results, we establish the formula that gives the upper bound of work-loss probability based only on the marginal distributions of work and interarrival processes. Numerical experiments using the data of actual-LAN (local area network) traffic show that the derived formula gives tight bounds sufficient for practical use.

Type
Research Article
Copyright
© 2004 Cambridge University Press

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References

REFERENCES

Chang, C.S., Chao, X.L., & Pinedo, M. (1991). Monotonicity results for queues with doubly stochastic Poisson arrivals: Ross's conjecture. Advances in Applied Probability 23: 210228.Google Scholar
Chang, C.S., Chao, X.L., Pinedo, M., & Shanthikumar, J.G. (1991). Stochastic convexity for multidimensional processes and its applications. IEEE Transactions on Automatic Controls 36: 13451355.Google Scholar
Gani, J. & Prabu, N.U. (1957). Continuous time treatment of a storage problem. Nature 182: 3940.Google Scholar
Gani, J. & Prabu, N.U. (1958). Remarks on the dam with Poisson type inputs. Australian Journal of Applied Science 10: 113122.Google Scholar
Leland, W.E., Taqqu, M.S., Willinger, W., & Wilson, D.V. (1994). On the self-similar nature of Ethernet traffic. IEEE/ACM Transactions on Networking 2(1): 115.Google Scholar
Jean-Marie, A. & Liu, Z. (1992). Stochastic comparison for queueing models via random sums and intervals. Advances in Applied Probability 24: 960985.Google Scholar
Meester, L.E. & Shanthikumar, J.G. (1993). Regularity of stochastic processes. Probability in the Engineering and Informational Sciences 7: 343360.Google Scholar
Miyazawa, M. & Shanthikumar, J.G. (1991). Monotonicity of the loss probabilities of single server finite queues with respect to convex order of arrival or service processes. Probability in the Engineering and Informational Sciences 5: 4352.Google Scholar
Shaked, M. & Shanthikumar, J.G. (1994) Stochastic orders and their applications. San Diego, CA: Academic Press.
Shanthikumar, J.G. (1994). Convexity of single stage queueing systems with bulk arrivals. Queueing Systems 16: 287299.Google Scholar
Stoyan, D. (1983). Comparison methods for queues and other stochastic models. New York: Wiley.
Takács, L. (1974). A single-server queue with limited virtual waiting time. Journal of Applied Probability 11: 612617.Google Scholar
Takada, H. (2001). Markov modulated fluid queues with batch fluid arrivals. Journal of Operations Research Society of Japan 44(4): 344365.Google Scholar
Takada, H., & Miyazawa M. (2001). A Markov modulated fluid queue with batch arrivals and preemption. IEICE Technical Report IN-2001-25, pp. 916. Tokyo: Institute of Electronics, Information, and Communication Engineers.
Toyoizumi, H., Shanthikumar, J.G., & Wolff, R.W. (1997). Two extremal autocorrelated arrival processes. Probability in the Engineering and Informational Sciences 11: 441450.Google Scholar