Hostname: page-component-586b7cd67f-gb8f7 Total loading time: 0 Render date: 2024-11-23T21:23:24.756Z Has data issue: false hasContentIssue false

A Note on Negative Customers, GI/G/1 Workload, and Risk Processes

Published online by Cambridge University Press:  27 July 2009

Richard J. Boucherie
Affiliation:
Department of Econometrics, University of Amsterdam, Roetersstraat 11, 1018 WB Amsterdam, The Netherlands
Onno J. Boxma
Affiliation:
CWI, P.O. Box 94079, 1090 GB Amsterdam, The Netherlands, Tilburg University, Faculty of Economics, P.O. Box 90153, 5000 LE Tilburg, The Netherlands
Karl Sigman
Affiliation:
Department of Industrial Engineering and Operations Research, Columbia University, 500 West 120th Street, New York, New York, 10027-6699

Abstract

This note illustrates that a combination of the approach in our previous papers (Boucherie and Boxma, 1996, Probability in the Engineering and Informational Sciences10: 261–277; Jain and Sigman, 1996, Probability in the Engineering and Informational Sciences 10: 519–531) directly leads to a Pollaczek-Khintchine form for the workload in a queue with negative customers. The same technique is also applied to risk processes with lump additions.

Type
Research Article
Copyright
Copyright © Cambridge University Press 1997

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

1.Asmussen, S. & Sigman, K. (1996). Monotone stochastic recursions and their duals. Probability in the Engineering and Information Sciences 10: 120.CrossRefGoogle Scholar
2.Boucherie, R.J. & Boxma, O.J. (1996). The workload in the M/G/l queue with work removal. Probability in the Engineering and Informational Sciences 10: 261277.CrossRefGoogle Scholar
3.Cohen, J.W. (1982). The single server queue. Amsterdam: North-Holland.Google Scholar
4.Cramér, H. (1955). Collective risk theory. Reprinted from the Jubilee Volume of Skandia Insurance Company, Esselte, Stockholm.Google Scholar
5.Fakinos, D. (1981). The G/G/l queueing system with a particular queue discipline. Journal of the Royal Statistical Society B 43: 190196.Google Scholar
6.Gelenbe, E. (1991). Product-form queueing networks with negative and positive customers. Journal of Applied Probability 28: 656663.CrossRefGoogle Scholar
7.Gelenbe, E. (1993). G-networks with triggered customer movement. Journal of Applied Probability 30: 742748.CrossRefGoogle Scholar
8.Jain, G. & Sigman, K. (1996). Generalizing the Pollaczek-Khintchine formula to account for arbitrary work removal. Probability in the Engineering and Informational Sciences 10: 519531.CrossRefGoogle Scholar
9.Jain, G. & Sigman, K. (1996). A Pollaczek-Khintchine formulation for M/G/l queues with disasters. Journal of Applied Probability 33: 11911200.CrossRefGoogle Scholar
10.Lukacs, E. (1970). Characteristic functions. London: Charles Griffin.Google Scholar
11.Niu, S.-C. (1988). Representing workloads in GI/G/1 queues through the preemptive-resume L1FO queue discipline. Queueing Systems 3: 157178.CrossRefGoogle Scholar
12.Prabhu, N.U. (1961). On the ruin problem of collective risk theory. Annals of Mathematical Statistics 32: 757764.CrossRefGoogle Scholar
13.Siegmund, D. (1976). The equivalence of absorbing and reflecting barrier problems for stochastically monotone Markov processes. Annals of Probability 4: 914924.CrossRefGoogle Scholar
14.Sigman, K. (1996). Continuous time stochastic recursions and duality. Manuscript.Google Scholar
15.Wolff, R.W. (1989). Stochastic modeling and the theory of queues. Englewood Cliffs, New Jersey: Prentice-Hall.Google Scholar