Hostname: page-component-8448b6f56d-xtgtn Total loading time: 0 Render date: 2024-04-23T12:22:19.373Z Has data issue: false hasContentIssue false

REDIALING POLICIES: OPTIMALITY AND SUCCESS PROBABILITIES

Published online by Cambridge University Press:  01 January 1999

E. G. Coffman
Affiliation:
Bell Labs, Lucent Technologies, Murray Hill, New Jersey 07974
E. N. Gilbert
Affiliation:
Bell Labs, Lucent Technologies, Murray Hill, New Jersey 07974
Y. A. Kogan
Affiliation:
AT&T Labs, Holmdel, New Jersey 07733

Abstract

Since callers encountering busy signals often want to redial, modern communication networks have been designed to provide automatic redialing. Redialing services commonly have two parameters: a maximum number n of retries and a total duration τ over which retries are to be made. Typically, retries are made at evenly spaced time intervals of length τ/n until either the call succeeds or n retries have failed. This rule has an obvious intuitive appeal; indeed, among the main results of this paper are proofs that τ/n-spacing is optimal in certain basic models of called-number behavior. However, it is easy to find situations where τ/n-spacing is not optimal, as the paper verifies.

All of our models assume Poisson arrivals, but different assumptions are studied for the call durations; for a given mean, these are allowed to have the relatively high-variance exponential distribution or the zero-variance distribution concentrated at a point. We approximate the probability of success for the Erlang loss model with c > 1 trunks, and we calculate exact probabilities of success for the c = 1 Erlang model and the model with one trunk and constant call durations. For the latter model, we present two intriguing conjectures, one about the optimal choice of τ when n = 1 and one about the optimality of the τ/n-spacing policy. In spite of their apparent simplicity, these conjectures seem difficult to resolve. Finally, we study policies that continue redialing until they succeed, balancing a short mean wait against a small mean number of retries to success.

Type
Research Article
Copyright
© 1999 Cambridge University Press

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.)