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Empirical and Analytical Evaluation of Systems with Multiple Unreliable Servers

Authors: Palmer J; Mitrani I;

Empirical and Analytical Evaluation of Systems with Multiple Unreliable Servers

Abstract

We construct, analyze and solve models of systems where a number of servers offer services to an incoming stream of demands. Each server goes through alternating periods of being operative and inoperative. The objective is to evaluate and optimize performance and cost metrics. A large real-life data set containing information about server breakdowns is analyzed first. The results indicate that the durations of the operative periods are not distributed exponentially. However, hyper exponential distributions are found to be a good fit for the observed data. A model based on these distributions is then formulated, and is solved exactly using the method of spectral expansion. A simple approximation which is accurate for heavily loaded systems is also proposed. The results of a number of numerical experiments are reported

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
7
Average
Average
Average
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