December 2012 A strong law for the rate of growth of long latency periods in a cloud computing service
Souvik Ghosh, Soumyadip Ghosh
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Adv. in Appl. Probab. 44(4): 995-1017 (December 2012). DOI: 10.1239/aap/1354716587


Cloud-computing shares a common pool of resources across customers at a scale that is orders of magnitude larger than traditional multiuser systems. Constituent physical compute servers are allocated multiple `virtual machines' (VMs) to serve simultaneously. Each VM user should ideally be unaffected by others' demand. Naturally, this environment produces new challenges for the service providers in meeting customer expectations while extracting an efficient utilization from server resources. We study a new cloud service metric that measures prolonged latency or delay suffered by customers. We model the workload process of a cloud server and analyze the process as the customer population grows. The capacity required to ensure that the average workload does not exceed a threshold over long segments is characterized. This can be used by cloud operators to provide service guarantees on avoiding long durations of latency. As part of the analysis, we provide a uniform large deviation principle for collections of random variables that is of independent interest.


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Souvik Ghosh. Soumyadip Ghosh. "A strong law for the rate of growth of long latency periods in a cloud computing service." Adv. in Appl. Probab. 44 (4) 995 - 1017, December 2012.


Published: December 2012
First available in Project Euclid: 5 December 2012

zbMATH: 1260.60053
MathSciNet: MR3052847
Digital Object Identifier: 10.1239/aap/1354716587

Primary: 60F10
Secondary: 60F15 , 60G99

Keywords: Cloud computing , large deviations , latency period , long strange segment , moving average , nonstationary process

Rights: Copyright © 2012 Applied Probability Trust


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Vol.44 • No. 4 • December 2012
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