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QoS Evaluation of End-to-End Services in Virtualized Computing Environments: A Stochastic Model Approach

QoS Evaluation of End-to-End Services in Virtualized Computing Environments: A Stochastic Model Approach

Guofeng Yan, Yuxing Peng, Shuhong Chen, Pengfei You
Copyright: © 2015 |Volume: 12 |Issue: 1 |Pages: 18
ISSN: 1545-7362|EISSN: 1546-5004|EISBN13: 9781466675711|DOI: 10.4018/IJWSR.2015010103
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MLA

Yan, Guofeng, et al. "QoS Evaluation of End-to-End Services in Virtualized Computing Environments: A Stochastic Model Approach." IJWSR vol.12, no.1 2015: pp.27-44. http://doi.org/10.4018/IJWSR.2015010103

APA

Yan, G., Peng, Y., Chen, S., & You, P. (2015). QoS Evaluation of End-to-End Services in Virtualized Computing Environments: A Stochastic Model Approach. International Journal of Web Services Research (IJWSR), 12(1), 27-44. http://doi.org/10.4018/IJWSR.2015010103

Chicago

Yan, Guofeng, et al. "QoS Evaluation of End-to-End Services in Virtualized Computing Environments: A Stochastic Model Approach," International Journal of Web Services Research (IJWSR) 12, no.1: 27-44. http://doi.org/10.4018/IJWSR.2015010103

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Abstract

Quality of service (QoS) optimization for end-to-end (e2e) services always depends on performance analysis in cloud-based service delivery industry. However, performance analysis of e2e services becomes difficult as the scale and complexity of virtualized computing environments increase. In this paper, the authors present a novel hierarchical stochastic approach to evaluate the QoS of e2e virtualized cloud services using Quasi-Birth Death structures, where jobs arrive according to a stochastic process and request virtual machines (VMs), which are specified in terms of resources, i.e., VM-configuration. To reduce the complexity of performance evaluation, the overall virtualized cloud services are partitioned into three sub-hierarchies. The authors analyze each individual sub-hierarchy using stochastic queueing approach. Thus, the key performance metrics of e2e cloud service QoS, such as acceptance probability and e2e response delay incurred on user requests, are obtained.

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