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Performance Analysis of Heterogeneous Data Centers in Cloud Computing Using a Complex Queuing Model

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  • Wei-Hua Bai
  • Jian-Qing Xi
  • Jia-Xian Zhu
  • Shao-Wei Huang

Abstract

Performance evaluation of modern cloud data centers has attracted considerable research attention among both cloud providers and cloud customers. In this paper, we investigate the heterogeneity of modern data centers and the service process used in these heterogeneous data centers. Using queuing theory, we construct a complex queuing model composed of two concatenated queuing systems and present this as an analytical model for evaluating the performance of heterogeneous data centers. Based on this complex queuing model, we analyze the mean response time, the mean waiting time, and other important performance indicators. We also conduct simulation experiments to confirm the validity of the complex queuing model. We further conduct numerical experiments to demonstrate that the traffic intensity (or utilization) of each execution server, as well as the configuration of server clusters, in a heterogeneous data center will impact the performance of the system. Our results indicate that our analytical model is effective in accurately estimating the performance of the heterogeneous data center.

Suggested Citation

  • Wei-Hua Bai & Jian-Qing Xi & Jia-Xian Zhu & Shao-Wei Huang, 2015. "Performance Analysis of Heterogeneous Data Centers in Cloud Computing Using a Complex Queuing Model," Mathematical Problems in Engineering, Hindawi, vol. 2015, pages 1-15, July.
    • Handle: RePEc:hin:jnlmpe:980945
    DOI: 10.1155/2015/980945
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    Cited by:

    1. Sunil K. Panigrahi & Veena Goswami & Hemant K. Apat & Ganga B. Mund & Himansu Das & Rabindra K. Barik, 2023. "PQ-Mist : Priority Queueing-Assisted Mist–Cloud–Fog System for Geospatial Web Services," Mathematics, MDPI, vol. 11(16), pages 1-21, August.

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