1. BURSE: A Bursty and Self-Similar Workload Generator for Cloud Computing.
- Author
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Yin, Jianwei, Lu, Xingjian, Zhao, Xinkui, Chen, Hanwei, and Liu, Xue
- Subjects
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WORKLOAD of computer networks , *CLOUD computing , *SELF-similar processes , *COMPUTER performance , *COMPUTER simulation , *POISSON processes - Abstract
As two of the most important characteristics of workloads, burstiness and self-similarity are gaining more and more attention. Workload generation, which is a key technique for performance analysis and simulations, has also attracted an increasing interest in cloud community in recent years. Though a large number of methods for synthetically generating bursty or self-similar workloads have been proposed in the literature, none of them can deal with workload generation with both of the two characteristics. In this paper, a configurable and intelligible synthetic generator (BURSE) is proposed for bursty and self-similar workloads in cloud computing based on a superposition of two-state Markov Modulated Poisson Processes (MMPP2s). The proposed generator can produce workloads with both specified intension of burstiness and self-similarity. Detailed experimental evaluation demonstrates the accuracy, robustness and good applicability of BURSE. [ABSTRACT FROM AUTHOR]
- Published
- 2015
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