Abstract
With the ever increasing demands of cloud computing services, planning and management of cloud resources has become a more and more important issue which directed affects the resource utilization and SLA and customer satisfaction. But before any management strategy is made, a good understanding of applications’ workload in virtualized environment is the basic fact and principle to the resource management methods. Unfortunately, little work has been focused on this area. Lack of raw data could be one reason; another reason is that people still use the traditional models or methods shared under non-virtualized environment. The study of applications’ workload in virtualized environment should take on some of its peculiar features comparing to the non-virtualized environment. In this paper, we are open to analyze the workload demands that reflect applications’ behavior and the impact of virtualization. The results are obtained from an experimental cloud testbed running web applications, specifically the RUBiS benchmark application. We profile the workload dynamics on both virtualized and non-virtualized environments and compare the findings. The experimental results are valuable for us to estimate the performance of applications on computer architectures, to predict SLA compliance or violation based on the projected application workload and to guide the decision making to support applications with the right hardware.
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Acknowledgment
We would like to thank the anonymous reviewers for their constructive comments and suggestions. A preliminary version of this paper was accepted by the fourth Workshop on Big Data Benchmarks, Performance Optimization and Emerging Hardware in conjunction with ACM ASPLOS 2014 [27]. This work was performed in the Dependable Computing Systems Laboratory at the University of North Texas.
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Wang, X., Huang, S., Fu, S., Kavi, K. (2014). Characterizing Workload of Web Applications on Virtualized Servers. In: Zhan, J., Han, R., Weng, C. (eds) Big Data Benchmarks, Performance Optimization, and Emerging Hardware. BPOE 2014. Lecture Notes in Computer Science(), vol 8807. Springer, Cham. https://doi.org/10.1007/978-3-319-13021-7_8
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DOI: https://doi.org/10.1007/978-3-319-13021-7_8
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