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Virtualization technology is widely used in server consolidation, high performance computing, and cloud data center due to its benefits on high resource utilization, flexible manageability, and dynamically scalability. However, it also introduces additional performance overheads. It’s worthy to evaluate the overheads and to find the bottleneck of virtualization in different scenarios. In this paper, we propose a combinative evaluation method to analyze the performance from single virtual machine to multiple virtual machine systems that measures and analyzes both the macro-performance and micro-performance. By correlating the analysis results of two-granularity performance data, some potential performance bottlenecks come out.
}, issn = {2617-8710}, doi = {https://doi.org/}, url = {http://global-sci.org/intro/article_detail/ijnam/633.html} }Virtualization technology is widely used in server consolidation, high performance computing, and cloud data center due to its benefits on high resource utilization, flexible manageability, and dynamically scalability. However, it also introduces additional performance overheads. It’s worthy to evaluate the overheads and to find the bottleneck of virtualization in different scenarios. In this paper, we propose a combinative evaluation method to analyze the performance from single virtual machine to multiple virtual machine systems that measures and analyzes both the macro-performance and micro-performance. By correlating the analysis results of two-granularity performance data, some potential performance bottlenecks come out.