CloudRank-D: benchmarking and ranking cloud computing systems for data processing applications
Chunjie LUO, Jianfeng ZHAN, Zhen JIA, Lei WANG, Gang LU, Lixin ZHANG, Cheng-Zhong XU, Ninghui SUN
CloudRank-D: benchmarking and ranking cloud computing systems for data processing applications
With the explosive growth of information, more and more organizations are deploying private cloud systems or renting public cloud systems to process big data. However, there is no existing benchmark suite for evaluating cloud performance on the whole system level. To the best of our knowledge, this paper proposes the first benchmark suite CloudRank-D to benchmark and rank cloud computing systems that are shared for running big data applications.We analyze the limitations of previous metrics, e.g., floating point operations, for evaluating a cloud computing system, and propose two simple metrics: data processed per second and data processed per Joule as two complementary metrics for evaluating cloud computing systems. We detail the design of CloudRank-D that considers representative applications, diversity of data characteristics, and dynamic behaviors of both applications and system software platforms. Through experiments, we demonstrate the advantages of our proposed metrics. In several case studies, we evaluate two small-scale deployments of cloud computing systems using CloudRank-D.
data center systems / clouds / big data applications / benchmarks / evaluation metrics
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