56 citations · 88 across the 8 of their papers we have counts for
9 papers
AccurateML: Information-aggregation-based Approximate Processing for Fast and Accurate Machine Learning on MapReduce
Rui Han, Fan Zhang, Zhentao Wang
The growing demands of processing massive datasets have promoted irresistible trends of running machine learning applications on MapReduce. When processing large input data, it is…
AccuracyTrader: Accuracy-aware Approximate Processing for Low Tail Latency and High Result Accuracy in Cloud Online Services
Rui Han, Siguang Huang, Fei Tang +2
Modern latency-critical online services such as search engines often process requests by consulting large input data spanning massive parallel components. Hence the tail latency of…
Investigations into Elasticity in Cloud Computing
Rui Han
The pay-as-you-go model supported by existing cloud infrastructure providers is appealing to most application service providers to deliver their applications in the cloud. Within t…
PCS: Predictive Component-level Scheduling for Reducing Tail Latency in Cloud Online Services
Rui Han, Junwei Wang, Siguang Huang +4
Modern latency-critical online services often rely on composing results from a large number of server components. Hence the tail latency (e.g. the 99th percentile of response time)…
Benchmarking Big Data Systems: State-of-the-Art and Future Directions
Rui Han, Zhen Jia, Wanling Gao +2
The great prosperity of big data systems such as Hadoop in recent years makes the benchmarking of these systems become crucial for both research and industry communities. The compl…
BigDataBench-MT: A Benchmark Tool for Generating Realistic Mixed Data Center Workloads
Rui Han, Shulin Zhan, Chenrong Shao +5
Long-running service workloads (e.g. web search engine) and short-term data analysis workloads (e.g. Hadoop MapReduce jobs) co-locate in today's data centers. Developing realistic…