Institute of Computing Technology, Chinese Academy IR
CLAP: Component-Level Approximate Processing for Low Tail Latency and High Result Accuracy in Cloud Online Services | |
Han, Rui1; Huang, Siguang2; Wang, Zhentao1; Zhan, Jianfeng1 | |
2017-08-01 | |
发表期刊 | IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS |
ISSN | 1045-9219 |
卷号 | 28期号:8页码:2190-2203 |
摘要 | 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 these components determines the service latency. To trade off result accuracy for tail latency reduction, existing techniques use the components responding before a specified deadline to produce approximate results. However, they skip a large proportion of components when load gets heavier, thus incurring large accuracy losses. In this paper, we propose CLAP to enable component-level approximate processing of requests for low tail latency and small accuracy losses. CLAP aggregates information of input data to create small aggregated data points. Using these points, CLAP reduces latency variance of parallel components and allows them to produce initial results quickly; CLAP also identifies the parts of input data most related to requests' result accuracies, thus first using these parts to improve the produced results to minimize accuracy losses. We evaluated CLAP using real services and datasets. The results show: (i) CLAP reduces tail latency by 6.46 times with accuracy losses of 2.2 percent compared to existing exact processing techniques; (ii) when using the same latency, CLAP reduces accuracy losses by 31.58 times compared to existing approximate processing techniques. |
关键词 | Cloud online services tail latency result accuracy component-level approximate processing aggregated data points |
DOI | 10.1109/TPDS.2017.2650988 |
收录类别 | SCI |
语种 | 英语 |
资助项目 | National Natural Science Foundation of China[61502451] ; National Key Research and Development Plan of China[2016YFB1000601] |
WOS研究方向 | Computer Science ; Engineering |
WOS类目 | Computer Science, Theory & Methods ; Engineering, Electrical & Electronic |
WOS记录号 | WOS:000405750200006 |
出版者 | IEEE COMPUTER SOC |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://119.78.100.204/handle/2XEOYT63/7033 |
专题 | 中国科学院计算技术研究所期刊论文_英文 |
通讯作者 | Han, Rui |
作者单位 | 1.Chinese Acad Sci, Inst Comp Technol, Beijing 100864, Peoples R China 2.Tsinghua Univ, Sch Software, Beijing 100084, Peoples R China |
推荐引用方式 GB/T 7714 | Han, Rui,Huang, Siguang,Wang, Zhentao,et al. CLAP: Component-Level Approximate Processing for Low Tail Latency and High Result Accuracy in Cloud Online Services[J]. IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS,2017,28(8):2190-2203. |
APA | Han, Rui,Huang, Siguang,Wang, Zhentao,&Zhan, Jianfeng.(2017).CLAP: Component-Level Approximate Processing for Low Tail Latency and High Result Accuracy in Cloud Online Services.IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS,28(8),2190-2203. |
MLA | Han, Rui,et al."CLAP: Component-Level Approximate Processing for Low Tail Latency and High Result Accuracy in Cloud Online Services".IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS 28.8(2017):2190-2203. |
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