load shedding for shared window join over real-time data streams
Ma Li; Liang Dangwei; Zhang Qiongsheng; Li Xin; Wang Hongan
2009
会议名称Joint International Conference on Advances in Data and Web Management, APWeb/WAIM 2009
会议录名称Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
页码590-596
会议日期37348
会议地点Suzhou, China
收录类别其他
出版地Germany
出版者Germany
ISSN3029743
ISBN9783642006715
部门归属(1) School of Computer Science and Communication Engineering, China University of Petroleum, Dongying 257061, China; (2) Institute of Software, Chinese Academy of Sciences, Beijing 100190, China; (3) Geophysical Research Institute of Shengli Oil Field, China Petroleum and Chemical Corporation, Dongying 257000, China; (4) Shandong University, Jinan 250101, China
摘要Join is a fundamental operator in a Data Stream Management System (DSMS). It is more efficient to share execution of multiple windowed joins than separate execution of everyone because the former saves a part of cost in common windows. Therefore, shared window join is adopted widely in multiqueries DSMS. When all tasks of queries exceed maximum system capacity, the overloaded DSMS fails to process all of its input data and keep up with the rates of data arrival. Especially in a time-critical environment, queries should be completed not just timely but within certain deadlines. In this paper, we address load shedding approach for shared window join over real-time data streams. A load shedding algorithm LS-SJRT-CW is proposed to handle queries shared window join in overloaded real-time system effectively. It would reduce load shedding overhead by adjusting sliding window size. Experiment results show that our algorithm would decrease average deadline miss ratio over some ranges of workloads. © Springer-Verlag Berlin Heidelberg 2009.
关键词Ad Hoc Networks
语种英语
内容类型会议论文
URI标识http://ir.iscas.ac.cn/handle/311060/8512
专题人机交互技术与智能信息处理实验室
推荐引用方式
GB/T 7714
Ma Li,Liang Dangwei,Zhang Qiongsheng,et al. load shedding for shared window join over real-time data streams[C]. Germany:Germany,2009:590-596.
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