Journal of Software:2015.26(8):2138-2154

(中国科学院 信息工程研究所, 北京 100093;信息内容安全技术国家工程实验室, 北京 100093;中国科学院大学, 北京 100049)
Approach to Performance Optimization of Mashup Operation
ZHANG Peng,LIU Qing-Yun,XU Ke-Fu,LIN Hai-Lun,SUN Yong,TAN Jian-Long
(Institute of Information Engineering, The Chinese Academy of Sciences, Beijing 100093, China;National Engineering Laboratory for Information Security Technologies, Beijing 100093, China;University of Chinese Academy of Sciences, Beijing 100049, China)
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Received:April 15, 2013    Revised:September 28, 2014
> 中文摘要: 近几年来,互联网上出现了一类称为Mashup的新型应用,它使最终用户能够个性化地聚合和操作分布在互联网上的数据源.然而,关于Mashup在动态环境下运行时的性能研究还比较缺乏.为此,利用缓存技术提出了Mashup运行时的性能优化方法——POMO.POMO具有以下3个主要创新点:首先,POMO通过算子序列的缓存点的成本和收益模型实现了动态缓存点选取;其次,POMO通过缓存点的B+树索引实现了缓存点重用;第三,POMO通过两阶段切换数据传输协议实现了缓存点更新.实验分析结果表明:POMO减少了Mashup在动态环境下的运行成本,提高了Mashup运行时的性能
中文关键词: Mashup  缓存点  B+树  索引  增量传输
Abstract:In recent years, a new type of applications called “Mashup” has developed on the Internet. These applications can help end-users to collect and operate the distributed data sources on the Internet. However, the research on performance optimization of Mashup operation is lacking. To address this shortfall, this paper proposes a new approach, POMO, for performance optimization of Mashup operation. POMO engages progress in three areas. Firstly, it implements dynamic cache point selection through the tradeoff between operation cost and caching benefit. Secondly, it implements cache point reusing by B+ tree index. Thirdly, it implements cache point update through incremental transmission. Experimental results show that POMO reduces the cost of Mashup operation and improves the performance of Mashup operation in dynamic environment.
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基金项目:国家自然科学基金(61402464); 中国博士后基金(2013M541076) 国家自然科学基金(61402464); 中国博士后基金(2013M541076)
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ZHANG Peng,LIU Qing-Yun,XU Ke-Fu,LIN Hai-Lun,SUN Yong,TAN Jian-Long.Approach to Performance Optimization of Mashup Operation.Journal of Software,2015,26(8):2138-2154