| An on-line scaling method for improving scalability of a database cluster |
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| 作者姓名： | JANG Yong ll LEE Chung ho LEE Jae dong BAE Hae young |
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| 作者单位： | Dept. of Computer Science and Engineering，Inha University，South Korea，Dept. of Computer Science and Engineering，Inha University，South Korea，Dept. of Computer Science，Dankook University，Yonghyun Dong，Nam ku，Inchon，402 751，Korea，Dept. of Computer Science and Engineering，Inha University，South Korea |
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| 摘 要： | The explosive growth of the Internet and database applications has driven database to be more scalable and available, and able to support on-line scaling without interrupting service. To support more client‘s queries without downtime and degrading the response time, more nodes have to be scaled up while the database is running. This paper presents the overview of scalable and available database that satisfies the above characteristics. And we propose a novel on-line scaling method. Our method improves the existing on-line scaling method for fast response time and higher throughputs. Our proposed method reduces unnecessary network use, i.e. , we decrease the number of data copy by reusing the backup data. Also, our on-line scaling operation can be processed parallel by selecting adequate nodes as new node. Our performance study shows that our method results in significant reduction in data copy time.
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| 关 键 词： | 数据库串 在线缩放方法 可量测性 改进方法 |
An on-line scaling method for improving scalability of a database cluster |
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| JANG Yong ll ,LEE Chung ho ,LEE Jae dong ,BAE Hae young.An on-line scaling method for improving scalability of a database cluster[J].Journal of Chongqing University of Posts and Telecommunications(Natural Sciences Edition),2004,16(5):71-77. |
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| Authors: | JANGYong-ll LEEChung-ho LEEJae-dong BAEHae-young |
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| Institution: | [1]Dept.ofComputerScienceandEngineering,lnhaUniversity,SouthKorea [2]Dept.ofComputerScience,DankookUniversity,Yonghyun-Dong,Nam-ku,Inchon,402-751,Korea |
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| Abstract: | The explosive growth of the Internet and database applications has driven database to be more scalable and available, and able to support on line scaling without interrupting service. To support more client's queries without downtime and degrading the response time, more nodes have to be scaled up while the database is running. This paper presents the overview of scalable and available database that satisfies the above characteristics. And we propose a novel on line scaling method. Our method improves the existing on line scaling method for fast response time and higher throughputs. Our proposed method reduces unnecessary network use, i.e., we decrease the number of data copy by reusing the backup data. Also, our on line scaling operation can be processed parallel by selecting adequate nodes as new node. Our performance study shows that our method results in significant reduction in data copy time. |
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| Keywords: | database cluster on line scaling mothod scalability |
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