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浙江大学学报(理学版)  2016, Vol. 43 Issue (4): 452-457    DOI: 10.3785/j.issn.1008-9497.2016.04.012
地理信息系统     
用户行为选择参与的五层十五级瓦片缓存置换策略研究
褚信1,2, 蔡阳军3, 杜震洪1,2, 张丰1,2, 刘仁义2, 王炼刚1,2, 何敬1,2
1. 浙江大学 浙江省资源与环境信息系统重点实验室, 浙江 杭州 310028;
2. 浙江大学 地理信息科学研究所, 浙江 杭州 310027;
3. 杭州市住房保障办公室, 浙江 杭州 310006
Research on the user preference based cache replacement algorithm of the Five-layer Fifteen-level tile
CHU Xin1,2, CAI Yangjun3, DU Zhenhong1,2, ZHANG Feng1,2, LIU Renyi2, WANG Liangang1,2, HE Jing1,2
1. Zhejiang Provincial Key Lab of GIS, Zhejiang University, Hangzhou 310028, China;
2. Department of Geographic Information Science, Zhejiang University, Hangzhou 310027, China;
3. Hangzhou Housing Security office, Hangzhou 310006, China
 全文: PDF(1194 KB)  
摘要: FIFO、LRU、LFU、GDLVF等传统瓦片缓存置换算法侧重于瓦片访问时间和频率、瓦片大小、空间位置关系,不适合具有多源、异构特点的五层十五级瓦片数据,在五层十五级瓦片数据缓存的应用上存在局限性.提出了用户行为参与的缓存置换算法UPBA(User Preference Based Tile Cache Replacement Algorithm),并从用户行为、瓦片访问的时间和频率、瓦片大小、空间位置关系等方面分析了UPBA算法,提出了提高置换效率的方法.并对最高分辨率为100和250 m、生产时间为2014年11月、2015年1~3月的高分一号、高分二号、资源三号影像数据集进行日志驱动仿真实验.结果表明:相较传统的缓存置换算法,UPBA提高了瓦片请求的命中率和字节命中率,降低了客户端流量消耗和服务器端负载.
关键词: 五层十五级瓦片缓存置换空间数据    
Abstract: Traditional tile cache replacement algorithms such as FIFO, LRU, LFU, GDLVF focusing on tile's access time, access frequency, size, and spatial location relationship, have limitations in practice of caching the Five-layer Fifteen-level tile, and are not suitable for the Five-layer Fifteen-level tile which is multi-source heterogeneous. In this paper, a tile cache replacement algorithm for Five-layer Fifteen-level named UPBA (User Preference Based Tile Cache Replacement Algorithm) was proposed, and its features including user preference, tile access time and frequency, tile size, and spatial location relationship were analyzed. And then, the enhanced tile replacement method of UPBA was presented. The image datasets of GF-1, GF-2 and ZY-3 with resolution of 100 and 250 m, and production time in November of 2014 and January, February, March of 2015 were used in log-driven simulations of UPBA. The result showed that the UPBA had improved the request hit rate and byte hit rate, meanwhile reduced the client traffic consumption and the server load compared to the traditional cache replacement algorithm.
Key words: Five-layer Fifteen-level    tile cache replacement    spatial data
收稿日期: 2015-12-21 出版日期: 2016-04-28
CLC:  TN433  
基金资助: 国家自然科学基金资助项目(41471313,41101356,41101371,41171321);国家科技基础性工作专项(2012FY112300);国家海洋公益性行业科研专项经费资助项目(2015418003,201305012);浙江省科技攻关计划项目(2014C33G20,2013C33051);中央高校基本科研业务费专项资金资助项目(2016XZZX004-02,2016QNA3015).
通讯作者: 杜震洪,ORCID:http://orcid.org/0000-0001-9449-0415,E-mail:duzhenhong@zju.edu.cn.     E-mail: duzhenhong@zju.edu.cn
作者简介: 禇信(1991-),ORCID:http://orcid.org/0000-0001-8883-8728,男,硕士研究生,主要从事移动GIS、GIS及其应用研究.
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引用本文:

褚信, 蔡阳军, 杜震洪, 张丰, 刘仁义, 王炼刚, 何敬. 用户行为选择参与的五层十五级瓦片缓存置换策略研究[J]. 浙江大学学报(理学版), 2016, 43(4): 452-457.

CHU Xin, CAI Yangjun, DU Zhenhong, ZHANG Feng, LIU Renyi, WANG Liangang, HE Jing. Research on the user preference based cache replacement algorithm of the Five-layer Fifteen-level tile. Journal of ZheJIang University(Science Edition), 2016, 43(4): 452-457.

链接本文:

https://www.zjujournals.com/sci/CN/10.3785/j.issn.1008-9497.2016.04.012        https://www.zjujournals.com/sci/CN/Y2016/V43/I4/452

[1] 段龙方.面向遥感数据的云数据库技术研究与应用[D].开封:河南大学,2014. DUAN Longfang. The Research and Application of Cloud Database Technology for Remote Sensing Data[D]. Kaifeng: Henan University,2014.
[2] 王浩,俞占武,曾武,等.网络地理信息服务中的空间数据缓存算法研究[J].测绘学报,2009,38(4):348-355. WANG Hao, YU Zhanwu, ZENG Wu, et al. The research on the algorithm of spatial data cache in network geographic information service[J]. Acta Geodaetica et Cartographics Sinica,2009,38(4):348-355.
[3] 涂振发,孟令奎,张文,等.面向网络GIS的最小价值空间数据缓存替换算法研究[J].华中师范大学学报:自然科学版,2012,46(2):230-234. TU Zhengfa, MENG Lingkui, ZHANG Wen, et al. Research on the lowest-value cache replacement algorithm of geospatial data in Network GIS[J]. Journal of Huazhong Normal University: Natural Sciences,2012,46(2):230-234.
[4] 刘磊,熊小鹏.最小驻留价值缓存替换算法[J].计算机应用,2013,33(4):1018-1022.LIU Lei, XIONG Xiaopeng. Least cache value replacement algorithm[J]. Journal of Computer Applications,2013,33(4):1018-1022.
[5] 石磊,叶海琴,卫琳,等.Web缓存命中率与字节命中率关系[J].计算机工程,2007,44(13):84-86. SHI Lei, YE Haiqin, WEI Lin, et al. Relationship between hit ratio and byte hit ratio of web caching[J]. Computer Engineering,2007,44(13):84-86.
[6] 王小燕.一种高效的流媒体代理缓存替换算法[J].计算机工程,2009,35(14):72-74. WANG Xiaoyan. High effective stream media proxy cache replacement algorithm[J]. Computer Engineering,2009,35(14):72-74.
[7] 王栋,郑逢斌,赖包积,等.基于五层十五级遥感数据结构的并行算法研究[J].微计算机信息,2012,28(1):166-167. WANG Dong, ZHENG Fengbin, LAI Baoji, et al. A new parallel algorithm based on Five-layer Fifteen-level remote sensing data[J]. Microcomputer Information,2012,28(1):166-167.
[8] 王啸.基于新技术的海量遥感影像并行切分方法研究[D].开封:河南大学,2012. WANG Xiao. Research of Remote Sensing Image Parallel Segmentation Method Based on the New Technology[D]. Kaifeng: Henan University,2012.
[9] PODLIPNIG S, BOSZORMENYI L. A survey of web cache replacement strategies[J]. ACM Computing Surveys,2003,35(4):374-398.
[10] 卢秉亮,梅义博,刘娜.位置相关查询中基于最小访问代价的缓存替换算法[J].计算机应用,2011,31(3):690-693. LU Bingliang, MEI Yibo, LIU Na. Cache replacement method based on lowest access cost for location dependent query[J]. Journal of Computer Applications,2011,31(3):690-693.
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