| 用户访问驱动的空间数据存储组织策略 |
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| 引用本文： | 潘少明,赖新果,种衍文,李红.用户访问驱动的空间数据存储组织策略[J].武汉大学学报(信息科学版),2019,44(2):296. |
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| 作者姓名： | 潘少明 赖新果 种衍文 李红 |
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| 作者单位： | 1.武汉大学测绘遥感信息工程国家重点实验室, 湖北 武汉, 430079 |
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| 基金项目： | 国家自然科学基金41671382国家自然科学基金61572372国家自然科学基金41271398国家重点研发计划2017YFB0504202 |
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| 摘 要： | 针对用户访问服务负载均衡的分布存储要求和磁盘连续读取的合并存储要求之间的矛盾，提出一种基于用户访问行为的综合考虑存储节点连续读取效率和网络负载均衡效率的空间数据存储组织方法（combined strategy of data placement and load balance，CSDL）。该方案根据用户访问行为，通过空间数据的访问相关性计算，将热点数据分布存储在不同的服务器上，以实现用户并发访问时的负载均衡；同时，通过对存储在相同服务器内数据的并发度计算，将并发度高的数据存储在连续的磁盘空间上，以实现磁盘存储服务的连续读取。CSDL方法试图同时从上层应用的负载均衡和底层磁盘效率两个方面对空间数据的存储进行分布组织，以提高地理信息系统服务效率。试验结果表明，该方案可有效提高45.2%~245.3%的系统平均请求响应时间，与此同时，分布式服务器节点的负载均衡度可提高约0.5%~440.9%，能满足大规模分布式环境的应用需求。
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| 关 键 词： | 空间数据 负载均衡 数据组织 访问相关性 分布式地理信息系统 |
| 收稿时间： | 2018-06-09 |
User-driving Based Storage and Organization Strategy for Spatial Data |
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| Affiliation: | 1.State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430079, China |
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| Abstract: | Aimed at the conflict between load balancing for user access services and sequentially reading for disk storage services, a user-driving storage and organization strategy for spatial data is proposed, which takes a comprehensive consideration of the strategy of data placement and load balance (CSDL). This scheme mines the users' behaviors and computes the correlations among all data so as to distribute and store the popular data into different storage nodes to realize load balancing. Then, the concurrency degree is also computed among the data stored in the same storage node and which can be used to store some data in contiguous disk space to realize continuous reading. The CSDL method proposed in this paper tries to organize spatial data storage from two aspects of load balancing and lower disk efficiency at the same time, so as to improve the service efficiency of GIS. Experimental results show that our scheme improves the performance of average request response time by 45.2%-245.3% and also improves the performance of load balance degree by 0.5%-440.9%, which can meet the requirements of large scale distributed environments. |
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