电动汽车充电网络云平台下一种基于Chord-R的多租户多维索引方法

李军良; 张杨; 王睿; 高欣; 李晓蕾; 任昺

doi:10.3969/j.issn.1000-7229.2018.10.011

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电力建设 ›› 2018, Vol. 39 ›› Issue (10) : 92-98. DOI: 10.3969/j.issn.1000-7229.2018.10.011

智能电网

电动汽车充电网络云平台下一种基于Chord-R的多租户多维索引方法

李军良1, 张杨2，王睿3，高欣3，李晓蕾1，任昺3

作者信息 +

A Multi-tenant Multidimensional Indexing Based on Chord-R for Cloud Platform of Electric Vehicle Charging Network

LI Junliang1, ZHANG Yang2，WANG Rui3，GAO Xin3，LI Xiaolei1，REN Bing3

Author information +

文章历史 +

摘要

面向不同运营商多租户数据的高效索引方法是构建电动汽车充电网络云平台的关键技术之一。现有多租户数据索引方法在面对海量多维信息索引时存在效率低的问题。在此背景下，提出了一种基于共享存储模式的Chord-R双层索引方法，上层采用对等结构中的Chord协议作为全局索引，使单个租户的数据聚集并有序地分布在尽量少且相邻的节点上，保证数据具有良好的隔离性和扩展性；下层引入空间索引方法R树进行本地数据的局部索引，最终实现了多租户数据多维信息的高效索引。实验结果表明，在进行多维信息索引时，与典型多租户索引方法（multi-tenant indexing mechanism based on improved Chord mapping approach，MIMC）相比，查询时间至少可以节省48%。

Abstract

Efficient indexing of multi-tenant data for different operators is one of the key technologies in building a cloud platform for electric vehicle charging network. The existing index method for multi-tenant data remains inefficiency when facing massive multidimensional information. Thus, a Chord-R double layered multidimensional index method based on shared storage is proposed in this paper. The upper layer adopts the Chord protocol in the Peer-to-Peer as global index, which ensures the data of single tenant is centrally and orderly on adjacent nodes so that the data possess good isolation and scalability, while the lower layer introduces spatial index method R-tree to launch local index with local data. Experimental evaluation demonstrates that query time can be reduced at least 48% compared with multi-tenant indexing method MIMC.

导出引用

李军良, 张杨，王睿，高欣，李晓蕾，任昺. 电动汽车充电网络云平台下一种基于Chord-R的多租户多维索引方法[J]. 电力建设. 2018, 39(10): 92-98 https://doi.org/10.3969/j.issn.1000-7229.2018.10.011

LI Junliang, ZHANG Yang，WANG Rui，GAO Xin，LI Xiaolei，REN Bing. A Multi-tenant Multidimensional Indexing Based on Chord-R for Cloud Platform of Electric Vehicle Charging Network[J]. Electric Power Construction. 2018, 39(10): 92-98 https://doi.org/10.3969/j.issn.1000-7229.2018.10.011

中图分类号： TM 734

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