测绘通报 ›› 2021, Vol. 0 ›› Issue (2): 77-81,166.doi: 10.13474/j.cnki.11-2246.2021.0048

• 学术研究 • 上一篇    下一篇

顾及空间访问密度的地理信息服务请求负载均衡算法

刘晓丽1, 孙伟2, 李成名1   

  1. 1. 中国测绘科学研究院, 北京 100830;
    2. 易时代新图软件有限公司, 北京 100144
  • 收稿日期:2020-03-12 修回日期:2020-10-10 出版日期:2021-02-25 发布日期:2021-03-09
  • 作者简介:刘晓丽(1985-),女,博士,助理研究员,主要从事智慧城市时空大数据平台方面的工作。E-mail:83391860@qq.com
  • 基金资助:
    中国测绘科学研究院基本科研业务费(AR1909)

Geographic information service request load balancing algorithm considering spatial access density

LIU Xiaoli1, SUN Wei2, LI Chengming1   

  1. 1. Chinese Academy of Surveying and Mapping, Beijing 100830, China;
    2. E-Age NewMap Software Co., Ltd., Beijing 100144, China
  • Received:2020-03-12 Revised:2020-10-10 Online:2021-02-25 Published:2021-03-09

摘要: 有效的负载均衡是提升当前海量地理信息网络服务请求响应效率最常用的方法,但现有算法存在空间服务调用方面难以兼顾空间性和服务请求量的不足。为此,本文通过引入空间访问密度,同时考虑地理信息服务请求本身的频繁程度与数据在空间分布上的关系,提出一种顾及空间访问密度的地理信息服务请求负载均衡算法。首先,统计地理信息服务访问调用日志信息,提取数据的外包框数据集,并生成四叉树索引,通过四叉树索引建立空间访问密度均衡模型;然后,在地理信息服务请求时,利用空间访问密度均衡模型进行轮询分配;最后,对比经同等试验环境下的效率和性能,本文算法可有效提高地理信息服务请求响应效率。

关键词: 空间访问密度, 地理信息服务, 负载均衡, 访问调用日志, 四叉树

Abstract: Effective load balancing is the most commonly used method to improve the response efficiency of the geographic information service request, but the existing load balancing algorithm cannot take into account the deficiency of both spatial and service request volume in the aspect of spatial service invocation. Therefore, by introducing the spatial access density and considering the relationship between the frequency of geographic information service requests and the spatial distribution of data, this paper proposes a load balancing algorithm of mass geographic information service requests based on spatial access density. Firstly, based on the geographic information data access call log, the spatial frequent range of data access is obtained and the quadtree index is constructed to establish the spatial access density equilibrium model. Then, based on the spatial access density equilibrium model, the polling allocation of geographic information service requests is carried out. Finally, by comparing the efficiency and performance experiments under the same experimental environment, the proposed algorithm can effectively improve the efficiency of geographic information service request response.

Key words: spatial access density, geographic information service, load balance, data access call log, quadtree

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