计算机科学 ›› 2014, Vol. 41 ›› Issue (11): 107-111.doi: 10.11896/j.issn.1002-137X.2014.11.021

• 2013’全国软件与应用学术会议 • 上一篇    下一篇

一种基于Hadoop的BIM云服务框架和空间位置检索算法

陈泽琳,潘运军,何浥尘,齐德昱   

  1. 华南理工大学软件学院 广州510640;华南理工大学软件学院 广州510640;华南理工大学软件学院 广州510640;华南理工大学软件学院 广州510640
  • 出版日期:2018-11-14 发布日期:2018-11-14
  • 基金资助:
    本文受国家自然科学基金(61003157),广东省自然科学基金资助

Framework of BIM Cloud Services and Retrieval Algorithm of Spatial Location Based on Hadoop

CHEN Ze-lin,PAN Yun-jun,HE Yi-chen and QI De-yu   

  • Online:2018-11-14 Published:2018-11-14

摘要: 云平台存储和管理应用复杂的海量数据已成为必然。建筑信息模型(Building Information Modeling,BIM)是从全工程建设生命周期的视角组织相关数据并协同工作,所以BIM迫切需要云计算的支持。但是面对复杂的BIM应用,如何构建云平台的超级计算模式将是一个巨大的挑战。提出一个面向BIM应用的云服务框架,在Hadoop分布式软件框架上设计了云存储、云平台服务、应用服务和客户端应用四层结构。提出了该框架下的城市空间位置检索算法,该算法采用改进的KD树作为索引表。针对大用户群的并发访问,提出了面向空间位置检索的负载均衡算法,通过统计节点访问频度设计了数据块均衡分布策略。实验表明,该框架组织的建筑信息具有并发处理能力强、响应速度快等特点。

关键词: 云计算,建筑信息模型,框架,KD树,空间位置检索,负载均衡

Abstract: Cloud platform becomes a necessity to store and manage huge data for complex applications.The task of Building Information Modeling (BIM) is to organize the relevant data and work collaboratively during the whole life-cycle of the construction informationize.BIM is in urgent need of cloud computing.How to build a supercomputing model on cloud platform is a big challenge when facing the complex BIM application.This paper presented a framework of cloud services for BIM application.Hadoop is a distributed software framework.The four layers of the framework were designed:cloud storage,cloud platform services,application services and client applications.The retrieval algorithm of urban spatial location was proposed on the framework,which uses the improved KD tree as index table.The paper presented the load balancing algorithm for spatial location retrieval by which many groups of users access the data block concurrently.By statistical access frequency of the nodes,the strategy of balanced distribution for data block was designed.Experiments show that the framework has the characteristics of concurrent processing capability and rapid response for building information.

Key words: Cloud computing,Building information modeling,Framework,KD tree,Spatial location retrieval,Load balancing

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