集群并发环境下大规模矢量数据负载均衡算法

Content Grid Load Balancing Algorithm for Large-Scale Vector Data in the Server Cluster Concurrent Environment

  • 摘要: 为了提高集群环境下网络地理信息系统(WebGIS)大规模矢量数据的并发访问性能,提出了集群并发环境下大规模矢量数据内容网格化负载均衡算法,研究了大规模矢量数据内容网格化方法,集群并发访问时内容网格的自动识别、分析、聚合、反馈算法,实现了面向任务的负载均衡。实验表明,本算法能在大规模、高强度的矢量数据提取和显示中均衡地分发请求,使集群服务器充分发挥其优势从而获得最小的请求响应时间。

     

    Abstract: In order to improve the concurrent access performance with large-scale vector data in WebGIS,a content grid load balancing algorithm is proposed.The server processing capability,service contents,and request time are taken into account.A proposed method to divide large-scale vector data into a content grid,the algorithm of content automatic identification,analysis,aggregation and feedback in the server cluster concurrent environment is discussed.This algorithm implements all servers in the cluster to complete visualization tasks submitted by clients at the same time and realizes task-oriented load balancing.For the extraction and display of large-scale and high-intensity vector data,the algorithm balances the servers’ load efficiently and responds to requests in minimal time.As compared to t traditional load balancing algorithms,the algorithm proposed in this paper has the best performance.The larger the scale,the more obvious is the load balancing effect.

     

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