摘要
随着用户的增加,在传统的C/S模式下,中心服务器面临着负载过大、性能下降等诸多问题。基于对等网结构,利用P2P技术解决大规模海量地形漫游中服务器带宽和性能瓶颈问题得到了快速发展,但由于网络节点的动态性,通过P2P进行瓦片数据共享时如何解决节点搜索问题成为关键。针对上述问题,提出了一种基于分组洪泛式的节点搜索模型GFLOOD ING,通过组内缓存映射、组外邻居组映射的洪泛模式查询服务节点;通过实验原型系统的比较测试表明,该算法满足大规模节点模式下的动态性要求,且查询效率高。
As the number of clients increases, the server performance will drop too rapidly to satisfy the client real-time rending requirement because the server loads are increasing linearly for the kind of client/server architecture. The method through peer-to-peer （P2P） to address the server bandwidth and performance bottleneck in large scale massive terrain navigation has attracted much effort based on P2P networks. Due to peers＇ dynamics, how to find the server peers quickly is the key problem on sharing the tiles based on P2P. A searching model, called GFLOODING, was proposed for the system, which was based on the buffer map （ BM ） info and group peer map （GPM） info, when deciding from which peers to get the tiles. Compared test result in prototype system indicates that the proposed module can satisfy the large scale massive terrain navigation system, and has higher efficiency than traditional module.
出处
《计算机应用研究》
CSCD
北大核心
2009年第5期1659-1662,共4页
Application Research of Computers
基金
国家"973"计划资助项目(2004CB318206)
国家"863"计划资助项目(2007AA12Z214)
武汉大学测绘遥感信息工程国家重点实验室专项科研经费资助
关键词
搜索模型
地形漫游
分组
洪泛
对等网
search model
terrain navigation
group
flooding
P2P （peer-to-peer）
