P2P Delaunay网络远程空间数据访问的远程接触分布生成算法

M. Ohnishi, Shinji Tsuboi, Masao Hirayama, Takayuki Eguchi, S. Ueshima
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引用次数: 4

摘要

P2P Delaunay网络是利用一种众所周知的几何结构,即计算地理几何中的Delaunay三角剖分,在二维平面上连接节点的网络。该结构具有两个相邻节点连接的特性。给出了该算法在任意两个节点间具有贪心路由的P2P环境下的自治生成算法,并证明了网络的可扩展性。通过将Voronoi区域设置为节点管辖区域,将P2P Delaunay网络作为空间数据库,并在网络上轻松嵌入范围查询机制,实现P2P环境下可扩展的空间数据库。我们的目标是在地理信息系统(GIS)、虚拟协作系统、位置感知服务等方面的各种应用。但是,当P2P Delaunay网络由大量节点组成时,其直径和节点之间的跳数以O(N1/2)的速度增加,这会导致远程数据访问的通信延迟严重。因此,我们在此提出了P2P Delaunay网络的远程接触(LRC)及其分布式生成算法。我们的LRC是一组桥,它们以O(logN)跳数连接两个节点,节点度为O(logN)。我们提出了一种自主节点协作下的水平/垂直组合生成算法,以及一种利用LRC的路由方法。我们还评估了LRC生成中的CPU和通信负载,以及LRC的路由效率。最后,讨论了基于LRC的P2P Delaunay网络的应用领域。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Distributive Generation Algorithm of Long Range Contact for Remote Spatial-data Access on P2P Delaunay Network
A P2P Delaunay network is a network that connects nodes over 2-dimensional plane by utilizing a well-known geometric structure, a Delaunay triangulation in computational geographically geometry. This structure possesses the property that two adjacent nodes are connected. We have shown its autonomous generation algorithm in P2P settings with a greedy routing among two arbitrary nodes, and also shown the extensibility of the network. By setting Voronoi regions as a node's governing a area, a P2P Delaunay network works as a spatial database, and we can easily embed a range query mechanism over the network, realizing a extensible spatial database in P2P contexts. We aim at the diverse applications in geographical information systems (GIS), virtual collaboration systems, location-aware services, and so on. However, in case a P2P Delaunay network consists of a large number of nodes, its diameter and hop counts between two nodes increase in O(N1/2), which causes a serious communication delay in remote data accesses. Hence, we here propose long range contact(LRC) for a P2P Delaunay network and its distributive generation algorithm. Our LRC is a set of bridges that connect two nodes in O(logN) hops with O(logN) node degree. We present a combination of horizontal/vertical generation algorithm in a collaboration of autonomous nodes, as well as a routing methods that utilizes LRC. We also evaluate both CPU and communication loads in our LRC generation, as well as routing efficiencies of LRC numerically. Finally, we discuss application fields of a P2P Delaunay network with LRC.
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