论文标题
顶部适应对覆盖网络中搜索性能的影响
The effect of the toplolgy adaptation on search performance in overlay network
论文作者
论文摘要
本研究论文中介绍的工作集中在网络待办事项适应对同行覆盖网络中的搜索性能的影响。已经研究了指导搜索与盲目搜索,目的是改善搜索重新申请并减少搜索消息到达目的地的时间。该网络已被配制为带顶点的双向图表,代表网络节点,边缘代表连接。这项研究的网络主题级别是在应用层上,这意味着如果彼此了解彼此的联系地址,则连接两个节点。这种网络的一个很好的例子是社交网络,其中所有下层都隐藏在最终用户中。在这种情况下,已经研究了两种不同的搜索算法:深度第一算法和广度第一算法。此外,在随机拓扑(无标度网络拓扑)和拓扑适应下检查了算法性能。已经设计了一种模拟场景来研究系统的忠诚度并研究建议的解决方案。仿真结果表明,搜索算法在拓扑改编的质量和搜索时间方面的性能较好。
The work presented in this research paper has focused on the effect of network to-pology adaptation on search performance in peer to peer overlay network. Guided search vs. blind search have been studied with the aim of improving the search re-sults and decreasing the time a search message would take to reach the destination. The network has been formulated as a bi-direction graph with vertices represent network nodes and edges represent connections. The level of network subject of this study is on application layer, that means two nodes are connected if they know each other contact addresses. A good example of this kind of network is the social network where all the lower layers are hidden from the end user. Two different search algorithms have been studied under these circumstances, namely: depth first algorithm and breadth first algorithm. Furthermore, the algorithms performance is examined under random topology (scale free network topology) and under topology adaptation. A simulation scenario has been designed to investigate the fidelity of the system and study the suggested solutions. Simulation results have shown that the search algorithms are performing better under topology adaptation in terms of re-sults quality and search time.