Studies on Autonomous Distributed Traffic Control for Overlay Networks

在由底层物理节点和链路组成的覆盖网络中，数据文件通过应用层管理的覆盖路由进行传输。端到端文件传输延迟取决于由覆盖路由导致的逻辑和物理拓扑。在本研究中，我们针对六种四端四路由器的物理网路，探讨拓扑不一致性对档案传输延迟的影响。该分析模型基于一个两层的嵌入式网络，同时考虑到逻辑和物理拓扑结构。通过与ns-2仿真结果的比较，验证了该模型的有效性。数值算例表明，当逻辑和物理拓扑结构相同时，端到端的文件传输延迟较小。我们还观察到，端到端的延迟显着地依赖于某些逻辑拓扑的流量强度，而不管物理拓扑如何。 ...更多信息 语音应用程序。在Skype中，通过从普通终端用户节点中选择的超级节点建立语音连接。在线Skype节点的IP地址和端口号等用户信息由超级节点以分散的方式管理，其中超级节点的数量根据在线Skype节点的数量动态变化。在这里，我们分析了这种分散的用户信息管理系统的性能。在我们的分析模型中，新的节点加入系统根据一个非平稳泊松过程，并与超级节点的数量与非平稳马尔可夫链的在线节点过程进行了分析。我们推导出系统的差分微分方程的在线节点的数量的概率分布，以计算性能指标，使用固定的峰值近似方法。数值算例表明，基于P2P的用户信息管理系统比采用高性能集中式服务器的客户-服务器系统更能保持服务质量（QoS）的稳定性。少

In overlay networks consisting of underlying physical nodes and links, data files are transferred by overlay routing managed at application level. The end-to-end file transfer delay depends on both logical and physical topologies resulting from overlay routing. In this research, we focus on six types of four-terminal four-router physical networks, and investigate the impact of topology inconsistency on the file-transfer delay. The analysis model is based on a two-layer queueing network, taking into account both logical and physical topologies. The model is validated in comparison with ns-2 simulation. Numerical examples show that the end-to-end file-transfer delay is small when both logical and physical topologies are the same. It is also observed that the end-to-end delay significantly depends on the traffic intensity for some logical topologies, regardless of physical topology.Next, we consider Skype which has been receiving considerable attention as a peer-to-peer (P2P) Internet tel … More ephony application. In Skype, a voice connection is established via super nodes chosen from among ordinary end-user nodes. User information such as an IP address and port number of an online Skype node is managed by super nodes in a decentralized manner where the number of super nodes changes dynamically according to the number of online Skype nodes. Here, we analyze the performance of this decentralized management system of user information. In our analytical model, new nodes join the system according to a nonstationary Poisson process, and the online-node process associated with the number of super nodes is analyzed with a nonstationary Markov chain. We derive the system of difference-differential equations for the probability distribution of the number of online nodes to compute performance measures using the stationary peakedness approximation method. Numerical examples show that the user-information management system based on P2P can keep the quality of service (QoS) more stable than a client-server system with a centralized server of high performance. Less