Scalable and Efficient End-to-End Network Topology Inference

To construct an efficient overlay network, the information of underlay is important. We consider using end-to-end measurement tools such as traceroute to infer the underlay topology among a group of hosts. Previously, Max-Delta has been proposed to infer a highly accurate topology with a low number of traceroutes. However, Max-Delta relies on a central server to collect traceroute results and to select paths for hosts to traceroute. It is not scalable to large groups. In this paper, we investigate a distributed inference scheme to support scalable inference. In our scheme, each host joins an overlay tree before conducting traceroute. A host then independently selects paths for tracerouting and exchanges traceroute results with others through the overlay tree. As a result, each host can maintain a partially discovered topology. We have studied the key issue in the scheme, that is, how a low-diameter overlay tree can be constructed. Furthermore, we propose several techniques to reduce th...

• Type: Journal
• Year: 2008
• Where: TPDS
• Authors: Xing Jin, Wanqing Tu, S.-H. Gary Chan
• Keywords: Overlay Tree, Topology, TPDS 2008, Traceroute