Abstract — In this paper, we present the design, implementation, and evaluation of the iPlane, a scalable service providing accurate predictions of Internet path performance for emerging overlay services. Unlike the more common black box latency prediction techniques in use today, the iPlane builds an explanatory model of the Internet. We predict end-to-end performance by composing measured performance of segments of known Internet paths. This method allows us to accurately and efficiently predict latency, bandwidth, capacity and loss rates between arbitrary Internet hosts. We demonstrate the feasibility and utility of the iPlane service by applying it to several representative overlay services in use today: content distribution, swarming peer-to-peer filesharing, and voice-over-IP. In each case, we observe that using iPlane’s predictions leads to a significant improvement in end user performance. 1

The lack of an accurate representation of the Internet topology at the Autonomous System (AS) level is a limiting factor in the design, simulation, and modeling efforts in inter-domain routing protocols. In this paper, we design and implement a framework for identifying AS links that are missing from the commonly-used Internet topology snapshots. We apply our framework and show that the new links that we find change the current Internet topology model in a non-trivial way. First, in more detail, our framework provides a large-scale comprehensive synthesis of the available sources of information. We cross-validate and compare BGP routing tables, Internet Routing Registries, and traceroute data, while we extract significant new information from the less-studied Internet Exchange Points (IXPs). We identify 40 % more edges and approximately 300 % more peer-to-peer edges compared to commonly used data sets. Second, we identify properties of the new edges and quantify their effects on important topological properties. Given the new peer-topeer edges, we find that for some ASes more than 50% of their paths stop going through their ISP providers assuming policy-aware routing. A surprising observation is that the degree of a node may be a poor indicator of which ASes it will peer with: the two degrees differ by a factor of four or more in 50 % of the peer-to-peer links. Finally, we attempt to estimate the number of edges we may still be missing. 1

Recent progress in active measurement techniques has made it possible to estimate end-to-end path available bandwidth. However, how to efficiently obtain available bandwidth information for the N paths in a large N -node system remains an open problem. While researchers have developed coordinate-based models that allow any node to quickly and accurately estimate latency in a scalable fashion, no such models exist for available bandwidth. In this paper we introduce BRoute --- a scalable available bandwidth estimation system that is based on a route sharing model. The characteristics of BRoute are that its overhead is linear with the number of end nodes in the system, and that it requires only limited cooperation among end nodes. BRoute leverages the fact that most Internet bottlenecks are on path edges, and that edges are shared by many different paths. It uses AS-level source and sink trees to characterize and infer path-edge sharing in a scalable fashion. In this paper, we describe the BRoute architecture and evaluate the performance of its components. Initial experiments show that BRoute can infer path edges with an accuracy of over 80%. In a small case study on Planetlab, 80% of the available bandwidth estimates obtained from BRoute are accurate within 50%.

Abstract — Topology discovery systems are starting to be introduced in the form of easily and widely deployed software. Unfortunately, the research community has not examined the problem of how to perform such measurements efficiently and in a network-friendly manner. This paper describes several contributions towards that end. These were first presented in the proceedings of ACM SIGMETRICS 2005. We show that standard topology discovery methods (e.g., skitter) are quite inefficient, repeatedly probing the same interfaces. This is a concern, because when scaled up, such methods will generate so much traffic that they will begin to resemble DDoS attacks. We propose two metrics focusing on redundancy in probing and show that both are important. We also propose and evaluate Doubletree, an algorithm that strongly reduces redundancy while maintaining nearly the same level of node and link coverage. The key ideas are to exploit the tree-like structure of routes to and from a single point in order to guide when to stop probing, and to probe each path by starting near its midpoint. Following the SIGMETRICS work, we implemented Doubletree, and deployed it in a real network environment. This paper describes that implementation, as well as preliminary favorable results. Index Terms — network topology, traceroute, cooperative algorithms. I.

Traceroute is the most widely used Internet diagnostic tool today. Network operators use it to help identify routing failures, poor performance, and router misconfigurations. Researchers use it to map the Internet, predict performance, geolocate routers, and classify the performance of ISPs. However, traceroute has a fundamental limitation that affects all these applications: it does not provide reverse path information. Although various public traceroute servers across the Internet provide some visibility, no general method exists for determining a reverse path from an arbitrary destination. In this paper, we address this longstanding limitation by building a reverse traceroute tool. Our tool provides the same information as traceroute, but for the reverse path, and it works in the same case as traceroute, when the user may lack control of the destination. Our approach combines a number of ideas: source spoofing, IP timestamp and record route options, and multiple vantage points. We deploy our system on PlanetLab and compare reverse traceroute paths with traceroutes issued from the destinations. In the median case our tool finds 87 % of the hops seen in a directly measured traceroute along the same path, versus only 38 % if one simply assumes the path is symmetric, a common fallback given the lack of available tools. We then use our reverse traceroute system to study previously unmeasurable aspects of the Internet: we uncover more than a thousand peer-to-peer AS links invisible to current topology mapping efforts, we present a case study of how a content provider could use our tool to troubleshoot poor path performance, and we measure the latency of individual backbone links with, on average, sub-millisecond precision. 1

Mapping the router topology is an important component of Internet measurement. Alias resolution, the process of mapping IP addresses to routers, is critical to accurate Internet mapping. Ally, a popular alias resolution tool, was developed to resolve aliases in individual ISPs, but its probabilistic accuracy and need to send O(n 2) probes to infer aliases among n IP addresses make it unappealing for large-scale Internet mapping. In this paper, we present RadarGun, a tool that uses IP identifier velocity modeling to improve the accuracy and scalability of the Ally-based resolution technique. We provide analytical bounds on Ally’s accuracy and validate our predicted aliases against Ally. Additionally, we show that velocity modeling requires only O(n) probes and thus scales to Internet-sized mapping efforts.

We consider using traceroute-like end-to-end measurement to infer the underlay topology for a group of hosts. One major issue is the measurement cost. Given hosts in an asymmetric network without anonymous routers, traditionally full @ IA traceroutes are needed to determine the underlay topology. We investigate how to efficiently infer an underlay topology with low measurement cost, and propose a heuristic called Max-Delta. In the heuristic, a server selects appropriate host-pairs to measure in each iteration so as to reveal the most undiscovered information on the underlay. We further observe that the presence of anonymous routers significantly distorts and inflates the inferred topology. Previous research has shown that obtaining both exact and approximate topology in the presence of anonymous routers under certain consistency constraints is intractable. We hence propose fast algorithms on how to practically construct an approximate topology by relaxing some constraints. We investigate and compare two algorithms to merge anonymous routers. The first one uses Isomap to map routers into a multidimensional space and merges anonymous routers according to their interdistances. The second algorithm is based on neighbor router information, which trades off some accuracy with speed. We evaluate our inference algorithms on Internet-like and real Internet topologies. Our results show that almost full measurement is needed to fully discover the underlay topology. However, substantial reduction in measurements can be achieved if a little accuracy, say 5%, can be compromised. Moreover, our merging algorithms in the presence of anonymous routers can efficiently infer an underlay topology with good accuracy.

(OCI-0532233), the workshop was intended to begin a discussion regarding the viability and utility of a community-oriented network measurement infrastructure. This report was published 20 December

The topology of the Internet at the Autonomous System (AS) level is not yet fully discovered despite significant research activity. The community still does not know how many links are missing, where these links are and finally, whether the missing links will change our conceptual model of the Internet topology. An accurate and complete model of the topology would be important for protocol design, performance evaluation and analyses. The goal of our work is to develop methodologies and tools to identify and validate such missing links between ASes. In this work, we develop several methods and identify a significant number of missing links, particularly of the peer-to-peer type. Interestingly, most of the missing AS links that we find exist as peer-to-peer links at the Internet Exchange Points (IXPs). First, in more detail, we provide a large-scale comprehensive synthesis of the available sources of information. We cross-validate and compare BGP routing tables, Internet Routing Registries, and traceroute data, while we extract significant new information from the less-studied Internet Exchange Points (IXPs). We identify 40 % more edges and approximately 300 % more peer-to-peer edges compared to commonly used data sets. All of these edges have been verified by either BGP tables or traceroute. Second, we identify properties of the new edges and quantify their effects on important topological properties. Given the new peer-to-peer edges, we find that for some ASes more than 50 % of their paths stop going through their ISPs assuming policy-aware routing. A surprising observation is that the degree of an AS may be a poor indicator of which ASes it will peer with.

Internet measurement studies require availability of representative topology maps. Depending on the map resolution (e.g., autonomous system level or router level), the procedure of collecting and processing an Internet topology map involves different tasks. In this paper, we present a new task, i.e., subnet inference, to advance the current state of the art in topology collection studies. Utilizing a technique to infer the subnet relations among the routers in the resulting topology map, we identify IP addresses that are connected over the same connection medium. We believe that the successful inclusion of subnet relations among the routers will yield topology maps that are closer, at the network layer, to the sampled segments of the Internet in router level topology measurement studies.