Abstract—The use of peer-to-peer (P2P) applications is growing dramatically, particularly for sharing large video/audio files and software. In this paper, we analyze P2P traffic by measuring flowlevel information collected at multiple border routers across a large ISP network, and report our investigation of three popular P2P systems—FastTrack, Gnutella, and Direct-Connect. We characterize the P2P trafffic observed at a single ISP and its impact on the underlying network. We observe very skewed distribution in the traffic across the network at different levels of spatial aggregation (IP, prefix, AS). All three P2P systems exhibit significant dynamics at short time scale and particularly at the IP address level. Still, the fraction of P2P traffic contributed by each prefix is more stable than the corresponding distribution of either Web traffic or overall traffic. The high volume and good stability properties of P2P traffic suggests that the P2P workload is a good candidate for being managed via application-specific layer-3 traffic engineering in an ISP’s network. Index Terms—File sharing, peer-to-peer, P2P, traffic characterization, traffic measurement.

The Border Gateway Protocol (BGP) allows an autonomous system (AS) to apply diverse local policies for selecting routes and propagating reachability information to other domains. However, BGP permits ASes to have conflicting policies that can lead to routing instability. This paper proposes a set of guidelines for an AS to follow in setting its routing policies, without requiring coordination with other ASes. Our ap-proach exploits the Internet's hierarchical structure and the commercial relationships between ASes to impose a partial order on the set of routes to each destination. The guide-lines conform to conventional traffic-engineering practices of ISPs, and provide each AS with significant flexibility in se-lecting its local policies. Furthermore, the guidelines ensure route convergence even under changes in the topology and routing policies. Drawing on a formal model of BGP, we prove that following our proposed policy guidelines guaran-tees route convergence. We also describe how our method-ology can be applied to new types of relationships between ASes, how to verify the hierarchical AS relationships, and how to realize our policy guidelines. Our approach has sig-nificant practical value since it preserves the ability of each AS to apply complex local policies without divulging its BGP configurations to others. 1.

Traceroute is widely used to detect routing problems, characterize end-to-end paths, and discover the Internet topology. Providing an accurate list of the Autonomous Systems (ASes) along the forwarding path would make traceroute even more valuable to researchers and network operators. However, conventional approaches to mapping traceroute hops to AS numbers are not accurate enough. Address registries are often incomplete and out-of-date. BGP routing tables provide a better IP-to-AS mapping, though this approach has significant limitations as well. Based on our extensive measurements, about 10% of the traceroute paths have one or more hops that do not map to a unique AS number, and around 15% of the traceroute AS paths have an AS loop. In addition, some traceroute AS paths have extra or missing AS hops due to Internet eXchange Points, sibling ASes managed by the same institution, and ASes that do not advertise routes to their infrastructure. Using the BGP tables as a starting point, we propose techniques for improving the IP-to-AS mapping as an important step toward an AS-level traceroute tool. Our algorithms draw on analysis of traceroute probes, reverse DNS lookups, BGP routing tables, and BGP update messages collected from multiple locations. We also discuss how the improved IP-to-AS mapping allows us to home in on cases where the BGP and traceroute AS paths differ for legitimate reasons.

Following the long-held belief that the Internet is hierarchical, the network topology generators most widely used by the Internet research community, Transit-Stub and Tiers, create networks with a deliberately hierarchical structure. However, in 1999 a seminal paper by Faloutsos et al. revealed that the Internet's degree distribution is a power-law. Because the degree distributions produced by the Transit-Stub and Tiers generators are not power-laws, the research community has largely dismissed them as inadequate and proposed new network generators that attempt to generate graphs with power-law degree distributions.

Recent studies concerning the Internet connectivity at the AS level have attracted considerable attention. These studies have exclusively relied on the BGP data from Oregon route-views [1] to derive some unexpected and intriguing results. The Oregon route-views data sets reflect AS peering relationships, as reported by BGP, seen from a handful of vantage points in the global Internet. The possibility that these data sets from Oregon route-views may provide only a very sketchy picture of the complete inter-AS connections that exist in the actual Internet has received surprisingly little scrutiny. In this paper, we will use the term "AS peering relationship" to mean that there is "at least one direct router-level connection" between two existing ASs, and that these two ASs agree to exchange traffic by enabling BGP between them. By augmenting the Oregon route-views data sets with BGP summary information from a large number of Internet Looking Glass sites and with routing policy information from Internet Routing Registry (IRR) databases, we find that (1) a significant number of existing AS connections remain hidden from most BGP routing tables, (2) the AS connections to tier-1 ASs are in general more easily observed than those to non tier-1 ASs, and (3) there are at least about 25--50% more AS connections in the Internet than commonly-used BGP-derived AS maps reveal (but only about 2% more ASs). These findings point out the need for an increased awareness of and a more critical attitude toward the applicability and completeness of given data sets at hand when establishing the generality of any particular observations about the Internet.

Recent work has focused on increasing availability in the face of Internet path failures. To date, proposed solutions have relied on complex routing and pathmonitoring schemes, trading scalability for availability among a relatively small set of hosts. This paper proposes a simple, scalable approach to recover from Internet path failures. Our contributions are threefold. First, we conduct a broad measurement study of Internet path failures on a collection of 3,153 Internet destinations consisting of popular Web servers, broadband hosts, and randomly selected nodes. We monitored these destinations from 67 PlanetLab vantage points over a period of seven days, and found availabilities ranging from 99.6 % for servers to 94.4 % for broadband hosts. When failures do occur, many appear too close to the destination (e.g., last-hop and end-host failures) to be mitigated through alternative routing techniques of any kind. Second, we show that for the failures that can be addressed through routing, a simple, scalable technique, called one-hop source routing, can achieve close to the maximum benefit available with very low overhead. When a path failure occurs, our scheme attempts to recover from it by routing indirectly through a small set of randomly chosen intermediaries. Third, we implemented and deployed a prototype onehop source routing infrastructure on PlanetLab. Over a three day period, we repeatedly fetched documents from 982 popular Internet Web servers and used one-hop source routing to attempt to route around the failures we observed. Our results show that our prototype successfully recovered from 56 % of network failures. However, we also found a large number of server failures that cannot be addressed through alternative routing. Our research demonstrates that one-hop source routing is easy to implement, adds negligible overhead, and achieves close to the maximum benefit available to indirect routing schemes, without the need for path monitoring, history, or a-priori knowledge of any kind. 1

A detailed understanding of the many facets of the Internet's topological structure is critical for evaluating the performance of networking protocols, for assessing the effectiveness of proposed techniques to protect the network from nefarious intrusions and attacks, or for developing improved designs for resource provisioning. Previous studies of topology have focused on interpreting measurements or on phenomenological descriptions and evaluation of graph-theoretic properties of topology generators. We propose a complementary approach of combining a more subtle use of statistics and graph theory with a first-principles theory of router-level topology that reflects practical constraints and tradeoffs. While there is an inevitable tradeoff between model complexity and fidelity, a challenge is to distill from the seemingly endless list of potentially relevant technological and economic issues the features that are most essential to a solid understanding of the intrinsic fundamentals of network topology. We claim that very simple models that incorporate hard technological constraints on router and link bandwidth and connectivity, together with abstract models of user demand and network performance, can successfully address this challenge and further resolve much of the confusion and controversy that has surrounded topology generation and evaluation.

Embedding of a graph metric in Euclidean space efficiently and accurately is an important problem in general with applications in topology aggregation, closest mirror selection, and application level routing. We propose a new graph embedding scheme called Big-Bang Simulation (BBS), which simulates an explosion of particles under force field derived from embedding error. BBS is shown to be significantly more accurate, compared to all other embedding methods including GNP. We report an extensive simulation study of BBS compared with several known embedding schemes and show its advantage for distance estimation (as in the IDMaps project), mirror selection and topology aggregation.

This paper presents a methodology for identifying the autonomous system (or systems) responsible when a routing change is observed and propagated by BGP. The origin of such a routing instability is deduced by examining and correlating BGP updates for many prefixes gathered at many observation points. Although interpreting BGP updates can be perplexing, we find that we can pinpoint the origin to either a single AS or a session between two ASes in most cases. We verify our methodology in two phases. First, we perform simulations on an AS topology derived from actual BGP updates using routing policies that are compatible with inferred peering /customer/provider relationships. In these simulations, in which network and router behavior are "ideal", we inject inter-AS link failures and demonstrate that our methodology can effectively identify most origins of instability. We then develop several heuristics to cope with the limitations of the actual BGP update propagation process and monitoring infrastructure, and apply our methodology and evaluation techniques to actual BGP updates gathered at hundreds of observation points. This approach of relying on data from BGP simulations as well as from measurements enables us to evaluate the inference quality achieved by our approach under ideal situations and how it is correlated with the actual quality and the number of observation points.

Conventional wisdom has been that the performance limitations in the current Internet lie at the edges of the network – i.e last mile connectivity to users, or access links of stub ASes. As these links are upgraded, however, it is important to consider where new bottlenecks and hot-spots are likely to arise. In this paper, we address this question through an investigation of non-access bottlenecks. These are links within carrier ISPs or between neighboring carriers that could potentially constrain the bandwidth available to longlived TCP flows. Through an extensive measurement study, we discover, classify, and characterize bottleneck links (primarily in the U.S.) in terms of their location, latency, and available capacity. We find that about 50 % of the Internet paths explored have a nonaccess bottleneck with available capacity less than 50 Mbps, many of which limit the performance of well-connected nodes on the Internet today. Surprisingly, the bottlenecks identified are roughly equally split between intra-ISP links and peering links between ISPs. Also, we find that low-latency links, both intra-ISP and peering, have a significant likelihood of constraining available bandwidth. Finally, we discuss the implications of our findings on related issues such as choosing an access provider and optimizing routes through the network. We believe that these results could be valuable in guiding the design of future network services, such as overlay routing, in terms of which links or paths to avoid (and how to avoid them) in order to improve performance.