The study of network topology has attracted a great deal of attention in the last decade, but has been hampered by a lack of accurate data. Existing methods for measuring topology have flaws, and arguments about the importance of these have overshadowed the more interesting questions about network structure. The Internet Topology Zoo is a store of network data created from the information that network operators make public. As such it is the most accurate large-scale collection of network topologies available, and includes meta-data that couldn't have been measured. With this data we can answer questions about network structure with more certainty than ever before - we illustrate its power through a preliminary analysis of the PoP-level topology of over 140 networks. We find a wide range of network designs not conforming as a whole to any obvious model.

/pdf/the-internet-topology-zoo-7l35zrvwl3.pdf

The Internet Topology Zoo

2005년 대한 생화학·분자생물학회 하계학술대회를 다녀와서

Since the emergence of peer-to-peer (P2P) networking in the late '90s, P2P applications have multiplied, evolved and established themselves as the leading `growth app' of Internet traffic workload. In contrast to first-generation P2P networks which used well-defined port numbers, current P2P applications have the ability to disguise their existence through the use of arbitrary ports. As a result, reliable estimates of P2P traffic require examination of packet payload, a methodological landmine from legal, privacy, technical, logistic, and fiscal perspectives. Indeed, access to user payload is often rendered impossible by one of these factors, inhibiting trustworthy estimation of P2P traffic growth and dynamics. In this paper, we develop a systematic methodology to identify P2P flows at the transport layer, i.e., based on connection patterns of P2P networks, and without relying on packet payload. We believe our approach is the first method for characterizing P2P traffic using only knowledge of network dynamics rather than any user payload. To evaluate our methodology, we also develop a payload technique for P2P traffic identification, by reverse engineering and analyzing the nine most popular P2P protocols, and demonstrate its efficacy with the discovery of P2P protocols in our traces that were previously unknown to us. Finally, our results indicate that P2P traffic continues to grow unabatedly, contrary to reports in the popular media.

/pdf/transport-layer-identification-of-p2p-traffic-4rbzzivzl9.pdf

Transport layer identification of P2P traffic

Two-person Cooperative Games

In this paper, we examine changes in Internet inter-domain traffic demands and interconnection policies. We analyze more than 200 Exabytes of commercial Internet traffic over a two year period through the instrumentation of 110 large and geographically diverse cable operators, international transit backbones, regional networks and content providers. Our analysis shows significant changes in inter-AS traffic patterns and an evolution of provider peering strategies. Specifically, we find the majority of inter-domain traffic by volume now flows directly between large content providers, data center / CDNs and consumer networks. We also show significant changes in Internet application usage, including a global decline of P2P and a significant rise in video traffic. We conclude with estimates of the current size of the Internet by inter-domain traffic volume and rate of annualized inter-domain traffic growth.

/pdf/internet-inter-domain-traffic-2uzxsfk562.pdf

Internet inter-domain traffic

Business relationships between ASes in the Internet are typically confidential, yet knowledge of them is essential to understand many aspects of Internet structure, performance, dynamics, and evolution. We present a new algorithm to infer these relationships using BGP paths. Unlike previous approaches, our algorithm does not assume the presence (or seek to maximize the number) of valley-free paths, instead relying on three assumptions about the Internet's inter-domain structure: (1) an AS enters into a provider relationship to become globally reachable; and (2) there exists a peering clique of ASes at the top of the hierarchy, and (3) there is no cycle of p2c links. We assemble the largest source of validation data for AS-relationship inferences to date, validating 34.6% of our 126,082 c2p and p2p inferences to be 99.6% and 98.7% accurate, respectively. Using these inferred relationships, we evaluate three algorithms for inferring each AS's customer cone, defined as the set of ASes an AS can reach using customer links. We demonstrate the utility of our algorithms for studying the rise and fall of large transit providers over the last fifteen years, including recent claims about the flattening of the AS-level topology and the decreasing influence of tier-1 ASes on the global Internet.

/pdf/as-relationships-customer-cones-and-validation-3hatwfq0l5.pdf

AS relationships, customer cones, and validation

Recent measurements and anecdotal evidence indicate that the Internet ecosystem is rapidly evolving from a multi-tier hierarchy built mostly with transit (customer-provider) links to a dense mesh formed with mostly peering links. This transition can have major impact on the global Internet economy as well as on the traffic flow and topological structure of the Internet. In this paper, we study this evolutionary transition with an agent-based network formation model that captures key aspects of the interdomain ecosystem, viz., interdomain traffic flow and routing, provider and peer selection strategies, geographical constraints, and the economics of transit and peering interconnections. The model predicts several substantial differences between the Hierarchical Internet and the Flat Internet in terms of topological structure, path lengths, interdomain traffic flow, and the profitability of transit providers. We also quantify the effect of the three factors driving this evolutionary transition. Finally, we examine a hypothetical scenario in which a large content provider produces more than half of the total Internet traffic.

/pdf/the-internet-is-flat-modeling-the-transition-from-a-transit-2w83x9po3h.pdf

The Internet is flat: modeling the transition from a transit hierarchy to a peering mesh

The distributed nature of the Internet makes it difficult for a single service provider to troubleshoot the disruptions experienced by its customers. We propose NetDiagnoser, a troubleshooting algorithm to identify the location of failures in an internetwork environment. First, we adapt the well-known Boolean tomography technique to work in this environment. Then, we significantly extend this technique to improve the diagnosis accuracy in the presence of multiple link failures, logical failures (for instance, misconfigurations of route export filters), and incomplete topology inference. In particular, NetDiagnoser takes advantage of rerouted paths, routing messages collected at one provider's network and Looking Glass servers. We evaluate each feature of Net-Diagnoser separately using C-BGP simulations on realistic topologies. Our results show that NetDiagnoser can successfully identify a small set of links, which almost always includes the actually failed/misconfigured links.

/pdf/netdiagnoser-troubleshooting-network-unreachabilities-using-2xbb81kyjo.pdf

NetDiagnoser: troubleshooting network unreachabilities using end-to-end probes and routing data

Our goal is to understand the evolution of the Autonomous System (AS) ecosystem over the last decade. Instead of focusing on abstract topological properties, we classify ASes into a number of "species" depending on their function and business type. Further, we consider the semantics of inter-AS links, in terms of customer-provider versus peering relations. We find that the available historic datasets from RouteViews and RIPE are not sufficient to infer the evolution of peering links, and so we restrict our focus to customer-provider links. Our findings highlight some important trends in the evolution of the Internet over the last decade, and hint at what the Internet is heading towards. After an exponential increase phase until 2001, the Internet now grows linearly in terms of both ASes and inter-AS links. The growth is mostly due to enterprise networks and content/access providers at the periphery of the Internet. The average path length remains almost constant mostly due to the increasing multihoming degree of transit and content/access providers. In recent years, enterprise networks prefer to connect to small transit providers, while content/access providers connect equally to both large and small transit providers. The AS species differ significantly from each other with respect to their rewiring activity; content/access providers are the most active. A few large transit providers act as "attractors" or "repellers" of customers. For many providers, strong attractiveness precedes strong repulsiveness by 3-9 months. Finally, in terms of regional growth, we find that the AS ecosystem is now larger and more dynamic in Europe than in North America.

https://www.cc.gatech.edu/~dovrolis/Papers/amogh-ton-rewiring.pdf

Ten years in the evolution of the internet ecosystem

Recent research results suggest that the buffers of router interfaces can be made very small, much less than the link's and width-delay product, without causing a utilization loss, as long as the link carries many TCP flows. In this letter we raise some concerns about the previous recommendation. We show that the use of such small buffers can lead to excessively high loss rates (up to 5%-15%in our simulations) in congested access links that carry many flows. Even if the link is fully utilized, small buffers lead to lower throughput for most large TCP flows, and significant variability in the per-flow throughput and transfer latency. We also discuss some important issues in router buffer sizing that are often ignored

/pdf/open-issues-in-router-buffer-sizing-4qsz0jn40q.pdf

Amogh Dhamdhere

Papers

AS relationships, customer cones, and validation

The Internet is flat: modeling the transition from a transit hierarchy to a peering mesh

NetDiagnoser: troubleshooting network unreachabilities using end-to-end probes and routing data

Ten years in the evolution of the internet ecosystem

Open issues in router buffer sizing