The Internet is constantly changing, and its hierarchy was recently shown to become flatter. Recent studies of inter-domain traffic showed that large content providers drive this change by bypassing tier-1 networks and reaching closer to their users, enabling them to save transit costs and reduce reliance of transit networks as new services are being deployed, and traffic shaping is becoming increasingly popular. In this paper we take a first look at the evolving connectivity of large content provider networks, from a topological point of view of the autonomous systems (AS) graph. We perform a 5-year longitudinal study of the topological trends of large content providers, by analyzing several large content providers and comparing these trends to those observed for large tier-1 networks. We study trends in the connectivity of the networks, neighbor diversity and geographical spread, their hierarchy, the adoption of IXPs as a convenient method for peering, and their centrality. Our observations indicate that content providers gradually increase and diversify their connectivity, enabling them to improve their centrality in the graph, and as a result, tier-1 networks lose dominance over time.
Kuai al @cite_37 , He al @cite_11 @cite_34 , and more recently Augustin al @cite_7 studied the AS-graph, and discuss in details methods for discovering IXP participants. These works report significantly higher number of peering relationships discovered among ASes that are IXP participants than among ASes that are not connecting via an IXP.
@cite_37 @cite_34 @cite_7 @cite_11
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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 exchange points (IXPs) are an important ingredient of the Internet AS-level ecosystem - a logical fabric of the Internet made up of about 30,000 ASes and their mutual business relationships whose primary purpose is to control and manage the flow of traffic. Despite the IXPs' critical role in this fabric, little is known about them in terms of their peering matrices (i.e., who peers with whom at which IXP) and corresponding traffic matrices (i.e., how much traffic do the different ASes that peer at an IXP exchange with one another). In this paper, we report on an Internet-wide traceroute study that was specifically designed to shed light on the unknown IXP-specific peering matrices and involves targeted traceroutes from publicly available and geographically dispersed vantage points. Based on our method, we were able to discover and validate the existence of about 44K IXP-specific peering links - nearly 18K more links than were previously known. In the process, we also classified all known IXPs depending on the type of information required to detect them. Moreover, in view of the currently used inferred AS-level maps of the Internet that are known to miss a significant portion of the actual AS relationships of the peer-to-peer type, our study provides a new method for augmenting these maps with IXP-related peering links in a systematic and informed manner. Research on performance, robustness, and evolution of the global Internet is fundamentally handicapped without accurate and thorough knowledge of the nature and structure of the contractual relationships between Autonomous Systems (ASs). In this work we introduce novel heuristics for inferring AS relationships. Our heuristics improve upon previous works in several technical aspects, which we outline in detail and demonstrate with several examples. Seeking to increase the value and reliability of our inference results, we then focus on validation of inferred AS relationships. We perform a survey with ASs' network administrators to collect information on the actual connectivity and policies of the surveyed ASs. Based on the survey results, we find that our new AS relationship inference techniques achieve high levels of accuracy: we correctly infer 96.5 customer to provider (c2p), 82.8 peer to peer (p2p), and 90.3 sibling to sibling (s2s) relationships. We then cross-compare the reported AS connectivity with the AS connectivity data contained in BGP tables. We find that BGP tables miss up to 86.2 of the true adjacencies of the surveyed ASs. The majority of the missing links are of the p2p type, which highlights the limitations of present measuring techniques to capture links of this type. Finally, to make our results easily accessible and practically useful for the community, we open an AS relationship repository where we archive, on a weekly basis, and make publicly available the complete Internet AS-level topology annotated with AS relationship information for every pair of AS neighbors. The connectivity of the Internet crucially depends on the relationships between thousands of Autonomous Systems (ASes) that exchange routing information using the Border Gateway Protocol (BGP). These relationships can be modeled as a graph, called the AS-graph, in which the vertices model the ASes, and the edges model the peering arrangements between the ASes. Based on topological studies, it is widely believed that the Internet graph contains a central dense-core: Informally, this is a small set of high-degree, tightly interconnected ASes that participate in a large fraction of end-to-end routes. Finding this dense-core is a very important practical task when analyzing the Internet's topology. In this work we introduce a randomized sublinear algorithm that finds a dense-core of the AS-graph. We mathematically prove the correctness of our algorithm, bound the density of the core it returns, and analyze its running time. We also implemented our algorithm and tested it on real AS-graph data and on real undirected version of WWW network data. Our results show that the core discovered by our algorithm is nearly identical to the cores found by existing algorithms - at a fraction of the running time.