Effective engineering of the Internet is predicated upon a detailed understanding of issues such as the large-scale structure of its underlying physical topology, the manner in which it evolves over time, and the way in which its constituent components contribute to its overall function. Unfortunately, developing a deep understanding of these issues has proven to be a challenging task, since it in turn involves solving difficult problems such as mapping the actual topology, characterizing it, and developing models that capture its emergent behavior. Consequently, even though there are a number of topology models, it is an open question as to how representative the generated topologies they generate are of the actual Internet. Our goal is to produce a topology generation framework which improves the state of the art and is based on the design principles of representativeness, inclusiveness, and interoperability. Representativeness leads to synthetic topologies that accurately reflect many aspects of the actual Internet topology (e.g. hierarchical structure, node degree distribution, etc.). Inclusiveness combines the strengths of as many generation models as possible in a single generation tool. Interoperability provides interfaces to widely-used simulation applications such as ns and SSF and visualization tools like otter. We call such a tool a universal topology generator.

Recent empirical studies [6] have shown that Internet topologies exhibit power laws of the form Ý Ü « for the following relationships: (P1) outdegree of node (domain or router) versus rank; (P2) number of nodes versus outdegree; (P3) number of node pairs within a neighborhood versus neighborhood size (in hops); and (P4) eigenvalues of the adjacency matrix versus rank. However, causes for the appearance of such power laws have not been convincingly given. In this paper, we examine four factors in the formation of Internet topologies. These factors are (F1) preferential connectivity of a new node to existing nodes; (F2) incremental growth of the network; (F3) distribution of nodes in space; and (F4) locality of edge connections. In synthetically generated network topologies, we study the relevance of each factor in causing the aforementioned power laws as well as other properties, namely diameter, average path length and clustering coefficient. Different kinds of network topologies are generated: (T1) topologies generated using our parametrized generator, we call BRITE 1 ; (T2) random topologies generated using the well-known Waxman model [12]; (T3) Transit-Stub topologies generated using GT-ITM tool [3]; and (T4) regular grid topologies. We observe that some generated topologies may not obey power laws P1 and P2. Thus, the existence of these power laws can be used to validate the accuracy of a given tool in generating representative Internet topologies. Power laws P3 and P4 were observed in nearly all considered topologies, but different topologies showed different values of the power exponent «. Thus, while the presence of power laws P3 and P4 do not give strong evidence for the representativeness of a generated topology, the value of « in P3 and P4 can be used as a litmus test for the representativeness of a generated topology. We also find that factors F1 and F2 are the key contributors in our study which provide the resemblance of our generated topologies to that of the Internet.

In this paper we explore the evolution of both the Internet's most heavily used transport protocol, TCP, and the current network environment with respect to how the network's evolution ultimately impacts end-to-end protocols. The traditional end-to-end assumptions about the Internet are increasingly challenged by the introduction of intermediary network elements (middleboxes) that intentionally or unintentionally prevent or alter the behavior of end-to-end communications. This paper provides measurement results showing the impact of the current network environment on a number of traditional and proposed protocol mechanisms (e.g., Path MTU Discovery, Explicit Congestion Notification, etc.). In addition, we investigate the prevalence and correctness of implementations using proposed TCP algorithmic and protocol changes (e.g., selective acknowledgment-based loss recovery, congestion window growth based on byte counting, etc.). We present results of measurements taken using an active measurement framework to study web servers and a passive measurement survey of clients accessing information from our web server. We analyze our results to gain further understanding of the differences between the behavior of the Internet in theory versus the behavior we observed through measurements. In addition, these measurements can be used to guide the definition of more realistic Internet modeling scenarios. Finally, we present several lessons that will benefit others taking Internet measurements.

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In this paper we explore the current network environment with respect to how the network's evolution ultimately impacts end-to-end protocols. The traditional end-to-end assumptions about the Internet are increasingly challenged by the introduction of intermediary network elements (middleboxes) that intentionally or unintentionally prevent or alter the behavior of end-to-end communications. This paper provides measurement results showing the impact of the current network environment on a number of traditional and proposed protocol mechanisms (e.g., Path MTU Discovery, Explicit Congestion Notification, etc.). We present results of measurements taken using an active measurement framework to study web servers. We analyze our results to gain further understanding of the differences between the behavior of the Internet in theory versus the behavior we observed through measurements. In addition, these measurements can be used to guide the definition of more realistic Internet modeling scenarios.