An Economically-Principled Generative Model of AS Graph Connectivity

End-to-end packet delivery in the Internet is achieved through a system of interconnections between the network domains of independent entities called Autonomous Systems (ASes). Inter-domain connections are the result of a complex

An Economically Principled Generative Model of AS Graph Connectivity

We explore the problem of modeling Internet connectivity at the Autonomous System (AS) level and present an economically-principled dynamic model that reproduces key features of the AS graph structure. We view the graph as the outcome of optimizing decisions made by each AS given its business model. In our model, nodes (representing ASs) arrive over time and choose and change providers to maximize their utility. Our formulation of AS utility includes revenue from an AS’s own generated demand for traffic, congestion and routing costs, as well as transfers to and from provider and customer ASs, respectively. Our model has the following features: it uses an empirically-motivated model of traffic demand (Chang, Jamin, Mao, Willinger, 2005) which considers the variation in demand with ASs’ business models and the graph of business relationships; it allows for nodes to revise their connections over time, in a fashion similar to the well-known ‘forest fire’ model (Leskovec, Kleinberg, Faloutsos, 2005); a node’s utility explicitly models many of the major economic and technological issues at play. We validate our model-generated graphs against those of other generative models. Building on previous work that has shown that rule-based generative models like preferential attachment yield poorly-performing traffic routing graphs (Li, Alderson, Doyle, Willinger, 2006), we show that our graphs perform well as designed, engineered systems, while retaining measured statistical properties of the AS graph.Engineering and Applied Science

Provider and peer selection in the evolving internet ecosystem

The Internet consists of thousands of autonomous networks connected together to provide end-to-end reachability. Networks of different sizes, and with different functions and business objectives, interact and co-exist in the evolving "Internet Ecosystem". The Internet ecosystem is highly dynamic, experiencing growth (birth of new networks), rewiring (changes in the connectivity of existing networks), as well as deaths (of existing networks). The dynamics of the Internet ecosystem are determined both by external "environmental" factors (such as the state of the global economy or the popularity of new Internet applications) and the complex incentives and objectives of each network. These dynamics have major implications on how the future Internet will look like. How does the Internet evolve? What is the Internet heading towards, in terms of topological, performance, and economic organization? How do given optimization strategies affect the profitability of different networks? How do these strategies affect the Internet in terms of topology, economics, and performance? In this thesis, we take some steps towards answering the above questions using a combination of measurement and modeling approaches. We first study the evolution of the Autonomous System (AS) topology over the last decade. In particular, we classify ASes and inter-AS links according to their business function, and study separately their evolution over the last 10 years. Next, we focus on enterprise customers and content providers at the edge of the Internet, and propose algorithms for a stub network to choose its upstream providers to maximize its utility (either monetary cost, reliability or performance). Third, we develop a model for interdomain network formation, incorporating the effects of economics, geography, and the provider/peer selections strategies of different types of networks. We use this model to examine the "outcome" of these strategies, in terms of the topology, economics and performance of the resulting internetwork. We also investigate the effect of external factors, such as the nature of the interdomain traffic matrix, customer preferences in provider selection, and pricing/cost structures. Finally, we focus on a recent trend due to the increasing amount of traffic flowing from content providers (who generate content), to access providers (who serve end users). This has led to a tussle between content providers and access providers, who have threatened to prioritize certain types of traffic, or charge content providers directly -- strategies that are viewed as violations of "network neutrality". In our work, we evaluate various pricing and connection strategies that access providers can use to remain profitable without violating network neutrality.Ph.D.Committee Chair: Dovrolis, Constantine; Committee Member: Ammar, Mostafa; Committee Member: Feamster, Nick; Committee Member: Willinger, Walter; Committee Member: Zegura, Elle