We are designing, implementing, deploying, and operating a secure measurement platform capable of performing various types of Internet infrastructure measurements and assessments. We integrate state-of-the-art measurement and analysis capabilities to try to build a coherent view of Internet topology. In September 2007 we began to use this novel architecture to support ongoing global Internet topology measurement and mapping, and are now gathering the largest set of IP topology data for use by academic researchers. We are using the best available techniques for IP topology mapping, and are developing some new techniques, as well as supporting software for data analysis, topology generation, and interactive visualization of resulting large annotated graphs. This paper presents our current results, next steps, and future goals. 1.

The topology of the Internet has been extensively studied in recent years, driving a need for increasingly complex measurement infrastructures. These measurements have produced detailed topologies with steadily increasing temporal resolution, but concerns exist about the ability of active measurement to measure the true Internet topology. Difficulties in ensuring the accuracy of every individual measurement when millions of measurements are made daily, and concerns about the bias that might result from measurement along the tree of routes from each vantage point to the wider reaches of the Internet must be addressed. However, early discussions of these concerns were based mostly on synthetic data, oversimplified models or data with limited or biased observer distributions. In this paper, we show the importance that extensive sampling from a broad distribution of vantage points has on the resulting topology and bias. We present two methods for designing and analyzing the topology coverage by vantage points: one, when system-wide knowledge exists, provides a near-optimal assignment of measurements to vantage points; while the second one is suitable for an oblivious system and is purely probabilistic. The majority of the paper is devoted to a first look at the importance of the distribution’s quality. We show that diversity in the locations and types of vantage points is required for obtaining an unbiased topology. We analyze the effect that broad distribution has over the convergence of various autonomous systems topology characteristics. We show that although diverse and broad distribution is not required for all inspected properties, it is required for some. Finally, some recent bias claims that were made against active traceroute sampling are revisited, and we empirically show that diverse and broad distribution can question their conclusions.

A growing consensus among experts is that the routing system is approaching a critical architectural breaking point [1] which any significant deployment of IPv6 will only exacerbate. The issue has recently drawn so much concern from engineering, operational, and policy communities that the Internet Architecture Board [2] held a workshop in November 2006 trying to identify the factors that limit routing scalability, and formulate a coherent statement of the problem [1]. Their conclusion was expected: the most acutely scale-limiting parameter of the current routing system is routing table size, not so much for its memory requirements as for its reaction to network dynamics. Specifically, topology changes require recalculation of routing tables, a computational burden as well as a performance hit since traffic is often delayed or even lost as nodes converge to the updated routing state. Already having articulated the need for a fundamental reexamination of the routing and concomitant addressing architecture, our previous NeTS proposal allowed us to rigorously examine and evaluate known routing schemes in pursuit of one that would work on Internet-like scale-free topologies without a radical architectural shift. We learned that there are no existing dynamic routing schemes with reasonable scalability bounds on Internet-like graphs. Our current work [3],