Compact routing for the future internet

The Internet relies on its inter-domain routing system to allow data transfer between any two endpoints regardless of where they are located. This routing system currently uses a shortest path routing algorithm (modified by local policy constraints) called the Border Gateway Protocol. The massive growth of the Internet has led to large routing tables that will continue to grow. This will present a serious engineering challenge for router designers in the long-term, rendering state (routing table) growth at this pace unsustainable. There are various short-term engineering solutions that may slow the growth of the inter-domain routing tables, at the expense of increasing the complexity of the network. In addition, some of these require manual configuration, or introduce additional points of failure within the network. These solutions may give an incremental, constant factor, improvement. However, we know from previous work that all shortest path routing algorithms require forwarding state that grows linearly with the size of the network in the worst case. Rather than attempt to sustain inter-domain routing through a shortest path routing algorithm, compact routing algorithms exist that guarantee worst-case sub-linear state requirements at all nodes by allowing an upper-bound on path length relative to the theoretical shortest path, known as path stretch. Previous work has shown the promise of these algorithms when applied to synthetic graphs with similar properties to the known Internet graph, but they haven't been studied in-depth on Internet topologies derived from real data. In this dissertation, I demonstrate the consistently strong performance of these compact routing algorithms for inter-domain routing by performing a longitudinal study of two compact routing algorithms on the Internet Autonomous System (AS) graph over time. I then show, using the k-cores graph decomposition algorithm, that the structurally important nodes in the AS graph are highly stable over time. This property makes these nodes suitable for use as the "landmark" nodes used by the most stable of the compact routing algorithms evaluated, and the use of these nodes shows similar strong routing performance. Finally, I present a decentralised compact routing algorithm for dynamic graphs, and present state requirements and message overheads on AS graphs using realistic simulation inputs. To allow the continued long-term growth of Internet routing state, an alternative routing architecture may be required. The use of the compact routing algorithms presented in this dissertation offer promise for a scalable future Internet routing system

Multilevel MDA-Lite Paris Traceroute

Since its introduction in 2006-2007, Paris Traceroute and its Multipath Detection Algorithm (MDA) have been used to conduct well over a billion IP level multipath route traces from platforms such as M-Lab. Unfortunately, the MDA requires a large number of packets in order to trace an entire topology of load balanced paths between a source and a destination, which makes it undesirable for platforms that otherwise deploy Paris Traceroute, such as RIPE Atlas. In this paper we present a major update to the Paris Traceroute tool. Our contributions are: (1) MDA-Lite, an alternative to the MDA that significantly cuts overhead while maintaining a low failure probability; (2) Fakeroute, a simulator that enables validation of a multipath route tracing tool's adherence to its claimed failure probability bounds; (3) multilevel multipath route tracing, with, for the first time, a Traceroute tool that provides a router-level view of multipath routes; and (4) surveys at both the IP and router levels of multipath routing in the Internet, showing, among other things, that load balancing topologies have increased in size well beyond what has been previously reported as recently as 2016. The data and the software underlying these results are publicly available.Comment: Preprint. To appear in Proc. ACM Internet Measurement Conference 201

Characterizing User-to-User Connectivity with RIPE Atlas

Characterizing the interconnectivity of networks at a country level is an interesting but non-trivial task. The IXP Country Jedi is an existing prototype that uses RIPE Atlas probes in order to explore interconnectivity at a country level, taking into account all Autonomous Systems (AS) where RIPE Atlas probes are deployed. In this work, we build upon this basis and specifically focus on "eyeball" networks, i.e. the user-facing networks with the largest user populations in any given country, and explore to what extent we can provide insights on their interconnectivity. In particular, with a focused user-to-user (and/or user-to-content) version of the IXP Country Jedi we work towards meaningful statistics and comparisons between countries/economies. This is something that a general-purpose probe-to-probe version is not able to capture. We present our preliminary work on the estimation of RIPE Atlas coverage in eyeball networks, as well as an approach to measure and visualize user interconnectivity with our Eyeball Jedi tool.Comment: In Proceedings of the Applied Networking Research Workshop (ANRW '17

A Long Way to the Top: Significance, Structure, and Stability of Internet Top Lists

A broad range of research areas including Internet measurement, privacy, and network security rely on lists of target domains to be analysed; researchers make use of target lists for reasons of necessity or efficiency. The popular Alexa list of one million domains is a widely used example. Despite their prevalence in research papers, the soundness of top lists has seldom been questioned by the community: little is known about the lists' creation, representativity, potential biases, stability, or overlap between lists. In this study we survey the extent, nature, and evolution of top lists used by research communities. We assess the structure and stability of these lists, and show that rank manipulation is possible for some lists. We also reproduce the results of several scientific studies to assess the impact of using a top list at all, which list specifically, and the date of list creation. We find that (i) top lists generally overestimate results compared to the general population by a significant margin, often even an order of magnitude, and (ii) some top lists have surprising change characteristics, causing high day-to-day fluctuation and leading to result instability. We conclude our paper with specific recommendations on the use of top lists, and how to interpret results based on top lists with caution.Comment: To be published at ACM IMC 2018. Web site with live data under: https://toplists.github.i

Clusters in the expanse: Understanding and unbiasing IPv6 Hitlists

Network measurements are an important tool in understanding the Internet. Due to the expanse of the IPv6 address space, exhaustive scans as in IPv4 are not possible for IPv6. In recent years, several studies have proposed the use of target lists of IPv6 addresses, called IPv6 hitlists. In this paper, we show that addresses in IPv6 hitlists are heavily clustered. We present novel techniques that allow IPv6 hitlists to be pushed from quantity to quality. We perform a longitudinal active measurement study over 6 months, targeting more than 50 M addresses. We develop a rigorous method to detect aliased prefixes, which identifies 1.5 % of our prefixes as aliased, pertaining to about half of our target addresses. Using entropy clustering, we group the entire hitlist into just 6 distinct addressing schemes. Furthermore, we perform client measurements by leveraging crowdsourcing. To encourage reproducibility in network measurement research and to serve as a starting point for future IPv6 studies, we publish source code, analysis tools, and data