Towards Reproducing Inter-Domain AS Paths

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1 Lehrstuhl für Netzwerkarchitekturen Faktultät für Informatik Technische Universität München Diplomarbeit Towards Reproducing Inter-Domain AS Paths Wolfgang Mühlbauer 15th November 2005 Aufgabenstellerin: Prof. Anja Feldmann, Ph.D. Betreuer: Olaf Maennel

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3 Erklärung Ich versichere, dass ich diese Diplomarbeit selbständig verfasst und nur die angegebenen Quellen und Hilfsmittel verwendet habe. Wolfgang Mühlbauer München, 15. November 2005 iii

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5 Kurzfassung Das Internet setzt sich aus ungefähr autonomen Systemen (AS) zusammen. Diese werden in der Regel von verschiedenen Instanzen betrieben und stehen miteinander im Wettbewerb. Ungeachtet dieser Tatsache, muss die weltweite Erreichbarkeit gewährleistet sein, unter gleichzeitiger Beibehaltung der Autonomie der einzelnen Teilnetze: Jedes AS kann Verkehrslenkungsstrategien (Routing Policies) definieren, welche eigene wirtschaftliche oder technische Interessen berücksichtigen. Bedauerlicherweise mangelt es immer noch einem grundlegenden Verständnis des komplexen Zusammenspiels zwischen den einzelnen autonomen Systemen. Im Rahmen dieser Diplomarbeit stellen wir eine Methode vor, welche die in der Realität gewählten Wege möglichst genau in Simulationen nachbildet. Auf der Basis eines AS Graphen, der aus realen Wegewahl-Tabellen ermittelt wird, wird ein einfaches Simulationsmodell erstellt. Die anfängliche Vernachlässigung von Policies führt im allgemeinen dazu, dass sich die simulierten Wege von den Pfaden unterscheiden, die man in der Realität beobachten kann. Im folgenden wird die Simulation schrittweise verfeinert, mit dem Ziel die simulierten Wegewahl(Routing)-Entscheidungen mit der Realität in Einklang zu bringen. Internetdienstanbieter (ISPs) können von solchen realistischen Simulationen in vielerlei Hinsicht profitieren. Leichtere Diagnose von auftretenden Problemen, Optimierung der Netzwerkleistung, Erkennen von Peering Nachbarn, ebenso wie eine Verbesserung der Anbindung an das restliche Internet, sind nur einige wenige Beispiele. In der wissenschaftlichen Welt können solche Simulationen einen Beitrag zur Entwicklung von ausgereifteren Techniken in der Verkehrskapazitätsplanung (traffic engineering) leisten oder helfen das Zusammenspiel zwischen Routingschicht und darüberliegenden Netzwerkebenen (overlay networks) besser zu verstehen. v

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7 Abstract Today s Internet is composed of approximately 20,000 competing autonomous systems (ASes) which have to cooperate with each other to provide global reachability. Each AS is controlled by different administrative entities, and therefore encodes various economic, business, and performance decisions in its routing policy. Unfortunately, the complex interactions arising from such a distributed system are still poorly understood. In this thesis, we present a methodology to reproduce the BGP inter-domain routing decisions as realistically as possible by means of simulation. We start with a simple simulation model, relying solely on an AS graph which is derived from BGP table dumps. Due to missing policies, the routes chosen in the simulation will be different from those observed in reality. In an iterative process, we try to refine our simulation to accommodate the simulated routing decisions with those observed in reality. Such an Internet-wide simulation technique can be very valuable for ISPs to diagnose problems, optimize network performance, identify peering partners and provide better connectivity to the rest of the Internet. In addition, researchers can benefit from such a model. The design of more sophisticated traffic engineering techniques, as well as a better understanding of the interplay between the routing layer and overlay networks are only two applications. vii

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10 List of Figures 2.1 Update processing per router Example: update propagation Example: Path sections of ASes Initial setup Empirical cumulative distribution function (ECDF) of the average number of Rib-In entries per prefix Frequency of number of distinct AS paths selected by routers inside the same AS Frequency of the number of distinct AS paths selected by the transit routers during the 10 simulation runs Histogram of the number of route changes inside a transit AS if random IGP weights are assigned Principle of the route reflector experiment Empirical cumulative distribution functions (ECDF) of the number of distinct AS paths inside transit ASes for the two scenarios Basic intra-domain topologies (from left to right: route reflector, full mesh, isolated nodes) Route reflectors impose an additional step of filtering Example topology with two ASes Input files for generation a C-BGP script file ibgp sessions unequal to physical links (Y uses direct link over X) Basic approach for simulation refinement and validation Splitting heuristic (arrows indicate traffic flows) Nondeterminism of splitting heuristic (arrows indicate traffic flow) Histogram and estimated density of the number of routers per AS Filter detection heuristic - basic idea (arrows indicate traffic flow) Per-prefix heuristic applied at AS 1 (arrows indicate traffic flow) Problem of direct Loc-RIB matches (arrows indicate traffic flows) Per-prefix heuristic: number of routers per AS A.1 divergence due to local-pref and filter Misconfigurations

11 List of Tables 3.1 Raw data collection (broken down by Public and Akamai data) Basic statistics on used raw data (including Public and Akamai) Comparison of Public and Akamai data Final steps needed in the BGP decision process (one router per AS, prefix at AS 3320) Full mesh ibgp - final steps needed in the BGP decision process IGP weights - final step needed in the BGP decision process implementation of standard policies Splitting heuristic - results for Public-Sample and Akamai-Sample Filter detection - results for Public-Sample and Akamai-Sample Results for per-prefix heuristic Comparison of the presented heuristic B.1 Overview on used scripts B.2 Command-line arguments for CBGPInputGenerator.pl B.3 Command-line arguments for runsim.pl B.4 Command-line arguments for runsimforprefixes.pl B.5 Command-line arguments for analyzesimresults.pl B.6 Command-line arguments for splittingheuristic.pl B.7 Command-line arguments for filteringheuristic.pl B.8 Command-line arguments for perprefixheuristic.pl

12 List of Algorithms 1 Splitting Heuristic Filter Detection Per-prefix heuristic (one iteration)

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