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Inter-Domain Traffic Management in an Evolving Internet Peeringeco-System

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Inter-Domain Traffic Management in an Evolving Internet Peeringeco-System UNIVERSIDAD CARLOS III DE MADRID TESIS DOCTORAL INTER-DOMAIN TRAFFIC MANAGEMENT IN AN EVOLVING INTERNET PEERING ECO-SYSTEM Autor: Juan Camilo Cardona, Institute IMDEA Networks Director[/es]: Pierre Francois, Cisco Systems Rade Stanojevic, Telefonica I+D DEPARTAMENTO DE INGENIERIA´ TELEMATICA´ Leganes´ (Madrid), noviembre de 2015 UNIVERSIDAD CARLOS III DE MADRID PH.D. THESIS INTER-DOMAIN TRAFFIC MANAGEMENT IN AN EVOLVING INTERNET PEERING ECO-SYSTEM Author: Juan Camilo Cardona, Institute IMDEA Networks Director[/s]: Pierre Francois, Cisco Systems Rade Stanojevic, Telefonica I+D DEPARTMENT OF TELEMATIC ENGINEERING Leganes´ (Madrid), November 2015 Inter-domain traffic management in an evolving Internet peering eco-system A dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy Prepared by Juan Camilo Cardona, Institute IMDEA Networks Under the advice of Pierre Francois, Cisco Systems Rade Stanojevic, Telefonica I+D Departamento de Ingenier´ıa Telematica,´ Universidad Carlos III de Madrid Date: noviembre, 2015 Web/contact: [[email protected]] This work has been supported by IMDEA Networks Institute. VI TESIS DOCTORAL INTER-DOMAIN TRAFFIC MANAGEMENT IN AN EVOLVING INTERNET PEERING ECO-SYSTEM Autor: Juan Camilo Cardona, Institute IMDEA Networks Director[/es]: Pierre Francois, Cisco Systems Rade Stanojevic, Telefonica I+D Firma del tribunal calificador: Presidente: Vocal: Secretario: Calificacion:´ Leganes,´ de de Acknowledgements I learnt a lot on my own over these four years, but it is the lessons from Pierre and Rade what I appreciate the most. Pierre helped me go deeper in the networking world, by introducing me to people, anecdotes, knowledge, and experiences from the core of the industry. Rade opened my mind to the world of research, and showed me the thrill of data exploration, always in the most pragmatic way. It would have been impossible to have this professional and complementary training with a single person. I am a better engineer thanks to them. Doing research requires a lot of work and resources. I wouldn’t have been able to do much without the help of many. I would like to thank, Stefano, Nikos, Sergey, and all my other co- authors for their great help. Special thanks go to Ignacio de Castro, whose point of view helped me see the world and its problems in a very different way. I would also like to thank the operators of the anonymous Tier-2 network and of Rediris, for supporting me through their network data. I also acknowledge Pradeep Bangera for making possible to obtain the data of the latter. These years in Madrid would have been boring and lonely without the presence of many people. Thanks to Pablo and Isabel for their trust, their patience over my money saving habits, and the best pink birthday cake. To Fabio, for the always necessary football discussion, and to Chiara for her endless happiness. To Christian, for tolerating my daily complains. To Andrea, for always raising my self-esteem. To Jordi (and therefore to his complement, Mari Carmen), for being a great flat-mate and better friend. In general, thanks to my colleagues and staff of IMDEA for their great help and company. I would like to thank my parents for their support at all possible levels. I wouldn’t have been able to achieve anything abroad without them. My appreciation also goes to all my cousins, aunts, and uncles who remember me even when I am far, and are always happy to see me when I am back for a few days. Finally, my gratitude to Monica for her unworldly patience. For keep fighting, although we knew it was going to be hard. She is a cornerstone of my life. IX Abstract Operators of the Autonomous Systems (ASes) composing the Internet must deal with constant traffic growth, while striving to reduce the overall cost-per-bit and keep an acceptable quality of service. These challenges have motivated ASes to evolve their infrastructure from basic intercon- nectivity strategies, using a couple transit providers and a few settlement-free peers, to employ geographical scoped transit services (e.g. partial transit) and multiplying their peering efforts. Internet Exchange Points (IXPs), facilities allowing the establishment of sessions to multiple net- works using the same infrastructure, have hence become central entities of the Internet. Although the benefits of a diverse interconnection strategy are manifold, it also encumbers the inter-domain Traffic Engineering process and potentially increases the effects of incompatible interests with neighboring ASes. To efficiently manage the inter-domain traffic under such challenges, opera- tors should rely on monitoring systems and computer supported decisions. This thesis explores the IXP-centric inter-domain environment, the managing obstacles aris- ing from it, and proposes mechanisms for operators to tackle them. The thesis is divided in two parts. The first part examines and measures the global characteristics of the inter-domain ecosys- tem. We characterize several IXPs around the world, comparing them in terms of their number of members and the properties of the traffic they exchange. After highlighting the problems aris- ing from the member overlapping among IXPs, we introduce remote peering, an interconnection service that facilitates the connection to multiple IXPs. We describe this service and measure its adoption in the Internet. In the second part of the thesis, we take the position of the network operators. We detail the challenges surrounding the control of inter-domain traffic, and introduce an operational frame- work aimed at facilitating its management. Subsequently, we examine methods that peering co- ordinators and network engineers can use to plan their infrastructure investments, by quantifying the benefits of new interconnections. Finally, we delve into the effects of conflicting business ob- jectives among ASes. These conflicts can result in traffic distributions that violate the (business) interests of one or more ASes. We describe these interest violations, differentiating their impact on the ingress and egress traffic of a single AS. Furthermore, we develop a warning system that operators can use to detect and rank them. We test our warning system using data from two real networks, where we discover a large number of interest violations. We thus stress the need for operators to identify the ones having a larger impact on their network. XI Table of Contents Acknowledgements IX Abstract XI Table of Contents XIII List of Abbreviations XVIII List of Tables XIX 1. Introduction 1 1.1. Part one: Characterizing the IXP-centric Internet ecosystem . 4 1.2. Part two: Inter-domain Traffic Management . 5 1.3. Thesis structure . 5 1.4. Summary of thesis contributions and publications . 6 List of Figures 1 2. Background 9 2.1. Economic relationships between ASes . 9 2.2. Introduction to BGP . 10 2.2.1. BGP sessions . 11 2.2.2. BGP Policy and decision process . 12 2.3. Inter-domain Traffic Engineering . 13 2.4. Internet Exchange Points and Internet flattening . 15 I Characterizing the IXP-centric Internet ecosystem 17 3. Overview of IXP characteristics 19 3.1. Comparing number of members and maximum traffic . 19 3.2. Overlapping among IXPs . 22 3.2.1. Number of unique members . 23 XIII XIV TABLE OF CONTENTS 3.2.2. Inter-domain routing reachability . 24 3.3. Short and long term trends in IXP traffic: A weather impact study . 26 3.3.1. Datasets description . 28 3.3.2. Short-term effects: Traffic vs. precipitation . 29 3.3.3. Long-term effects: Demand vs. temperature . 32 3.4. Related Work . 34 3.5. Summary . 34 4. History of an IXP 37 4.1. The dataset . 37 4.2. Evolution of SIX . 39 4.2.1. Peering matrix . 40 4.2.2. Traffic dynamics . 42 4.2.3. Capacity and utilization dynamics . 43 4.2.4. Traffic matrix dynamics . 45 4.3. Discussion . 46 4.4. Related work . 47 4.5. Summary . 48 5. Remote Peering 51 5.1. Introduction to remote peering . 52 5.1.1. Technical aspects . 52 5.1.2. Economical aspects . 53 5.2. Spread of remote peering . 54 5.2.1. Measurement methodology . 54 5.2.2. Experimental results . 58 5.2.3. Method validation . 60 5.3. Discussion: Remote peering repercussions in the Internet infrastructure . 61 5.4. Related work . 63 5.5. Summary . 64 II Inter-domain Traffic Management 65 6. Framework for Inter-domain traffic Management 67 6.1. Introduction . 67 6.2. Data Collection . 68 6.2.1. Collecting received BGP paths and paths installed in FIB . 69 6.2.2. Collecting traffic data . 70 6.2.3. Collecting external AS policies . 70 6.2.4. Collecting network infrastructure and Shared Risk Link Groups . 71 TABLE OF CONTENTS XV 6.2.5. Collecting path performance details . 71 6.2.6. Collecting internal Policies . 72 6.3. Simulation . 72 6.3.1. Simulation for inter-domain outbound traffic . 72 6.3.2. Simulation for inter-domain Inbound traffic . 73 6.4. Validation and verification . 73 6.5. Optimization . 75 6.6. Operation . 76 6.7. Related Work . 77 6.8. Summary . 77 7. Peering expansion using remote peering 79 7.1. Traffic data . 79 7.2. Offload scenarios and evaluation . 81 7.2.1. Offload evaluation results . 82 7.3. Quantifying other benefits . 85 7.4. Related Work . 88 7.5. Summary . 88 8. Detecting inter-domain policy conflicts 91 8.1. Interest violations from the Perspective of a Single AS . 94 8.1.1. Outbound interest violations . 94 8.1.2. Inbound interest violations . 96 8.2. Detection of interest violations . 97 8.2.1. Detection of Outbound Violations . 98 8.2.2. Detection of inbound Violations . 101 8.3. System architecture . 103 8.3.1. General Architecture . 104 8.3.2. Implementation . 105 8.4. Evaluation . 108 8.4.1.
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