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Position Statement Debbie Perouli, PhD Student Sonia Fahmy, Associate Professor

Position Statement Debbie Perouli, PhD Student Sonia Fahmy, Associate Professor Computer Science Department Purdue University WODNAFO 10. Central Problem. Simplify an experimental scenario before we study it using simulation, emulation, or testbeds. Main Focus:

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Position Statement Debbie Perouli, PhD Student Sonia Fahmy, Associate Professor

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  1. Position Statement Debbie Perouli, PhD Student Sonia Fahmy, Associate Professor Computer Science Department Purdue University WODNAFO 10

  2. Central Problem • Simplify an experimental scenario • before we study it • using simulation, emulation, or testbeds. • Main Focus: • Preserve the important • routing characteristics • for this scenario.

  3. Characteristics of the Problem • Why simplify? Large scale (ASes, prefixes, messages) meaning high memory requirements, long execution times • What is important to preserve? Depends on the goal of the experimenter, and which properties may change with the scale • Why do it before running the experiment? This is just one approach...

  4. Where are we now? • Glenn Carl, Towards Large-Scale Testing of Policy-Based Routing via Path Algebraic and Scaled-Down Topological Modeling, Ph.D. Dissertation, The Pennsylvania State University, May 2008.

  5. References I • [DR] X. Dimitropoulos and G. Riley, Large-Scale Simulation Models of BGP, MASCOTS, 2004. • Shared memory among RIBs, Nix-vectors. Also parallel. • [HK] F. Hao and Pramod Koppol, An Internet Scale Simulation Setup for BGP, ACM SIGCOMM CCR, 2003. • Single global RIB, no TCP/IP modeling. • [LN] L. Liljenstam and D. Nicol, On-Demand Computation of Policy Based Routes for Large-Scale Network Simulation, Winter Simulation Conference, 2004. • PAO routing algorithm, no routing dynamics.

  6. Graph Topology Tools • Generators Orbis [MH]: given a set of metrics of a small graph, produce a larger graph preserving those values could we use it in the opposite way? • Reducers HBR [HF]: sampling method which produces a topology preserving the hierarchical structure of the Internet

  7. Topological Scale Down [CK] • Remove nodes through Gaussian elimination, rewire edges, modify policy configuration. • Preserves • path length, composition & ordering • import policies, i.e. local preference • Also, developed a BGP solver (no TCP/IP) based on Path Algebras.

  8. References II [CK] G. Carl and G. Kesidis, Large-Scale Testing of the Internet's Border Gateway Protocol (BGP) via Topological Scale-Down, ACM TOMACS, 2008. [KFR] J. Karlin, S. Forrest, and J. Rexford, Pretty Good BGP: Improving BGP by Cautiously Adopting Routes, ICNP, 2006. [HF] Y. He, M. Faloutsos, S. Krishnamurthy and M. Chrobak, Policy-Aware Topologies for Efficient Inter-Domain Routing Evaluations, IEEE INFOCOM Mini-Conference, 2008. [MH] Priya Mahadevan, Calvin Hubble, Dmitri Krioukov, Bradley Huffaker, and Amin Vahdat, Orbis: Rescaling Degree Correlations to Generate Annotated Internet Topologies, ACM SIGCOMM, 2007. [QU] B. Quoitin and S. Uhlig, Modelling the Routing of an Autonomous System with C-BGP, IEEE Network, 2005.

  9. Thank you! depe@purdue.edu

  10. Are graph metrics important?

  11. Metrics in Routing Papers • # of candidate or best paths • path length • # of BGP updates • protocol convergence time • end-to-end delay (intra-domain) • # of prefixes and origin • # of infected nodes or links • node degree distribution

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