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Considering End-to-End QoS Constraints in IP Network Design and Planning

Considering End-to-End QoS Constraints in IP Network Design and Planning. M.Ajmone Marsan, M. Garetto, E. Leonardi. M. Mellia, E. Wille Dipartimento di Elettronica - Politecnico di Torino. Networks 2004. Dimensioning problem definition. Given: The traffic matrix The network topology

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Considering End-to-End QoS Constraints in IP Network Design and Planning

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  1. Considering End-to-End QoS Constraints in IP Network Design and Planning M.Ajmone Marsan, M. Garetto, E. Leonardi. M. Mellia, E. Wille Dipartimento di Elettronica - Politecnico di Torino Networks 2004

  2. Dimensioning problem definition • Given: • The traffic matrix • The network topology • The routing algorithm • Minimize: • Network cost • Over the variables: • Link capacities • Subject to: • QoS constraints

  3. Classical Approach • Open network of M/M/1 queues (with infinite buffers) • Layer-3 QoS constraint: average network-wide packet delay • TCP effects are ignored!

  4. Our new approach • Start from: User-layer End-to-End QoS constraints (SLAs) for all traffic relations • Translate QoS: • user-layer constraint  transport layer (L4) constraints • transport-layer (L4) constraint  network layer (L3) constraints • Explicitly account for TCP behavior • Use existing analytical TCP models to perform QoS translation (L4  L3) • Consider impact of TCP traffic on the network (burstiness)  more sophisticated network models

  5. Dimensioning procedure QoS translators BA problem CA problem

  6. L4L3 constraints translator • For each sd pair and flow length, invert TCP models (CSA model, PFTK formula) : • input: either the desired connection throughput or the desired file transfer latency • output: RTT and packet loss (ploss).   • one input parameter, two output parameters !

  7. L4L3 constraints translator II • Fix the maximum tolerable end-to-end loss probability (ploss) for each sd relation • Example: ploss = 0.01 • given either the minimum throughput or maximum latency find the maximum tolerable average RTT (for each sd pair)

  8. L3 Model • Each buffer in the network is modeled as a M[x]/M/1 network of queues. • CA assignment then reduces to a convex optimization problem • Problem: How can we evaluate [X]? • Use an analytical model of TCP to evaluate the window size distribution of TCP flows (given ploss and RTT).

  9. L3 Model • After the CA problem has been solved, buffers are dimensioned in such a way that end-to-end ploss constraints are satisfied. • The resulting Buffer Assignment (BA) problem is convex, but requires the evaluation of the overflow probability in M[x]/M/1/B queues.

  10. Example • Consider a single bottleneck, and suppose users traffic at peak hours is 16 Mb/s • Assign link capacity and buffer such that: • Latency for files shorter than 20 pkts is < 0.3 s • Throughput of longer flows is > 512 kbps • We fix ploss = 0.01 • QoS translators give RTT < 0.03s

  11. Single Bottleneck

  12. QoS Verification

  13. Meshed Network

  14. Meshed Network Results

  15. Results • Similar results were obtained for other topologies. • Thanks for your attention

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