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Tango1 Considering End-to-End QoS Constraints in IP Network Design and Planning M.Ajmone Marsan, M. Garetto, E. Leonardi. M. Mellia, E. Wille Dipartimento.

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Presentation on theme: "Tango1 Considering End-to-End QoS Constraints in IP Network Design and Planning M.Ajmone Marsan, M. Garetto, E. Leonardi. M. Mellia, E. Wille Dipartimento."— Presentation transcript:

1 Tango1 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 Tango2 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 Tango3 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 Tango4 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 Tango5 Dimensioning procedure QoS translators CA problem BA problem

6 Tango6 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 (p loss ).  one input parameter, two output parameters !

7 Tango7 L4  L3 constraints translator II  Fix the maximum tolerable end-to-end loss probability (p loss ) for each s  d relation  Example: p loss = 0.01  given either the minimum throughput or maximum latencyfind the maximum tolerable average RTT (for each s  d pair)

8 Tango8 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 p loss and RTT).

9 Tango9 L3 Model  After the CA problem has been solved, buffers are dimensioned in such a way that end-to-end p loss 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 Tango10 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 p loss = 0.01  QoS translators give RTT < 0.03s

11 Tango11 Single Bottleneck M[x]/M/1/B (new approach) M/M/1/B (classic approach) Link utilization 0.640.93 C [Mb/s]2517 B [pkts]7928

12 Tango12 QoS Verification CSAM/M/1 M[x]/M/1 Flow length (pkts) DropTailREDDropTailRED 10.05s1.84s1.56s0.08s0.05s 20.08s2.12s2.31s0.09s0.08s 40.12s2.443.71s0.12s0.11s 100.20s2.84s5.26s0.15s0.16s 190.26s3.16s10.41s0.18s0.19s 1952.0Mbs180kbs15kbs5.2Mbs5.1Mbs

13 Tango13 Meshed Network

14 Tango14 Meshed Network Results

15 Tango15 Results  Similar results were obtained for other topologies.  Thanks for your attention


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