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Routing Games for Traffic Engineering
F. Larroca and J.L. Rougier
IEEE International Conference on Communications (ICC 2009)
Dresden, Germany, June 14-18 2009
page 2
Introduction Current traffic is highly dynamic and unpredictable How may we define a routing scheme that performs well
under these demanding conditions? Possible answer: Dynamic Load-Balancing
• We connect each Origin-Destination (OD) pair with several pre-established paths
• Traffic distribution depends on current TM and network condition
Greedy algorithms on path cost function fP:
• Minimum coordination• Ideal case study for game theory: Routing GameRouting Game
F. Larroca and J.L. Rougier IEEE ICC 2009
page 3
Introduction First Contribution:
• New routing game designed for elastic traffic• Basic Idea: use load-balancing to further maximize the
utility obtained by TCP flows Second Contribution:
• Performance comparison of three routing games• Considered games:
- Congestion Game
- Bottleneck Game
- Our proposition
F. Larroca and J.L. Rougier IEEE ICC 2009
page 4
Agenda
Introduction
Basic Definitions and Results
New Routing Game
Evaluation
Conclusions
F. Larroca and J.L. Rougier IEEE ICC 2009
page 5
Definitions 3 functions to define a Routing Game:
• Link cost: fl(l)
• Path cost: fP=g ({fl(l)}lϵP)
• Social Cost: SC(d) Congestion Game:
• Equilibrium minimizes instead of SC(d)
• To converge to the optimum we should use
• Example: MPLS adaptive traffic engineering (MATE) [EJLW01]
F. Larroca and J.L. Rougier IEEE ICC 2009
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page 6
Definitions 3 functions to define a Routing Game:
• Link cost: fl(l)
• Path cost: fP=g ({fl(l)}lϵP)
• Social Cost: SC(d)
Bottleneck Game:
• Equilibrium and social optimum coincide!
• Examples: TeXCP [KKDC05] and REPLEX [FKF06]
F. Larroca and J.L. Rougier IEEE ICC 2009
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page 7
Agenda
Introduction
Basic Definitions and Results
New Routing Game
Evaluation
Conclusions
F. Larroca and J.L. Rougier IEEE ICC 2009
page 8
New Routing Game: Intuition
Assume each OD pair s has exactly Ns TCP flows Congestion Control Problem (x = TCP rate):
Nsi (flows per path) are given. Why not optimize in both x and N?
First idea: à la Multi-Path TCP (optimized by end-users) Our idea: keep the separation between end-to-end
congestion control (maximization on x) and routing (maximization on N)
F. Larroca and J.L. Rougier IEEE ICC 2009
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page 9
New Routing Game: Definition First problem: Considered time-scale
• Time-Scale(TCP) << Time-Scale(Routing)
• Approximations of xsi and Nsi are necessary:
Second problem: Usi(x) is not known by routing
• Use arbitrary U(x) Result:
Equilibrium and SC optimum are not the same! However, we provide an adaptation of fl(l)
F. Larroca and J.L. Rougier IEEE ICC 2009
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page 10
Agenda
Introduction
Basic Definitions and Results
New Routing Game
Evaluation
Conclusions
F. Larroca and J.L. Rougier IEEE ICC 2009
page 11
Evaluation: simple examples Example 1:
Congestion Game is reluctant to use longer paths => bigger maximum link utilization
F. Larroca and J.L. Rougier IEEE ICC 2009
page 12
Evaluation: simple examples Example 2:
Path lengths relatively similar (even if link capacities are different) => UM and CG obtain similar results (plus: difference with BG not as important)
F. Larroca and J.L. Rougier IEEE ICC 2009
page 13
Evaluation: simple examples Example 3:
The only mechanism that enforce fairness at a path level is Utility Maximization
F. Larroca and J.L. Rougier IEEE ICC 2009
Evaluation: Realistic Topologies
page 14 F. Larroca and J.L. Rougier IEEE ICC 2009
ABWsi is always bigger in our proposal
• Not very big over CG in mean (<5%) but significant in the minimum (>15%). Origin: fairness
• More important with respect to BG Link utilization relatively similar among all games
• CG obtains a bigger maximum (5-10%)
page 15
Agenda
Introduction
Basic Definitions and Results
New Routing Game
Evaluation
Conclusions
F. Larroca and J.L. Rougier IEEE ICC 2009
page 16
Conclusions and Future Work The proposed game is the most balanced one:
• It generally outperforms the rest• When it does not, the difference is not important
However, it is more difficult to implement We are interested in the total mean delay
• Answer: Congestion Routing Game• Heavily depends on the assumed model• Load-balancing mechanism that converges to the
minimum-delay configuration without assuming any model? Yes! [LR09][LR09a]
F. Larroca and J.L. Rougier IEEE ICC 2009
page 17
References• [EJLW01]: A. Elwalid; C. Jin; S. Low and I. Widjaja "MATE: MPLS adaptive
traffic engineering" INFOCOM 2001. • [KKDC05]: S. Kandula; D. Katabi; B. Davie and A. Charny "Walking the
tightrope: responsive yet stable traffic engineering" ACM SIGCOMM '05• [FKF06]: S. Fischer; N. Kammenhuber and A. Feldmann "REPLEX: dynamic
traffic engineering based on wardrop routing policies" CoNEXT '06• [LR09]: F. Larroca and J.L. Rougier "Minimum-Delay Load-Balancing Through
Non-Parametric Regression" IFIP/TC6 NETWORKING 2009• [LR09a]: F. Larroca and J.L. Rougier "Robust Regression for Minimum-Delay
Load-Balancing" 21st International Teletraffic Congress (ITC 21)
Thank you
Questions?F. Larroca and J.L. Rougier IEEE ICC 2009