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					                  A Fair and Dynamic Load
                   Balancing Mechanism

                     F. Larroca and J.L. Rougier


    International Workshop on Traffic
Management and Traffic Engineering for the
              Future Internet
  Porto, Portugal, 11-12 December, 2008
          Agenda

         Introduction
         Utility Maximization Load-Balancing
         Distributed Algorithm
         Simulations
          • Packet-Level Simulations
          • Fluid-Level Comparison
         Conclusions


page 1     F. Larroca and J.L. Rougier   FITRAMEN 08, Dec. 2008
           Introduction
          Network    Convergence:
           • Traffic increasingly unpredictable and dynamic
          Classic TE techniques (i.e. over-provisioning)
           inadequate:
           • Ever-increasing access rates
           • New emerging architectures with low link capacities
          Possible answer: Dynamic Load-Balancing
           • Origin-Destination (OD) pairs with several paths:
             how to distribute its traffic?
           • Paths configured a priori and distribution dependent
             on current TM and network condition


page 2     F. Larroca and J.L. Rougier   FITRAMEN 08, Dec. 2008
           Introduction

          Network   operator interested OD pairs obtained
           performance
           • Why not state the problem in their terms?
          Analogy with Congestion Control (TCP):
           • End-hosts = OD pairs
           • Rate = OD performance indicator
          Differences:
           • Decision variable: portion of traffic sent through each
             path (total traffic is given)
           • Much larger time-scale


page 3     F. Larroca and J.L. Rougier   FITRAMEN 08, Dec. 2008
           Introduction

          Previous   proposals:
           • Define a link-cost function Fl(rl) for each link l=1..L
           • Minimize the total network’s cost
          Example:
           Limitations:
           • Indirect way of proceeding
           • Cannot prioritize an OD pair or enforce fairness




page 4     F. Larroca and J.L. Rougier   FITRAMEN 08, Dec. 2008
          Agenda

         Introduction
         Utility Maximization Load-Balancing
         Distributed Algorithm
         Simulations
          • Packet-Level Simulations
          • Fluid-Level Comparison
         Conclusions


page 5     F. Larroca and J.L. Rougier   FITRAMEN 08, Dec. 2008
           Utility Maximization Load-Balancing

          Define   a single performance indicator per OD pair
           • us(d): performance perceived by OD pair s when
             traffic distribution is d
          “Distribute” us(d) among OD pairs to maximize total
           Utility (à la Congestion Control)
                                               S
                                     max
                                          d
                                              d U
                                              s 1
                                                     s    s   (u s (d ))
           • ds = total demand of OD pair s (given)
           • dsi = traffic sent through path i of OD pair s (∑dsi= ds)
           • d = [ d11 d12 .. dS1 .. dSnS ]T
          How to define us(d)?


page 6      F. Larroca and J.L. Rougier       FITRAMEN 08, Dec. 2008
          Utility Maximization Load-Balancing

             choice for us(d): mean path’s Available
          Our
          Bandwidth (ABW)
                         us(d)   psi ABWsi  psi arg min ABWl 
                                                                  lsi

          Assumptions:
           • Majority of traffic is elastic (i.e. TCP)
           • Path choice considered propagation delay
          Advantages:
           • Mean ABW rough approximation of rate obtained by
             TCP flows (ABW is the most important indicator)
           • Sudden increases in demand may be
             accommodated

page 7     F. Larroca and J.L. Rougier   FITRAMEN 08, Dec. 2008
           Utility Maximization Load-Balancing

          Final     version of the problem:

                                          ns
                                          S
                                                       
                            max  d sU s   psi ABWsi 
                                                      
                             d  s 1      i 1        
                                                           ns
                       s.t. Rd  c, d  0,  d si  d s s
                                                          i 1
          IfABWsi is the flow obtained rate, the problem is
           very similar to Multi-Path TCP
           • By only changing ingress routers, users may be
             regarded as if they used MP-TCP: improved
             performance and more supported demands

page 8      F. Larroca and J.L. Rougier       FITRAMEN 08, Dec. 2008
          Agenda

         Introduction
         Utility Maximization Load-Balancing
         Distributed Algorithm
         Simulations
          • Packet-Level Simulations
          • Fluid-Level Comparison
         Conclusions


page 9     F. Larroca and J.L. Rougier   FITRAMEN 08, Dec. 2008
          Distributed Algorithm

       The optimization problem is not convex
       However, not too “unconvex”
       The distributed algorithm solves the dual problem
        and results in a good approximation
       Based on the Harrow-Hurwitz method: greedy on
        path utility (PU) minus path cost (PC)
            PU si  U ' (u s ) ABWsi PCsi   l
                                              ˆ
                                                             lsi

                where  l    sil and
                       ˆ
                                        s i:lsi

                                     d siU ' ( ABWl ), if l  arg minABWl 
                                     
                              sil                             lsi

                                     0, otherwise
                                     
page 10   F. Larroca and J.L. Rougier         FITRAMEN 08, Dec. 2008
          Agenda

      Introduction
      Utility Maximization Load-Balancing
      Distributed Algorithm
      Simulations
       • Packet-Level Simulations
       • Fluid-Level Comparison
      Conclusions


page 11   F. Larroca and J.L. Rougier   FITRAMEN 08, Dec. 2008
          Packet-Level Simulations

      A    simple example: all links have the same capacity
          and probabilities are updated every 50 seconds




page 12   F. Larroca and J.L. Rougier   FITRAMEN 08, Dec. 2008
          Fluid-Level Simulations

        Comparison with two and TMs:
       In two real topologies previous proposals:
          • MATE: minimize total M/M/1 delay

                                                   1
                                        min   
                                              l   ABWl
          • TeXCP: greedy on the path’s maximum utilization

       Two    performance indicators:
          • Mean ABW (us) (weighted mean, 10% quantile and
            minimum)
          • Link Utilization (mean, 90% quantile and maximum)


page 13   F. Larroca and J.L. Rougier     FITRAMEN 08, Dec. 2008
          Fluid-Level Simulations – Abilene
       Mean        ABW (us)




                             UM/MATE                         UM/TeXCP

       Link     Utilization




                         TeXCP - MATE                     TeXCP - UM
page 14   F. Larroca and J.L. Rougier   FITRAMEN 08, Dec. 2008
          Fluid-Level Simulations – Géant
       Mean        ABW (us)




                             UM/MATE                              UM/TeXCP

       Link     Utilization




                          TeXCP - MATE                            TeXCP - UM
page 15   F. Larroca and J.L. Rougier    FITRAMEN 08, Dec. 2008
          Agenda

      Introduction
      Utility Maximization Load-Balancing
      Distributed Algorithm
      Simulations
       • Packet-Level Simulations
       • Fluid-Level Comparison
      Conclusions


page 16   F. Larroca and J.L. Rougier   FITRAMEN 08, Dec. 2008
          Conclusions

         Performance as perceived by OD pairs is always better
          in UM than in MATE or TeXCP
          • MATE: relatively small differences in mean, but
            significant in the worst case
          • TeXCP: more significant differences
         Link utilization results for TeXCP and UM are very
          similar
          • MATE: although similar in mean and quantile, the
            maximum link utilization may increase significantly
         Future Work:
          • Stability
          • Other simpler methods or objective function that obtains
            similar results

page 17   F. Larroca and J.L. Rougier   FITRAMEN 08, Dec. 2008
                                        Thank you
                                        Questions?




page 18   F. Larroca and J.L. Rougier    FITRAMEN 08, Dec. 2008

				
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