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Quantifying Overprovisioning vs. Class-of-Service: Informing the Net Neutrality Debate Murat Yuksel (University of Nevada – Reno) yuksem@cse.unr.edu K. K. Ramakrishnan (AT&T Labs Research) kkrama@research.att.com Shiv Kalyanaraman (IBM Research India) shivkumar-k@in.ibm.com Joseph D. Houle (AT&T) jdhoule@att.com Rita Sadhvani (Verizon Wireless) rita.sadhvani@verizonwireless.com 1

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Motivation: Thick (Over-provisioned) or Thin (Engineered) Pipes? Thin: How to deal with bursts/overload? And meet premium SLAs… ! Thick: Cost of overprovisioning? Can this commodity model break even? 04000080000 10000 0 rate time [Jim Roberts et al.] Media-rich applications require performance guarantees: –e.g.: VoIP requires <300ms round-trip delay, <1% loss How to respond to these application needs? –CoS approach: provide priority (i.e. higher class) to premium traffic –Classless (best-effort) service approach: over-provision the capacity Question: How much extra capacity does the classless service require to match the performance of the higher class (premium) service in the CoS approach? 04000080000 10000 0 rate time 2

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Two Approaches: CoS vs. Classless Premium BE DD CoS Link (differentiated) D Prem = g D BE =(1-g) D D GIVEN: D, D and a performance target (i.e. t target or p target ) FIND: The minimum N that gives the same performance as in the premium class of the CoS case? N =? Classless Link (neutral) BE Scheduling (e.g. priority) 3

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REC: Required Extra Capacity REC= - = N - D (rate) = 100( N / D – 1)(%) How to quantify REC? 4

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Analytical Link Model: Poisson traffic Assume: –Poisson traffic, Exponential packet lengths for traffic in each class i.e. Premium class traffic is Poisson with g D Best-effort class traffic is Poisson with (1-g) D –The aggregate traffic for the neutral link is also Poisson with rate D 5 Both the performance target and the REC can be expressed in terms of two key parameters: (i) ρ – utilization, (ii) g – proportion of premium traffic.

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More Bursty Traffic: MMPP MMPP = Markov-Modulated Poisson Process –Easy to do the math… –Simplest MMPP is of two states. MMPP traffic with mean D –Traffic w/ equivalent rate to the neutral case, but w/ more burstiness. 1 2 Higher r means more bursty traffic. 6

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Simulated Link Model: Delay MMPP/M/1 model a=0.5, r=4 If packet size is 1KB and the CoS link is D = 1Gb/s: 5,000packets of delay = 40.1ms Surface color shows the performance target. REC can be quite high even for very small g and medium utilizations. 7

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Simulated Link Model: Delay MMPP/M/1 model a=0.5, r=4 REC increases as link utilization increases REC is large even for small proportion of premium traffic 8 Can be drawn in multiple 2-d graphs

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Simulated Link Model: Loss MMPP/M/1/K model The graphs are generic for various buffer sizes. An example: For a 10Mb/s link carrying 1KB packets: K = ~15pkts 25ms buffer time K = ~60pkts 100ms buffer time 9 REC for the same performance target decreases as buffer size increases

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Simulated Link Model: LRD Traffic 10 Internet traffic : known to be LRD with Hurst parameter value between 0.7 and 0.9. REC for Hurst=0.75 is significantly higher than our 2-state MMPP model results. We also observed that REC increases as Hurst value increases towards 0.9. DELAY – LRD/D/1 LOSS – LRD/D/1/K Also looked at closed-loop traffic - many TCP flows - and observed similar trends. We further looked at the case when Premium traffic is CBR and BE is TCP, and this increased REC further.

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Network Model Steps to calculate network REC (NREC): –Step 1: Construct the routing matrix R FxL based on shortest path Run Dijkstra’s algorithm on the topology matrices A NxN and W NxN –Step 2: Form the traffic vector Fx1 from T NxN –Step 3: Calculate the traffic load on each link: R T = Q –Step 4: Check the feasibility of the traffic load and routing For any link –If link capacity is less than the traffic load (e.g. C < Q) then update T accordingly and go to Step 2. –Step 5: Calculate the required per-link REC (i.e. N - D ) by using Q I as the traffic rate D for Ith link, and the performance goal p target or t target. Used Rocketfuel topologies for A NxN and W NxN. Used gravity model for T NxN. Made a look-up to the simulated link model results. 11

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NREC: Two ways to calculate Steps to calculate network REC (NREC) (cont’d): –Step 6: Calculate the NREC by averaging the per-link RECs from Step 5. We calculated NRECs for the Rocketfuel topologies: –Used the MMPP link model (a=0.5 and r=4) or the LRD link model (H=0.75) – Much more conservative than real or TCP traffic –Assumed K=100ms buffer time –Only report Sprintlink, as the other topologies gave higher REC values 12 total extra capacity needed on the whole network average extra capacity needed on each link

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NREC for Sprintlink: G2G Delay Solid lines are NREC I and dashed lines are NREC A 13 NREC can be much higher than 100% for a network operating with 60% utilization. 10ms queueing delay target for VoIP may require large REC values.

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NREC for Sprintlink: G2G Loss Solid lines are NREC I and dashed lines are NREC A 14 NREC can be much higher than 1000% even for a network operating with 40% utilization. 0.1% loss target may require large REC values.

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Summary A framework to study REC for delay or loss being the performance target. Link model –REC grows when: traffic becomes more bursty the utilization of the CoS link becomes higher the performance target becomes tighter the fraction g of the Premium class traffic becomes smaller –Closed-loop (e.g., TCP) or LRD traffic further increases REC Network model: –For legacy g2g performance targets, REC ranges from 50% to over 100% as g reduces below 0.5 and the utilization goes up to 60%. Future trends/work: –The performance targets will keep becoming tighter. REC is high perpetually – not just today, but in future also.. –The value of g is a crucial factor. Small g does not necessary favor a classless network. –Further research should estimate the actual costs of CoS and classless designs, as scheduling & management complexity need to be considered. 15

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Thank you! THE END 16

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