1 Value of Supporting Class-of- Service in IP Backbones Murat Yuksel (University of Nevada – Reno) K. K. Ramakrishnan (AT&T Labs Research) Shiv Kalyanaraman (Rensselaer Polytechnic Institute) Joseph D. Houle (AT&T) Rita Sadhvani (AT&T)
2 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? 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? rate time
3 Two Service Types: 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: What is 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)
4 REC: Required Extra Capacity REC= - = N - D (rate) = 100( N / D – 1)(%) How to quantify REC?
5 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 conservative: the superposition would be more bursty Delay: M/M/1 N = 1/t target + D Loss: M/M/1/K
6 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.
7 Simulated Link Model: Delay MMPP/M/1 model a=0.5, r=8 a=0.5, r=4 If packet size is 1KB and the CoS link is D = 10Gb/s: 5,000packets of delay = 4.1 ms REC can be quite high even for very small g and medium utilization.
8 a=0.5, r=4, K=15 Simulated Link Model: Loss MMPP/M/1/K model a=0.5, r=4, K=6 For a 1Gb/s link carrying 1KB packets: K = ~6pkts 0.1ms buffer time K = ~15pkts 0.25ms buffer time K = ~60pkts 1ms buffer time a=0.5, r=4, K=60
9 Network Model Steps to calculate REC for a network: 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.
10 Network Model: Delay Conservative MMPP: a=0.5, r=4 Abovenet Sprintlink Queuing delay range for legacy applications such as VoIP.
11 Network Model: Loss Conservative MMPP: a=0.5, r=4 Sprintlink Abovenet Reasonable buffer: K=60 pkts Loss probability range for typical ISP practices.
12 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 With conservative burstiness assumptions of MMPP traffic, REC ranges up to 100% even when g is 0.2 and the CoS link utilization is 40%. Network model: For legacy g2g performance targets, REC ranges from 50% to over 100% as g reduces below 0.5 and the CoS link utilization goes up to 60%.
13 Thank you! THE END