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Throughput Analysis of End-to-End Measurement Based Admission Control in IP

Throughput Analysis of End-to-End Measurement Based Admission Control in IP. G. Bianchi, A. Capone, C. Petrioli. Infocom 2000. Goals. Achieve tight QoS control over the Internet without modifying its fundamental architectural principles.

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Throughput Analysis of End-to-End Measurement Based Admission Control in IP

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  1. Throughput Analysis of End-to-End Measurement Based Admission Control in IP G. Bianchi, A. Capone, C. Petrioli. Infocom 2000

  2. Goals • Achieve tight QoS control over the Internet without modifying its fundamental architectural principles. • Whether an stateless, scalable architecture (DiffServ) can provide performance comparable to heavyweight per-flow resource management approaches.

  3. EMBAC Operation • Connection consists of two phases • Probing Phase • Data Phase • Probing Phase • Constant rate flow of packets with low priority, tagged Probing • Measure packet arrival statistics over measurement interval Tm • Based on measured statistics, indicate if resources available - send a Feedback packet • If favorable, switch to Data phase.

  4. EMBAC Features • Core routers are stateless- only differentiate between classes of packets (Probing or Data) • Probe packets do not compete with Data packets for bandwidth - router maintains two different queues. • Implies that in case of high congestion Probe packets suffer considerably which is measures at the end nodes. • Reduce Probe packet congestion by setting Probe packet life time (PLT) • All accepted connections share same loss/delay performance • Self stabilizing and robust • EMBAC throughput lower than centralized decision based scheme

  5. EMBAC Throughput analysis: Constant Rate Sources • Call arrivals, Poisson, rate /s • Tm = Constant duration of probing phase • 1/, average connection duration • Each accepted connection has data rate B • Bp = Probing rate, Bt = decision threshold rate • Bp  Bt  B • m(t) : number of probing connections at time instant t • K(t) : number of accepted connections at time instant t

  6. Analysis Contd. • Instantaneous rate Br(t) , perceived at a probing connection end point is approximated by • Use Approximation A1: Br  Br(td) • Then, due to acceptance condition Br  Bt

  7. Analysis Contd. • We get the following constraint on m(t): • Consider {K(t), m(t)} as a two-dimensional stochastic process • Approx. 2: K(t) and m(t) are independent • Number of probing connections has a poisson distribution • and one can calculate Pa(K): probability of being admitted given ‘K’ data connections • And once can then model this system as a Birth-death Markov chain, and hence calculate the throughput.

  8. Simulations

  9. Simulations

  10. Analysis VBR: Notations • B= rate during ON period • Nk(t): Number of active connections • Ton = Average period of ON state • Toff = Average period of OFF state • x(Tm,t): average number of active sources found in time interval (t-Tm,t)

  11. Simulations VBR

  12. Simulations VBR

  13. Simulations (VBR)

  14. Simulations (VBR)

  15. Simulations (VBR)

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