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Colored GSPN Models for the QoS Design of Internet Subnets

Colored GSPN Models for the QoS Design of Internet Subnets. Marco Ajmone Marsan IEIIT-CNR and Politecnico di Torino - Italy. Eindhoven – June 27, 2003 ICATPN 2003. Venice 1988. M y previous invited talk at ICATPN. Goal : convince researchers to use GSPN models. Today.

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Colored GSPN Models for the QoS Design of Internet Subnets

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  1. Colored GSPN Models for the QoS Design of Internet Subnets Marco Ajmone Marsan IEIIT-CNR and Politecnico di Torino - Italy Eindhoven – June 27, 2003 ICATPN 2003

  2. Venice 1988 My previous invited talk at ICATPN Goal: convince researchers to use GSPN models

  3. Today Original goal: publish a paper that I thought nobody would accept … …but the paper was accepted!

  4. Today New goal: explain why (IMO) GSPN models (and discrete-state models in general) are becoming inadequate for Internet modeling

  5. Colored GSPN Models for the QoS Design of Internet Subnets? Marco Ajmone Marsan IEIIT-CNR and Politecnico di Torino - Italy Eindhoven – June 27, 2003

  6. Outline • The Internet today • Dimensioning IP networks • GSPN and Queuing network models • Fluid approaches • Conclusions

  7. Outline • The Internet today • Dimensioning IP networks • GSPN and Queuing network models • Fluid approaches • Conclusions

  8. Source: Internet Software Consortium (http://www.isc.org/)

  9. Source: Internet Traffic Report (http://www.internettrafficreport.com/)

  10. Source: Internet Traffic Report (http://www.internettrafficreport.com/)

  11. Source: Internet Traffic Report (http://www.internettrafficreport.com/)

  12. Source: Internet Traffic Report (http://www.internettrafficreport.com/)

  13. Source: Sprint ATL (http://ipmon.sprint.com/packstat) April 7th 2003, 2.5 Gbps link

  14. Source: Sprint ATL (http://ipmon.sprint.com/packstat) April 7th 2003, 2.5 Gbps link

  15. Source: Sprint ATL (http://ipmon.sprint.com/packstat) April 7th 2003, 2.5 Gbps link

  16. Source: Sprint ATL (http://ipmon.sprint.com/packstat) April 7th 2003, 2.5 Gbps link

  17. Source: Sprint ATL (http://ipmon.sprint.com/packstat) April 7th 2003, 2.5 Gbps link

  18. Source: Sprint ATL (http://ipmon.sprint.com/packstat) April 7th 2003, 2.5 Gbps link

  19. Source: Sprint ATL (http://ipmon.sprint.com/packstat) April 7th 2003, 2.5 Gbps link

  20. Source: Sprint ATL (http://ipmon.sprint.com/packstat) April 7th 2003, 2.5 Gbps link

  21. And still growing ... Subject: [news] Internet still growing 70 to 150 per cent per year Date: Mon, 23 Jun 2003 09:55:45 -0400 (EDT) From: CAnet-NEWS@canarie.ca ... Andrew Odlyzko, director of the Digital Technology Center at the University of Minnesota, ... says Internet traffic is steadily growing about 70 percent to 150 percent per year. On a conference call yesterday to discuss the results, he said traffic growth slowed moderately over the last couple of years, but it had mostly remained constant for the past five years. ...

  22. Outline • The Internet today • Dimensioning IP networks • GSPN and Queuing network models • Fluid approaches • Conclusions

  23. Consideration • Over 90 % of all Internet traffic is due to TCP connections • TCP drives both the network behavior and the performance perceived by end-users • Analytical models of TCP are a must for IP network design and planning

  24. A TCP Primer in 10 Slides • TCP is a reliable packet transfer protocol that uses a variable window algorithm for: • Error control • Flow control • Congestion control • Two main algorithms (and a number of gadgets): • Slow start • Congestion avoidance

  25. Slow Start Algorithm • Idea: • The new segment (packet) transmission rate adapts to the ACK reception rate • The TCP transmitter “tests” the link capacity • At connection setup, cwnd = 1 segment (actually, cwnd=MSS) • At every received ACK, cwnd = cwnd + 1 • The resulting growth is exponential

  26. Time Slow Start Algorithm Host A Host B 1 segment RTT 2 segments 4 segments

  27. Slow Start: Sample Trace

  28. Congestion Avoidance Algorithm • Idea: • Slower growth of cwnd • At every ACK reception • cwnd = cwnd + 1/ cwnd • cwnd = cwnd + MSS*MSS/ cwnd (in bytes) • The resulting growth is linear • cwnd grows by 1 MSS per RTT

  29. Congestion AvoidanceSample Trace

  30. When a Segment is Lost … • …the transmitter rate has exceeded the available bandwidth • Idea: • Reset the window size (cwnd=1) • Quickly recover the transmission rate • The TCP transmitter detects the loss when the timeout expires, or 3 dupacks are received

  31. Graphically … RTO 20 congestion avoidance 15 cwnd ssthresh 10 slow start 5 Time [RTT]

  32. TCP Fairness • The congestion control algorithm in TCP is AIMD (additive increase, multiplicative decrease) • Fairness: N TCP connections sharing one bottleneck link of capacity C, obtain each C/N

  33. Fairness with 2 TCP connections • AI: linear increase • MD: proportional decrease Fair bandwidth sharing R loss: window reduced by factor 2 Throughput connection 2 congestion avoidance: AI Throughput connection 1 R

  34. AQM: RED RED P(d) 1 Pmax maxth minth Avg

  35. Consideration • Accurate TCP models must consider: • closed loop behavior • short-lived flows • multi-bottleneck topologies • AQM schemes (or droptail) • QoS approaches, two-way traffic, ...

  36. Consideration Developing accurate analytical models of the behavior of TCP is difficult. A number of approaches have been proposed, some based on sophisticated modeling tools.

  37. Outline • The Internet today • Dimensioning IP networks • GSPN and Queuing network models • Fluid approaches • Conclusions

  38. Literature T. Lakshman and U. Madhow, "The performance of TCP/IP for networks with high bandwidth-delay products and random loss," IEEE/ACM Transactions on Networking, vol. 5, no. 3, 1997. M.Ajmone Marsan, E.de Souza e Silva, R.Lo Cigno, M.Meo, “An Approximate Markovian Model for TCP over ATM”, UKPEW '97 J. Padhye, V. Firoiu, D. Towsley, J. Kurose, "A Stochastic Model of TCP Reno Congestion Avoidance and Control“, UMASS CMPSCI Technical Report, Feb 1999.

  39. Literature C.Casetti, M.Meo, “A New Approach to Model the Stationary Behavior of TCP Connections”, Infocom 2000 M.Ajmone Marsan, C.Casetti, R.Gaeta, M.Meo, “An Approximate GSPN Model for the Accurate Performance Analysis of Correlated TCP Connections”, SPECTS 2000 M.Garetto, R.Lo Cigno, M.Meo, E.Alessio, M.Ajmone Marsan, “Modeling Short-Lived TCP Connections with Open Multiclass Queueing Networks”, PfHSN 2002 A.Goel, M.Mitzenmacher, "Exact Sampling of TCP Window States", Infocom 2002

  40. Literature R.Gaeta, M.Sereno, D.Manini, "Stochastic Petri Netsmodels for the performance analysis of TCP connections supporting finite data transfer", QOS-IP 2003 R.Gaeta, M.Gribaudo, D.Manini, M.Sereno, "On the Use of Petri Netsfor the Computation of Completion Time Distributon for Short TCP Transfers", ICATPN 2003

  41. Problem statement 2 finite flows (mice) 1 greedy flows  URLs/sec IP core  URLs/sec finite flows 3 N greedy flows (elephants) 4 ...

  42. Problem statement Input variables: onlyprimitive network parameters: • IP network: channel data rates, node distances, buffer sizes, AQM algorithms (or droptail), ... • TCP: number of elephants, mice establishment rates and file length distribution, segment size, max window size, ... Output variables: • IP network: link utilizations, queuing delays, packet loss probabilities, ... • TCP: average elephant window size and throughput, average mice completion times, ...

  43. Our modeling approach TCP sub-model 1 load 1 IP network sub-model TCP sub-model N load N packet loss probabilities, queuing delays • decomposition of the whole system into subsystems: sub-models are built for groups ofhomogeneous TCP connections (same TCP version, similar RTT and routing, ...) and for the IP network. • iterative solution with FPA (Fixed Point Algorithm).

  44. Our modeling approach

  45. TCP sub-model • GSPNs or . / G /  queuesdescribe statesof the TCP protocol • tokens or customers stand for TCP connections • transition probabilities and service or firing times depend on TCP rules and network feedback (packet losses, round trip times, ...) • in the case of mice,colors or classesare introduced to represent the number of segments still to be transferred

  46. TCP sub-model(Elephants)

  47. TCP sub-model (Mice)

  48. IP network sub-model The IP network sub-model is anopen queuing network, where each queue represents an output interface of an IP router, with its buffer of finite capacity. Different queuing models were tested: • M / M / 1 / B: very simple, but only suitable when dealing with elephants and heavy load links • M [D] / M / 1 / B: to better model the traffic burstiness of mice under variable link utilization • M [D] / M [D] / 1 / B: a very accurate model, capable of coping with complex multi-bottleneck topologies

  49. Numerical results: topology Bottleneck 2 Bottleneck 1

  50. Numerical results: settings Packet size: 1000 bytes Buffer size: 64, 128, 512 packets Maximum TCP window size: 64 segments TCP tic: 0.5 s probability Flow length distribution (when mixing different flow lengths) 0.5 0.4 0.1 length (segments) 10 20 100

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