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ECEN4533 Data Communications Lecture #21 25 February 2013 Dr. George Scheets

ECEN4533 Data Communications Lecture #21 25 February 2013 Dr. George Scheets. Read 11.4 Problems: Chapter 11.2, 4, & 5 Quiz #2, 25 March (Live) < 1 April (DL). ECEN4533 Data Communications Lecture #22 27 February 2013 Dr. George Scheets. Read 11.5 Corrected Exams Due 6 March (Live)

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ECEN4533 Data Communications Lecture #21 25 February 2013 Dr. George Scheets

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  1. ECEN4533 Data CommunicationsLecture #21 25 February 2013Dr. George Scheets • Read 11.4 • Problems: Chapter 11.2, 4, & 5 • Quiz #2, 25 March (Live) < 1 April (DL)

  2. ECEN4533 Data CommunicationsLecture #22 27 February 2013Dr. George Scheets • Read 11.5 • Corrected Exams • Due 6 March (Live) • One week after return (DL) • Scan Design Problem #2

  3. ECEN4533 Data CommunicationsLecture #23 1 March 2013Dr. George Scheets • Read 11.6.1, 11.7 • Problems Web 13-15 • Corrected Exams • Due 6 March (Live) • One week after return (DL) • Design #2 • Due 15 March (Live) • Due 22 March (DL)

  4. RedNeckNetLow Bid MegaMoron • Cost = $12, 643.40 per month • Promoted to MegaMoron Senior Engineer • TsegaDebele

  5. Design #2 Improved RedNeckNet Combined Traffic Options (Pick One): (1) Standard Internet (FIFO) (2) QoS Enabled Internet (3) ATM: VBR Video, UBR Data Redundancy: Two Connectivity Analysis Calculate Single Hop Delays Queuing + Propagation Delays Multiple Hop Delays = sum of single Hops Make sure you account for the overhead!!! Traffic Matrix is application traffic

  6. Design Comments: Link Costs Proportional to distance1.0traffic0.0?Centralized Star is best. Proportional to distance0.0traffic1.0?Full Mesh is Best. Ours is proportional to distance0.22traffic0.77 Otherwise pay attention to traffic matrixHigh traffic node?Generally best to have many links.

  7. Classical Queuing Theory • M/x/x • Exponentially Distributed IAT • M/G/1, M/M/1, M/D/1 • Single server, various packet distributions • M/M/1 with priorities • M/M/a • Several (a) output servers

  8. Real vs Artificial Trace 10 Seconds Real Traffic 10 Seconds Artificial M/M/1 Traffic Source: Willinger et al, "Self-Similarity through High Variability", IEEE/ACM Transactions on Networking, February 1997.

  9. Real vs Artificial Trace 100 Seconds Real Traffic 100 Seconds Artificial M/M/1 Traffic

  10. Real vs Artificial Trace 16.7 Minutes Real Traffic 16.7 Minutes Artificial M/M/1 Traffic

  11. Real vs Artificial Trace 167 Minutes Real Traffic 167 Minutes Artificial M/M/1 Traffic

  12. Real vs Artificial Trace 27.78 Hours Real Traffic 27.78 Hours Artificial M/M/1 Traffic

  13. Self Similar Behavior

  14. Fall 2002 Final • 'Average' based on 1 test chosen at random126.00 out of 150 • One point average X1 • 'Average' based on 10 tests chosen randomly109.44 out of 150 • Ten point average X10 • Actual Midterm Average106.85 out of 150

  15. Harold Edwin Hurst (1880-1978) British Hydrologist Found Long Term Dependence in Reservoir Storage.

  16. One way to estimate H • Compute Variance of original trace, X • Merge 10 consecutive points into new point YY = 10 point average of X Compute variance of this new trace • Merge 10 consecutive points of Y into new point ZZ = 100 point average of XCompute variance of this new trace • How is variance decreasing? • By factor of N? Not self-similar, H = 0.5 • By factor of N2(1-H)? Evidence of self-similarity

  17. Classical Queuing TheoryVs. Self Similar Average Delay Self Similar M/M/1 M/D/1 0% 100% Offered Load

  18. Traffic Rate over time Source: "Dimensioning Network Links", IEEE Network Magazine, April 2009

  19. Carrying Capacity% of Line Speed carrying Application Traffic Line Speed Load (63% Active) 37% Idle 84% Traffic 16% Overhead Carrying Capacity = Traffic Moved/Line Speed = 84% * 63% = 53%

  20. Carrying Capacity Estimate Packet/Cell overhead Estimate Traffic Characteristics Classical? Self-Similar? What is Hurst Parameter? Estimate allowable trunk load Delay constrained? (low speed tendency) Buffer constrained? (high speed tendency) Calculate Carrying Capacity =(% Trunk Load)(% of Traffic in packet/cell)

  21. Low Speed LinksLikely Delay ConstrainedPlenty of Memory Available Average Delay Target Maximum PDF Target Average 0% 100% 50% Offered Load

  22. High Speed LinksLikely Memory ConstrainedPlenty of Time Available Queue Size Memory Limit Target Average 0% 100% 50% Offered Load

  23. Circuit Switch TDM Trunking(Leased Line Telephone Network) Fixed Rate Traffic TDM Switch SONET OC-N Bursty Data Traffic Assumptions: Fixed Rate Traffic gets fixed number of time slots. (N Bytes every 1/8000th second). Bursty Data Traffic channels get fixed number of time slots based on peak (line) input rates.

  24. Carrier Leased Line Network Trunks Leased Line Cross-Connect Leased Line ‘Cloud’ Trunk capacity shared via TDM & Circuit Switching

  25. Packet Switch StatMux Trunking(Pure Internet Model) Fixed Rate Traffic Router SONET OC-N Bursty Data Traffic Assumptions: All traffic is packetized & Statistically Multiplexed onto the trunk BW.

  26. Internet Service Provider Backbone Trunks Leased Line Router ISP ‘Cloud’ Trunk capacity shared via StatMux & Packet Switching

  27. Cell Switch StatMux Trunking(ATM Model) Fixed Rate Traffic ATM Switch SONET OC-N Bursty Data Traffic Assumptions: Fixed rate traffic moved over CBR VC's. Gets reserved bandwidth and near-TDM like service. Data or Variable Rate Traffic is StatMuxed onto the trunk bandwidth that’s not reserved for CBR.

  28. ATM Backbone Trunks Leased Line ATM Switch ATM ‘Cloud’ Trunks use StatMux/TDM & Cell Switching

  29. Switched Network Carrying CapacitiesHigh Speed Trunk (OC-3) Carrying Capacity Packet Switch StatMux Cell Switch StatMux Circuit Switch TDM 0% Bursty 100% Bursty 100% Fixed Rate 0% Fixed Rate Offered Mix

  30. Traffic Growth Data Voice time

  31. 70’s & 80’s Voice Dominates Data Voice 70’s & 80’s time

  32. Switched Network Carrying CapacitiesHigh Speed Trunks Carrying Capacity Circuit Switch TDM 0% Bursty 100% Bursty 100% Fixed Rate 0% Fixed Rate Offered Traffic Mix

  33. Turn of the CenturyA Mixed Traffic Environment Data Voice 2000 time

  34. Switched Network Carrying CapacitiesHigh Speed Trunks Carrying Capacity Cell Switch StatMux 0% Bursty 100% Bursty 100% Fixed Rate 0% Fixed Rate Offered Traffic Mix

  35. Today, Data Dominates Data Voice time 2013

  36. Switched Network Carrying CapacitiesHigh Speed Trunks Carrying Capacity Packet Switch StatMux 0% Bursty 100% Bursty 100% Fixed Rate 0% Fixed Rate Offered Traffic Mix

  37. The Big Unknown...What impact will Video have? • If Video becomes dominant,is a packet switched statmux network best?

  38. ISO OSI Seven Layer Model • Layer 7 ApplicationWord Perfect • Layer 6 Presentation Windows API • Layer 5 SessionTCP, Windows • Layer 4 Transport TCP, Windows • Layer 3 NetworkIP, Windows • Layer 2 Data Link PC NIC • Layer 1 Physical PC NIC

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