ecen4533 data communications lecture #2125 february 2013 dr. george scheets n read 11.4 n problems:...
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ECEN4533 Data CommunicationsLecture #21 25 February 2013Dr. George Scheets
ECEN4533 Data CommunicationsLecture #21 25 February 2013Dr. George Scheets
Read 11.4Read 11.4 Problems: Chapter 11.2, 4, & 5Problems: Chapter 11.2, 4, & 5 Quiz #2, 25 March (Live) Quiz #2, 25 March (Live) << 1 April (DL) 1 April (DL)
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ECEN4533 Data CommunicationsLecture #22 27 February 2013Dr. George Scheets
ECEN4533 Data CommunicationsLecture #22 27 February 2013Dr. George Scheets
Read 11.5Read 11.5 Corrected ExamsCorrected Exams
Due 6 March (Live)Due 6 March (Live) One week after return (DL)One week after return (DL)
Scan Design Problem #2Scan Design Problem #2
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ECEN4533 Data CommunicationsLecture #23 1 March 2013Dr. George Scheets
ECEN4533 Data CommunicationsLecture #23 1 March 2013Dr. George Scheets
Read 11.6.1, 11.7Read 11.6.1, 11.7 Problems Web 13-15Problems Web 13-15 Corrected ExamsCorrected Exams
Due 6 March (Live)Due 6 March (Live) One week after return (DL)One week after return (DL)
Design #2Design #2 Due 15 March (Live)Due 15 March (Live) Due 22 March (DL)Due 22 March (DL)
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RedNeckNetLow BidRedNeckNetLow Bid
Cost = $12, 643.40 per monthCost = $12, 643.40 per month
Promoted to MegaMoron Senior EngineerPromoted to MegaMoron Senior Engineer Tsega DebeleTsega Debele
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Design #2 Improved RedNeckNetDesign #2 Improved RedNeckNet Combined Traffic Options (Pick Combined Traffic Options (Pick OneOne):):
(1) Standard Internet (FIFO)(1) Standard Internet (FIFO) (2) QoS Enabled Internet(2) QoS Enabled Internet (3) ATM: VBR Video, UBR Data(3) ATM: VBR Video, UBR Data
Redundancy: Two ConnectivityRedundancy: Two Connectivity AnalysisAnalysis
Calculate Single Hop DelaysCalculate Single Hop Delays Queuing + Propagation DelaysQueuing + Propagation Delays
Multiple Hop Delays = sum of single HopsMultiple Hop Delays = sum of single Hops Make sure you account for the overhead!!!Make sure you account for the overhead!!!
Traffic Matrix is application trafficTraffic Matrix is application traffic
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Design Comments:Design Comments: Link CostsLink Costs
Proportional to distanceProportional to distance1.01.0traffictraffic0.00.0??Centralized Star is best.Centralized Star is best.
Proportional to distanceProportional to distance0.00.0traffictraffic1.01.0??Full Mesh is Best.Full Mesh is Best. Ours is proportional to distanceOurs is proportional to distance0.220.22traffictraffic0.770.77
Otherwise pay attention to traffic matrixOtherwise pay attention to traffic matrixHigh traffic node?High traffic node?Generally best to have many links.Generally best to have many links.
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Classical Queuing TheoryClassical Queuing Theory
M/x/xM/x/x Exponentially Distributed IATExponentially Distributed IAT
M/G/1, M/M/1, M/D/1 M/G/1, M/M/1, M/D/1 Single server, various packet distributionsSingle server, various packet distributions
M/M/1 with prioritiesM/M/1 with priorities M/M/aM/M/a
Several (a) output serversSeveral (a) output servers
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Real vs Artificial TraceReal vs Artificial Trace
10 SecondsReal Traffic 10 Seconds
Artificial M/M/1 Traffic
Source: Willinger et al, "Self-Similarity through High Variability", IEEE/ACM Transactions on Networking, February 1997.
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Real vs Artificial TraceReal vs Artificial Trace
100 SecondsReal Traffic 100 Seconds
Artificial M/M/1 Traffic
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Real vs Artificial TraceReal vs Artificial Trace
16.7 MinutesReal Traffic 16.7 Minutes
Artificial M/M/1 Traffic
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Real vs Artificial TraceReal vs Artificial Trace
167 MinutesReal Traffic 167 Minutes
Artificial M/M/1 Traffic
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Real vs Artificial TraceReal vs Artificial Trace
27.78 HoursReal Traffic 27.78 Hours
Artificial M/M/1 Traffic
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Self Similar BehaviorSelf Similar Behavior
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Fall 2002 FinalFall 2002 Final 'Average' based on 1 test chosen at random'Average' based on 1 test chosen at random
126.00 out of 150126.00 out of 150 One point average XOne point average X11
'Average' based on 10 tests chosen randomly'Average' based on 10 tests chosen randomly109.44 out of 150109.44 out of 150 Ten point average XTen point average X1010
Actual Midterm AverageActual Midterm Average106.85 out of 150106.85 out of 150
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Harold Edwin Hurst (1880-1978)Harold Edwin Hurst (1880-1978)
British Hydrologist
Found Long Term Dependence in Reservoir Storage.
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One way to estimate HOne way to estimate H Compute Variance of original trace, XCompute Variance of original trace, X Merge 10 consecutive points into new point YMerge 10 consecutive points into new point Y
Y = 10 point average of X Y = 10 point average of X Compute variance of this new traceCompute variance of this new trace
Merge 10 consecutive points of Y into new point ZMerge 10 consecutive points of Y into new point ZZ = 100 point average of XZ = 100 point average of XCompute variance of this new traceCompute variance of this new trace
How is variance decreasing?How is variance decreasing? By factor of N? Not self-similar, H = 0.5By factor of N? Not self-similar, H = 0.5 By factor of NBy factor of N2(1-H)2(1-H)? Evidence of self-similarity? Evidence of self-similarity
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Classical Queuing TheoryVs. Self Similar
Classical Queuing TheoryVs. Self Similar
0% 100%Offered Load
M/D/1M/M/1AverageDelay
SelfSimilar
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Traffic Rate over timeTraffic Rate over time
Source: "Dimensioning Network Links", IEEE Network Magazine, April 2009
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Carrying Capacity% of Line Speed carrying Application TrafficCarrying 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%
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Carrying CapacityCarrying Capacity Estimate Packet/Cell overhead Estimate Packet/Cell overhead Estimate Traffic Characteristics Estimate Traffic Characteristics
Classical?Classical? Self-Similar? What is Hurst Parameter?Self-Similar? What is Hurst Parameter?
Estimate allowable trunk loadEstimate allowable trunk load Delay constrained? Delay constrained? (low speed tendency)(low speed tendency) Buffer constrained? Buffer constrained? (high speed tendency)(high speed tendency)
Calculate Carrying Capacity =Calculate Carrying Capacity =(% Trunk Load)(% of Traffic in packet/cell)(% Trunk Load)(% of Traffic in packet/cell)
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Low Speed LinksLikely Delay Constrained
Plenty of Memory Available
Low Speed LinksLikely Delay Constrained
Plenty of Memory Available
0% 100%
Offered Load
AverageDelay
50%
TargetAverage
TargetMaximum
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High Speed LinksLikely Memory Constrained
Plenty of Time Available
High Speed LinksLikely Memory Constrained
Plenty of Time Available
0% 100%
Offered Load
50%
MemoryLimit
QueueSize
TargetAverage
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Circuit Switch TDM Trunking(Leased Line Telephone Network)
Circuit Switch TDM Trunking(Leased Line Telephone Network)
TDMSwitch
SONET OC-N
Fixed Rate Traffic
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 oftime slots based on peak (line) input rates.
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Carrier Leased Line NetworkCarrier Leased Line Network
Leased Line ‘Cloud’Trunk capacity shared via TDM & Circuit Switching
Cross-ConnectCross-Connect
TrunksLeased Line
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Packet Switch StatMux Trunking(Pure Internet Model)
Packet Switch StatMux Trunking(Pure Internet Model)
Router
SONET OC-N
Fixed Rate Traffic
Bursty Data Traffic
Assumptions: All traffic is packetized & Statistically Multiplexed onto the trunk BW.
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Internet Service Provider BackboneInternet Service Provider Backbone
Router
TrunksLeased Line
ISP ‘Cloud’Trunk capacity shared via StatMux & Packet Switching
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Cell Switch StatMux Trunking(ATM Model)
Cell Switch StatMux Trunking(ATM Model)
ATMSwitch
SONET OC-N
Fixed Rate Traffic
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.
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ATM BackboneATM Backbone
ATM ‘Cloud’ Trunks use StatMux/TDM & Cell Switching
ATM SwitchATM Switch
TrunksLeased Line
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Switched Network Carrying CapacitiesHigh Speed Trunk (OC-3)
Switched Network Carrying CapacitiesHigh Speed Trunk (OC-3)
0% Bursty 100% Bursty100% Fixed Rate 0% Fixed Rate
Offered Mix
Carrying Capacity
Circuit Switch TDM
Packet Switch StatMux
Cell Switch StatMux
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Traffic GrowthTraffic Growth
Voice
Data
time
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70’s & 80’s Voice Dominates70’s & 80’s Voice Dominates
Voice
Data
time70’s & 80’s
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Switched Network Carrying CapacitiesHigh Speed Trunks
Switched Network Carrying CapacitiesHigh Speed Trunks
Carrying Capacity
Circuit Switch TDM
0% Bursty 100% Bursty100% Fixed Rate 0% Fixed Rate
OfferedTraffic Mix
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Turn of the CenturyA Mixed Traffic EnvironmentTurn of the CenturyA Mixed Traffic Environment
Voice
Data
time2000
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Switched Network Carrying CapacitiesHigh Speed Trunks
Switched Network Carrying CapacitiesHigh Speed Trunks
Carrying Capacity
Cell Switch StatMux
0% Bursty 100% Bursty100% Fixed Rate 0% Fixed Rate
OfferedTraffic Mix
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Today, Data DominatesToday, Data Dominates
Voice
Data
time
2013
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Switched Network Carrying CapacitiesHigh Speed Trunks
Switched Network Carrying CapacitiesHigh Speed Trunks
Carrying Capacity
Packet Switch StatMux
0% Bursty 100% Bursty100% Fixed Rate 0% Fixed Rate
OfferedTraffic Mix
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The Big Unknown...
What impact will Video have?
The Big Unknown...
What impact will Video have?
If Video becomes dominant,If Video becomes dominant,is a packet switched statmux is a packet switched statmux network best?network best?
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ISO OSI Seven Layer ModelISO OSI Seven Layer Model
Layer 7 ApplicationLayer 7 Application Word PerfectWord Perfect Layer 6 Presentation Layer 6 Presentation Windows APIWindows API Layer 5 SessionLayer 5 Session TCP, WindowsTCP, Windows Layer 4 TransportLayer 4 Transport TCP, WindowsTCP, Windows Layer 3 NetworkLayer 3 Network IP, WindowsIP, Windows Layer 2 Data LinkLayer 2 Data Link PC NICPC NIC Layer 1 Physical Layer 1 Physical PC NICPC NIC
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