capprobe: an efficient and accurate capacity estimation technique

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CapProbe: An Efficient CapProbe: An Efficient and Accurate Capacity and Accurate Capacity Estimation Technique Estimation Technique Rohit Kapoor**, Ling-Jyh Chen*, Rohit Kapoor**, Ling-Jyh Chen*, Li Lao*, M.Y. Sanadidi*, Mario Li Lao*, M.Y. Sanadidi*, Mario Gerla* Gerla* ** Qualcomm Corp R&D ** Qualcomm Corp R&D *UCLA Computer Science Department *UCLA Computer Science Department

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CapProbe: An Efficient and Accurate Capacity Estimation Technique. Rohit Kapoor**, Ling-Jyh Chen*, Li Lao*, M.Y. Sanadidi*, Mario Gerla* ** Qualcomm Corp R&D *UCLA Computer Science Department. 100 Mbps. 50 Mbps. 100 Mbps. 10 Mbps ( Link Capacity ). The Capacity Estimation Problem. - PowerPoint PPT Presentation

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Page 1: CapProbe: An Efficient and Accurate Capacity Estimation Technique

CapProbe: An Efficient and CapProbe: An Efficient and Accurate Capacity Estimation Accurate Capacity Estimation

TechniqueTechnique

Rohit Kapoor**, Ling-Jyh Chen*, Li Lao*, Rohit Kapoor**, Ling-Jyh Chen*, Li Lao*, M.Y. Sanadidi*, Mario Gerla*M.Y. Sanadidi*, Mario Gerla*

** Qualcomm Corp R&D** Qualcomm Corp R&D*UCLA Computer Science Department*UCLA Computer Science Department

Page 2: CapProbe: An Efficient and Accurate Capacity Estimation Technique

The Capacity Estimation ProblemThe Capacity Estimation Problem Estimate minimum link capacity on an Internet Estimate minimum link capacity on an Internet

path, as seen at the IP levelpath, as seen at the IP level

Design GoalsDesign Goals End-to-endEnd-to-end: assume no help from routers: assume no help from routers InexpensiveInexpensive: Minimal additional traffic and processing: Minimal additional traffic and processing FastFast: converges to capacity fast enough for the : converges to capacity fast enough for the

applicationapplication

100 Mbps 100 Mbps50 Mbps10 Mbps

(Link Capacity)

Page 3: CapProbe: An Efficient and Accurate Capacity Estimation Technique

ApplicationsApplications Adaptive multimedia streamingAdaptive multimedia streaming Congestion controlCongestion control Capacity planning by ISPs Capacity planning by ISPs Overlay network structuringOverlay network structuring Wireless link monitoring and mobility detectionWireless link monitoring and mobility detection

Page 4: CapProbe: An Efficient and Accurate Capacity Estimation Technique

Packet Pair DispersionPacket Pair Dispersion

T3

T2 T3

T3

T1

T3

Narrowest Link

20Mbps 10Mbps 5Mbps 10Mbps 20Mbps 8Mbps

Page 5: CapProbe: An Efficient and Accurate Capacity Estimation Technique

Ideal Packet DispersionIdeal Packet Dispersion No cross-trafficNo cross-traffic

Capacity = (Packet Size) / (Dispersion)

Page 6: CapProbe: An Efficient and Accurate Capacity Estimation Technique

Expansion of DispersionExpansion of Dispersion Cross-traffic (CT) serviced between PP packetsCross-traffic (CT) serviced between PP packets Second packet queues due to Cross Traffic (CT )=> Second packet queues due to Cross Traffic (CT )=>

expansion of dispersion =>Under-estimationexpansion of dispersion =>Under-estimation More pronounced when CT pkt size < probe pkt sizeMore pronounced when CT pkt size < probe pkt size

Page 7: CapProbe: An Efficient and Accurate Capacity Estimation Technique

Compression of DispersionCompression of Dispersion First packet queueing => compressed dispersion => First packet queueing => compressed dispersion =>

Over-estimationOver-estimation More pronounced when CT pkt size > probe pkt sizeMore pronounced when CT pkt size > probe pkt size

Page 8: CapProbe: An Efficient and Accurate Capacity Estimation Technique

Previous WorkPrevious Work Jacobson’s PathcharJacobson’s Pathchar

Estimates capacity for every linkEstimates capacity for every link Sends varying size packetsSends varying size packets Relies on round trip delaysRelies on round trip delays

Packet Pairs (PP)Packet Pairs (PP) CrovellaCrovella

• Capacity is reflected by the packet pair dispersion that Capacity is reflected by the packet pair dispersion that occurs with highest frequencyoccurs with highest frequency

LaiLai• Filters samples whose dispersion reflects a capacity Filters samples whose dispersion reflects a capacity

greater than their “potential bandwidth”greater than their “potential bandwidth” Both these techniques assume Both these techniques assume unimodal unimodal

distributiondistribution Paxson showed distribution can be Paxson showed distribution can be multimodalmultimodal

Page 9: CapProbe: An Efficient and Accurate Capacity Estimation Technique

Previous WorkPrevious Work

Dovrolis’ WorkDovrolis’ Work Analyzed under/over estimation of capacityAnalyzed under/over estimation of capacity Designed PathrateDesigned Pathrate

• First send packet pairsFirst send packet pairs• If multimodal, send packet trainsIf multimodal, send packet trains• Identifies modes to distinguish ADR (Asymptotic Identifies modes to distinguish ADR (Asymptotic

Dispersion Rate), PNCM (Post Narrow Capacity Mode) Dispersion Rate), PNCM (Post Narrow Capacity Mode) and Capacity Modes and Capacity Modes

Previously proposed techniques have relied Previously proposed techniques have relied eithereither on dispersion on dispersion oror delay delay

Page 10: CapProbe: An Efficient and Accurate Capacity Estimation Technique

Key ObservationKey Observation First packet queues more than the secondFirst packet queues more than the second

CompressionCompressionOver-estimationOver-estimation

Second packet queues more than the firstSecond packet queues more than the first• ExpansionExpansion• Under-estimationUnder-estimation

Both Both expansionexpansion and and compressioncompression are the are the result of probe packets experiencing queuingresult of probe packets experiencing queuing• Sum of PP delay includes queuing delaySum of PP delay includes queuing delay

Page 11: CapProbe: An Efficient and Accurate Capacity Estimation Technique

CapProbe ApproachCapProbe Approach

Filter PP samples that do not have minimum Filter PP samples that do not have minimum queuing timequeuing time

Dispersion of PP sample with minimum delay Dispersion of PP sample with minimum delay sum reflects capacitysum reflects capacity

CapProbe combines both dispersion and e2e CapProbe combines both dispersion and e2e transit delay informationtransit delay information

Page 12: CapProbe: An Efficient and Accurate Capacity Estimation Technique

Techniques for Convergence DetectionTechniques for Convergence Detection Consider set of packet pair probes 1…nConsider set of packet pair probes 1…n

If min(d1) + min(d2) If min(d1) + min(d2) ≠≠ min(d1+d2), dispersion obtained min(d1+d2), dispersion obtained from min delay sum may be distortedfrom min delay sum may be distorted

• Above condition increases correct detection probability to that Above condition increases correct detection probability to that of a single packet (as opposed to packet pair)of a single packet (as opposed to packet pair)

If above minimum delay sum condition is not If above minimum delay sum condition is not satisfied in a runsatisfied in a run New run, with packet size of probesNew run, with packet size of probes

• IncreasedIncreased if bandwidth estimated varied a lot across probes if bandwidth estimated varied a lot across probes Errors in dispersion measured by OSErrors in dispersion measured by OS

• DecreasedDecreased if bandwidth estimated varied little across probes if bandwidth estimated varied little across probes Packet sizes too large to go through without queuingPacket sizes too large to go through without queuing

Page 13: CapProbe: An Efficient and Accurate Capacity Estimation Technique

ExperimentsExperiments

SimulationsSimulations TCP (responsive), CBR (non-responsive), LRD TCP (responsive), CBR (non-responsive), LRD

(Pareto) cross-traffic(Pareto) cross-traffic Path-persistent, non-persistent cross-trafficPath-persistent, non-persistent cross-traffic

Page 14: CapProbe: An Efficient and Accurate Capacity Estimation Technique

SimulationsSimulations 6-hop path: capacities {10, 7.5, 5.5, 4, 6, 8} Mbps6-hop path: capacities {10, 7.5, 5.5, 4, 6, 8} Mbps PP pkt size = 200 bytes, CT pkt size = 1000 bytesPP pkt size = 200 bytes, CT pkt size = 1000 bytes Path-Persistent TCP Cross-TrafficPath-Persistent TCP Cross-Traffic

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

0 1.6 3.2 4.8 6.4 8Bandwidth Estimate (Mbps)

Fre

qu

ency

1Mbps2Mbps4Mbps

Over-Estimation

Cross Traffic Rate

Bandwidth Estimate Frequency

0

0.001

0.002

0.003

0.004

0.005

0.006

0.007

0.008

0.009

0.01

0 1.6 3.2 4.8 6.4 8Bandwidth Estimate (Mbps)

Min

Del

ay S

um

s (s

ec)

1Mbps2Mbps4Mbps

Cross Traffic Rate

Minimum Delay Sums

Page 15: CapProbe: An Efficient and Accurate Capacity Estimation Technique

SimulationsSimulations

PP pkt size = CT pkt size = 500 bytesPP pkt size = CT pkt size = 500 bytes Non-Persistent TCP Cross-TrafficNon-Persistent TCP Cross-Traffic

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

0 1.6 3.2 4.8 6.4 8Bandwidth Estimate (Mbps)

Fre

qu

ency

1Mbps

3Mbps

Under-Estimation

Bandwidth Estimate Frequency

0

0.0021

0.0042

0.0063

0 1.6 3.2 4.8 6.4 8Bandwidth Estimate (Mbps)

Min

Del

ay S

um

(se

c)

1Mbps

3Mbps

Minimum Delay Sums

Page 16: CapProbe: An Efficient and Accurate Capacity Estimation Technique

SimulationsSimulations

Non-Persistent UDP CBR Cross-TrafficNon-Persistent UDP CBR Cross-Traffic

Case where CapProbe may not workCase where CapProbe may not work UDP (non-responsive), extremely intensiveUDP (non-responsive), extremely intensive No correct samples are obtainedNo correct samples are obtained

0

0.002

0.004

0.006

0.008

0.01

0.012

0.014

0 1.6 3.2 4.8 6.4 8Bandwidth Estimate (Mbps)

Min

Del

ay S

um

s (s

ec)

1Mbps2Mbps3Mbps4Mbps

0

0.1

0.2

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1

0 1.6 3.2 4.8 6.4 8Bandwidth Estimate (Mbps)

Fre

qu

ency

1Mbps2Mbps3Mbps4Mbps

Minimum Delay SumsBandwidth Estimate

Frequency

Page 17: CapProbe: An Efficient and Accurate Capacity Estimation Technique

CapProbe AccuracyCapProbe Accuracy

Sufficient requirementSufficient requirement At least one PP sample where both packets At least one PP sample where both packets

experience experience no CT induced queuing delayno CT induced queuing delay..

How realistic is this requirement?How realistic is this requirement? Internet is reactive (mostly TCP): high chance of Internet is reactive (mostly TCP): high chance of

some probing samples not being queuedsome probing samples not being queued To validate, we performed extensive To validate, we performed extensive

experimentsexperiments• Only cases where such undistorted samples are Only cases where such undistorted samples are

not obtained is when cross-traffic is UDP and not obtained is when cross-traffic is UDP and very intensive (typically >75% load)very intensive (typically >75% load)

Page 18: CapProbe: An Efficient and Accurate Capacity Estimation Technique

Probability of Obtaining SampleProbability of Obtaining Sample

Assuming PP samples arrive in a Poisson mannerAssuming PP samples arrive in a Poisson manner Poisson cross-trafficPoisson cross-traffic: product of probabilities: product of probabilities

No queue in front of first packet: p(0) = 1 – No queue in front of first packet: p(0) = 1 – λ/μλ/μ No CT packets enter between the two packets No CT packets enter between the two packets

(conservative estimate)(conservative estimate)• Only dependent on arrival processOnly dependent on arrival process

p = p(0) p = p(0) * e* e- λL/μ- λL/μ = (1 – = (1 – λ/μ) * eλ/μ) * e- λL/μ- λL/μ Analysis also for Analysis also for DeterministicDeterministic and and ParetoPareto cross-traffic cross-traffic

Link

No Cross Traffic Packets

First Packet

No Queue

Second Packet

Page 19: CapProbe: An Efficient and Accurate Capacity Estimation Technique

Probability of Obtaining Sample (cont)Probability of Obtaining Sample (cont)

Avg number of samples required to obtain an unqueued PP for a single

link; Poisson cross-traffic

Avg number of samples required to obtain an unqueued PP for a single

link; LRD cross-traffic

Page 20: CapProbe: An Efficient and Accurate Capacity Estimation Technique

Effect of Packet Size on AccuracyEffect of Packet Size on Accuracy For CapProbe to estimate accuratelyFor CapProbe to estimate accurately

Neither packet of the PP should queue due to cross traffic Neither packet of the PP should queue due to cross traffic Second packet of PPSecond packet of PP

Smaller Smaller less chances of queuing due to cross-traffic less chances of queuing due to cross-traffic

First packet of PPFirst packet of PP Probability of queuing independent of size (queuing theory)Probability of queuing independent of size (queuing theory)

Thus, smaller PP packets Thus, smaller PP packets higher probability of sample higher probability of sample not subject to queuingnot subject to queuing

Previous authors (Dovrolis) have shown thatPrevious authors (Dovrolis) have shown that Smaller packets reduce chances of under-estimation but increase Smaller packets reduce chances of under-estimation but increase

chances of over-estimationchances of over-estimation

Page 21: CapProbe: An Efficient and Accurate Capacity Estimation Technique

Effect of Packet Size on AccuracyEffect of Packet Size on Accuracy Our observations are entirely consistent with earlier onesOur observations are entirely consistent with earlier ones

For the second packet, smaller packet size For the second packet, smaller packet size Smaller Smaller probability of being queued probability of being queued Relative probability of Relative probability of queuing of first packet is increased queuing of first packet is increased Chances of over- Chances of over-estimation are increasedestimation are increased

0

0.05

0.1

0.15

0.2

0.25

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0 1 2 3 4 5 6 7 8

Bandw idth ( Mbps)

Fre

qu

ency

(a)

0

0.02

0.04

0.06

0.08

0.1

0.12

0 1 2 3 4 5 6 7 8

Bandwidt h (M bps)

Fre

que

ncy

(b)

Frequency of occurrence of bandwidth samples when packet size of probes is (a) 100 and (b) 1500 bytes

Page 22: CapProbe: An Efficient and Accurate Capacity Estimation Technique

Measurements- Internet, Internet2 (Abilene), Measurements- Internet, Internet2 (Abilene), Wireless (802.11, Bluetooth)Wireless (802.11, Bluetooth)

ToUCLA-2 UCLA-3 UA NTNU

Time Capacity Time Capacity Time Capacity Time Capacity

CapProbe

0’03 5.5 0’01 96 0’02 98 0’07 97

0’03 5.6 0’01 97 0’04 79 0’07 97

0’03 5.5 0’02 97 0’17 83 0’22 97

Pathrate

6’10 5.6 0’16 98 5’19 86 0’29 97

6’14 5.4 0’16 98 5’20 88 0’25 97

6’5 5.7 0’16 98 5’18 133 0’25 97

Pathchar

21’12 4.0 22’49 18 3 hr 34 3 hr 34

20’43 3.9 27’41 18 3 hr 34 3 hr 35

21.18 4.0 29’47 18 3 hr 30 3 hr 35

• CapProbe implemented using PING packets, sent in pairs

Page 23: CapProbe: An Efficient and Accurate Capacity Estimation Technique

IssuesIssues CapProbe may be implemented either in the CapProbe may be implemented either in the

kernel or user modekernel or user mode Kernel mode more accurate, particularly over high-Kernel mode more accurate, particularly over high-

speed linksspeed links

One-way or round-trip estimationOne-way or round-trip estimation One-way One-way

• Requires cooperation from receiverRequires cooperation from receiver• Can be used to estimate forward/reverse linkCan be used to estimate forward/reverse link

Active vs passiveActive vs passive Probing packets Probing packets oror data packets used as probes data packets used as probes

Heavy cross-traffic/extremely fast linksHeavy cross-traffic/extremely fast links Difficulty in correct estimationDifficulty in correct estimation

Page 24: CapProbe: An Efficient and Accurate Capacity Estimation Technique

SummarySummary

CapProbe is accurate, fast, and CapProbe is accurate, fast, and inexpensive, across a wide range of inexpensive, across a wide range of scenariosscenarios

Potential applications in overlay structuring, Potential applications in overlay structuring, and in case of fast changing wireless link and in case of fast changing wireless link speedsspeeds

High-speed dispersion measurements High-speed dispersion measurements needs more investigationneeds more investigation

CapProbe website: CapProbe website: http://nrl.cs.ucla.edu/CapProbehttp://nrl.cs.ucla.edu/CapProbe