Analyzing and - PowerPoint Presentation

test . @test

400 views
Uploaded On 2016-06-27

Analyzing and - PPT Presentation

Improving BitTorrent Ashwin R Bharambe Carnegie Mellon University Cormac Herley Microsoft Research Redmond Venkat Padmanabhan Microsoft Research Redmond April 27 2006 IEEE INFOCOM Barcelona ID: 379946

seed nodes uplink block nodes seed block uplink utilization blocks bittorrent tft fairness download based kbps rarest high crowd

Link:

Copy

Embed:

<iframe width="560" height="315" src="https://www.docslides.com/embed/379946" frameborder="0" allowfullscreen></iframe>

Download Presentation from below link

Download Presentation The PPT/PDF document "Analyzing and" is the property of its rightful owner. Permission is granted to download and print the materials on this web site for personal, non-commercial use only, and to display it on your personal computer provided you do not modify the materials and that you retain all copyright notices contained in the materials. By downloading content from our website, you accept the terms of this agreement.

Presentation Transcript

Slide1

Analyzing and Improving BitTorrent

Ashwin R. Bharambe (Carnegie Mellon University)Cormac Herley (Microsoft Research, Redmond)Venkat Padmanabhan (Microsoft Research, Redmond) April 27, 2006 @ IEEE INFOCOM, BarcelonaSlide2

How BitTorrent WorksSeed

Seed

…

Content Distribution Tool

File is chopped into

piecesSlide3

How BitTorrent worksDownloaders exchange blocks with each otherUtilizes perpendicular bandwidthTracker keeps track of connected peersSalient featuresWhich block to download first? Locally rarest blockWhich peers should I upload blocks to?Tit-for-tat: peers which give best download ratesSlide4

Why study BitTorrent (again) ?Very popular, successful: empiricallyWhat exactly makes it perform so well? Which parameter it chose is crucial?Motivating QuestionsAre download rates optimal? Can we do better?Is the Rarest First policy really beneficial?Does rate-based Tit-for-tat (TFT) work? Must nodes continue seeding after downloading?

Answers depend on many parameters!

Hard to control in measurements or analyticallySlide5

Talk OutlineEvaluation MethodologySimulation-basedScalability under homogeneous settings Impact of block-choosing policy, degree, etc.

Fairness under heterogeneous settings

Impact of Tit-for-tat

Post-flash-crowd scenario: pre-seeded nodes

Conclusion

Goal: Analyze and understand BitTorrent

under various scenariosSlide6

Experimental SetupDiscrete-event simulatorModels BitTorrent joins, leaves, block exchangesModels queuing delays, no propagation delayFluid model of link sharing, no TCP dynamicsAssumes bw-bottlenecks only at the edgeCommon parameters100 MB file; 400 blocks of 256 KB1 seed always on, flash-crowd: 100 joins/secSeed-uplink = 6 Mbps, Nodes = 1500/400 kbps#nodes = 1000, #neighbors = 7Slide7

ScalabilityQuestions:Does BitTorrent scale as the size of the flash crowd increases?Does it perform optimally?High uplink utilizationHigh fairness (in the heterogeneous case)Measurement MetricsMean uplink utilizationMean over time, across all nodesMean download time is directly relatedSlide8

Scalability: Uplink UtilizationUpload utilization is constantly very highSlide9

Problem Case: Slow SeedNode capacitiesUplink: 400 kbpsDownlink: 1500 kbpsSeed capacityUplink: varies from 200 kbps  1000 kbpsScenario: seed uplink = 400 kbpsIf BitTorrent is performing optimally, we should see near 100% uplink utilizatoinSlide10

Problem Case: Slow SeedVanilla BitTorrent:

Connected nodes decide

which blocks to request from seed

The seed node decides

which blocks to serve

Avoid sending duplicate blocks from seed

at all costsSlide11

Neighbor Count and Block PolicyQuestions:How many neighbors required to guarantee good uplink utilization?When does Local Rarest First matter?Slide12

Neighbor Count and Block PolicyVery low neighbor count is sub-optimal

Beyond a threshold,

neighbor count does not

affect utilization

Local Rarest First policy

works better than Random

block picking

However, differences are

discernible only when the

seed bandwidth is low!Slide13

Improving FairnessGoal: ensure nodes upload as much as they downloadISPs have begun to charge heavy P2P usersUploaders will bear the brunt of the chargesBitTorrent’s rate-based TFT and optimistic unchoke can result in high unfairnessProposed solution: pair-wise block-based TFTBound the difference between blocks uploaded and downloadedSlide14

Improving FairnessQuestions:In the worst case, how many blocks does a node serve? Measure as ratio to #blocks downloadedWhat is the overall uplink utilization?TFT advocates blocking a link even when there is data to sendCan hurt link utilizationSlide15

Improving Fairness: Blocks servedVanilla BitTorrent results in high unfairness

Block-level TFT effective

Matching Tracker usefulSlide16

Improving Fairness: Uplink UtilizationMatching Tracker helpsincrease utilization

Pairwise TFT needs

higher node degrees

for better utilizationSlide17

Other Workloads: Pre-seeded NodesScenarioSome nodes join a flash crowdPartially finish the downloadRe-join a flash crowd laterQuestion:Other nodes start afresh; hence not so choosy These nodes are looking for specific blocks Do they require more time to finish?Slide18

Pre-seeded nodes: Download TimeLRF “equalizes” rate of block “flow”  pre-seeded nodes takes longer

Small amount of FEC

improves performance

significantly!Slide19

ConclusionFocus: upload utilization and (un)fairness FindingsBitTorrent scales wellLocal Rarest First eliminates last-block problemDesign decisions crucial when seed uplink is slowRate-based TFT can result in unfairness in heterogeneous settings

Block-based TFT can alleviate it

LRF may be sub-optimal if nodes have differing objectives

Source-based FEC sometimes usefulSlide20

Thank You!Find simulator-code (C#) at:http://research.microsoft.com/projects/btsim

Questions?