Content Availability and Bundling in Swarming Systems Reporter: Jian He.

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Presentation transcript:

Content Availability and Bundling in Swarming Systems Reporter: Jian He

2 BitTorrent: The Good and The Bad Peer-to-peer content distribution immensely successful Accounts for 60% of all Internet traffic [CacheLogic] BitTorrent accounts for 57% of P2P traffic [IPOQUE] P2P but availability a severe problem: About half of the swarms unavailable half the time.

3 Outline Motivation: Measurements in the Wild Content Unavailability Bundling: Prevalence and Implications Modeling Content Availability Implications of Model for Bundling Experimental Validation of Model

4 BitTorrent Terminology Swarm: set of users interested in the same content Publisher (seed): interested in dissemination Peers (leechers): interested in download Availability: Model: at least one publisher or sufficient peers present. Measurement: at least one publisher present

5 Swarm N Swarm 2 Measurement Setup Monitors in ~100 PlanetLab nodes 45,693 swarms monitored 8 months (August 2008-March 2009) PlanetLAB Monitors UMass Swarm 1 PEX & bitmap

6 Finding 1: Content Unavailability Severe Fraction of swarms available at most 100 x% time x=fraction of time with at least one seed available Swarms more available during first month. 40% of swarms unavailable 50% of time. Entire measurement First month

7 Finding 2: Bundling Common Bundle: A single swarm consisting of multiple files episodes of a TV show songs in an album books in a collection Bundle TV Show Music Book Non bundle Bundle Non bundle Bundle Non bundle

8 Finding 3: Bundled Content More Available Example 1: Books Among all books 62% swarms with no seeds Among collections only 36% Example 2: “Friends” episodes 52 swarms 23 with at least one seed (21 bundles) 29 with no seeds (7 bundles)

9 Measurement Findings: Summary 1. Content unavailability severe 2. Bundling common 3. Bundled content is more available

10 Outline Motivation: Measurements in the Wild Modeling Content Availability Implications of Model for Bundling Experimental Model Validation

11 Capturing Availability using Busy Periods Question: How long is content available without a publisher? Busy period: Model: M/G/∞ Poisson arrivals with rate Mean download times publisher time Number of peers and publishers contiguous period when at least one peer is online

Availability in BitTorrent

13 Quantifying Unavailability(Publishers Only) What is fraction of time in which content is unavailable? Asssumptions Publisher arrival Poisson, rate r Publisher residence,u Fraction of time in which content is unavailable time Number of peers and publishers idle length of idle period length of idle period + length of busy period busy

14 Outline Motivation: Measurements in the Wild Modeling Content Availability Implications of Model for Bundling Experimental Model Validation

15 Bundling and Unavailability(Publishers Only) Bundling K files assumed to: increase arrival rate by factor K R=Kr increase residence time by factor K U=Ku Unavailability of isolated swarm: Kr Ku

Unavailability with Publishers and Peers Assumption ■ coverage threshold is one ■ aggregate arrival rate of peers and publishers individual swarm bundled ■ ■ file size: individual swarm s bundled S=Ks Unavailability of isolated swarm R S

17 Availability Theorem Bundling K files together decreases unavailability by a factor

Assumption ▪ Peers wait for content to be available ▪ publishers' residence time are different ▪ coverage threshold is greater than one LEMMA The mean number of peers served in a busy period, E(N), increases as by bundling K files A Model for Availability and Download Time

19 Quantifying Download Time What is the mean download time of peers? Mean download time is sum of Idle waiting P(idle)1/r= Active download time time Number of peers and publishers

20 Implication of Bundling on Download Time Recall that bundling K files increases arrival rate by factor K increases file size by factor K Download time of individual file: Download time of bundle: Ks R

21 Download Time Theorem Implications: Bounded damage: Bundling K files can increase the mean download time by at most a factor K (when R ∞) Unbounded gain: Bundling K files can decrease (for ) the mean download time by up to a factor (when R 0) Download time ≈

22 Outline Motivation: Measurements in the Wild Modeling Content Availability Implications of Model for Bundling Experimental Model Validation

23 Experimental Setup Questions: 1. Can bundling reduce download time? 2. What is the impact of bundling if different files have different popularities? 150 PlanetLab nodes as peers UMass node to control arrivals Setup: private swarms

24 Can bundling reduce download time? (I) Peer capacity =33 KBps Intermittent publisher On time=300 s Off time=600 s No bundling Publisher arrival Publisher departure Bundle of size 4 Peer arrival rate =4 peer/min File size=16 Mb Peer arrival rate =1 peer/min File size=4 Mb

25 Can bundling reduce download time? (II) Bundling increases active download time Bundling reduces idle waiting time Download time (s) Bundle size Model (threshold coverage=9) Experiment Bundling can reduce download time (idle waiting plus active download time).

26 Heterogeneous Popularities Experimental setup 4 swarms with Zipfian popularities Download time (s) Popularity (Peer Arrival Rate) Bundle download time Bundling reduces download time for unpopular content at the expense of popular content.

27 Conclusions Measurements show severe content unavailability Around half swarms unavailable half the time Key contribution: Availability model Result 1: bundling improves availability Result 2: bundling can reduce download times Experimental validation of model conclusions Questions?