John S. Otto, Mario A. Sanchez, David R. Choffnes*, Fabin E. - - PowerPoint PPT Presentation

john s otto mario a sanchez david r choffnes fabi n e
SMART_READER_LITE
LIVE PREVIEW

John S. Otto, Mario A. Sanchez, David R. Choffnes*, Fabin E. - - PowerPoint PPT Presentation

John S. Otto, Mario A. Sanchez, David R. Choffnes*, Fabin E. Bustamante, Georgos Siganos** Northwestern, EECS * U. Wash, CSE ** Telefnica Research http://aqualab.cs.northwestern.edu 2 Otto, Snchez, Choffnes, Bustamante & Siganos On


slide-1
SLIDE 1

http://aqualab.cs.northwestern.edu

John S. Otto, Mario A. Sanchez, David R. Choffnes*, Fabián E. Bustamante, Georgos Siganos**

Northwestern, EECS * U. Wash, CSE ** Telefónica Research

slide-2
SLIDE 2

Otto, Sánchez, Choffnes, Bustamante & Siganos

2

On Blind Mice and the Elephant

slide-3
SLIDE 3

Otto, Sánchez, Choffnes, Bustamante & Siganos

3

  • A large, global peer-to-peer system
  • Millions of users exchanging content
  • Virtually every country in the world

On Blind Mice and the Elephant

slide-4
SLIDE 4

Otto, Sánchez, Choffnes, Bustamante & Siganos

4

System’s measured network impact depends on

measurement vantage point

– How much of network traffic is from BitTorrent?

On Blind Mice and the Elephant

Eastern Europe 57% (ipoque) South America 20% (ipoque) No, Germany is 9-15% (Maier et al. IMC’09) Germany 37% (ipoque)

slide-5
SLIDE 5

Otto, Sánchez, Choffnes, Bustamante & Siganos

5

A view from a broad set of end users

– To sample its overall network traffic – Understand where it flows – Who pays for it (and how expensive it is)

This work

– Relies on end users as vantage points

  • Captures a sample of all BitTorrent traffic
  • Reveals traffic’s path through the network

– Public view is not sufficient to map most BitTorrent traffic

– ISP data provides context to understand cost of BitTorrent traffic

On Blind Mice and the Elephant

slide-6
SLIDE 6

Otto, Sánchez, Choffnes, Bustamante & Siganos

6

Representative sample of users

– 500,000 users, 3,300 networks, 169 countries

Running extensions (Ono & NEWS) for Vuze

BitTorrent client

– Anonymously report statistics – Provide application-level data

  • e.g. session length, per-connection transfer volumes
  • Log 13 TB of traffic per day

– Conduct active measurements to reveal traffic paths

  • With public view alone, we can map 25% of traffic
  • Supplemented with traceroutes, we can map 89%

On Blind Mice and the Elephant

slide-7
SLIDE 7

Otto, Sánchez, Choffnes, Bustamante & Siganos

7

How BitTorrent is being used

– Who is using BitTorrent? – When do people run BitTorrent? – How much traffic does it generate? – Study data from Nov. 2008 to Nov. 2010

Where the generated traffic flows Who pays for it and how much

On Blind Mice and the Elephant

slide-8
SLIDE 8

Otto, Sánchez, Choffnes, Bustamante & Siganos

8

On Blind Mice and the Elephant

EU 52% NA 20% AS 19% SA 4% OC 3% AF 2% EU 61% NA 19% AS 13% SA 4% OC 2% AF 1%

2009 2010

  • Decrease in Europe
  • Increase in Asia, Africa and Oceania

Connected peers by continent

  • Overall population reduced by 10%
  • Locations of users change over time
slide-9
SLIDE 9

Otto, Sánchez, Choffnes, Bustamante & Siganos

9

On Blind Mice and the Elephant

Rate of growth of connected users per continent relative to

  • Nov. 2008
  • Europe continues to drop
  • N. America, S. America remain stable since 2009
  • 76% growth in Africa and 47% in Asia
slide-10
SLIDE 10

Otto, Sánchez, Choffnes, Bustamante & Siganos

10

06 08 10 12 14 16 18 20 22 00 02 04 06 20 40 60 80 100 Normalized % of hourly peers seen

2009

  • Shift away from overnight use
  • Peak usage aligns with evening hours, local time

– Potential impact on ISPs’ costs under burstable billing

On Blind Mice and the Elephant

European peers seen on weekdays

Normalized number

  • f peers seen per

hour in Europe, depending on time

  • f day
slide-11
SLIDE 11

Otto, Sánchez, Choffnes, Bustamante & Siganos

11

06 08 10 12 14 16 18 20 22 00 02 04 06 20 40 60 80 100 Normalized % of hourly peers seen

2009

  • Shift away from overnight use
  • Peak usage aligns with evening hours, local time

– Potential impact on ISPs’ costs under burstable billing

On Blind Mice and the Elephant

European peers seen on weekdays

Normalized number

  • f peers seen per

hour in Europe, depending on time

  • f day

06 08 10 12 14 16 18 20 22 00 02 04 06 20 40 60 80 100 Normalized % of hourly peers seen

2009 2010

slide-12
SLIDE 12

Otto, Sánchez, Choffnes, Bustamante & Siganos

12

  • 25% increase in per-peer hourly download volume
  • Despite a 20% drop in total connections,

a 12% increase in overall system traffic

On Blind Mice and the Elephant

Nov ’09 Jan ’10 Mar ’10 May ’10 Jul ’10 Sep ’10 Nov ’10 20 40 60 80 100 120 140 160 Hourly Peer Download Volume (MB)

Per-peer hourly download volume (in MB) over the last year

slide-13
SLIDE 13

Otto, Sánchez, Choffnes, Bustamante & Siganos

13

Overall population reduced by 10%

– But large increase in Africa and Asia

Peak usage aligns with evening hours 12% increase in overall system traffic

– 25% increase in per-peer hourly download volume

So where’s the traffic?

On Blind Mice and the Elephant

slide-14
SLIDE 14

Otto, Sánchez, Choffnes, Bustamante & Siganos

14

How “deep” does traffic go in the network? Who is paying for it? Traffic path analysis to see which networks carry

most BitTorrent traffic

– Tier 1: Well-known networks – Tier 2: Large transit providers – Tier 3: Small transit providers – Tier 4: Content/access/hosting providers Enterprise customers

On Blind Mice and the Elephant

Tiers based on Dhamdhere and Dovrolis, IMC 2008

slide-15
SLIDE 15

Otto, Sánchez, Choffnes, Bustamante & Siganos

15

0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 CDF [X ≤ x] Proportion of Traffic

  • Most traffic stays at or below Tier 3
  • Significant fraction of traffic never reaches Tiers 1 or 2

– Typically missed by in-network monitoring studies from the core

On Blind Mice and the Elephant

Fraction of each peer’s traffic that reaches Tier X

Smaller fraction

  • f traffic

Tier 1 Tier 2 Tier 3 Tier 4

slide-16
SLIDE 16

Otto, Sánchez, Choffnes, Bustamante & Siganos

16

  • Most traffic stays at or below Tier 3
  • Significant fraction of traffic never reaches Tiers 1 or 2

– Typically missed by in-network monitoring studies from the core

On Blind Mice and the Elephant 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 CDF [X ≤ x] Proportion of Traffic

Fraction of each peer’s traffic that reaches Tier X

Tier 1 Tier 2 Tier 3 Tier 4

slide-17
SLIDE 17

Otto, Sánchez, Choffnes, Bustamante & Siganos

17

  • Traffic generally stays in the originating tier
  • Tier 2 networks do not provide “intermediate” level of

connectivity between Tiers 1 & 3

On Blind Mice and the Elephant

0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 Proportion of Traffic Tier 1 Tier 2 Tier 3

Traffic from Tier 2 to Tier 2 Traffic from Tier 3 to Tier 3

0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 CDF [X ≤ x] Proportion of Traffic Tier 1 Tier 2

slide-18
SLIDE 18

Otto, Sánchez, Choffnes, Bustamante & Siganos

18

How BitTorrent is being used Where the generated traffic flows

– Most traffic is handled at or below Tier 3

Who pays for it and how much

On Blind Mice and the Elephant

slide-19
SLIDE 19

Otto, Sánchez, Choffnes, Bustamante & Siganos

19

Determine BitTorrent cost relative to other traffic

– ISP X’s data provides context to interpret traffic sample

Study at granularity of individual network links Consider common burstable billing model

– e.g. 95th-percentile billing

Data for several

  • f ISP X’s links
  • ver 1 week

On Blind Mice and the Elephant

ISP X ISP A ISP B ISP C ISP G

Providers

Customers

slide-20
SLIDE 20

Otto, Sánchez, Choffnes, Bustamante & Siganos

20

  • Aggregate link volume for each 5 minute bin
  • Cost is based on 95th-percentile bin’s value
  • Under burstable billing model, not all bytes may have the

same cost

– Peak-hour bytes are more expensive than off-peak

On Blind Mice and the Elephant

95th-percentile value When value is defined All Traffic

slide-21
SLIDE 21

Otto, Sánchez, Choffnes, Bustamante & Siganos

21

On Blind Mice and the Elephant

Other BT Other BT

  • BitTorrent at peak hour is more expensive
  • Use Shapley value to determine relative cost of BitTorrent

– Shapley value gives the cost contribution of BitTorrent traffic – Compare to other traffic on the network – Is BitTorrent’s cost more than its “fair share” by volume?

BitTorrent peaks at 3AM BitTorrent peaks at 9PM

slide-22
SLIDE 22

Otto, Sánchez, Choffnes, Bustamante & Siganos

22

On Blind Mice and the Elephant

Other BT Other BT

  • BitTorrent at peak hour is more expensive
  • Use Shapley value to determine relative cost of BitTorrent

– Shapley value gives the cost contribution of BitTorrent traffic – Compare to other traffic on the network – Is BitTorrent’s cost more than its “fair share” by volume?

BitTorrent peaks at 3AM BitTorrent peaks at 9PM

BitTorrent’s contribution to cost

BT BT Other Other

slide-23
SLIDE 23

Otto, Sánchez, Choffnes, Bustamante & Siganos

23

On Blind Mice and the Elephant

  • BitTorrent traffic is generally more

expensive than other traffic

  • What traffic characteristics result in

high relative cost?

Additional cost of BitTorrent traffic, percent above relative cost of 1

ISP X ISP A ISP B ISP C ISP G

slide-24
SLIDE 24

Otto, Sánchez, Choffnes, Bustamante & Siganos

24

  • High relative cost of BitTorrent

– Large coefficient of variation (“C.V.”, size of peaks in BitTorrent traffic) – Small cross-correlation offset (“X-corr”, alignment with overall traffic)

On Blind Mice and the Elephant

Out-of-phase peaks Aligned peaks Small peaks Large peaks

slide-25
SLIDE 25

Otto, Sánchez, Choffnes, Bustamante & Siganos

25

  • High relative cost of BitTorrent

– Large coefficient of variation (“C.V.”, size of peaks in BitTorrent traffic) – Small cross-correlation offset (“X-corr”, alignment with overall traffic)

On Blind Mice and the Elephant

Out-of-phase peaks Aligned peaks ISP B X-corr: 3.2 hours C.V.: 188% Relative cost: 50% ISP A X-corr: -7.1 hours C.V.: 130% Relative cost: 13% ISP F X-corr: 7.4 C.V.: 325% Relative cost: 52% ISP E X-corr: 1.6 C.V.: 158% Relative cost: 83% Small peaks Large peaks

slide-26
SLIDE 26

Otto, Sánchez, Choffnes, Bustamante & Siganos

26

BitTorrent is still alive and costly

– Most traffic stays at the edge of the network – It is moving into prime-time – Logically, it is relatively more expensive

A broad view from the edge of the network is

required to see the system’s full usage spectrum

Approach is general to understanding other

distributed systems

– Video streaming – Peer-to-peer CDNs

On Blind Mice and the Elephant