a modeling framework to understand the tussle between isps and peer to peer file sharing users n.
Download
Skip this Video
Loading SlideShow in 5 Seconds..
Michele Garetto - unito Daniel R. Figueiredo - EPFL Rossano Gaeta - unito Matteo Sereno - unito PowerPoint Presentation
Download Presentation
Michele Garetto - unito Daniel R. Figueiredo - EPFL Rossano Gaeta - unito Matteo Sereno - unito

Loading in 2 Seconds...

play fullscreen
1 / 24

Michele Garetto - unito Daniel R. Figueiredo - EPFL Rossano Gaeta - unito Matteo Sereno - unito - PowerPoint PPT Presentation


  • 131 Views
  • Uploaded on

IFIP – Performance 2007. A Modeling Framework to Understand the Tussle between ISPs and Peer-to-Peer File Sharing Users. Michele Garetto - unito Daniel R. Figueiredo - EPFL Rossano Gaeta - unito Matteo Sereno - unito. P2P is starting to dominate Internet Traffic.

loader
I am the owner, or an agent authorized to act on behalf of the owner, of the copyrighted work described.
capcha
Download Presentation

PowerPoint Slideshow about 'Michele Garetto - unito Daniel R. Figueiredo - EPFL Rossano Gaeta - unito Matteo Sereno - unito' - pallavi-gaurav


An Image/Link below is provided (as is) to download presentation

Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author.While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server.


- - - - - - - - - - - - - - - - - - - - - - - - - - E N D - - - - - - - - - - - - - - - - - - - - - - - - - -
Presentation Transcript
a modeling framework to understand the tussle between isps and peer to peer file sharing users

IFIP – Performance 2007

A Modeling Framework to Understand the Tussle between ISPs and Peer-to-Peer File Sharing Users

Michele Garetto - unito

Daniel R. Figueiredo - EPFL

Rossano Gaeta - unito

Matteo Sereno - unito

p2p is starting to dominate internet traffic
P2P is starting to dominate Internet Traffic

P2P represented 60% of Internet

Traffic at the end of 2004

impact on service providers
Impact on Service Providers

P2P is driving consumer broadband uptake

…and broadband is driving P2P uptake

  • P2P is the dominant protocol
    • In excess of 92% of P2P traffic crosses transit/peering links
    • P2P protocols will aggressively consume any available bandwidth capacity
    • Due to P2P’s symmetrical nature on average 80% of upstream capacity is consumed by P2P
  • P2P affects QoS levels for ALL subscribers
  • Service Providers can not afford to block or restrict P2P
  • ISPs must intelligently manage P2P - blocking and shaping doesn’t work
the isp perspective vs p2p threat or opportunity
The ISP perspective vs P2P:threat or opportunity ?
  • P2P traffic: friend or foe ?
    • friend: driving force for adoption of broadband access by the users
    • foe: overwhelming amount of traffic
  • What is the best strategy to manage P2P traffic in my network ?
    • Try to kill it ?
    • Do nothing ?
    • Educate it ? How ?
strategies to manage p2p traffic
Strategies to manage P2P traffic
  • Acquire more bandwidth
  • Block P2P traffic
  • Traffic shaping (e.g., priority to non-P2P)
  • Pricing schemes based on user traffic volumes / bandwidth caps
  • Network caching / customized P2P application within ISP
  • Application-layer redirection of P2P traffic
our contribution
Our contribution
  • Simple model to analyze the impact of P2P traffic on an ISP network
  • Basic insights about system dynamics
  • Performance evaluation tool to evaluate different strategies to manage P2P traffic and guide ISP choices
network scenario
Network scenario

User issues a query

Solved outside  consumes bandwidth Bd

Solved inside  does not use bandwidth Bd

  • Exploitation of “traffic locality”
system model
System model

object retrieval probability:

user utility function

Minimum service level for user i

User Utility Function
  • We express the utility of user i as:

probability of successful object retrieval

shape parameter

subscription

cost

User utility

1

0.5

σ

0

1

0

0.2

0.4

0.6

0.8

-0.5

-1

isp utility function
ISP Utility Function
  • We express the utility of the ISP as:

cost per unit of external bandwidth

fixed

charge

profit from subscribers’ fee

  • The ISP starts the service only if
modeling traffic locality
Modeling traffic locality
  • Probability that there exist at least one internalcopy of an object replicated r times in the system

Number of internal copies

Number of external copies

  • Probability to download from internal (existing) copy (i.e., exploit traffic locality) :
modeling object replication
Modeling object replication
  • We need to compute the number r of replicas of an object at the time the object is requested, taking into account:
  • Different popularity of contents
  • Temporal evolution of object popularity
  • Introduction of new contents
  • Cancellation of replicas by the users
  • We have developed an analytical technique based on Poisson shot noise processes
modeling object replication1
Modeling object replication
  • Example: (2 objects)

popularity

A video from the news

A popular song

time

t1

t2

request

results
Results
  • Assumption: n identical users
  • N = 50 millions
  • request rate by user (object/day)
  • introduction of new contentsby

user (object/day)

Minimum required external bandwidth:

the impact of object replication r
The impact of object replication (r)

5000

Minimum

required

bandwidth

Bmin

(objects/day)

r = 500

r = 1000

4000

r = 1500

3000

2000

1000

0

0

10000

20000

30000

40000

Number of users, n

the impact of efficacy in exploiting traffic locality
The impact of efficacy in exploiting traffic locality ()

100000

Minimum

required

bandwidth

Bmin

(objects/day)

= 0.25

= 0.5

80000

= 0.75

= 1.0

60000

40000

20000

0

0

100000

300000

500000

700000

Number of users, n

impact of subscription cost c

nmin

Impact of subscription cost, c

40000

c = 0.25

UISP

Utility of ISP

c = 1.0

30000

c = 1.4

20000

c = 1.6

10000

0

-10000

0

5000

10000

15000

20000

25000

30000

Number of users, n

critical mass of users n min
Critical mass of users, nmin

140000

β2 = 6

nmin

β2 = 5

120000

Cost per unit of bandwidth

β2 = 4

100000

β2 = 3

80000

60000

40000

20000

0

0

200

400

600

800

1000

Average object replication, r

model refinements
Model refinements
  • Impact of finite bandwidth of the users
model refinements1
Model refinements
  • Impact of finite bandwidth of the users
    • In case of constant traffic load, the cost for the ISP increases if it provides more download bandwidth to the users (!)
    • The system performance is strongly affected by the upload bandwidth of the users, thatshould be larger than or equal to the download bandwidth (contrary to common practices, e.g., ADSL lines !)
impact of asymmetric access bandwidths
Impact of asymmetric access bandwidths

(for fixed number of users = 20000)

12000

Minimum

required

bandwidth

Bmin

(objects/day)

bd = 0.1 bu

bd = bu

10000

bd = 2 bu

bd = 3 bu

8000

bd = 4 bu

6000

4000

2000

0

0

500

1000

1500

2000

2500

3000

3500

4000

Upload bandwidth, bu

the impact of b d
The impact of bd

7000

bd = 2000

Minimum

required

bandwidth

Bmin

(objects/day)

bd = 1000

6000

bd = 500

bd = 100

5000

bd = 10

4000

3000

2000

1000

0

0

5000

10000

15000

20000

25000

30000

Number of users, n

conclusions
Conclusions
  • We have developed a simple analytical model to:
    • analyze the interaction between P2P traffic and ISP
    • understand the impact of several parameters
    • guide the selection of the optimal strategy to manage P2P traffic
  • Future work
    • More model refinements
    • Multiple ISPs competing with each other