1. 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

2. P2P is starting to dominate Internet Traffic
P2P represented 60% of Internet
Traffic at the end of 2004

3. 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

4. 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 ?

5. 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

6. 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

7. Network scenario Exploitation of “traffic locality”
User issues a query
Solved inside  does not use bandwidth Bd
Solved outside  consumes bandwidth Bd
Exploitation of “traffic locality”

8. System model
object retrieval probability:

9. User Utility Function We express the utility of user i as: σ
probability of successful object retrieval
shape parameter
subscription
cost
User utility 1
Minimum service level for user i
0.5 σ
0.2
0.4
0.6
0.8 1
-0.5 -1

10. 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

11. Modeling traffic locality
Probability that there exist at least one internal copy 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) :

12. 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

13. Modeling object replication
Example: (2 objects)
popularity
A video from the news
A popular song
time t1 t2
request

14. Results Assumption: n identical users N = 50 millions
request rate by user (object/day)
introduction of new contents by
user (object/day)
Minimum required external bandwidth:

15. The impact of object replication (r)
Minimum
required
bandwidth
Bmin
(objects/day)
5000
r = 500
r = 1000
4000
r = 1500
3000
2000
1000
10000
20000
30000
40000
Number of users, n

16. The impact of efficacy in exploiting traffic locality ( )
Minimum
required
bandwidth
Bmin
(objects/day)
100000
= 0.25
= 0.5
80000
= 0.75
= 1.0
60000
40000
20000
100000
300000
500000
700000
Number of users, n

17. Impact of subscription cost, c
40000
c = 0.25
UISP
Utility of ISP
c = 1.0
30000
nmin
c = 1.4
20000
c = 1.6
10000
-10000
5000
10000
15000
20000
25000
30000
Number of users, n

18. Critical mass of users, nmin
140000
β2 = 6
nmin
120000
β2 = 5
Cost per unit of bandwidth
β2 = 4
100000
β2 = 3
80000
60000
40000
20000
200
400
600
800
1000
Average object replication, r

19. Model refinements
Impact of finite bandwidth of the users

20. 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, that should be larger than or equal to the download bandwidth (contrary to common practices, e.g., ADSL lines !)

21. 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
500
1000
1500
2000
2500
3000
3500
4000
Upload bandwidth, bu

22. The impact of bd Number of users, n bd = 2000 bd = 1000 bd = 500
7000
bd = 2000
Minimum
required
bandwidth
Bmin
(objects/day)
bd = 1000
6000
bd = 500
bd = 100
5000
bd = 10
4000
3000
2000
1000
5000
10000
15000
20000
25000
30000
Number of users, n

23. 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

24. Questions ? Comments ?