1. Peer-to-Peer Information Systems Week 6: Performance
Old Dominion University
Department of Computer Science
CS 495/595 Fall 2004
Michael L. Nelson
10/05/04

2. Regular & Random Graphs
vertices: n=4096
neighbors: k=8
Regular Graph
average diameter
n/2k
clustering coefficient
(connections present) / (k(k-1)/2)
approaches .75 for large n
Random Graph
average diameter
log(n/log k)
clustering coefficient
k/n
approaches 0 for large n
=256 =4
=0.002
=0.5
figures 14-4 & 14-5 from Ch. 14 &

3. Small Worlds, Revisited
Duncan J. Watts, Steven H. Strogatz. Collective Dynamics of 'Small-World' Networks. Nature 393, (1998)
figures 1 & 2 from Watts & Strogatz

4. Freenet Performance Simulation 1000 identical nodes capacity:
n=1000, k=4
diameter = 125, CC=0.5
capacity:
50 data items (all initially empty)
200 references (4 nearest neighbors initially linked)
every timestep, randomly pick a node for an insert or request
TTL=20
figure 14-8 from Ch. 14 &

5. Freenet Path Evolution
approaching 2
figure 14-9 from Ch. 14 &

6. Freenet Path Evolution
approaching 6; cf. ~50 for random routing (figure 14-13)
figures & from Ch. 14 &

7. Growing the Freenet Network
start with 20 nodes
add a new node every 5 timesteps until 1000 nodes
results
path length 2.2
CC 0.22
50% requests complete in <= 5 hops
figure from Ch. 14 &

8. Attacks vs. Failures
figure from Ch. 14 &

9. Free Riders in Freenet No real impact:
if you don’t share files, you don’t get linked into the network
the free riding node can contribute traffic to the network
if a node refuses incoming connections, it is considered “down” and the other nodes route around it

10. Freenet Scalability
slope increase probably due to a simulation side-effect
figures & from Ch. 14 &

11. Gnutella Performance build 1000 empty nodes, randomly add 1500 edges
n=1000, k=3
random graph! (cf. Figure 14-5)
after initialization, the network does not evolve
no adds or joins
“publish” 2500 data objects; each exists in 20 locations
50k (2500 * 20) total files in the network
perform 300 queries on random files, TTL=
halt query after file is found (unlike the real Gnutella)

12. Gnutella Communication
breadth-first search finds the shortest path…
figure 3 from Ripeanu, Iamnitchi & Foster,
IEEE IC, 6(1), 2002
figures from Ch. 14 &

13. Gnutella Communications
…but costs communications
figure from Ch. 14 &

14. Gnutella Attacks vs. Failures
no real difference between attacks and failures…
…but are assumptions still valid?
figures & from Ch. 14 &

15. Gnutella - Power Law? figures 5&6 from Ripeanu, Iamnitchi & Foster,
IEEE IC, 6(1), 2002

16. Free Riding in Gnutella
73% of Gnutella users share < 10 files!
Gnutella has no mechanism to describe or remember “good” hosts
free riders increase the path length w/o adding content
free riders increase the communications requirements
figure 1 from Adar & Huberman,

17. Gnutella Scalability cf. figures 14-21 & 14-22
figure from Ch. 14 &

18. Super-peers All peers are equal, but some peers are more equal than others
Beverly Yang, Hector Garcia-Molina, "Designing a Super-peer Network." In Proceedings of the 19th International Conference on Data Engineering (ICDE), Bangalore, India, March 2003.
definitions
pure P2P: Gnutella, Freenet, Free Haven
hybrid P2P: Napster
super-peer: a node that acts as a centralized server (hybrid system) to a subset of clients
super-peers are connected, and communication between them occurs as a pure P2P
for downloads, peer and super-peer distinctions don’t matter

19. Super-Peer Network

20. Super-Peer Motivation
very heterogeneous capability in P2P systems
combine pure & hybrid capabilities
build hierarchical structures?
super-super-peer? super-super-super-peer?
Super-peer examples:

21. Gnutella Reflectors
instead of forwarding queries, a Gnutella reflector answers them from its cache
resources:
also: gnuTellavision
figure from

22. Gnutella Maps
from: cf. figure 8-3 (p. 109)

23. Super-Peer Definitions from Yang & Garcia-Molina, 2003
load = f(incoming bandwidth, outgoing bandwidth, processing power)
individual load = load of 1 node
aggregate load = load of all nodes in system
k-redundancy = a super-peer has k backups

24. Super-Peer Rules of Thumb from Yang & Garcia-Molina, 2003
Increasing cluster size decreases aggregate load, but increases individual load
as the cluster size grows, super-peers work harder
Super-peer redundancy is good
additional complexity, but yields “good aggregate load of a large cluster size, and the good individual load of a smaller cluster size -- in addition to increased reliability”
Maximize outdegree of super-peers
decreases expected # of hops, provided that all super-peers take on more clients
Minimize TTL
TTL can be tuned: start high, look at how far away your results are, back down to that…

25. Meta Services in Dienst
Haven’t we been here before…
Meta Services in Dienst
Master Meta Server
Region B
Region A
Regional Meta Server
Regional Meta Server
Merged Index Server
Merged Index Server
Standard Dienst
Merged Index Server
Backup Server
Standard Dienst
Standard Dienst
Central Lite Site
Standard Dienst
Lite Site
Lite Site