1. Amir Rasti Daniel Stutzbach Reza Rejaie The ION P2P Project http://mirage.cs.uoregon.edu/P2P University of Oregon On the Long-term Evolution of the Two-Tier Gnutella Overlay Global Internet Symposium Barcelona, Spain April 28 th, 2006

2. Daniel Stutzbach The ION P2P Project http://mirage.cs.uoregon.edu/P2PSlide 2/16 Peer-to-peer applications are becoming increasingly popular. How do they adapt to long-term growth? Case study: The Gnutella population quadrupled in the 15 months between Oct 04 and Jan 06, from 800k to 3.2M. How does this affect properties of the network? Motivation

3. Daniel Stutzbach The ION P2P Project http://mirage.cs.uoregon.edu/P2PSlide 3/16 Gnutella uses a two-tier overlay. Improves scalability. Ultrapeers form an unstructured mesh. Leaf peers connect to the ultrapeers. Leaf peers self-promote to ultrapeers when they can’t find an available ultrapeer. Studying the overlay requires snapshots. Snapshots capture the overlay as a graph. Individual snapshots reveal graph properties. Consecutive snapshots reveal dynamics. Background Top-level overlay Leaf Ultrapeer

4. Daniel Stutzbach The ION P2P Project http://mirage.cs.uoregon.edu/P2PSlide 4/16 Cruiser, a P2P topology crawler Daniel Stutzbach and Reza Rejaie, “Capturing Accurate Snapshots of the Gnutella Network”, the Global Internet Symposium, 2005. Contacts only ultrapeers. Captures 2.2M peers in around 8 minutes. For each ultrapeer, records: Brand, version, and list of neighbors Characterizing the Gnutella topology Daniel Stutzbach, Reza Rejaie, and Subhabrata Sen, “Characterizing Unstructured Overlay Topologies in Modern P2P File-Sharing Systems”, Internet Measurement Conference, 2005. Examined various graph and dynamic properties Looked for similarities across different snapshots Prior Work

5. Daniel Stutzbach The ION P2P Project http://mirage.cs.uoregon.edu/P2PSlide 5/16 Outline Looking for differences in snapshots Client properties Brand Version Graph properties Percentage of ultrapeers Node degree Pair-wise distances Resiliency Geographic Properties Location Correlations with topology

6. Daniel Stutzbach The ION P2P Project http://mirage.cs.uoregon.edu/P2PSlide 6/16 Data Set To examine long-term trends, we need a series of comparable snapshots. We have 20,000 snapshots from Oct. 2004 through Jan. 2006. Unfortunately they’re not evenly distributed. Many of them are back-to-back. We selected 18 comparable snapshots taken at 3pm on weekdays.

7. Daniel Stutzbach The ION P2P Project http://mirage.cs.uoregon.edu/P2PSlide 7/16 Population and Brand Population has grown linearly. 15%—20% Ultrapeers LimeWire and BearShare have a fairly steady marketshare. Dip in LimeWire users in winter 2004—2005.

8. Daniel Stutzbach The ION P2P Project http://mirage.cs.uoregon.edu/P2PSlide 8/16 Version We breakdown LimeWire users by version. Users upgrade quickly 50% running latest version within 2 months of release. New features spread quickly. “Flag Days” feasible.

9. Daniel Stutzbach The ION P2P Project http://mirage.cs.uoregon.edu/P2PSlide 9/16 Percentage of Ultrapeers Each leaf aims for 3 parents and each ultrapeer may have up to 30 children. If everyone is full, 9% of peers would be ultrapeers. If there are too few ultrapeers, some leaves are stuck! If there are too many, efficiency decreases. In practice, we want slightly higher than 9%. Peaks at 18% and 20% show unnecessarily high number of ultrapeers. Decreases correlated with release of new versions of LimeWire.

10. Daniel Stutzbach The ION P2P Project http://mirage.cs.uoregon.edu/P2PSlide 10/16 Node Degree: Ultrapeer-to-Ultrapeer LimeWire ultrapeers try to maintain around 30 neighbors. We observe an increasing number of peers with 20— 30 neighbors. The number of peers with fewer neighbors has not increased much. Conclusion: Ultrapeers scalably find one another.

11. Daniel Stutzbach The ION P2P Project http://mirage.cs.uoregon.edu/P2PSlide 11/16 Node Degree: Ultrapeer-to-Leaf Number of children peak at 30 and 45, corresponding with the maximums used in LimeWire and BearShare. The peaks have hardly changed. The number of ultrapeers with many open slots has increased. Conclusion: Leaves are having an increasingly hard time finding ultrapeers, and are unnecessarily self-promoting. However, this trend is reversed in the latest snapshots (2006)

12. Daniel Stutzbach The ION P2P Project http://mirage.cs.uoregon.edu/P2PSlide 12/16 Pairwise Distance Distribution of distances between pairs of peers Important for searching Despite a dramatic change in population, only a slight change in distances. Similar to behavior in random graphs

13. Daniel Stutzbach The ION P2P Project http://mirage.cs.uoregon.edu/P2PSlide 13/16 Resiliency How many peers must be removed before the network is severely fragmented? Random Remove peers at random More than 90% must be removed. Little change Systematic Remove high degree peers first Typically more than 60% must be removed. Dip in winter 2004—2005, then little change

14. Daniel Stutzbach The ION P2P Project http://mirage.cs.uoregon.edu/P2PSlide 14/16 Geographic Location We examined the geographic location of ultrapeers. 98.5% of all users are in: North America (NA), Europe (EU), Asia (AS), or South America (SA). Relatively little change in geographic distribution over time. NA has decreased slightly, while EU has increased.

15. Daniel Stutzbach The ION P2P Project http://mirage.cs.uoregon.edu/P2PSlide 15/16 Geographical-Topological Correlation We find that a peer’s neighbors are disproportionately from within the same region. The effect is more pronounced in regions with fewer users. Causes: Locale-based neighbor selection Latency as a natural selection criteria Time of day effect

16. Daniel Stutzbach The ION P2P Project http://mirage.cs.uoregon.edu/P2PSlide 16/16 Conclusions We examined trends in the properties of a two- tier overlay, Gnutella, over 15 months. Gnutella witnessed a major increase in user- population over this time. The percentage of ultrapeers tends to creep upwards over time. Rapid adaptation of new releases enables developers to modify the software to cope with the growing user population. Peers tend to connect to other peers in the same geographic region.

17. Daniel Stutzbach The ION P2P Project http://mirage.cs.uoregon.edu/P2PSlide 17/16 Clustering Coefficient (CC) CC is inverseley related to the percentage of ultrapeers. Degree distribution in top layer is almost fixed so more nodes in top layer makes the graph sparser -> lower CC.

18. Daniel Stutzbach The ION P2P Project http://mirage.cs.uoregon.edu/P2PSlide 18/16 Node Degree: Leaf-to-Ultrapeer Peak in 1-3 parents growing with population increase. No other significant change.