Download presentation

Presentation is loading. Please wait.

Published byJada Strickland Modified over 4 years ago

1
Characterizing Overlay Topologies & Dynamics in Peer-to-Peer Networks Daniel Stutzbach, Reza Rejaie University of Oregon Subhabrata Sen AT&T Labs IEEE Computer & Communications Workshop, Huntington Beach October 25 th, 2005

2
Slide 2/18 CCW 2005http://mirage.cs.uoregon.edu/P2P Motivation P2P file-sharing systems are very popular in practice. Several million simultaneous users collectively. 60% of all Internet traffic [CacheLogic Research 2005] Most use an unstructured overlay. Understanding overlay properties & dynamics is important: Understanding how existing P2P systems function Developing and evaluating new systems Unstructured overlays are not well-understood. We characterized overlay topology in Gnutella because Size: one of the largest P2P systems; more than 1 million users Mature: In use for several years; older studies for comparisons Open: No reverse-engineering needed

3
Slide 3/18 CCW 2005http://mirage.cs.uoregon.edu/P2P Defining the Problem Gnutella uses a two-tier overlay. Improves scalability. Ultrapeers form an unstructured mesh. Leaf peers connect to the ultrapeers. eDonkey, FastTrack are similar. Studying the overlay requires snapshots. Snapshots capture the overlay as a graph. Individual snapshots reveal graph properties. Consecutive snapshots reveal dynamics. However, capturing accurate snapshots is difficult. Top-level overlay Leaf Ultrapeer

4
Slide 4/18 CCW 2005http://mirage.cs.uoregon.edu/P2P Challenges in Capturing Accurate Snapshots Snapshots are captured iteratively by a crawler. An ideal snapshot is instantaneous. But the overlay is large and rapidly changing. Captured snapshots are likely to be distorted. Previous studies captured either Complete snapshots with slow crawler => distorted Partial snapshots => less distorted, but unrepresentative Some types of analysis require the whole graph. Increasing crawler speed reduces distortion in captured snapshots.

5
Slide 5/18 CCW 2005http://mirage.cs.uoregon.edu/P2P Cruiser: a Fast Gnutella Crawler Features: Distributed, highly parallelized implementation Dynamic adaptation to bandwidth & CPU constraints Cruiser is orders of magnitude faster than other P2P crawlers: Captures one million nodes in around 7 minutes 140,000 peers/min, compared to 2,500 peers/min [Saroiu 02] We investigated the effects of speed on distortion. 4% node distortion and 15% edge distortion Daniel Stutzbach and Reza Rejaie, Capturing Accurate Snapshots of the Gnutella Network, the Global Internet Symposium, March, 2005.

6
Slide 6/18 CCW 2005http://mirage.cs.uoregon.edu/P2P Data Set More than 80,000 snapshots, over the past year. To examine static properties, we focus on four: To examine dynamic properties, we use slices: Each slice is 2 days of ~500 back-to-back snapshots Captured starting 10/14/04, 10/21/04, 11/25/04, 12/21/04, and 12/27/04 DateTotal NodesLeavesUltrapeersTop-level Edges 9/27/04725,120614,912110,2081,212,772 10/11/04779,535662,568116,9671,244,219 10/18/04806,948686,719120,2291,331,745 2/2/051,031,471873,130158,3451,964,121

7
Slide 7/18 CCW 2005http://mirage.cs.uoregon.edu/P2P Summary of Characterizations Graph Properties Implementation heterogeneity Degree Distribution: Top-level degree distribution Ultrapeer-leaf connectivity Degree-distance correlation Reachability: Path lengths Eccentricity Small world properties Resiliency Dynamic Properties Existence of stable core: Uptime distribution Biased connectivity Properties of stable core: Largest connected component Path lengths Clustering coefficient

8
Slide 8/18 CCW 2005http://mirage.cs.uoregon.edu/P2P Top-level Degree This is the degree distribution among ultrapeers. There are obvious peaks at 30 and 70 neighbors. A substantial number of ultrapeers have fewer than 30. What happened to the power-law reported by prior studies? Max 30 in most clients Max 75 in some clients Custom

9
Slide 9/18 CCW 2005http://mirage.cs.uoregon.edu/P2P What happened to power-law? When a crawl is slow, many short-lived peers report long-lived peers as neighbors. But those neighbors are not all present at the same time. Degree distribution from a slow crawl resembles prior results. [Ripeanu 02 ICJ]

10
Slide 10/18 CCW 2005http://mirage.cs.uoregon.edu/P2P Shortest-Path Distances Distribution of distances among ultrapeers (left) 70% of distances are exactly 4 hops. Distribution of distances among all peers (right) Most distances are 5 or 6 hops. Shows the effect of the two-tier with multiple parents Despite large size, pair-wise distances are short.

11
Slide 11/18 CCW 2005http://mirage.cs.uoregon.edu/P2P Small worlds arise naturally in many places. Movies actors, power grid, co-authors of papers Small world graphs have short distances, but significant clustering, compared to a similar random graph. Gnutella is a small world. Very high clustering adversely affects flooding queries. But Gnutella isnt too clustered to affect performance. Is Gnutella a Small World? Mean Distance Clustering Coefficient Gnutella4.20.018 Random3.80.00038

12
Slide 12/18 CCW 2005http://mirage.cs.uoregon.edu/P2P Resiliency to Node Failure Ratio of connected peers after node failure. The Gnutella topology is extremely resilient to random node failure. Its resilient even when the highest-degree nodes are removed. Complex algorithms are not necessary to achieve resiliency. Random Highest degree first

13
Slide 13/18 CCW 2005http://mirage.cs.uoregon.edu/P2P Dynamic Properties How does node churn affect overlay dynamics? Are some regions of the overlay more stable? How can we identify such a region? Methodology: Capture a long series of back-to-back snapshots Estimate the uptime of individual peers in the last snapshot Group peers with uptime higher than a threshold Examine biased connectivity within each group Newly arrived peer Departed peer Present for 2 snapshots Present for 5 snapshots Time

14
Slide 14/18 CCW 2005http://mirage.cs.uoregon.edu/P2P Stable Core Most peers have a short uptime. Other peers have been around for a long time. Stable core: a set of peers with uptime higher than a threshold ( ). Higher threshold => more stable group of peers T > 20 h T > 10 h

15
Slide 15/18 CCW 2005http://mirage.cs.uoregon.edu/P2P Biased Connectivity Hypothesis: long-lived nodes tend to be more connected to other long-lived nodes Rationale: Once connected, they stay connected. Long-lived peers have more opportunities to become neighbor. To quantify bias in the connectivity of the stable core: Randomize the edges to create a graph without biased connectivity. Compare the edges in the observed stable core with the randomized graph.

16
Slide 16/18 CCW 2005http://mirage.cs.uoregon.edu/P2P Stable Core Edges 20%40% more edges in the stable core compared to random. Connectivity exhibits an onion-like biased connectivity where peers are more likely to connect to other peers with same/higher uptime. We examined other properties of the stable core. Despite high churn, there is a relatively stable backbone.

17
Slide 17/18 CCW 2005http://mirage.cs.uoregon.edu/P2P Summary Characterizations of Gnutella overlay based on recent and accurate snapshots. Graph properties: The degree distribution in Gnutella is not power law. Gnutella exhibits small world characteristics. Gnutella is resilient. Dynamic properties: There is a stable core within the overlay topology. Peer churn causes the stable core to exhibit an onion-like biased connectivity. This effect is likely to occur in other unstructured P2P systems. Daniel Stutzbach, Reza Rejaie, Subhabrata Sen,Characterizing Unstructured Overlay Topologies in Modern P2P File-Sharing Systems, Internet Measurement Conference, Berkeley, 2005

18
Slide 18/18 CCW 2005http://mirage.cs.uoregon.edu/P2P Future Work Examining underlying causes of the biased connectivity. Exploring long-term trends in overlay properties. Characterizing churn Characterizing properties of other widely- deployed P2P systems Kad (a DHT with more than 1 million users) BitTorrent Developing sampling techniques for P2P

19
Slide 19/18 CCW 2005http://mirage.cs.uoregon.edu/P2P Ultrapeer->Leaf Degree LimeWire ultrapeers have a limit of 30 leaf peers. BearShare ultrapeers have a limit of 45 leaf peers. There are distinct spikes at those points, with an even distribution of fewer leaf peers. LimeWire BearShare Other Custom

Similar presentations

OK

Jeopardy Q 1 Q 6 Q 11 Q 16 Q 21 Q 2 Q 7 Q 12 Q 17 Q 22 Q 3 Q 8 Q 13

Jeopardy Q 1 Q 6 Q 11 Q 16 Q 21 Q 2 Q 7 Q 12 Q 17 Q 22 Q 3 Q 8 Q 13

© 2018 SlidePlayer.com Inc.

All rights reserved.

To make this website work, we log user data and share it with processors. To use this website, you must agree to our Privacy Policy, including cookie policy.

Ads by Google