1. Friendships that last Peer lifespan and its role in P2P protocols
Fabián E. Bustamante & Yi Qiao
Department of Computer Science
Northwestern University
{fabianb,yqiao}cs.northwestern.edu

2. Dept. of Computer Science Northwestern University
P2P and heterogeneity
P2P computing: sharing of computer resources & services by direct exchange between participants
Purest form … all peers are equal
Problem: clash between assumption and reality - peer populations show high variations on storage, bandwidth, latency, degree of sharing, uptime, …
P2P – Idea; purest form; problem: clash bet/ assumption and heterogeneity and transient population
Dept. of Computer Science Northwestern University

3. Transient peers and P2P systems
Peers defined an overlay network
Set of connections to other peers (their “friends”)
Maintenance protocol that repairs the overlay
Degree of peer transiency
Median up-time ~ 70’
Implications
Maintenance-related messages
Plus degree of replication, effectiveness of caches, spread of queries, overall system scalability, …
Dept. of Computer Science Northwestern University

4. Dept. of Computer Science Northwestern University
Our approach
Part of the problem is whom one befriends
One solution: pick those that will live/stay long
Without knowing the future, can we predict it?
Yes; peer lifespan follows a Pareto distribution!
Given a good prediction - how should it be used in P2P protocols?
Can it really help?
Dept. of Computer Science Northwestern University

5. Determining lifespan distribution
In Gnutella, using a modified client, between March 1st-8th, 2003
Some details:
Attempt a Gnutella connection setup
20 monitoring peers for fine probe granularity
First-time found peers only recorded with Time-When-Found
Peer considered dead when
Connection attempt fails 3rd time
Unexpected response is received
Dept. of Computer Science Northwestern University

6. Peer lifespan distribution
500,000 peers, ~1 million peers’ lifespans
Create-based method for sample limited scope
Figures show RCDF of peers with lifespan in [1,300 sec, 3.5 days]
Pareto distribution of the form λTk (k < 0)
Dept. of Computer Science Northwestern University

7. Peer Lifespan and P2P protocols
Choosing among “acquaintances”:
When deciding whom to befriend
Responding to requests for references
In most P2P protocols – random selection
Peer lifespan fits a Pareto distribution
Pareto distributions Є UBNE class (Used Better than New in Expectation)
Peer’s expected remaining lifetime directly proportional to current age
Dept. of Computer Science Northwestern University

8. Dept. of Computer Science Northwestern University
Some of the questions …
How could we incorporate lifespan-based ideas into P2P systems?
Potential gains in reduced maintenance overhead
Effects on application performance …
Dept. of Computer Science Northwestern University

9. Lifespan-based protocols
Increased dependency as commitment to the community becomes clear
Protocol
Connect?
Recommend?
LSPAN-1
Oldest
Random
LSPAN-2
LSPAN-3
Oldest & more available connections
Dept. of Computer Science Northwestern University

10. Dept. of Computer Science Northwestern University
Experimental setup
Trace-driven simulation – P2P simulator includes membership management and various query distribution, cache and replication strategies
Runs of one of the 20 collected traces for a period of 510,000 sec., ~36,577 peers
Cold start, warm-up ~80,000 sec. excluded
~1,000 peers under stable conditions
Newer results where obtained using 4 traces (instead of 1)
Dept. of Computer Science Northwestern University

11. Alternative protocols compared
Unstructured Decentralized Protocol (UDP)
~ early Gnutella
Separate pools for cached pongs (per connection)
Pong replies include random set of entries from cache
Hierarchical Decentralized Protocol (HDP)
~ new Gnutella, KaZaa
Leaf- and ultra-peers: leafs can only connect to ultras; ultras to anybody
To decide a peer’s role – trace information
Dept. of Computer Science Northwestern University

12. Comparing connection breakdowns
Indicator of stability
√ Lifespan-based protocols
More selective → fewer breakdowns
Reductions
42-43% -LSPAN-2
26-30% -LSPAN-1 and LSPAN-3
Saw-tooth shape → time-of-day patterns
Dept. of Computer Science Northwestern University

13. Comparing connection rejections
Does preference for long-lived peers have to mean high rejection rates?
True for LSPAN-2 – although may be a reasonable “cost”
Still, for LSPAN-1 and LSPAN-3 low enough to be ignored LSPAN-3 ~ 1/17.58 hrs!
Dept. of Computer Science Northwestern University

14. Comparing number of connections
… not just rejections, what about number of connections?
LSPAN-1 and LSPAN-3 – higher ratio of connections per peer
Little benefit from checking available connections
Dept. of Computer Science Northwestern University

15. A preview: Effects on applications
Gains in scalability
With random-walkers & NCU (Neighboring Caching)
Lifespan-based: 5 and random topology: 16 walkers
Dept. of Computer Science Northwestern University

16. Conclusions and future work
Peer lifespan fits a Pareto distribution – current age to predict lifespan
Illustrative lifespan-based protocols
Advantages of considering peers’ age in P2P protocols
Possible research paths
Effect on query distribution and cache strategies
Lifespan-based strategies
Determining a peer’s age in decentralized P2P systems
Lifespan and DHTs
Dept. of Computer Science Northwestern University