P2P Architecture

● "Making Gnutella-like P2P Systems Scalable", ACM SIGCOMM 2003

● "Using the Small-World Model to Improve Freenet Performance", Proc. IEEE INFOCOM, 2002

● "Samsara: Honor Among Thieves in Peer-to-Peer Storage", SOSP 2003

Making Gnutella-like P2P Systems Scalable

● Problems identified– Not scalable

● Due to flooding used on queries– Ineffective query results

● Due to TTL used to limit flooding bandwidth

● Gnutella advantages retained– Completely decentralized

● Therefore no (expensive) infrastructure required

Gnutella paper - Gia proposal

● Gia– Completely decentralized– Takes node capacity into account– Flow control– Improved search algorithm

● Replaces flooding– Content index replication on peer nodes

Gnutella paper - Why not DHTs?

● Distributed Hash Tables– Hash Table at the Internet scale

● Why are DHTs not in Gia?– DHT overhead is high for node churn– DHTs good at finding needles, not hay

● Think of the “needle in a haystack” analogy– Most P2P file searches are for hay

Gnutella paper – Gia design

● Topology adapation– Each node run the topology adaptation

algorithm until it is “satisfied”– Each node chooses new peer nodes based

on its capacity and degree– The effect of the algorithm is to

concentrate traffic to the nodes with higher capacity

Gnutella paper –Gia design (continued)

● Flow control– Active flow control - Receiver must

indicate it is willing to accept a query● It does this by granting tokens

– Avoids allowing queries to be dropped– Provides incentive for nodes to advertise

their true capacity● Query tokens assigned proportionally the

advertised capacity

Gnutella paper –Gia design (continued)

● One-hop Replication– Each node maintains an index of the

content available on each of its neighboring nodes

● Search Protocol– Searches are sent using a biased random

walk● Node capacity and search tokens are used to

bias the search

Gnutella paper – Results

Gnutella paper - Conclusion

● Gia Results– Showed that a scalable, fully

decentralized P2P network with good query results is possible

● Future work– Research centralized P2P systems

● Requires an underlying business model● Google, Yahoo show that large centralized

systems can be scalable/efficient

Using the Small-World Model to Improve Freenet Performance

● Freenet– P2P network focused on providing anonymous publishing and content access

– Each participating client provides hard drive space and network bandwidth

– Over time, only the most popular content is retained within freenet

Freenet Paper –Small world model

● Small world model– In a large population, it is likely that any

two individuals will be connected through a short sequence of intermediate acquaintances

Freenet Paper – Freenet problem

● Problem identified– Freenet hit ratio drops fast under load

● Paper identifies the simple LRU cache replacement algorithm as significant issue

Freenet Paper – Proposal

● Alter the cache replacement policy– Promote clustering– Add random short-cuts– Together this produces a small-world type

organization

Freenet Paper – Results

Freenet Paper – Conclusion

● This paper proposed an interesting P2P system model– Additionally, no change to the freenet

protocol would be required● They simulated the effects of the

proposed system● The results supported the small-world

model proposal

Samsara: Honor Among Thieves in Peer-to-Peer Storage

● Samsara is a P2P system which attempts to enforce the fair usage of resources by the nodes

● Focus is put on data storage● Attempts to have each node's

contribution approximate it's consumption

Samsara - Problem

● Tragedy of the commons– In most systems with a shared resource

● There is an incremental positive for each individual when they take additional advantage of the resource

● But, the incremental negatives aspects of them using the resource will be shared by everyone

● Therefore, each individual can easily conclude that they should maximize their usage of the resource

Samsara – Problem (continued)

● Tragedy of the commons– This is what leads to the disparity

between contribution and consumption in most P2P systems today

Samsara – Previous Solutions

● Absolute symmetric peer usage– But, usage in most P2P systems is not

symmetric● Fairness can be achieved with a

central authority– But, this runs counter to the decentralized

goal of most P2P systems

Samsara – Solution

● Samsara seeks a solution that– Enforces fair resource contributions– Is fully decentralized

● Samsara achieves these goals by “manufacturing” symmetric usage where it doesn't exist– Whenever a node uses resources of

another node, it agrees to provide an equal amount of resources in return

Samsara – Solution (continued)

● Each node can forward claims to other hosts– It retains responsibility for the data

● Cheaters are detected with queries– The queried host has a certain amount of

time to return a response● Eventually the querying host will conclude

that the other host is cheating, and it will start to drop some of it's data

Samsara – Issues

● Forwarding of claims– Each time storage is forwarded, the

systems stability is reduced● Cycles in forwarded storage

– First host in cycle once again holds the data

– Authors argue that this improves stability

Samsara – Performance

Samsara – Conclusion

● The problem was clearly identified● An unique solution was proposed● An implementation was built

– Although, it was not quite a mainstream P2P application

● The resulting implementation yielded data that supported the initial proposal