PAPER 9 The first paper (A Measurement Study of Peer-to-Peer File Sharing Systems) 
is a focused study on the usage patterns of people on the Gnutella and 
Napster file-sharing networks.  The authors developed a web-crawling-like 
system to scan the p2p infrastructure of the two networks.  They gathered 
information on number of files shared, reported bandwidth, actual bandwidth 
(by measuring it themselves), current # of uploads, current # of downloads, 
and other information.  They monitored Napster for four days and the 
Gnutella network for eight days.  Their results seemed to show that people 
on the Gnutella network were almost "better" than those people on the 
Napster network.  On average, their latencies were lower, their bandwidths 
were higher, and they misreported less.  Their initial reaction was the 
tech-savvy nature of people who used the Gnutella network (therefore having 
higher bandwidth connections).  One of the big takeaways of this paper was 
the heterogeneity of the users.  Many users (especially those on slower 
connections) acted more like clients while those on faster connections acted 
more like servers.  The authors kept making the argument that future p2p 
system designers should create systems which take this into account and do 
not assume everyone has a similar speed connection.
    One of the arguments the authors also constantly made was that software 
should not ask users for their bandwidth and other information, but rather 
that the software should measure that itself.  It seems almost ironic that 
they first say that high speed connections act like servers and are (on 
average) up more frequently and for longer durations yet they do not trust 
the end user.  It seems like the high speed connections are already doing a 
favor to the network by being up so much, it seems as if the authors do not 
trust the users.  Other problems (such as small sample size) are an issue, 
but this is resolved in the second paper.

The second paper,  Measurement, Modeling, and Analysis of a Peer-to-Peer 
File-Sharing Workload, was a detailed look at the Kazaa file sharing 
network.  This paper had a much longer sampling period (over half a year) 
which allowed the authors to view human-related cycles (such as college 
students going home over summer-break and coming back in the fall).  One of 
the first things the paper seems to point out is that people are willing to 
wait for content.  Unlike web surfing (where people normally don't wait for 
more than a few seconds before moving on to the next, possibly competing, 
site), people who downloaded content through Kazaa had no problem waiting a 
day, a week, or even longer to get files.  People, they discovered, are 
patient!  The next takeaway from this paper was that files on the Kazaa 
network did not follow a Zipf-like distribution.  Unlike DNS queries and 
other internet systems, the content, when graphed on a log-log plot, was 
clearly not Zipf.  They explain this by the fetch-at-most-once concept. 
Basically, once you have a media file you no longer need to download it. 
You have it stored locally and the external network's version is 
immutable -- there is no reason to download it again.  The phenomenon of 
"the new song" which is often immediately popular, might skew the network to 
be more zipf like temporarily, but then quickly dies back down as more and 
more people have the file.  The authors also measure something else of 
interest: the number of requests for small files (those under 10 megabytes) 
greatly outnumber (by over 10x) requests for large (>100 megabytes) files 
while the actual transferred bytes show that 65% of the bytes transferred 
are for big files and closer to 15% for smaller files.
    All in all, the papers were useful for determining the behaviors of the 
system and the users and should give insight to future p2p developers. 
While not all of the schemes are immediately realizable (like locality in 
the second paper, which will be difficult with hashing), they give good 
pointers.

--Kevin 

