churn, are an inherent property of Peer-to-Peer (P2P)
systems that should be incorporated in both the design
and evaluation of P2P systems. This requires a proper
characterization of churn in real-world P2P networks.
However, the few previous measurement-based studies
on the characterization of P2P systems have used either
unrepresentative group of peers or coarse-grain measurements.
In this extended abstract, we characterize
churn in the Gnutella network based on fine-grained
monitoring of the entire population. We developed a new
crawler that can capture a complete snapshot ofGnutella
network within a few minutes. This not only improves
the accuracy, by reducing distortion in captured snapshots,
but it also increase the granularity of captured dynamics.
We present our preliminary characterizations
of peer uptime and discuss their implications. In particular,
we show that peer uptime follows a power-law
distribution rather than the commonly assumed Poisson
distribution. In a nutshell, a large portion of up peers
are highly stable, yet the remaining peers turnover very
quickly.
churn, are an inherent property of Peer-to-Peer (P2P)systems that should be incorporated in both the designand evaluation of P2P systems. This requires a propercharacterization of churn in real-world P2P networks.However, the few previous measurement-based studieson the characterization of P2P systems have used eitherunrepresentative group of peers or coarse-grain measurements.In this extended abstract, we characterizechurn in the Gnutella network based on fine-grainedmonitoring of the entire population. We developed a newcrawler that can capture a complete snapshot ofGnutellanetwork within a few minutes. This not only improvesthe accuracy, by reducing distortion in captured snapshots,but it also increase the granularity of captured dynamics.We present our preliminary characterizationsof peer uptime and discuss their implications. In particular,we show that peer uptime follows a power-lawdistribution rather than the commonly assumed Poissondistribution. In a nutshell, a large portion of up peersare highly stable, yet the remaining peers turnover veryquickly.
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