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revision 1.167 by hemppah, Thu Mar 20 14:47:24 2003 UTC revision 1.168 by hemppah, Fri Mar 21 11:25:56 2003 UTC
# Line 198  Gnutella \cite{gnutellaurl} is a well-kn Line 198  Gnutella \cite{gnutellaurl} is a well-kn
198  is a pure Peer-to-Peer network as no peer is more important than any other peer in the network.  is a pure Peer-to-Peer network as no peer is more important than any other peer in the network.
199  The construction and maintenance of Gnutella network is extremely ad hoc, since participating  The construction and maintenance of Gnutella network is extremely ad hoc, since participating
200  peers can form the overlay network based on \emph{local} knowledge. Figure \ref{fig:gnutella_overlay}  peers can form the overlay network based on \emph{local} knowledge. Figure \ref{fig:gnutella_overlay}
201  illustrates the overlay network of Gnutella network. The Gnutella network can be considered as a variation of scale-free  illustrates the overlay network of Gnutella network. The Gnutella network can be considered as a variation of power-law
202  graph \cite{albert-02-statistical}. In scale-free graphs only a few peers have high  graph \cite{albert-02-statistical}. In power-law graphs only a few peers have high
203  number of neighbor links and the majority of peers have low number of neighbor links.  number of neighbor links and the majority of peers have low number of neighbor links.
204    
205  \begin{figure}  \begin{figure}
# Line 1104  Many techniques have been developed in o Line 1104  Many techniques have been developed in o
1104  several studies show, the popularity of queries in the Internet follow Zipf-like  several studies show, the popularity of queries in the Internet follow Zipf-like
1105  distributions\footnote{Zipf-distribution is a variant of power-law function.  distributions\footnote{Zipf-distribution is a variant of power-law function.
1106  Zipf-distribution can be used in observation of frequency of occurrence event $E$, as a function of the rank  Zipf-distribution can be used in observation of frequency of occurrence event $E$, as a function of the rank
1107  $i$ when the rank is determined by the frequency of occurrence, $E_i \sim \frac{1}{i^{a}}$, where the exponent  $i$ when the rank is determined by the frequency of occurrence, is a power-law function $E_i \sim \frac{1}{i^{a}}$,
1108  $a$ is close to unity.} (e.g., \cite{breslau98implications}). Therefore, caching and pre-computation  where the exponent $a$ is close to unity.} (e.g., \cite{breslau98implications}). Therefore, caching and pre-computation
1109  can be done for optimizing search indices \cite{li03feasibility}. Regular compression algorithms,  can be done for optimizing search indices \cite{li03feasibility}. Regular compression algorithms,
1110  Bloom filters \cite{362692}, vector space models \cite{CuencaAcuna2002DSIWorkshop} and view  Bloom filters \cite{362692}, vector space models \cite{CuencaAcuna2002DSIWorkshop} and view
1111  trees \cite{Bhattacharjee03resultcache} can be used for even better optimizations. Authors  trees \cite{Bhattacharjee03resultcache} can be used for even better optimizations. Authors

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