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} |
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 |