[Gzz-commits] gzz/Documentation/misc/hemppah-progradu mastert...

[Hermanni Hyytiälä]

CVSROOT:        /cvsroot/gzz
Module name:    gzz
Changes by:     Hermanni Hyytiälä <address@hidden>      03/03/21 06:25:56

Modified files:
        Documentation/misc/hemppah-progradu: masterthesis.tex 

Log message:
        Clarify zipf, scale-free and power-law

CVSWeb URLs:
http://savannah.gnu.org/cgi-bin/viewcvs/gzz/gzz/Documentation/misc/hemppah-progradu/masterthesis.tex.diff?tr1=1.167&tr2=1.168&r1=text&r2=text

Patches:
Index: gzz/Documentation/misc/hemppah-progradu/masterthesis.tex
diff -u gzz/Documentation/misc/hemppah-progradu/masterthesis.tex:1.167 
gzz/Documentation/misc/hemppah-progradu/masterthesis.tex:1.168
--- gzz/Documentation/misc/hemppah-progradu/masterthesis.tex:1.167      Thu Mar 
20 09:47:24 2003
+++ gzz/Documentation/misc/hemppah-progradu/masterthesis.tex    Fri Mar 21 
06:25:56 2003
@@ -198,8 +198,8 @@
 is a pure Peer-to-Peer network as no peer is more important than any other 
peer in the network.
 The construction and maintenance of Gnutella network is extremely ad hoc, 
since participating
 peers can form the overlay network based on \emph{local} knowledge. Figure 
\ref{fig:gnutella_overlay}
-illustrates the overlay network of Gnutella network. The Gnutella network can 
be considered as a variation of scale-free
-graph \cite{albert-02-statistical}. In scale-free graphs only a few peers have 
high 
+illustrates the overlay network of Gnutella network. The Gnutella network can 
be considered as a variation of power-law
+graph \cite{albert-02-statistical}. In power-law graphs only a few peers have 
high 
 number of neighbor links and the majority of peers have low number of neighbor 
links.
 
 \begin{figure}
@@ -1104,8 +1104,8 @@
 several studies show, the popularity of queries in the Internet follow 
Zipf-like 
 distributions\footnote{Zipf-distribution is a variant of power-law function. 
 Zipf-distribution can be used in observation of frequency of occurrence event 
$E$, as a function of the rank 
-$i$ when the rank is determined by the frequency of occurrence, $E_i \sim 
\frac{1}{i^{a}}$, where the exponent 
-$a$ is close to unity.} (e.g., \cite{breslau98implications}). Therefore, 
caching and pre-computation
+$i$ when the rank is determined by the frequency of occurrence, is a power-law 
function $E_i \sim \frac{1}{i^{a}}$, 
+where the exponent $a$ is close to unity.} (e.g., 
\cite{breslau98implications}). Therefore, caching and pre-computation
 can be done for optimizing search indices \cite{li03feasibility}. Regular 
compression algorithms,
 Bloom filters \cite{362692}, vector space models 
\cite{CuencaAcuna2002DSIWorkshop} and view 
 trees \cite{Bhattacharjee03resultcache} can be used for even better 
optimizations. Authors