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

[Hermanni Hyytiälä]

CVSROOT:        /cvsroot/gzz
Module name:    gzz
Changes by:     Hermanni Hyytiälä <address@hidden>      03/02/20 05:07:20

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

Log message:
        Contents updates

CVSWeb URLs:
http://savannah.gnu.org/cgi-bin/viewcvs/gzz/gzz/Documentation/misc/hemppah-progradu/masterthesis.tex.diff?tr1=1.51&tr2=1.52&r1=text&r2=text

Patches:
Index: gzz/Documentation/misc/hemppah-progradu/masterthesis.tex
diff -u gzz/Documentation/misc/hemppah-progradu/masterthesis.tex:1.51 
gzz/Documentation/misc/hemppah-progradu/masterthesis.tex:1.52
--- gzz/Documentation/misc/hemppah-progradu/masterthesis.tex:1.51       Thu Feb 
20 04:27:15 2003
+++ gzz/Documentation/misc/hemppah-progradu/masterthesis.tex    Thu Feb 20 
05:07:18 2003
@@ -17,9 +17,9 @@
 %***********************
 %   Tyyliluokan pakolliset määritykset
 %***********************
-\title{GZZ in Peer-to-Peer Enviroment}
+\title{Gzz in Peer-to-Peer Enviroment}
 
-\translatedtitle{GZZ in Peer-to-Peer Enviroment}
+\translatedtitle{Gzz in Peer-to-Peer Enviroment}
 
 \author{Hermanni Hyytiälä}
 
@@ -70,14 +70,18 @@
 
 footnote:use of the plural is customary even if research paper is authored 
solely
 
+\section{Research problems}
+
+\section{Thesis overview}
 
 definition \cite{p2pworkinggroup}
 definition \cite{graham02lecture}
 definition \cite{winer00whatisp2p}
 
-\chapter{Peer-to-Peer approaches}
+\chapter{Peer-to-Peer schemes}
+
+\section{Overview}
 
-\section{General}
 
 Approaches:
 1) centralized (napspter, audiogalaxy: search index on single server, p2p file 
transer between clients)
@@ -198,7 +202,7 @@
 \cite{joseph02neurogrid}
 
 
-\subsection{Super peers}
+\subsection{Super peers and Super peer clusters}
 
 \begin{figure}
 \centering
@@ -207,8 +211,6 @@
 \label{fig:gnutella_overlay_supernodes}
 \end{figure}
 
-\subsection{Super peer clusters}
-
 \begin{figure}
 \centering
 \includegraphics[width=10cm, height=6cm]{gnutella_overlay_clusters.eps}
@@ -291,6 +293,22 @@
 
 \cite{fips-sha-1}
 
+
+\subsection{Formal definition}
+
+-let S be the aggregate of all services s in system (data, service, computing 
power)
+-let P be the aggregate of all peers (providers) p in system (all physical 
entities participating)
+-let I be the aggregate of all identifiers i in system (All possible unique 
identifiers, based on e.g. SHA-1)
+-let IS be the aggregate of all identifier points ip in system (entity, where 
'closeness' of services are calculated, e.g. XOR/numerical metrics, based on 
identifiers)
+-for each service s 'mathematical belongs to' S, there is a provider of the 
service, expressed as 'p = provider(s)'
+-service's identifier is defined as 'i = identifier(s)' (in our case, 
SHA-1(content of data block))
+-metric space is defined as a pair '(IS,d)', where d is the distance between 
two coordinate points ip in IS space
+-mapping function is defined as 'map: I -> IS', and coordinate point as 'ip = 
map(identifier(s))', which maps service, expressed by a identifier to 
coordinate point ip in '(IS,d)'
+%-In DHT, peer's p resources are mapped onto a set IS = {ip 'mathematical 
belongs to' IS: 'mathematical there exists at least one' s 'mathematical 
belongs to' S, ip = map(identifier(s)) 'boolean AND' (provider(s) = p)}, which 
means
+that resources that a peer provides into the system, are not kept locally. 
This is a important feature of DHTs (to be specific, feature of 'map: I -> 
IS')! In SWAN and Skip Graphs, resources are can be kept locally, if wanted!
+%-every p has neighbor(s), named as p_neighbor, which are P = {p 'mathematical 
belongs to' P: 'mathematical there exists at least one' p_neighbor, where 
'difference(p,p_neighbor)= 'close'', where 'close' is minimal difference d in 
'(IS,d'}
+
+
 \subsection{Protocols}
 
 Measures:
@@ -352,24 +370,7 @@
 \cite{debruijn46graph}
 
 
-\subsection{Formal definition}
-
--let S be the aggregate of all services s in system (data, service, computing 
power)
--let P be the aggregate of all peers (providers) p in system (all physical 
entities participating)
--let I be the aggregate of all identifiers i in system (All possible unique 
identifiers, based on e.g. SHA-1)
--let IS be the aggregate of all identifier points ip in system (entity, where 
'closeness' of services are calculated, e.g. XOR/numerical metrics, based on 
identifiers)
--for each service s 'mathematical belongs to' S, there is a provider of the 
service, expressed as 'p = provider(s)'
--service's identifier is defined as 'i = identifier(s)' (in our case, 
SHA-1(content of data block))
--metric space is defined as a pair '(IS,d)', where d is the distance between 
two coordinate points ip in IS space
--mapping function is defined as 'map: I -> IS', and coordinate point as 'ip = 
map(identifier(s))', which maps service, expressed by a identifier to 
coordinate point ip in '(IS,d)'
-%-In DHT, peer's p resources are mapped onto a set IS = {ip 'mathematical 
belongs to' IS: 'mathematical there exists at least one' s 'mathematical 
belongs to' S, ip = map(identifier(s)) 'boolean AND' (provider(s) = p)}, which 
means
-that resources that a peer provides into the system, are not kept locally. 
This is a important feature of DHTs (to be specific, feature of 'map: I -> 
IS')! In SWAN and Skip Graphs, resources are can be kept locally, if wanted!
-%-every p has neighbor(s), named as p_neighbor, which are P = {p 'mathematical 
belongs to' P: 'mathematical there exists at least one' p_neighbor, where 
'difference(p,p_neighbor)= 'close'', where 'close' is minimal difference d in 
'(IS,d'}
-
-
-
-
-\subsection{Distributed Hash Table (DHT)}
+\subsection{Distributed Hash Tables and Decentralized Object Location and 
Routing Networks}
 
 \cite{Gribble:2000:SDD}
 
@@ -383,9 +384,6 @@
 
 -CFS splits files into blocks (<50Kb), PAST distributed whole files
 
-
-\subsection{Decentralized Object Location and Routing Networks (DOLR)}
-
 \cite{kubiatowicz00oceanstore}
 
 \begin{figure}
@@ -407,19 +405,104 @@
 \section{Summary}
 
 
+\subsection{Differences}
+
+
+\scriptsize
+\begin{longtable}{|l|l|l|}
+
+\caption[Comparison of Broadicasting and Structured approaches]{Comparison of 
Broadicasting and Structured approaches} 
+\label{table_comparison_approach} 
 
 
+\\ \hline 
+\multicolumn{1}{|c|}{\textbf{Property}} &
+\multicolumn{1}{c|}{\textbf{Unstructured}} & 
+\multicolumn{1}{c|}{\textbf{Structured}}  
+ 
+\\ \hline 
+\endfirsthead
 
+\multicolumn{3}{c}%
+{{\tablename\ \thetable{} -- continued from previous page}} \\
+\hline 
+\multicolumn{1}{|c|}{\textbf{Property}} &
+\multicolumn{1}{c|}{\textbf{Unstructured}} &
+\multicolumn{1}{c|}{\textbf{Structured}}
+\\ \hline 
+\endhead
 
+\endfoot
 
 
 
+\parbox{90pt}{Queries} &
+\parbox{100pt}{Uncontrolled} &
+\parbox{100pt}{Controlled}  
+\\ \hline
 
+\parbox{90pt}{A way for performing queries} &
+\parbox{100pt}{Keywords} &
+\parbox{100pt}{Exact keys} 
+\\ \hline
+         
+\parbox{90pt}{Query traffic} &
+\parbox{100pt}{$O(n)/O(n^{2})$}  &
+\parbox{100pt}{$O(1)/O(log n)$} 
+\\ \hline
 
+\parbox{90pt}{Guaranteed data lookup} &
+\parbox{100pt}{Not necessarily} &
+\parbox{100pt}{Yes} 
+\\ \hline
 
-\subsection{Protocols}
+\parbox{90pt}{Overlay's structure} &
+\parbox{100pt}{Uncontrolled and ad hoc}  &
+\parbox{100pt}{Controlled and structured}
+\\ \hline
+                 
+\parbox{90pt}{Max. number of nodes} &
+\parbox{100pt}{Millions} &
+\parbox{100pt}{Billions} 
+\\ \hline
+                       
+\parbox{90pt}{Data placement} &
+\parbox{100pt}{Local} &
+\parbox{100pt}{Not local} 
+\\ \hline
+                 
+\parbox{90pt}{Support for heterogeneity} &
+\parbox{100pt}{Yes} &
+\parbox{100pt}{No} 
+\\ \hline
+       
+\parbox{90pt}{Support for locality} &
+\parbox{100pt}{Yes} &
+\parbox{100pt}{Partial}        
+\\ \hline
+         
+\parbox{90pt}{Possibility for routing hotspots} &
+\parbox{100pt}{No} &
+\parbox{100pt}{Yes} 
+\\ \hline
+       
+\parbox{90pt}{Design/Implementation complexity} &
+\parbox{100pt}{Low} &
+\parbox{100pt}{High} 
+\\ \hline
+
+\parbox{90pt}{Fault-tolerant} &
+\parbox{100pt}{High} &
+\parbox{100pt}{High}
+\\ \hline
 
 
+\end{longtable}
+\normalsize
+
+
+\subsection{Protocols}
+
 \scriptsize
 \begin{longtable}{|l|c|c|c|c|l|}
 
@@ -613,100 +696,6 @@
 Search: 
 Number of messages when an object lookup is performed
 
-\subsection{Differences}
-
-
-\scriptsize
-\begin{longtable}{|l|l|l|}
-
-\caption[Comparison of Broadicasting and Structured approaches]{Comparison of 
Broadicasting and Structured approaches} 
-\label{table_comparison_approach} 
-
-
-\\ \hline 
-\multicolumn{1}{|c|}{\textbf{Property}} &
-\multicolumn{1}{c|}{\textbf{Unstructured}} & 
-\multicolumn{1}{c|}{\textbf{Structured}}  
- 
-\\ \hline 
-\endfirsthead
-
-\multicolumn{3}{c}%
-{{\tablename\ \thetable{} -- continued from previous page}} \\
-\hline 
-\multicolumn{1}{|c|}{\textbf{Property}} &
-\multicolumn{1}{c|}{\textbf{Unstructured}} &
-\multicolumn{1}{c|}{\textbf{Structured}}
-\\ \hline 
-\endhead
-
-\endfoot
-
-
-
-\parbox{90pt}{Queries} &
-\parbox{100pt}{Uncontrolled} &
-\parbox{100pt}{Controlled}  
-\\ \hline
-
-\parbox{90pt}{A way for performing queries} &
-\parbox{100pt}{Keywords} &
-\parbox{100pt}{Exact keys} 
-\\ \hline
-         
-\parbox{90pt}{Query traffic} &
-\parbox{100pt}{$O(n)/O(n^{2})$}  &
-\parbox{100pt}{$O(1)/O(log n)$} 
-\\ \hline
-
-\parbox{90pt}{Guaranteed data lookup} &
-\parbox{100pt}{Not necessarily} &
-\parbox{100pt}{Yes} 
-\\ \hline
-
-\parbox{90pt}{Overlay's structure} &
-\parbox{100pt}{Uncontrolled and ad hoc}  &
-\parbox{100pt}{Controlled and structured}
-\\ \hline
-                 
-\parbox{90pt}{Max. number of nodes} &
-\parbox{100pt}{Millions} &
-\parbox{100pt}{Billions} 
-\\ \hline
-                       
-\parbox{90pt}{Data placement} &
-\parbox{100pt}{Local} &
-\parbox{100pt}{Not local} 
-\\ \hline
-                 
-\parbox{90pt}{Support for heterogeneity} &
-\parbox{100pt}{Yes} &
-\parbox{100pt}{No} 
-\\ \hline
-       
-\parbox{90pt}{Support for locality} &
-\parbox{100pt}{Yes} &
-\parbox{100pt}{Partial}        
-\\ \hline
-         
-\parbox{90pt}{Possibility for routing hotspots} &
-\parbox{100pt}{No} &
-\parbox{100pt}{Yes} 
-\\ \hline
-       
-\parbox{90pt}{Design/Implementation complexity} &
-\parbox{100pt}{Low} &
-\parbox{100pt}{High} 
-\\ \hline
-
-\parbox{90pt}{Fault-tolerant} &
-\parbox{100pt}{High} &
-\parbox{100pt}{High}
-\\ \hline
-
-
-\end{longtable}
-\normalsize
 
 
 
@@ -715,6 +704,11 @@
 
 \section{Security problems in Peer-to-Peer}
 
+\subsection{Anonymity}
+\subsection{Attack models}
+\subsection{Data authenticity and integrity}
+\subsection{Access Control}
+
 
 -Could we use SDSI/SPKI in our system (it's hierarchical), like in ConChord 
\cite{ajmani02conchord}
 -is there any other implementations of SDSI/SPKI-like systems ?
@@ -889,6 +883,7 @@
 
 c) Quality of Service, QoS
 
+
 Security
 a) Availability (Gzz: priority 3)
 
@@ -1429,7 +1424,9 @@
 \end{figure}
 
 
-\chapter{Overview of Gzz}
+\chapter{Gzz hypermedia system}
+
+\section{Overview}
 
 \section{Objectives}
 
@@ -1492,6 +1489,8 @@
 
 \section{Motivation}
 
+-need to make Gzz distributed system
+
 \section{Objectives}
 
 2.1  "Searching for a specific Storm block"
@@ -1582,13 +1581,11 @@
 \cite{bittorrenturl}
 \cite{maymounkov03ratelesscodes}
 
-\section{Existing file sharing systems and Gzz}
-
 \section{Possible problems}
 
 \cite{gribble01p2pdatabase}
 
-\chapter{Conclusion}
+\chapter{Conclusions}
 
 -Currently, DHT is the best alternative for Gzz P2P, because:
        +blocks have unique IDs, they can be used as keys in DHT, it's a 
natural choice