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

[Hermanni Hyytiälä]

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Changes by:     Hermanni Hyytiälä <address@hidden>      03/03/12 07:57:42

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                                             progradu.bib 

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Index: gzz/Documentation/misc/hemppah-progradu/masterthesis.tex
diff -u gzz/Documentation/misc/hemppah-progradu/masterthesis.tex:1.130 
gzz/Documentation/misc/hemppah-progradu/masterthesis.tex:1.131
--- gzz/Documentation/misc/hemppah-progradu/masterthesis.tex:1.130      Wed Mar 
12 05:58:45 2003
+++ gzz/Documentation/misc/hemppah-progradu/masterthesis.tex    Wed Mar 12 
07:57:42 2003
@@ -19,7 +19,7 @@
 %***********************
 \title{Fenfire in Peer-to-Peer Environment}
 
-\translatedtitle{Fenfire ja vertaisverkot}
+\translatedtitle{Fenfire vertaisverkko ympäristössä}
 
 \author{Hermanni Hyytiälä}
 
@@ -35,14 +35,14 @@
 Hermanni Hyytiälä\\
 Huhtalammentie 5 as. 17\\
 40640 Jyväskylä\\
-sähköposti: address@hidden
+E-mail: address@hidden
 
 
 \abstract{
 In this thesis, we review existing Peer-to-Peer approaches, algorithms and 
their
 key properties. We summarize open problems in Peer-to-Peer networks and divide
 problems into three sub-categories. We observe that there are many
-problems, which have not solutions at all, or problems have proposed
+problems, which have no solutions at all, or problems that have proposed
 solutions but they are practically unrealizable.
 
 Then, we give an overview of Fenfire system.  We evaluate existing
@@ -51,7 +51,7 @@
 related data from Peer-to-Peer network.
 }
 \tiivistelma{
-Tässä opinnäytetyössä arvioimme olemassaolevia vertaisverkkoja, algoritmeja ja
+Tässä opinnäytetyössä esittelemme olemassaolevia vertaisverkkoja, algoritmeja 
ja
 niiden erityisominaisuuksia. Teemme yhteenvedon olemassa olevista ongelmista
 vertaisverkoissa ja jaamme ongelmat kolmeen alakategoriaan. Havaitsemme, että
 on olemassa useita ongelmia, joihin ei ole ratkaisua lainkaan, tai on ehdotelma
@@ -92,7 +92,9 @@
 Dave Winer \cite{winer00whatisp2p} lists several
 properties of Peer-to-Peer network, while most notably the statement 
 ''The user's machine is a client and a server'' describes best Peer-to-Peer
-systems. To summarize, Peer-to-Peer systems can be characterized as 
distributed 
+systems. Schollmeier \cite{schollmeier01p2pdefinition} characterizes a 
Peer-to-Peer network as a system of 
+distributed entities that share their own resources (e.g. CPU time or storage 
space). 
+To summarize, Peer-to-Peer systems can be characterized as distributed 
 systems in which all communication is symmetric and all participants have 
identical 
 capabilities and responsibilities. Each \emph{peer} may contribute data or 
 computing resources (e.g., unused storage) to the overall system and the 
welfare 
@@ -104,10 +106,10 @@
 data lookup and security. In this thesis, we\footnote{Use of the plural is 
customary even if research paper is authored solely.}
 focus on these aspects in Peer-to-Peer domain.
 Specifically, we review existing Peer-to-Peer approaches, algorithms and their 
key properties. We observe
-that despite of create amount of proposed Peer-to-Peer systems, all systems 
fall either
+that despite of great amount of proposed Peer-to-Peer systems, all systems 
fall either to
 loosely structured approach or tightly structured approach. We also discuss 
open problems in 
-Peer-to-Peer systems and divide problems into three sub-categories: security 
related problems, 
-performance related problems and miscellaneous problems. In the end, we 
summarize all 
+Peer-to-Peer systems and divide problems into three sub-categories: security 
problems, 
+performance problems and miscellaneous problems. In the end, we summarize all 
 problems in easy-to-understand tables. 
 
 Next, we give an overview of Fenfire hypermedia system, which implements 
xanalogical storage model. We
@@ -130,7 +132,7 @@
 is to find the most efficient way to locate and fetch Fenfire related data 
from the 
 Peer-to-Peer network, where Storm scroll block's identifier is given. Second, 
we want
 to find the most efficient way to locate and fetch most recent Fenfire related 
data from the
-the Peer-to-Peer network, which is associated with a given pointer random 
string. Third problem
+Peer-to-Peer network, which is associated with a given pointer random string. 
Third problem
 is otherwise same as the second problem, except we want to locate and fetch 
all Fenfire
 related data from the Peer-to-Peer network, where given date and/or time range 
is given.
 
@@ -139,7 +141,7 @@
 existing Peer-to-Peer approaches, algorithms and key differences. In chapter 
3, we
 address open problems in Peer-to-Peer domain and divide problems into three
 sub-categories. Chapter 4 gives an overview of Fenfire system. In chapter
-5, we evaluate existing Peer-to-Peer approaches with regard to Fenfire system, 
propose system
+5, we evaluate existing Peer-to-Peer approaches with regard to Fenfire system, 
propose a system
 model for Fenfire in Peer-to-Peer environment and present simple algorithms to 
perform data 
 lookups in Peer-to-Peer environment. In addition, we discuss possible problems 
of using Fenfire
 in Peer-to-Peer environment. In chapter 6, we present conclusions and future 
work.
@@ -185,18 +187,18 @@
 lookup and maintain security in a varying distributed environment. The most 
popular
 form of modern Peer-to-Peer computing is file-sharing. In this scenario, 
participants
 of Peer-to-Peer network share their resources to other participants while 
obtaining
-more resources from others. This can been seen as a variant of distributed 
file system
+more resources from others. This can be seen as a variant of distributed file 
system
 (e.g., \cite{levy90distributedfilesystems}). 
 
 In a development of modern Peer-to-Peer systems, lot of influences has been 
attained from 
-other research areas than computer science. There has been done research 
regarding 
-to ad-hoc nature of complex networks \cite{albert-02-statistical}, 
\cite{albert-00-tolerance}, \cite{watts00dynamics}. 
+other research areas than computer science. Research has been conducted 
regarding 
+to self-organizing nature of complex networks \cite{albert-02-statistical}, 
\cite{albert-00-tolerance}, \cite{watts00dynamics}. 
 It's interesting to realize that chemical properties of cells, the Internet, 
ad-hoc 
-Peer-to-Peer systems, have all in common that they self-organize based on same 
-principles.  Furthermore, the association between social connections among 
people 
+Peer-to-Peer systems, and social networks have all in common that they 
self-organize based on same 
+principles.  Furthermore, the association between social relationships among 
people 
 and Peer-to-Peer overlay topology has been studied recently  
\cite{watts00dynamics}, 
 \cite{kleinberg99small}, \cite{nips02-Kleinberg}. This insight is motivated
-by Milgram, how noticed that people are very effective to locate other people 
in a wide scale 
+by Milgram, who noticed that people are very effective to locate other people 
in a wide scale 
 based on local knowledge. This phenomenon is called as ''small-world 
phenomenon'' 
 \cite{milgram67smallworld}. As a consequence, many modern Peer-to-Peer systems
 have applied techniques outside of computer science when constructing and 
maintaining
@@ -204,24 +206,24 @@
 
 In the end, however, there are two main approaches in which all modern 
Peer-to-Peer
 systems fall: loosely structured approach and tightly structured approach. In 
loosely
-structured approach the construction and the maintenance of the overlay-- as 
the name
-suggests- is controlled loosely. This approach gives freedom for participating 
peers
+structured approach the construction and the maintenance of the overlay is 
controlled 
+loosely. This approach gives freedom for participating peers
 to perform certain tasks in Peer-to-Peer network. On the other hand, tightly 
structured
 approach has some rules, which all participating peers have to obey. In the 
following
-sections, we discuss in more detail both approaches, they disadvantages and 
advantages, and
+sections, we discuss in more detail both approaches, their disadvantages and 
advantages, and
 key differences. 
 
 
 \section{Centralized}
 
 Napster\footnote{We decided to include Napster in this section only because it 
has
-historical value (see previous section).} \cite{napsterurl}  was designed to 
to allow 
+historical value (see previous section).} \cite{napsterurl}  was designed to 
allow 
 people to share music. It was a hybrid Peer-to-Peer file-sharing system, i.e., 
the search 
 index was centralized and the distribution of storage and serving of files was 
distributed. 
 Peers in the Napster network performed requests to the central directory 
server to find 
-other peers hosting desirable content. Since service requests was totally 
based on 
+other peers hosting desirable content. Since service requests were totally 
based on 
 centralized index, Napster didn't scale well because of constantly updated 
central 
-directory, and had a possibility to single point of failure. 
+directory, and had a single point of failure. 
 
 
 \section{Loosely structured}
@@ -231,8 +233,10 @@
 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 how peers form an overlay network. Initially, peer 1 creates the 
overlay, since
-it's the first participating peer. Then, repeatly new peers join the network 
and connects to
-other nodes in a random manner. Thus, Gnutella can be considered as a 
variation of \emph{random graph}.
+it's the first participating peer. Then, repeatedly new peers join the network 
and connect to
+other nodes in a random manner. Thus, Gnutella can be considered as a 
variation of \emph{scale-free
+graph}\footnote{In scale-free graphs (also known as power-law graphs) only a 
few peers have high number of neighbor 
+links and major of peers have low number of neighbor links.}.
 
 \begin{figure}
 \centering
@@ -245,12 +249,12 @@
 In Gnutella, each participating peer maintains local index of its own shared 
content. Also,
 each peer has a few connections to other peer, i.e., peer's \emph{neighbors}. 
Basic Gnutella
 data lookup works as follows: peer broadcasts a query request to its 
neighbors, which in turn
-forwards the query to their neighbors. This leads in the situation where 
number of messages
-in the network can grow with $O(n^{2})$, where $n$ is the number of 
participating peers in the
+forwards the query to their neighbors. This leads to a situation where number 
of messages
+in the network can grow with $O(n^{2})$, where $n$ is the number of 
participating peers in
 Gnutella network. To limit the amount of network traffic, Gnutella uses 
Time-To-Live-limited
-(TTL) flooding to distributed queries. Gnutella uses a Breadth-First-Search 
(BFS) with depth limit 
-$T$ (e.g., 7), where $T$ is the system-wide maximum TTL of a message in hops. 
Therefore, only peers that 
-are TTL hops away from the query originator will forward the query or respond 
to the query. 
+(TTL) flooding to distributed queries. Therefore, Gnutella uses a 
Breadth-First-Search (BFS) algorithm
+with depth limit $T$ (e.g., 7), where $T$ is the system-wide maximum TTL of a 
message in hops. Thus, 
+only peers that are TTL hops away from the query originator will forward the 
query or respond to the query. 
 In Gnutella network, search results are fast, because BFS sends queries to 
 every possible neighbor. Clearly, this method wastes resources and doesn't 
scale well.
 Figure \ref{fig:gnutella_query} shows the data lookup process of the Gnutella 
network.
@@ -265,7 +269,7 @@
 According to \cite{lv02searchreplication}, Gnutella's way to perform data 
lookups, \emph{flooding}, has
 following limitations. First, choosing the appropriate TTL in practice is not 
easy. If the
 TTL is too high, query originator may unnecessarily strain the network. If the 
TTL is too
-low, the query originator might not find the desired data even it's available 
somewhere
+low, the query originator might not find the desired data even if it's 
available somewhere
 in the network. Second, there are many duplicate messages generated by 
flooding, especially
 in high connectivity graphs. It is obvious that with these limitations, 
flooding creates 
 significant message processing overhead for each data lookup. Even worse, 
flooding may increase 
@@ -273,21 +277,20 @@
 
 Lately, there has been done lot of research to improve Gnutella's data lookup 
efficiency 
 and scalability. Adamic et al. \cite{adamic99small}, 
\cite{adamic02localsearch}, 
-\cite{adamic01powerlawsearch} has been studied different random walk methods 
in power-law 
-networks\footnote{In power-law networks only a few peers have high number of 
neighbor 
-links and major of peers have low number of neighbor links.} and have found 
that by 
+\cite{adamic01powerlawsearch} has studied different random walk methods in 
power-law 
+networks and have found that by 
 instructing peers forwarding data lookups to select high degree peers, the 
performance of data lookup 
 increases significantly. As a result, some of the most recent loosely
 structured Peer-to-Peer systems have adopted this method with some 
modifications
 \cite{gnutella2url}, \cite{shareazaurl}, \cite{fasttrackurl}, 
\cite{morpheusurl}, 
-\cite{kazaaurl}, \cite{jxtaurl}, \cite{jxtaoverview}, 
\cite{botros01jxtasearch},
+\cite{kazaaurl}, \cite{waterhouse02searchp2p}, \cite{botros01jxtasearch},
 \cite{ganesan02yappers}.
 Figures \ref{fig:gnutella_overlay_supernodes} and 
\ref{fig:gnutella_overlay_cluster}
 illustrates two possible variations of power-law overlay networks. All the 
systems
 share the property of that high degree peers maintain index of all other peers 
 they know about. However, it's not clear whether this algorithm is scalable or 
not, 
-as majority of the query request are sent only to the high degree peers, 
making 
-them stress the overhead of nearly entire system.
+as majority of the query requests are sent only to the high degree peers, 
making 
+them stress the load of entire system.
 
 \begin{figure}
 \centering
@@ -318,16 +321,16 @@
 all peers $p$ in system. Then, $\forall s \in S$, there is a provider of the 
service, 
 expressed as $p = provider(s)$. Every $p$ has neighbor(s), named as 
$neighbor$, which 
 is $P$ = \{$p \in P: \exists neighbor$, which is randomly chosen from $P$\}.
-\emph{Super peer} is a peer, which hosts the indices of other peers, $sp = 
summaryindex(provider(s))$.
-Moreover, $\forall$ regular peer $p$, there is super peer, which has has a 
index of regular
-peer's content, specifically $ps$, $P$ = \{$p \in P: \exists ps$, 
-where $ps$ = $summaryindex(provider(s)) \wedge (p = provider(s))$\}
+\emph{Super peer} is a peer, which hosts the indices of other peers, $si = 
summaryindex(provider(s))$
+and $\forall$ regular peer $p$, there is super peer, which has has a index of 
regular
+peer's content, specifically $sp$, $P$ = \{$p \in P: \exists sp$, 
+where $sp$ = $provider(summaryindex(provider(s))) \wedge (p = provider(s))$\}
 
 
 \section{Tightly structured}
 
 Partly due to scalability problems of loosely structured systems, several 
tightly 
-structured overlays has been proposed.
+structured overlays have been proposed.
 This list includes CAN \cite{ratnasamy01can}, Chord \cite{stoica01chord}, 
 Kademlia \cite{maymounkov02kademlia}, Kelips \cite{gupta03kelips}, 
 Koorde \cite{kaashoek03koorde}, ODHDHT \cite{naor03simpledht}, 
@@ -351,7 +354,7 @@
 
 To store data into tightly structured overlay, each application-specific
 unique key (e.g., SHA-1 \cite{fips-sha-1}) is \emph{mapped} uniformly (e.g., 
using consistent
-hashing \cite{258660}) by the overlay to a existing peer in the overlay. Thus, 
tightly 
+hashing \cite{258660}) by the overlay to an existing peer in the overlay. 
Thus, tightly 
 structured overlay assigns a subset of all possible keys to every 
participating peer. 
 Also, each peer in tightly structured overlay maintains a \emph{routing 
table}, which 
 consists of identifiers and IP addresses of other peers in the overlay. 
Entries of routing
@@ -373,7 +376,7 @@
 bit-wise exclusive or (XOR) (e.g., Kademlia \cite{maymounkov02kademlia}).
 Because of XOR-metric, Kademlia's distance function is both unidirectional
 (for a given point $p_i$ in the identifier space and distance $d$ > 0, there
-is exactly one point $p_j$ in way that the distance between $p_i$ and $p_j$
+is exactly one point $p_j$ in a way that the distance between $p_i$ and $p_j$
 is $d$) and symmetric (the distance from $p_i$ to $p_j$ is same as the
 distance from $p_j$ to $p_i$) \cite{maymounkov02kademlia}. On the other
 hand, Chord's \cite{stoica01chord} distance function does have the property 
@@ -386,7 +389,7 @@
 hop in the overlay shortens the distance between current peer working with the 
data lookup 
 and the key which was looked up in the identifier space. 
 
-Skip Graphs and Swan employ a key space very similar to a tightly structured
+Skip Graphs \cite{AspnesS2003} and SWAN \cite{bonsma02swan} employ a key space 
very similar to a tightly structured
 overlay, but in which queries are routed  to \emph{keys}. In these systems
 peer occupies several positions in the identifier space, one for each 
 application-specific key. The indirection of placing close keys in the 
@@ -395,7 +398,7 @@
 ''resource peer'' in the overlay network for each resource item pair it 
publishes.
 
 PeerNet differs from other tightly structured overlays in that it operates
-at the \emph{network} level layer. PeerNet makes an explicit distinction 
+at the \emph{network} layer. PeerNet makes an explicit distinction 
 between peer identity and address, which is not supported by standard
 TCP/IP-protocols. Otherwise, PeerNet has the same performance properties
 as other tightly structured overlays, i.e., $O(\log{n})$ space required
@@ -416,19 +419,19 @@
 differences in the data structure that they use as a routing table. For 
example, Chord 
 \cite{stoica01chord}, Skip graphs \cite{AspnesS2003} and Skipnet 
\cite{harvey03skipnet2} maintain a local 
 data structure which resembles Skip lists \cite{78977}.
-In figure \ref{fig:structured_query}, we present overview of Chord's lookup 
process.
-On the left side of Chord's lookup process, we show the same data lookup 
process
-as binary-tree abstraction.  We can notice, that in each step, the distance 
between
-logarithmic efficiency. 
+In figure \ref{fig:structured_query}, we present an overview of Chord's lookup 
process.
+On the right side of Chord's lookup process, the same data lookup process
+is shown as a binary-tree abstraction.  It can be noticed, that in each step, 
the distance 
+decreases between with a logarithmic efficiency. 
 
 Kademlia \cite{maymounkov02kademlia}, Pastry \cite{rowston01pastry} and 
Tapestry 
 \cite{zhao01tapestry} uses balanced $k$-trees as routing table's data 
structure. Figure 
-\ref{fig:kademlia_lookup} shows the process of Kademlia
+\ref{fig:kademlia_lookup} shows the process of Kademlia's
 data lookup. Viceroy \cite{malkhi02viceroy} maintains a butterfly data 
structure (e.g., \cite{226658}), 
 which requires only constant number of neighbor peers while providing 
$O(\log{n})$ data lookup
 efficiency. Koorde \cite{kaashoek03koorde}, recent modification of Chord, uses 
de Bruijn graphs 
-\cite{debruijn46graph} to maintain local routing tables. Koorde requires each 
peer to have only 
-about two links to other peers to to provide $O(\log{n})$ performance.
+\cite{debruijn46graph} to maintain local routing tables. Koorde 
\cite{kaashoek03koorde} requires 
+each peer to have only about two links to other peers to provide $O(\log{n})$ 
performance.
 
 \begin{figure}
 \centering
@@ -500,11 +503,11 @@
 is defined as $i = identifier(s)$. Metric space is defined as a pair $(IS,d)$, 
where $d$
 is the distance between two coordinate points $ip_i$, $ip_j$ in $IS$ space. 
Mapping 
 function is defined as $map: I \longmapsto IS$, and coordinate point as 
-$ip = map(identifier(s))$, which maps data items, expressed by a identifier to 
coordinate 
+$ip = map(identifier(s))$, which maps data items, expressed by an identifier 
to coordinate 
 point $ip$ in $(IS,d)$. Peer's p resources are mapped onto a set $IS$ = \{$ip 
\in IS: 
 \exists s \in S$, $ip = map(identifier(s)) \wedge (provider(s) = p)$\}.
 Every $p$ has neighbor(s), named as $neighbor$, which are $P$ = \{$p \in P: 
\exists neighbor$, 
-where $difference(p,p_neighbor)= ''close''$, where $''close''$ is small 
difference $d$ in $(IS,d)$\}.
+where $difference(p,neighbor) = ''close''$, where $''close''$ is small 
difference $d$ in $(IS,d)$\}.
 
 
 \section{Summary}
@@ -515,19 +518,19 @@
 
 \subsection{Differences}
 
-Even loosely structured and tightly structured approach are both Peer-to-Peer 
schemes, they 
+Even though loosely structured and tightly structured approach are both 
Peer-to-Peer schemes, they 
 have very little in common. Indeed, the only thing they share is the fact that 
no other peer is more
-important than other peer in the Peer-to-Peer network. Fault tolerance 
\emph{may} may
-be an area, in which approaches have similar properties (e.g., single point of 
failure).
+important than an other in the Peer-to-Peer network. Fault tolerance \emph{may}
+be an area, in which approaches have similar properties (e.g., no single point 
of failure).
 However, fault-tolerance properties of both approaches are currently only 
initial calculations, or 
 experimented in simulation environments. In real-life, measuring fault 
tolerance is much more 
 challenging task and requires more research to get reliable answers.
  
-Thus, there are significant differences between loosely structured and tightly 
structured approaches.
-The most important aspect is the performance and scalability. While 
performance of loosely structured approach 
-is not always even linear, generally tightly structured approach can perform 
all internal operations in
-poly-logarithmic time\footnote{However, it is unknown whether all proposed 
algorithms can preserve 
-logarithmic properties in real-life applications or not.}. 
+There are significant differences between loosely structured and tightly 
structured approaches.
+The most important difference between approaches is performance and 
scalability properties. While 
+performance of loosely structured approach is not always even linear, 
generally tightly structured 
+approach can perform all internal operations in poly-logarithmic 
time\footnote{However, it is unknown 
+whether all proposed algorithms can preserve logarithmic properties in 
real-life applications or not.}. 
 
 Another key point is the philosophy how overlay network is constructed and 
maintained. While loosely 
 structured approach gives much freedom to individual peers to join and leave 
the overlay network, tightly 
@@ -535,12 +538,12 @@
 (such as mapping of data items). 
 
 To end user, biggest difference between these systems is how data lookups are 
performed. Loosely
-structured systems provide much more richer and user friendly way of searching 
data as they
-have support for keyword search and fuzzy search. On the other hand, tightly 
structured systems support
+structured systems provide more richer and user friendly way of searching data 
as they
+have support for keyword search. On the other hand, tightly structured systems 
support
 only exact key lookups as each data item is identified by globally unique keys.
 
-In the end, both systems have open problems and issues. We will discuss these 
aspects more detail in 
-chapter 3. Table \ref{table_comparison_approach} lists key differences between 
loosely structured 
+In the end, both systems have open problems and issues. We will discuss these 
aspects in more detail in 
+chapter 3. Table \ref{table_comparison_approach} lists the key differences 
between loosely structured 
 approach and tightly structured approach.
 
 
@@ -653,7 +656,7 @@
 listed above belongs to tightly structured approach since there has been 
active 
 research being pursued towards tightly structured approach lately. List 
doesn't 
 include \emph{all} proposed Peer-to-Peer algorithms. Only the ones which 
already have 
-been widely deployed in real life, or the ones which may promising in the 
future's 
+been widely deployed in real life, or the ones which may be promising in the 
future 
 Peer-to-Peer systems are included in this thesis.
  
 We decided to follow the guidelines from \cite{kaashoek03koorde} when
@@ -728,7 +731,7 @@
 \parbox{37pt}{$O(1)$} &
 \parbox{37pt}{$O(1)$} &
 \parbox{37pt}{$O(n)$} &
-\parbox{85pt}{Typical configuration is 5 connections (2*5=10 total), however, 
depends on implementation} &
+\parbox{85pt}{Typical configuration is 5 connections (2*5=10 total), however, 
this depends on implementation} &
 \parbox{85pt}{Number of messages can grow as fast as $O(n^{2})$}
 \\ \hline
 
@@ -738,7 +741,7 @@
 \parbox{37pt}{$O(\log{n})$} &
 \parbox{37pt}{$O(\log{n})$} &
 \parbox{85pt}{$2(\log{n})$} &
-\parbox{85pt}{There is no action required when nodes leaves the system}
+\parbox{85pt}{There is no action required when peers leave the system}
 \\ \hline
 
 
@@ -747,7 +750,7 @@
 \parbox{37pt}{$O$($\sqrt{n}$)} &
 \parbox{37pt}{$O(1)$} &
 \parbox{85pt}{$\frac{n}{\sqrt{n}} + c*(\sqrt{n}-1) + \frac{Totalnumber of 
files}{\sqrt{n}}$, where n is the number of nodes and c the number of 
contacts/foreign affinity group} &
-\parbox{85pt}{Insert/delete overhead is constant and performed background, the 
performance of system may decrease if nodes are not homogeneous and nodes join 
and leave the system in a dynamic manner}
+\parbox{85pt}{Insert/delete overhead is constant and performed in the 
background, the performance of system may decrease if nodes are not homogeneous 
and nodes join and leave the system in a dynamic manner}
 \\ \hline
 
 \parbox{37pt}{Koorde \cite{kaashoek03koorde}} &
@@ -755,7 +758,7 @@
 \parbox{37pt}{$O(1)$ or $O(\log{n})$} &
 \parbox{37pt}{$O(\log{n})$ or $O(\frac{\log{n}}{\log{}\log{n}})$} &
 \parbox{85pt}{$2(\log{n})$} &
-\parbox{85pt}{Based on Chord algorithm, uses de Bruijn graphs for better 
efficiency/fault-tolerance}
+\parbox{85pt}{Based on Chord algorithm, uses de Bruijn graphs for better 
efficiency and fault tolerance}
 \\ \hline
 
 \parbox{37pt}{ODHDHT \cite{naor03simpledht}} &
@@ -763,7 +766,7 @@
 \parbox{37pt}{$O(\log{n})$} &
 \parbox{37pt}{$O(\log{n})$} &
 \parbox{85pt}{$2(\log{n})$} &
-\parbox{85pt}{There are two lookup algorithms. The other is $O(\log{n})$, 
which is robust under random deletion. The second is $O(\log^2{n})$, which is 
also robust under spam generating model}
+\parbox{85pt}{There are two lookup algorithms. The other is $O(\log{n})$, 
which is robust under random deletion. The second is $O(\log^2{n})$, which is 
also robust under spam generating model.}
 \\ \hline
  
  
@@ -797,7 +800,7 @@
 \parbox{37pt}{$O(\log{n})$} &
 \parbox{37pt}{$O(\log{n})$} &
 \parbox{85pt}{$4r(\log{n}) + (\log{n})$, where r=number of resources 
provided)} &
-\parbox{85pt}{In this approach, node is treated as 'named resource'; in this 
approach, \emph{resources} self-organize (opposite to DHTs)}
+\parbox{85pt}{In this approach, node is treated as ''named resource''}
 \\ \hline
 
 \parbox{37pt}{SkipNet \cite{harvey03skipnet2}} &
@@ -813,7 +816,7 @@
 \parbox{37pt}{$O(1)$} &
 \parbox{37pt}{$O(n)$} &
 \parbox{85pt}{Can be 1-10000 connections (aka social connections, connections 
are permanent)} &
-\parbox{85pt}{Connection number depends on node's memory/network capabilities}
+\parbox{85pt}{Number of connections number depends on node's memory/network 
capabilities}
 \\ \hline
 
 \parbox{37pt}{Symphony \cite{gurmeet03symphony}} &
@@ -821,7 +824,7 @@
 \parbox{37pt}{$O(\log{n})$} &
 \parbox{37pt}{$O(\log{n})$} &
 \parbox{85pt}{$2k+2+f$, where k = long range connections, 2 = node's 
neighbors, f = fault-tolerance connections)} &
-\parbox{85pt}{Space can be also $O(1)$. Additional space of $space^2$ can be 
used as a lookahead list for better performance, not necessarily fault-tolerant 
because of constant degree of neighbors}
+\parbox{85pt}{Space can be also $O(1)$. Additional space of can be used as a 
lookahead list for better performance, not necessarily fault-tolerant because 
of constant degree of neighbors}
 \\ \hline
 
 \parbox{37pt}{SWAN \cite{bonsma02swan}} &
@@ -829,7 +832,7 @@
 \parbox{37pt}{$O(1)$} &
 \parbox{37pt}{$O(\log^2{n})$} &
 \parbox{85pt}{$r(2b+2s+2l)$ (where r=number of resources provided, b=boot 
connections, s=short range connections, l=long range connections), typical 
connection configuration: 2*(6+7+8)=36} &
-\parbox{85pt}{In this approach, node is treated as 'named resource'; in this 
approach, \emph{resources} self-organize (opposite to DHTs)}
+\parbox{85pt}{In this approach, node is treated as ''named resource''}
 \\ \hline
 
 
@@ -838,7 +841,7 @@
 \parbox{37pt}{$O(\log{n})$} &
 \parbox{37pt}{$O(\log{n})$} &
 \parbox{85pt}{$(2^{b - 1})\frac{\log{n}}{b}$, where $b$ is a configurable 
parameter for tuning digit-fixing properties (routing table)} &
-\parbox{85pt}{The performance of system performance may decrease if nodes are 
not homogeneous and nodes join and leave the system in a dynamic manner, based 
on Plaxton's algorithm}
+\parbox{85pt}{The system performance may decrease if nodes are not homogeneous 
and nodes join and leave the system in a dynamic manner, based on Plaxton's 
algorithm}
 \\ \hline
 
 \parbox{37pt}{Viceroy \cite{malkhi02viceroy}} &
@@ -846,7 +849,7 @@
 \parbox{37pt}{$O(1)$} &
 \parbox{37pt}{$O(\log{n})$} &
 \parbox{85pt}{11} &
-\parbox{85pt}{The performance of system performance may decrease if nodes are 
not homogeneous and nodes join and leave the system in a dynamic manner, not 
necessarily fault-tolerant because of constant degree of neighbors}
+\parbox{85pt}{The system performance may decrease if nodes are not homogeneous 
and nodes join and leave the system in a dynamic manner, not necessarily 
fault-tolerant because of constant degree of neighbors}
 \\ \hline
 
 
@@ -861,12 +864,12 @@
 
 \chapter{Open Problems in Peer-to-Peer}
 
-In this chapter, we discuss open problems in Peer-to-Peer domain. We describe
+In this chapter, we discuss open problems in Peer-to-Peer research. We describe
 open problems and their proposed solutions. Then, we list all issues in
 tables; we list description of the problem, solution and comments on that
 specific open problem. Note that open problems list considered here is not 
meant
 to be an exhaustive survey of \emph{all} open problems in Peer-to-Peer domain; 
-we focus our attention to security, scalability, usability and performance 
related issues
+we focus our attention to security, scalability, usability and performance 
issues
 only.
 
 \section{Overview}
@@ -877,20 +880,20 @@
 systems may no longer apply with Peer-to-Peer systems. Therefore, new 
solutions are 
 needed to make Peer-to-Peer systems more secure and efficient.
 
-Both loosely structured and tightly structured approach have their own main 
problems. 
-Since Napster \cite{napsterurl} and Gnutella \cite{gnutellaurl} was first time 
introduced 
-to public, researchers' main concern has been scalability problem of loosely 
structured 
+Both loosely structured and tightly structured approach have their own 
specific problems. 
+Since Napster \cite{napsterurl} and Gnutella \cite{gnutellaurl} was first 
introduced 
+to public, researchers' main concern has been the scalability problem of 
loosely structured 
 approach. However, people often misunderstand the scalability problem of 
loosely structured 
 approach; \emph{network} of loosely structured systems is scalable, but the 
\emph{data lookup model} is not. 
 The main concern of tightly structured system is to make overlay's data lookup 
-routing more flexible against hostile attacks. Another key problems in tightly 
structured 
+routing more flexible against hostile attacks. Other key problems in tightly 
structured 
 systems are the lack of keyword searches, support for heterogeneous peers and 
load balancing
 \cite{balakrishanarticle03lookupp2p}.
 
 To make Peer-to-Peer systems even more popular (e.g., in industry), 
Peer-to-Peer domain
 needs better infrastructures to deal with security issues. There has been done 
some
 research regarding anonymity, access control, data availability and data 
integrity but as
-we state in the following sections, much more research work is required to 
solve security related issues.
+we state in the following sections, much more research work is required to 
solve security issues.
 
 \section{Security problems in Peer-to-Peer}
 
@@ -905,7 +908,7 @@
 In Sybil attack model, hostile entity presents multiple 
 entities. Therefore, one hostile entity can control a large fraction of the 
Peer-to-Peer system. Optimal
 possible solution to Sybil attack would be that system could \emph{distinct} 
entities of the system reliably. Unfortunately,
-currently there no realizable techniques for this task. Partial solutions for 
Sybil attack is to replicate
+currently there are no realizable techniques for this task. Partial solutions 
for Sybil attack is to replicate
 and fragment data randomly among several participating peer. However, both 
suggestions assume that two different 
 remote entities are actually different; Sybil attacks are still possible and 
therefore, would need centralized 
 authority for reliable authentication. As author argues in 
\cite{douceur02sybil}, without centralized authority, 
@@ -914,22 +917,22 @@
  
 In random fail-stop model, cited in \cite{naor03simpledht}, faulty peer is 
deleted from the Peer-to-Peer system.
 The reason for faultiness of peer can be a software failure, a hostile attack, 
or external threat such as virus or
-Trojan. Closely related to fail-stop model is the Byzantine attack model 
-\cite{357176}. Byzantine model can been seen more severe than fail-stop model 
as there are no restrictions over 
+trojan. Closely related to fail-stop model is the Byzantine attack model 
+\cite{357176}. Byzantine model can be seen as more severe than fail-stop model 
as there are no restrictions over 
 the behavior of faulty peers. Practical, but partial solution for Byzantine 
failures has been proposed by Castro et 
-al \cite{296824}. 
+al. \cite{296824}. 
 
 Spam generating attack is another known attack model against Peer-to-Peer 
system. In Spam
 attack, hostile or faulty peer may produce false information of the data, or 
refuses/is not able to reply to requests. 
 Possible solution against this attack is that peer should not trust to single 
entity. Instead, peer should get 
-information from multiple entities and trust on majority's opinion. This 
methods requires more messages to be 
-sent to network while increasing the load of system. However, if Spam attack 
is combined with Sybil attack, obviously 
+information from multiple entities and trust on majority's opinion. This 
method requires more messages to be 
+sent to network while increasing system load. However, if Spam attack is 
combined with Sybil attack, obviously 
 previously mentioned solution doesn't work. Again, more research is required 
to solve this attack model 
 safely. Naor et al. \cite{naor03simpledht} has proposed a partial solution 
against Spam attack with 
 \emph{faulty} peers (not hostile).
 
-Traditional overload of targeted peers is best known form of distributed 
Denial of Service attack (DDoS). For example, 
-hostile entity can attempt to burden targeted peers with garbage network 
packets. As a implication, peers may act
+Traditional overloading of targeted peers is best known form of distributed 
Denial of Service attack (DDoS). For example, 
+hostile entity can attempt to burden targeted peers with garbage network 
packets. As an implication, peers may act
 incorrectly or stop working. DDoS attack may be very severe, especially if 
rate of replication and caching 
 in Peer-to-Peer system is low. This may lead to data loss in the Peer-to-Peer 
system. Daswani et al. 
 \cite{daswani02queryflooddos} has done research regarding to this subject. 
Authors suggest efficient load balancing 
@@ -947,27 +950,28 @@
 Trust in Peer-to-Peer systems is based on \emph{reputation}. Proposed 
reputation methods focus either
 on the semantic properties, or data management properties of the trust model. 
Some research has been 
 done on reputation models in Peer-to-Peer systems, such as 
\cite{aberer01trust}, \cite{cornelli02reputableservents}. 
-Implementations include Advogato \cite{advogatourl}. None of the current 
proposals or implementations 
+One implementation include Advogato \cite{advogatourl}. None of the current 
proposals or implementations 
 based on reputation address trust in a reliable way.
 
 Optimal solution for trust in Peer-to-Peer systems would be certificate based 
security models.
 Quite recently, widely used Public Key Infrastructure (PKI) has been deployed 
in distributed
-systems \cite{rivest96sdsi}, \cite{spkiworkinggroup}. PKI is an reliable 
technology for securing
+systems \cite{rivest96sdsi}, \cite{spkiworkinggroup}. PKI is reliable 
technology for securing
 data in rather \emph{static} computing systems, such as in the Internet. 
However, in Peer-to-Peer 
 network, the problem of key based security mechanism is the maintenance of the 
keys as participating
-peer constantly join and leave the system. Specifically, the distribution of 
key changes comes an essential
+peers constantly join and leave the system. Specifically, the distribution of 
key changes comes an essential
 problem in ad hoc environments. These include revocation of keys and new key 
distribution in hostile 
 environment.
 
 ConChord \cite{ajmani02conchord} is the first Peer-to-Peer system which has a 
support for PKI based
-security infrastructure. Unfortunately, ConChord is in early in development 
and lacks of important
-features of PKI to be fully usable yet. Furthermore, the hierarchy of 
SDSI/SPKI \cite{rivest96sdsi}, 
-\cite{spkiworkinggroup} may be a problem for Peer-to-Peer systems, in which 
hierarchy is intentionally missing.
+security infrastructure. Still, however, ConChord \cite{ajmani02conchord} is 
in early phase of development and lacks of 
+important features of PKI to be fully usable yet. Furthermore, the hierarchy 
of Simple Distributed Security Infrastructure 
+(SDSI) \cite{rivest96sdsi} and Simple Public Key Infrastructure (SPKI) 
\cite{spkiworkinggroup} may be a problem for 
+Peer-to-Peer systems, in which hierarchy is intentionally missing.
 
 For data integrity, on the other hand, there are few working solutions. 
Cryptographic content hashes
-\cite{fips-sha-1}, variations \cite{merkle87hashtree} and their implementation 
techniques \cite{mohr02thex},
-are efficient and reliable method for identifying the integrity of data in 
Peer-to-Peer systems. One
-possible application of cryptographic content hashes may in peer identifier 
creation process, in which
+\cite{fips-sha-1}, their variations \cite{merkle87hashtree} and implementation 
techniques \cite{mohr02thex},
+are efficient and reliable methods for identifying the integrity of data in 
Peer-to-Peer systems. One
+possible application of cryptographic content hashes may be in peer identifier 
creation process, in which
 IP address of peer can be verified by the other peer. This is one form of 
\emph{self-certifying data}. 
 
 
@@ -976,12 +980,12 @@
 According to \cite{dingledine00free}, there exists several kinds of anonymity. 
Author-anonymity is a form
 of anonymity in which no one can link author to a specific document. In 
publisher-anonymity system,
 no one is able to link publisher to a specific document. Reader-anonymity 
means that a specific
-document cannot be linked to document's readers. This form of anonymity 
protects the privacy of a
+document cannot be linked to document's readers. This form of anonymity 
protects the privacy of
 users of the system. Furthermore, peer-anonymity means that no peer can be 
linked to a specific document, i.e.,
-no one is able to determine the peer, in where document was originally 
published. Document-anonymity
+no one is able to determine the peer, where the document was originally 
published. Document-anonymity
 means that peer doesn't know which data it is currently hosting. Finally, 
query-anonymity is a form
 of document-anonymity; when other peers performs data lookups, peer doesn't 
know which data it serves
-to the data lookup originators. As the authors cite, some of forms of 
anonymity may imply each other and
+to the data lookup originators. As the authors cite, some forms of anonymity 
may imply each other and
 possible issues raised by this property is one area of future work.
 
 With regard to anonymity in Peer-to-Peer systems, there has been done much 
research work both at network 
@@ -990,9 +994,9 @@
 
 Obviously, providing several types of anonymity, it often conflicts with other 
key properties of
 Peer-to-Peer system. Let's consider anonymity and efficient data lookup. In 
efficient data lookup, we must know
-the peers responsible to given data in Peer-to-Peer system. Of course, when we 
know the peers responsible
+the peers responsible for given data in Peer-to-Peer system. Of course, when 
we know the peers responsible
 for the data, the anonymity of peer is lost. Fortunately, there are partial 
solutions to previously
-mentioned situations, such as \emph{pseudonym} which is a partial form of 
anonymity. For instance, pseudonym can used for 
+mentioned situations, such as \emph{pseudonym} which is a partial form of 
anonymity. For instance, pseudonym can be used for 
 addressing peer-anonymity by providing anonymous-like identifiers to peers 
(e.g., peer identifiers of tightly 
 structured system).
 
@@ -1001,12 +1005,12 @@
 Freenet \cite{clarke00freenet}, Publius \cite{pub00}, Free haven 
\cite{dingledine00free}, Crowds \cite{reiter98crowds},
 Tangler \cite{502002} and upcoming Mnet \cite{mneturl}. Forwarding proxies are 
used in Freenet, Crowds and 
 Free Haven in order to provide various types of anonymity. Tangler and Publius 
uses cryptographic
-sharing methods to split a data into data fragments \cite{Shamir1979a}. Mix 
mailer networks, such as
+sharing methods to split data into fragments \cite{Shamir1979a}. Mix mailer 
networks, such as
 \cite{mixminionurl}, are commonly used in distributed systems, which are able 
to provide some level
-of anonymity
+of anonymity.
 
 Even if many existing Peer-to-Peer systems are able to provide some of the 
types of anonymity, there is no
-such a system which is able to provide all kinds of anonymity as listed above. 
Specifically, the conflicts
+such system which is able to provide all kinds of anonymity as listed above. 
Specifically, the conflicts
 between anonymity and other Peer-to-Peer system properties requires more 
research work.
 
 
@@ -1014,13 +1018,14 @@
 
 Any distributed computing system must support different levels of access 
control. For instance, in Peer-to-Peer
 system, we may want to restrict the accessibility of data to only limited 
amount of participating peers. Yet, Peer-to-Peer 
-systems doesn't have working and distributed access control scheme. Moreover, 
+systems do not have working and distributed access control scheme. Moreover, 
 there has been a lot of violation of copyright laws by users of Peer-to-Peer 
file sharing systems. As a 
-consequence, some lawsuits has been created against the companies how have 
build popular file-sharing programs.
+consequence, some law suits have been created against the companies who have 
build popular file-sharing programs.
 
 To our knowledge, Nejdl et al. \cite{nejdl03accesscontrol} have proposed very 
recently first practical solution to access 
-control problem in Peer-to-Peer systems. They use RDF-based schema policies to 
restrict access to certain
-data. Unfortunately, their current prototype works only in loosely structured 
systems.
+control problem in Peer-to-Peer systems. They use Resource Description 
Framework (RDF) \cite{w3rdfurl} based 
+schema policies to restrict access to certain data. Unfortunately, their 
current prototype works only in 
+loosely structured systems.
 
 
 \subsection{Hostile entities}
@@ -1036,21 +1041,22 @@
 Of course centralized authorities could be used for assignment of peer 
identifiers, but they have 
 property of single point of failure. Furthermore, distributed peer 
identification assignment can
 be problematic as long as Sybil attack \cite{douceur02sybil} remains unsolved. 
However, there are some partial solutions
-for controlling the rate at which and hostile entity is able to obtain peer 
identifier, such as crypto-based
+for controlling the rate at which hostile entity is able to obtain peer 
identifier, such as crypto-based
 puzzles \cite{juels99clientpuzzles}.
 
-In the end, none of previously mentioned solutions are able to identify 
hostile entities in practical,
+In the end, none of the previously mentioned solutions are able to identify 
hostile entities in practical,
 efficient way. More research is required to solve these problems.
 
 
 \subsection{Secure query routing}
 
 Much work has been done on secure routing, especially related to tightly 
structured systems. In 
-\cite{castro02securitystructured} and \cite{castro02securerouting}, authors 
suggests the usage
+\cite{castro02securitystructured} and \cite{castro02securerouting}, authors 
suggest the usage
 of constrained routing tables and diverse routes, and detection of faults 
during query routing.
-Additionally, authors present a important aspect of tightly structured 
approach with regard
+Additionally, authors present an important aspect of tightly structured 
approach with regard
 to fault-tolerant query routing: the probability of routing successfully 
between to arbitrary, 
-correct peers, when a fraction $f$ of the other peers are faulty or hostile, 
is only $(1-f)^{h-1}$.
+correct peers, when a fraction $f$ of the other peers are faulty or hostile, 
is only $(1-f)^{h-1}$, where
+$h$ is the number of hops in the overlay.
 
 Sit and Morris \cite{sit02securitycons} discuss the possibility of allowing 
query originator 
 to observe lookup progress and cross-check routing tables using random 
queries. However, their
@@ -1058,7 +1064,7 @@
 in function.
 
 Additionally, Lynch et al. \cite{lynch02atomicdataaccess} propose a solution 
to secure routing table 
-maintenance, but their solution seems to have to major problems 
\cite{castro02securitystructured}. First,
+maintenance, but their solution seems to have two major problems 
\cite{castro02securitystructured}. First,
 the solution is very expensive even without faulty or hostile entities. 
Second, each group of replicas
 in their solution must have less than 1/3 of its peer faulty. Thus, this 
feature results in a low
 probability of successful routing.
@@ -1070,7 +1076,7 @@
 
 Fiat et al. in \cite{fiat02censorship}, 
\cite{saia02dynamicfaultcontentnetwork} and Datar in \cite{datar02butterflies}  
 describe tightly structured overlay with analytical results in the presence of 
hostile entities. However,
-none of these proposals doesn't address an efficient, dynamic tightly 
structured overlay and multiple rounds
+none of these proposals address an efficient, dynamic tightly structured 
overlay and multiple rounds
 of hostile attack. Also, above mentioned proposals are not very efficient. In 
\cite{fiat02censorship}, each node 
 must maintain information of $O(\log^3{n})$ other peers, and in 
\cite{datar02butterflies}, $O(\log^2{n})$ is required.
 
@@ -1081,7 +1087,7 @@
 
 \subsection{Other security threats}
 
-Ross Lee graham lists several external threats against Peer-to-Peer networks 
\cite{grahamp2psecurity}. Most important, 
+Ross Lee Graham lists several external threats against Peer-to-Peer networks 
\cite{grahamp2psecurity}. Most important, 
 the list includes viruses and Trojan. Currently, there are not even partial 
solutions
 to the problems mentioned above. General robustness properties of Peer-to-Peer 
system is able to 
 deal with software failures and hostile attack, but fault tolerance against 
external threats is unknown. 
@@ -1113,10 +1119,10 @@
 may not be fast when desired data item requires many consecutive flooding 
rounds.
 
 Directed BFS \cite{yang02improvingsearch} optimizes the original 
-BFS in way that peer selects neighbors with many quality results
-may be reached, thereby maintaining the the quality of costs and decreasing 
the amount
+BFS in a way that peer selects neighbors with many quality results are reached 
earlier, 
+thereby maintaining the quality of costs and decreasing the amount
 of messages sent to network. Alpine \cite{alpineurl} and NeuroGrid 
\cite{joseph02neurogrid} 
-are Peer-to-Peer system which use somewhat similar method when performing data 
lookups.
+are Peer-to-Peer systems which use somewhat similar method when performing 
data lookups.
 
 Local indices \cite{yang02improvingsearch} is one variation of active caching. 
 In this scheme, each peer maintains an index over the data of all nodes within 
@@ -1129,14 +1135,14 @@
 randomly selected neighbor. The basic random walk approach decreases the
 overhead generated by messages. On the other hand, basic random walk approach
 has poor response time. As suggested in \cite{lv02searchreplication},
-random walk approach can be done more effective by introducing
-multiple ''walkers''. Freenet \cite{clarke00freenet} Peer-to-Peer system uses 
+random walk approach can be made more effective by introducing
+multiple ''walkers''. Freenet \cite{clarke00freenet} uses 
 random walk searches in query lookups. Indeed, Freenet's query resembles
 Depth-First-Search (DFS) and peers' routing tables are dynamically built
 using caching. This is an outcome of Freenet's main design principles, 
 i.e., anonymity. Another property of Freenet's data lookup model is that
 it adapts well with varying usage patterns. Improvements to Freenet's data 
lookup using
-''small-world phenomenon'' has been proposed by Zhang et al.. 
\cite{zhang02using}.
+''small-world phenomenon'' has been proposed by Zhang et al. 
\cite{zhang02using}.
 
 
 Since tightly structured systems have efficient data lookup at the application 
level overlay,
@@ -1161,21 +1167,21 @@
 To make Peer-to-Peer systems even more popular (and usable), these systems 
have to support flexible, efficient
 and easy to use search methods. For instance, Internet's perhaps the most 
important feature
 is the ability to perform keyword or fuzzy searches (e.g., Google). Currently, 
only loosely
-structured systems are able carry out this requirement. Unfortunately, as 
discussed in this text,
+structured systems are able to carry out this requirement. Unfortunately, as 
discussed in this text,
 the data lookup model of loosely structured approach is not scalable. Thus, 
research efforts have
 been focused on tightly structured approach. 
 The main problem with tightly structured approach is the fact that tightly 
structured algorithms
-performs data lookups based on a globally unique identifier (key). Quite 
recent study has been focused 
+perform data lookups based on a globally unique identifier (key). Quite recent 
study has been focused 
 on the feasibility of Peer-to-Peer Web-like indexing and searching 
\cite{li03feasibility} on top of
 tightly structured overlays. Authors argue, that it is possible to implement 
Peer-to-Peer Web-like search with certain radical compromises. 
-First, Peer-to-Peer search engine may need to decrease result quality in order 
make searching more
+First, Peer-to-Peer search engine may need to decrease result quality in order 
to make searching more
 efficient. Second, Peer-to-Peer systems must observe better the properties of 
underlying network for
 better performance. 
 
 Some studies have been concentrated on SQL-like queries \cite{harren02complex}
-in tightly structured overlays. Another approaches include adaption of data 
lookup model of loosely 
+in tightly structured overlays. Other approaches include adaption of data 
lookup model of loosely 
 structured approach into tightly structured systems 
\cite{ansaryefficientbroadcast03}, \cite{chord:om_p-meng}.
-Additional studies include additional layer upon overlay network 
\cite{kronfol02fasdsearch}, 
+Some studies include additional layer upon overlay network 
\cite{kronfol02fasdsearch}, 
 \cite{joseph02p2players} and range queries \cite{andrzejak02rangequeries}.
 
 Many techniques have been developed in order to provide more efficient search 
indexing. As 
@@ -1203,27 +1209,27 @@
 structured system, peers join and leave the system constantly without any 
restrictions. On the
 other hand, however, peers in tightly structured system have less freedom, 
i.e. overlay chooses peer's
 neighbors on behalf of peer itself and maps data items randomly throughout the 
overlay network. However,
-Peer-to-Peer system is \emph{never} in ''ideal'' state as it is always 
evolving system.
+Peer-to-Peer system is \emph{never} in ''ideal'' state as it is continuouslys 
evolving system.
 
-Current research has been focused on system management of tightly structured 
systems, since all presented
+Current research has been focused on system management of tightly structured 
systems, and all presented
 algorithms of tightly structured approach have been analyzed under static 
simulation environments. Furthermore, proposed 
 tightly structured overlays are configured statically to achieve the desired 
reliability even in uncommon and adverse environment
 \cite{rowston03controlloingreliability}. The most important factor for
-future research is to get real-life experiences from tightly structured 
system, when there are frequent
+future research is to get real-life experiences from tightly structured 
systems, when there are frequent
 joins and leaves in the system. Some research has been done already in this 
area. 
 
 A concept of ''half-life'' was introduced by Liben-Nowell 
\cite{libennowell01observations}. Half-life is defined
 as follows: let there be $N$ live nodes at time $t$. The doubling from time 
$t$ is the time that pass before
 $N$ new additional nodes arrive into the system. The halving time from time 
$t$ is the time
-requires for half of the living nodes at time $t$ to leave the system. The 
half-life from 
+required for half of the living nodes at time $t$ to leave the system. The 
half-life from 
 time $t$ is smaller of the properties stated above. The half-life of the 
entire system is the 
-minimum half-life over all times $t$. Concept of half-time can be used as 
basic for developing
-more efficient analytical tools for modeling complex Peer-to-Peer system. 
+minimum half-life over all times $t$. Concept of half-time can be used as a 
basis for developing
+more efficient analytical tools for modeling complex Peer-to-Peer systems. 
 
 Some research has been done with regard to load balancing properties of 
tightly structured
 overlays. Byers et al. suggest "power of two choices" whereby data item is 
stored at the less loaded 
 of two (or more) random peer alternatives \cite{byers03dhtbalancing}. Rao et 
al. uses virtual servers
-to control load balance in Peer-to-Peer systems \cite{rao03loadbalancing}. 
Their work rests on
+to control load balance in Peer-to-Peer systems \cite{rao03loadbalancing}. 
Their work rests on the
 idea which was originally introduced by Chord \cite{stoica01chord} system.
 
 Also, query and routing hot spots may be an issue in tightly structured 
overlays \cite{ratnasamy02routing}. 
@@ -1234,24 +1240,24 @@
 
 As mentioned before, an implicit assumption of almost every tightly structured 
system is that there is random, uniform 
 distribution of peer and key identifiers. Even if participating peers are 
extremely heterogeneous, e.g., in
-face of computing power or network bandwidth, all data items are distributed 
uniformly. Clearly, this
+face of computing power or network bandwidth, all data items are distributed 
uniformly. Clearly, this is
 a serious problem of tightly structured overlays in face of performance and 
load balancing. Measurement study 
 by Saroiu et al. shows that there is extreme heterogeneity among participating 
peers in already deployed Peer-to-Peer 
-systems \cite{saroiu02measurementstudyp2p}. Symphony seems to be the first 
tightly structured overlay system 
-which support heterogeneity. Zhao et al. have proposed a secondary layer a top 
of structured overlay
+systems \cite{saroiu02measurementstudyp2p}. Symphony \cite{gurmeet03symphony} 
seems to be the first tightly structured overlay system 
+which supports heterogeneity. Zhao et al. have proposed a secondary layer on 
top of structured overlay
 to support heterogeneity better \cite{zhao02brocade}. 
 
 Research has been done on self-organization. Ledlie et al. propose techniques 
for forming and maintaining
 groups in highly dynamic environment \cite{ledlie02selfp2p}. Unfortunately 
their work relies on idea that
-participating peers would create multiple hierarchical groups; it's not clear 
whether this approach
+participating peers would create multiple hierarchical groups. It's not clear 
whether this approach
 is fault-tolerant and suitable to Peer-to-Peer environment. More promising 
work has been done by Rowston et al.
 in \cite{rowston03controlloingreliability}. Authors propose techniques for 
self-tuning, dealing with
 uncommon conditions (e.g., network partition and high failure rates). 
Moreover, authors argue that
-with these techniques, the concerns over the tightly structured overlay 
maintenance costs are no more
+with these techniques, the concerns over tightly structured overlay 
maintenance costs are no more
 an open issue.
 
 Finally, little research has been done regarding self-monitoring and data 
availability. Zhang et al.
-describe a arbitrary data structure on top of tightly structured overlay 
\cite{zhang03somo}. They
+describe an arbitrary data structure on top of tightly structured overlay 
\cite{zhang03somo}. They
 call their proposal as \emph{data overlay}, since it supports several 
fundamental data structures.
 Authors use this data overlay to build Self-Organized Meta data Overlay 
(SOMO), which can be used
 for monitoring health of tightly structured overlay. Fault tolerance of SOMO 
itself is currently
@@ -1264,7 +1270,7 @@
 
 \subsection{Programming guidelines and benchmarks}
 
-All existing Peer-to-Peer systems have rather different interfaces even they 
have common points and 
+All existing Peer-to-Peer systems have rather different interfaces even though 
they have common properties and 
 components. More important, all existing Peer-to-Peer systems are incompatible 
with each other. One
 of the most important area of future research is to create common programming 
abstractions, i.e.,
 interfaces, design patters and frameworks. Also, equal benchmarks are needed 
for comparing
@@ -1275,13 +1281,13 @@
 \subsection{Social behavior}
 
 Frequent assumption in Peer-to-Peer systems is that peers are willing to 
cooperate. Another belief 
-is that all peers would behave equally, i.e., all peers both consume resources 
and contributes resources.
-However, these assumptions are not true as several studies show peers rather 
consume than contribute and
-and peers are unwilling to cooperate \cite{saroiu02measurementstudyp2p}, 
\cite{oram01harnessingpower}, 
+is that all peers would behave equally, i.e., all peers both consume and 
contribute resources.
+However, these assumptions are not true as several studies show. Peers rather 
consume than contribute and
+peers are unwilling to cooperate \cite{saroiu02measurementstudyp2p}, 
\cite{oram01harnessingpower}, 
 \cite{hearn02mojonation}. 
 
-Somewhat surprisingly little research has been in this area, especially when 
considering 
-the possible impact of this \emph{unwanted social behavior} to performance of 
Peer-to-Peer 
+Somewhat surprisingly little research has been done in this area, especially 
when considering 
+the possible impact of \emph{unwanted social behavior} to performance of 
Peer-to-Peer 
 system. Problem is addressed by Golle et al. \cite{golle01incentivesp2p}. Some 
 research has been focused on semantic properties of the overlay in order to 
increase 
 cooperation among participating peers \cite{crespo02semanticoverlay}. 
Ramanathan et al. 
@@ -1291,31 +1297,31 @@
 Peer-to-Peer system, which uses empirical metrics for peer selection.
 
 
-\subsection{Simulating the Peer-to-Peer system}
+\subsection{Simulating Peer-to-Peer systems}
 
-Very little research has been done on simulating the \emph{global} 
Peer-to-Peer system. Presumably, this
+Very little research has been done on simulating a \emph{global} Peer-to-Peer 
system. Presumably, this
 is due to complex nature of Peer-to-Peer system, which makes comprehensive 
simulations very 
 difficult. Floyd et al. has been studying the simulation of the Internet in 
\cite{504642}. Authors
 state that simulating the Internet is very challenging task, because of 
Internet's heterogeneity
-and rapid change. Obviously, these factors exist also in Peer-to-Peer system 
even with higher
+and rapid change. Obviously, these factors exist also in Peer-to-Peer systems 
even with higher
 rates.
 
-As long as global simulations of Peer-to-Peer systems are lacking, we cannot 
we make any further
-analysis e.g., on usage patterns in Peer-to-Peer systems. However, we can 
assume that
-, e.g., query keywords follow the Zipf-like distributions 
\cite{breslau98implications} both in the 
+As long as global simulations of Peer-to-Peer systems are lacking, we cannot 
make any detailed
+analysis on usage patterns in Peer-to-Peer systems. However, we can assume 
that, e.g., 
+query keywords follow the Zipf-like distributions \cite{breslau98implications} 
both in the 
 Internet and in Peer-to-Peer systems.
 
 \section{Summary}
 
-In this section we summarize open problems in Peer-to-Peer systems. All open 
problems entries 
+In this section we summarize open problems in Peer-to-Peer systems. All open 
problem entries 
 listed in this section are not necessarily mentioned in the previous sections. 
Problems listed 
 here are variations of previously mentioned problems, or otherwise related to 
them. For each entry, 
-there is brief description of the problem, possible solutions and comments 
respectively.
+there is a brief description of the problem, possible solutions and comments 
respectively.
 
 Next, we list open problems in Peer-to-Peer domain. In table 
\ref{table_security_problems_Peer-to-Peer} 
-we list open problems related to security; in table 
\ref{table_performanceusability_problems_Peer-to-Peer}, 
-we list problems related to performance; in table 
\ref{table_Miscellaneous_problems_Peer-to-Peer}, 
-we list miscellaneous open problems.
+open problems related to security are listed; in table 
\ref{table_performanceusability_problems_Peer-to-Peer}, 
+problems related to performance are listed; in table 
\ref{table_Miscellaneous_problems_Peer-to-Peer}, 
+miscellaneous open problems are listed.
 
 
 \scriptsize
@@ -1620,7 +1626,7 @@
 \parbox{90pt}{Comprehensive simulations/analysis of Peer-to-Peer network} &
 \parbox{110pt}{Ability to simulate whole Peer-to-Peer network's usage 
patterns, network traffics, flux state etc} &
 \parbox{110pt}{Use same techniques as simulating/analyzing the Internet} &
-\parbox{110pt}{Only small subset of Peer-to-Peer networks has been able to 
22, because of ad hoc properties of network, more powerful solutions needed}
+\parbox{110pt}{Only small subsets of Peer-to-Peer networks has been analysed, 
because of ad hoc properties of network, more powerful solutions needed}
 \\ \hline
 
 
Index: gzz/Documentation/misc/hemppah-progradu/progradu.bib
diff -u gzz/Documentation/misc/hemppah-progradu/progradu.bib:1.103 
gzz/Documentation/misc/hemppah-progradu/progradu.bib:1.104
--- gzz/Documentation/misc/hemppah-progradu/progradu.bib:1.103  Fri Mar  7 
08:23:37 2003
+++ gzz/Documentation/misc/hemppah-progradu/progradu.bib        Wed Mar 12 
07:57:42 2003
@@ -2124,6 +2124,20 @@
        NUMBER = 2396
 }
 
address@hidden,
+       author = {Rüdiger Schollmeier},
+       title = {A definition of Peer-to-Peer Networking for the Classification 
of Peer-to-Peer Architectures and Applications},
+       booktitle = {Proceedings of the First International Conference on 
Peer-to-Peer Computing {(P2P'01)}},
+       year = {2001}
+}
 
 
-
address@hidden,
+       author = {S. R. Waterhouse and D. M. Doolin and G. Kan and Y. 
Faybishenko},
+       title = {Distributed Search in Peer-to-Peer Networks},  
+       journal = {IEEE Internet Computing},
+       volume = {6},
+       pages = {68--73}, 
+       year = {2002},
+       url = {http://www.jxta.org/project/www/docs/jsearch.pdf}
+}