Results 1  10
of
13
Freenet: A Distributed Anonymous Information Storage and Retrieval System
 INTERNATIONAL WORKSHOP ON DESIGNING PRIVACY ENHANCING TECHNOLOGIES: DESIGN ISSUES IN ANONYMITY AND UNOBSERVABILITY
, 2001
"... We describe Freenet, an adaptive peertopeer network application that permits the publication, replication, and retrieval of data while protecting the anonymity of both authors and readers. Freenet operates as a network of identical nodes that collectively pool their storage space to store data ..."
Abstract

Cited by 1062 (12 self)
 Add to MetaCart
(Show Context)
We describe Freenet, an adaptive peertopeer network application that permits the publication, replication, and retrieval of data while protecting the anonymity of both authors and readers. Freenet operates as a network of identical nodes that collectively pool their storage space to store data files and cooperate to route requests to the most likely physical location of data. No broadcast search or centralized location index is employed. Files are referred to in a locationindependent manner, and are dynamically replicated in locations near requestors and deleted from locations where there is no interest. It is infeasible to discover the true origin or destination of a file passing through the network, and difficult for a node operator to determine or be held responsible for the actual physical contents of her own node.
A model of a trustbased recommendation system on a social network. Autonomous Agents and MultiAgent Systems
, 2008
"... In this paper, we present a model of a trustbased recommendation system on a social network. The idea of the model is that agents use their social network to reach information and their trust relationships to filter it. We investigate how the dynamics of trust among agents affect the performance of ..."
Abstract

Cited by 76 (0 self)
 Add to MetaCart
(Show Context)
In this paper, we present a model of a trustbased recommendation system on a social network. The idea of the model is that agents use their social network to reach information and their trust relationships to filter it. We investigate how the dynamics of trust among agents affect the performance of the system by comparing it to a frequencybased recommendation system. Furthermore, we identify the impact of network density, preference heterogeneity among agents, and knowledge sparseness to be crucial factors for the performance of the system. The system selforganises in a state with performance near to the optimum; the performance on the global level is an emergent property of the system, achieved without explicit coordination from the local interactions of agents. 1
∗ Corresponding author
"... In order to determine a success criterion for opensource software projects, we analyzed 122,205 projects in the SourceForge database. There were 80,597 projects with no downloads at all. We restricted our analysis to the 41,608 projects that together were downloaded 704,897,520 times. Contrary to w ..."
Abstract

Cited by 2 (0 self)
 Add to MetaCart
(Show Context)
In order to determine a success criterion for opensource software projects, we analyzed 122,205 projects in the SourceForge database. There were 80,597 projects with no downloads at all. We restricted our analysis to the 41,608 projects that together were downloaded 704,897,520 times. Contrary to what we had expected, the distribution of the number of downloads of each project is not Zipflike; only a portion of the loglog plot of the number of downloads and their rank appears to be a straight line. We performed leastsquares analysis (utilizing the Bayesian information criterion) to divide the plot into three segments. On the basis of the shapes of the corresponding curves and the locations of their boundary points, we categorized the projects as follows: 85 superprojects (highly successful projects with more than 1.1 million downloads); just over 10,000 successful projects (with more than 1680 downloads each); and struggling projects (with 1680 downloads or fewer). In terms of our criterion, only a quarter of the projects that have one or more downloads can be deemed to be successful.
A NOTE ON THE DIAMETER OF PROTEAN GRAPHS
, 2008
"... The web graph is a realworld selforganizing network whose vertices correspond to web pages, and whose edges correspond to links between pages. Many stochastic models for the web graph have been recently proposed, with the aim of reproducing one or more of its observed properties and parameters. S ..."
Abstract
 Add to MetaCart
The web graph is a realworld selforganizing network whose vertices correspond to web pages, and whose edges correspond to links between pages. Many stochastic models for the web graph have been recently proposed, with the aim of reproducing one or more of its observed properties and parameters. Some of the most intensely studied parameters for the web graph are the degree distribution and diameter. A recent stochastic model of the web graph is the protean graph Pn(d, η). In this model, vertices are renewed over time, and older vertices are more likely to receive edges than younger ones. While previous work on the model focussed on the power law degree distribution of protean graphs, in this note we study its diameter. Since the protean graphs may be disconnected, we focus on the diameter of the giant component. Our main result is that diameter of the giant component of Pn(d, η) is equal to Θ(log n), which supports experimental data observed in the actual web graph.
1Understanding Complex Systems: A Communication Networks Perspective
, 2007
"... Recent approaches on the study of networks have exploded over almost all the sciences across the academic spectrum. Over the last few years, the analysis and modeling of networks as well as networked dynamical systems have attracted considerable interdisciplinary interest. These efforts were driven ..."
Abstract
 Add to MetaCart
(Show Context)
Recent approaches on the study of networks have exploded over almost all the sciences across the academic spectrum. Over the last few years, the analysis and modeling of networks as well as networked dynamical systems have attracted considerable interdisciplinary interest. These efforts were driven by the fact that systems as diverse as genetic networks or the Internet can be best described as complex networks. On the contrary, although the unprecedented evolution of technology, basic issues and fundamental principles related to the structural and evolutionary properties of networks still remain unaddressed and need to be unraveled since they affect the function of a network. Therefore, the characterization of the wiring diagram and the understanding on how an enormous network of interacting dynamical elements is able to behave collectively, given their individual non linear dynamics are of prime importance. In this study we explore simple models of complex networks from real communication networks perspective, focusing on their structural and evolutionary properties. The limitations and vulnerabilities of real communication networks drive the necessity to develop new theoretical frameworks to help explain the complex and unpredictable behaviors of those networks based on the aforementioned principles, and design alternative network methods and techniques which may be provably effective, robust and resilient to accidental failures and coordinated attacks. Index Terms Complex systems, random networks, smallworld networks, scalefree networks, communication networks.
Frequency of occurrence of numbers in the World Wide Web
, 2005
"... www.elsevier.com/locate/physa The distribution of numbers in human documents is determined by a variety of diverse natural and human factors, whose relative significance can be evaluated by studying the numbers ’ frequency of occurrence. Although it has been studied since the 1880’s, this subject re ..."
Abstract
 Add to MetaCart
(Show Context)
www.elsevier.com/locate/physa The distribution of numbers in human documents is determined by a variety of diverse natural and human factors, whose relative significance can be evaluated by studying the numbers ’ frequency of occurrence. Although it has been studied since the 1880’s, this subject remains poorly understood. Here, we obtain the detailed statistics of numbers in the World Wide Web, finding that their distribution is a heavytailed dependence which splits in a set of powerlaw ones. In particular, we find that the frequency of numbers associated to western calendar years shows an uneven behavior: 2004 represents a ‘singular critical ’ point, appearing with a strikingly high frequency; as we move away from it, the decreasing frequency allows us to compare the amounts of existing information on the past and on the future. Moreover, while powers of ten occur extremely often, allowing us to obtain statistics up to the huge 10 127, ‘nonround ’ numbers occur in a much more limited range, the variations of their frequencies being dramatically different from standard statistical fluctuations. These findings provide a view of the array of numbers used by humans as a highly nonequilibrium and inhomogeneous system, and shed a new light on an issue that, once fully investigated, could lead to a better understanding of many sociological and psychological phenomena.
Physica D 198 (2004) 51–73 Modeling share dynamics by extracting competition structure
, 2004
"... We propose a new method for analyzing multivariate timeseries data governed by competitive dynamics such as fluctuations in the number of visitors to Web sites that form a market. To achieve this aim, we construct a probabilistic dynamical model using a replicator equation and derive its learning a ..."
Abstract
 Add to MetaCart
(Show Context)
We propose a new method for analyzing multivariate timeseries data governed by competitive dynamics such as fluctuations in the number of visitors to Web sites that form a market. To achieve this aim, we construct a probabilistic dynamical model using a replicator equation and derive its learning algorithm. This method is implemented for both categorizing the sites into groups of competitors and predicting the future shares of the sites based on the observed timeseries data. We confirmed experimentally, using synthetic data, that the method successfully identifies the true model structure, and exhibits better prediction performance than conventional methods that leave competitive dynamics out of consideration. We also experimentally demonstrated, using real data of visitors to 20 Web sites offering streaming video contents, that the method suggested a reasonable competition structure that conventional methods failed to find and that it outperformed them in terms of predictive performance.