Abstract:Abstract. In the real world, cities exist because of external economies associated with the geographic concentration of firms within a city. Of course, such a geographic proximity with input providers and consumers, would at first reduce transportation costs. But why cities, information cities, i.e. large agglomerations of people and economic activity emerge in the virtual world? In the Internet, transportation costs are zero. Web sites can easily be reached from anybody and everywhere with no particular cost.… Show more
“…The simulation output is a sequence of statistic vectors containing numbers of visits per each site taken at every N th step. The simulation has shown that the distribution of users per sites follows a universal power law [1]. Note that the model is stochastic.…”
Section: Agent-based Modeling and Simulationmentioning
confidence: 99%
“…The "word of mouth" (WoM) simulation model is a stochastic socio-economical model that addresses the real-world phenomena of the behavior of the Internet population [1]. The model of time is discrete.…”
Section: Agent-based Modeling and Simulationmentioning
confidence: 99%
“…number of site visits) and the ratio of sites with that popularity, as well as the formation of clusters of popular sites are studied. Large-scale simulations with millions of model users may aid the understanding of the evolution of the Internet [1]. The simulator distributes data among workstations because of the memory consumption.…”
We discuss a parallel implementation of an agent-based simulation. Our approach allows to adapt a sequential simulator for large-scale simulation on a cluster of workstations. We target discrete-time simulation models that capture the behavior of Web users and Web sites. Web users are connected with each other in a graph resembling the social network. Web sites are also connected in a similar graph. Users are stateful entities. At each time step, they exhibit certain behaviour such as visiting bookmarked sites, exchanging information about Web sites in the "word-of-mouth" style, and updating bookmarks. The real-world phenomena of emerged aggregated behavior of the Internet population is studied. The system distributes data among workstations, which allows large-scale simulations infeasible on a stand-alone computer. The model properties cause traffic between workstations proportional to partition sizes. Network latency is hidden by concurrent simulation of multiple users. The system is implemented in Mozart that provides multithreading, dataflow variables, component-based software development, and network-transparency. Currently we can simulate up to 10 6 Web users on 10 4 Web sites using a cluster of 16 computers, which takes few seconds per simulation step, and for a problem of the same size, parallel simulation offers speedups between 11 and 14.
“…The simulation output is a sequence of statistic vectors containing numbers of visits per each site taken at every N th step. The simulation has shown that the distribution of users per sites follows a universal power law [1]. Note that the model is stochastic.…”
Section: Agent-based Modeling and Simulationmentioning
confidence: 99%
“…The "word of mouth" (WoM) simulation model is a stochastic socio-economical model that addresses the real-world phenomena of the behavior of the Internet population [1]. The model of time is discrete.…”
Section: Agent-based Modeling and Simulationmentioning
confidence: 99%
“…number of site visits) and the ratio of sites with that popularity, as well as the formation of clusters of popular sites are studied. Large-scale simulations with millions of model users may aid the understanding of the evolution of the Internet [1]. The simulator distributes data among workstations because of the memory consumption.…”
We discuss a parallel implementation of an agent-based simulation. Our approach allows to adapt a sequential simulator for large-scale simulation on a cluster of workstations. We target discrete-time simulation models that capture the behavior of Web users and Web sites. Web users are connected with each other in a graph resembling the social network. Web sites are also connected in a similar graph. Users are stateful entities. At each time step, they exhibit certain behaviour such as visiting bookmarked sites, exchanging information about Web sites in the "word-of-mouth" style, and updating bookmarks. The real-world phenomena of emerged aggregated behavior of the Internet population is studied. The system distributes data among workstations, which allows large-scale simulations infeasible on a stand-alone computer. The model properties cause traffic between workstations proportional to partition sizes. Network latency is hidden by concurrent simulation of multiple users. The system is implemented in Mozart that provides multithreading, dataflow variables, component-based software development, and network-transparency. Currently we can simulate up to 10 6 Web users on 10 4 Web sites using a cluster of 16 computers, which takes few seconds per simulation step, and for a problem of the same size, parallel simulation offers speedups between 11 and 14.
“…If the vertexes 1, and 4 are going to be rewired concurrently, the edges (1, 2) and (4, 5) will be deleted. The possible edges to insert are: vertex -1 = (1, 2), (1, 3), (1,4), (1,5); and vertex-4 = (4, 5), (4,6), (1,4), (2,4). The edge (1, 4) can be added by both processes.…”
Section: The Motivation Approaches and Problemsmentioning
confidence: 99%
“…The sequential agent-based simulation environment can be found in [2]. Also, one of the implemented behavior models can be reviewed in [5]. The parallel environment is under publication [3].…”
Abstract. The research goal is to develop a large-scale agent-based simulation environment to support implementations of Internet simulation applications. The Small Worlds (SW) graphs are used to model Web sites and social networks of Internet users. Each vertex represents the identity of a simple agent. In order to cope with scalability issues, we have to consider distributed parallel processing. The focus of this paper is to present two parallel-distributed algorithms for the construction of a particular type of SW graph called ¡ -model. The first algorithm serializes the graph construction, while the second constructs the graph in parallel.
We discuss a parallel implementation of an agent-based simulation. Our approach allows to adapt a sequential simulator for largescale simulation on a cluster of workstations. We target discrete-time simulation models that capture the behavior of WWW. The real-world phenomena of emerged aggregated behavior of the Internet population is studied. The system distributes data among workstations, which allows large-scale simulations infeasible on a stand-alone computer. The model properties cause traffic between workstations proportional to partition sizes. Network latency is hidden by concurrent simulation of multiple users. The system is implemented in Mozart that provides multithreading, dataflow variables, component-based software development, and network-transparency. Currently we can simulate up to 10 6 Web users on 10 4 Web sites using a cluster of 16 computers, which takes few seconds per simulation step, and for a problem of the same size, parallel simulation offers speedups between 11 and 14.
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