Mahmoud Rafea

Publications of Mahmoud Rafea

• What makes a Web site popular?

  Authors: Petros Kavassalis, Stelios Lelis, Mahmoud Rafea, Seif Haridi

  Communications of the ACM. 01/2004; 47:50-55.

  To ensure a constant increase in user interest, clicks, recommendations, loyalty, and market share, first understand the information flows and connection networks surrounding each Web site inTo ensure a constant increase in user interest, clicks, recommendations, loyalty, and market share, first understand the information flows and connection networks surrounding each Web site in cyberspace.

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• Parallel Distributed Algorithms of the beta-Model of the Small World Graphs.

  Authors: Mahmoud Rafea, Konstantin Popov, Per Brand, Fredrik Holmgren, Seif Haridi

  Euro-Par 2003. Parallel Processing, 9th International Euro-Par Conference, Klagenfurt, Austria, August 26-29, 2003. Proceedings; 01/2003

• Parallel Agent-Based Simulation on a Cluster of Workstations.

  Authors: Konstantin Popov, Vladimir Vlassov, Mahmoud Rafea, Fredrik Holmgren, Per Brand, Seif Haridi

  Euro-Par 2003. Parallel Processing, 9th International Euro-Par Conference, Klagenfurt, Austria, August 26-29, 2003. Proceedings; 01/2003

• Parallel Agent-Based Simulation On A Cluster Of Workstations.

  Authors: Konstantin Popov, Mahmoud Rafea, Fredrik Holmgren, Per Brand, Vladimir Vlassov, Seif Haridi

  Parallel Processing Letters. 01/2003; 13:629-641.

• Application Architecture Of The Internet Simulation

  Authors: Mahmoud Rafea, Fredrik Holmgren, Konstantin Popov, Seif Haridi, Stelios Lelis, Petros Kavassalis, Jakka Sairamesh

  09/2002;

  In this paper, we present an Internet simulation application: WoM. The WoM simulation aims at showing agglomerations of users in few web sites and at studying the different factors that lead to suchIn this paper, we present an Internet simulation application: WoM. The WoM simulation aims at showing agglomerations of users in few web sites and at studying the different factors that lead to such a macro-structure. The paper focuses on the architecture of the multi-agent simulation environment. In this environment, a simulation application is constructed using four different components categories, namely: agent collections, a worker, a communication channels component, and a control component. An agent collection can be constructed from different kinds of Small World graph components. Small World graphs are used to represent the social network and web sites links. An agent collection scales to hundreds of thousands of agents. A worker component is configured from a set of behavior components to implement the behavior of agent collections. Simulation input/output is monitored through a communication channel component. The control component is responsible for configuration and initialization of the application components. The control component, also, invokes the worker at each simulation time step. For scalability, the environment architecture is designed to be suitable for distribution and parallelization.

• Regularities in the Formation and Evolution of

  Authors: Stelios Lelis, Petros Kavassalis, Jakka Sairamesh, Seif Haridi, Mahmoud Rafea

  09/2002;

  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 andIn 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. In these conditions of equal access distance, one would rather expect a smooth web geography with a relatively even distribution of visitors per site. However, the web economy illustrates strong agglomeration trends with a very small number of web sites capturing a large segment of the web population and the most of virtual economic activity. This paper attempts to provide a sound basis for the dynamics of population concentration in the web under increasing returns.

• Regularities in the Formation and Evolution of Information Cities.

  Authors: Stelios Lelis, Petros Kavassalis, Jakka Sairamesh, Seif Haridi, Fredrik Holmgren, Mahmoud Rafea, Antonis Hatzistamatiou

  Digital Cities II, Computational and Sociological Approaches, Second Kyoto Workshop on Digital Cities, Kyoto, Japan, October 18-20, 2001, Revised Papers; 01/2001

• Network Explanations to Web Economy's Patterns of Growth

  Authors: Stelios Lelis, Petros Kavassalis, Mahmoud Rafea, Seif Harid

  Society for Computational Economics, Modeling, Computing, and Mastering Complexity 2003.

  From its early days, the World Wide Web space has demonstrated strong agglomeration trends with a very small number of web sites capturing the larger part of the Internet population. At a firstFrom its early days, the World Wide Web space has demonstrated strong agglomeration trends with a very small number of web sites capturing the larger part of the Internet population. At a first glance, agglomeration over the virtual space sounds as a paradox. Web sites are numerous and highly diversified and can be easily reached from everywhere and anybody, with no particular transportation or search cost. However, Internet users use only a small number of sites for searching for information and products, interacting with others and socialize, thus producing dense concentrations and locational patterns similar to those observed in the physical space where few cities and industrial clusters host the huge majority of population and the entire industrial activity. Is that depending on the attractiveness of the popular web sites or are there agglomeration economies providing incentives to users to be in a location which have been visited by other users or pointed-in by other sites? This paper provides a sound basis for the dynamics of population concentration in the Web and put forward an explanation to web sites' growth by developing an agent-based computational model, with behavioural and economic variables, where the aggregate outcome emerges from the interaction of individual decisions. The model reproduces the empirically observed power law distribution of Internet users across web sites, demonstrating that a plausible explanation of web agglomeration phenomena can lie on the assumption of increasing returns and the percolation-like diffusion of the information over the Internet.