A Service Discovery Model for Mobile Agent Based Distributed Data Mining

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Author(s): Xining Li (University of Guelph, Canada)and Lei Song (University of Guelph, Canada)
Copyright: 2008
Pages: 13
Source title: Data Warehousing and Mining: Concepts, Methodologies, Tools, and Applications
Source Author(s)/Editor(s): John Wang (Montclair State University, USA)
DOI: 10.4018/978-1-59904-951-9.ch045

Keywords: Data Mining and Databases / Data Warehousing / Information Science Reference / Library & Information Science

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Abstract

Mining information from distributed data sources over the Internet is a growing research area. The introduction of mobile agent paradigm opens a new door for distributed data mining and knowledge discovery applications. One of the main challenges of mobile agent technology is how to locate hosts that provide services requested by mobile agents. Traditional Service Location Protocols can be applied to mobile agent systems to explore the service discovery issue. However, because of their architecture deficiencies, they do not adequately solve all the problems that arise in a dynamic domain such as database location discovery. From this point of view, we need some enhanced service discovery techniques for the mobile agent community. This paper proposes a new model for solving the database service location problem in the domain of mobile agents by implementing a Service Discovery Module based on Search Engine techniques. As a typical interface provided by a mobile agent server, the Service Discovery Module improves the decision ability of mobile agents with respect to information retrieval. This research is part of the IMAGO system - an infrastructure for mobile agent based data mining applications. This paper focuses on the design of an independent search engine, IMAGOSearch and discusses how to integrate service discovery into the IMAGO system, thus providing a global scope service location tool for intelligent mobile agents.

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A Service Discovery Model for Mobile Agent Based Distributed Data Mining

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