Title: Process-driven biometric identification by means of autonomic grid components

Authors: Thomas Weigold; Marco Aldinucci; Marco Danelutto; Vladimir Getov

Addresses: Department of Computer Science, IBM Research - Zurich, Rueschlikon, Switzerland ' Department of Computer Science, University of Torino, Torino, Italy ' Department of Computer Science, University of Pisa, Pisa, Italy ' School of Electronics and Computer Science, University of Westminster, London, UK

Abstract: Today's business applications are increasingly process driven, meaning that the main application logic is executed by a dedicate process engine. In addition, component-oriented software development has been attracting attention for building complex distributed applications. In this paper, we present the experiences gained from building a process-driven biometric identification application that makes use of grid infrastructures via the Grid Component Model (GCM). GCM, besides guaranteeing access to grid resources, supports autonomic management of notable parallel composite components. This feature is exploited within our biometric identification application to ensure real-time identification of fingerprints. Therefore, we briefly introduce the GCM framework and the process engine used, and we describe the implementation of the application by means of autonomic GCM components. Finally, we summarise the results, experiences and lessons learned focusing on the integration of autonomic GCM components and the process-driven approach.

Keywords: autonomic computing; grid component model; biometric identification; parallel applications; distributed applications; process-driven applications; biometrics; fingerprints; fingerprint identification.

DOI: 10.1504/IJAACS.2012.047659

International Journal of Autonomous and Adaptive Communications Systems, 2012 Vol.5 No.3, pp.274 - 291

Published online: 05 Dec 2014 *

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