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AGE-P: An Evolutionary Platform for the Self-Organization of Smart-Appliance Ensembles

AGE-P: An Evolutionary Platform for the Self-Organization of Smart-Appliance Ensembles

Ralf Salomon, Stefan Goldmann
Copyright: © 2010 |Pages: 22
ISBN13: 9781605667058|ISBN10: 1605667056|ISBN13 Softcover: 9781616924188|EISBN13: 9781605667065
DOI: 10.4018/978-1-60566-705-8.ch008
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MLA

Salomon, Ralf, and Stefan Goldmann. "AGE-P: An Evolutionary Platform for the Self-Organization of Smart-Appliance Ensembles." Nature-Inspired Informatics for Intelligent Applications and Knowledge Discovery: Implications in Business, Science, and Engineering, edited by Raymond Chiong, IGI Global, 2010, pp. 182-203. https://doi.org/10.4018/978-1-60566-705-8.ch008

APA

Salomon, R. & Goldmann, S. (2010). AGE-P: An Evolutionary Platform for the Self-Organization of Smart-Appliance Ensembles. In R. Chiong (Ed.), Nature-Inspired Informatics for Intelligent Applications and Knowledge Discovery: Implications in Business, Science, and Engineering (pp. 182-203). IGI Global. https://doi.org/10.4018/978-1-60566-705-8.ch008

Chicago

Salomon, Ralf, and Stefan Goldmann. "AGE-P: An Evolutionary Platform for the Self-Organization of Smart-Appliance Ensembles." In Nature-Inspired Informatics for Intelligent Applications and Knowledge Discovery: Implications in Business, Science, and Engineering, edited by Raymond Chiong, 182-203. Hershey, PA: IGI Global, 2010. https://doi.org/10.4018/978-1-60566-705-8.ch008

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Abstract

Smart-appliance ensembles consist of intelligent devices that interact with each other and that are supposed to support their users in an autonomous, non-invasive way. Since both the number and the composition of the participating devices may spontaneously change at any time without any notice, traditional approaches, such as rule-based systems and evolutionary algorithms, are not appropriate mechanisms for their self-organization. Therefore, this chapter describes a new evolutionary framework, called appliancesgo- evolution platform (AGE-P) that accounts for the inherent system dynamics by distributing all data structures and all operations across all participating devices. This chapter illustrates the behavior of this framework by presenting several results obtained from simulations as well as real-world case studies.

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