Abstract
In mobile agents systems, classical techniques for system optimization are not applicable due to continuous changes of the execution contexts. MAWeS (MetaPL/HeSSE Autonomic Web Services) is a framework whose aim is to support the development of self-optimizing autonomic systems for Web service architectures. In this paper we apply the autonomic approach to the reconfiguration of agent-based applications. The enrichment of the Aglet Workbench with a Web Services interface is described, along with the extensions to the MAWeS framework needed to support the mobile agents programming paradigm. Then a mobile agents application solving the N-Body problem is presented as a case study. © Springer-Verlag Berlin Heidelberg 2007.
Cite
CITATION STYLE
Mancini, E. P., Rak, M., Venticinque, S., & Villano, U. (2007). Mobile agents self-optimization with MAWeS. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4699 LNCS, pp. 1158–1167). Springer Verlag. https://doi.org/10.1007/978-3-540-75755-9_133
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