Autonomic communication in a computing system analyzes the individual system element as it is affected by and affects other elements. In the human-machine communication aspect, the autonomic system performs its services autonomously, adjusting the behavior of its services to suit what the user might request implicitly or explicitly. The pervasive multimodal multimedia computing system aims at realizing anytime, anywhere computing. Its autonomic communication includes the protocols that selects, on behalf of the user, the modalities and media devices that are appropriate to the given interaction context. The modalities are the modes of interaction (i.e. for data input and output) between the user and the computer while the media devices are the physical devices that are used to support the chosen modalities. The interaction context itself is the combined user, environment, and system contexts. In this paper, we present the autonomic communication protocols involved in the detection of interaction context and the multimodal computing system's corresponding adaptation. The heart of this paradigm's design is the machine learning's knowledge acquisition and the use of the layered virtual machine for definition and detection of interaction context. © 2009 Springer Science+Business Media, LLC.
CITATION STYLE
Hina, M. D., Tadj, C., Ramdane-Cherif, A., & Lévy, N. (2009). Autonomic communication in pervasive multimodal multimedia computing system. In Autonomic Communication (pp. 251–283). Springer US. https://doi.org/10.1007/978-0-387-09753-4_10
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