Abstract
We discuss our research towards developing special properties that introduce autonomic behavior in distributed pattern-recognition systems. In our approach we use ASSL (Autonomic System Specification Language) to formally develop such properties for DMARF (Distributed Modular Audio Recognition Framework). These properties enhance DMARF with an autonomic middleware that manages the four stages of the framework’s pattern-recognition pipeline. DMARF is a biologically inspired system employing pattern recognition, signal processing, and natural language processing helping us process audio, textual, or imagery data needed by a variety of scientific applications, e.g., biometric applications. In that context, the notion go autonomic DMARF (ADMARF) can be employed by autonomous and robotic systems that theoretically require less-to-none human intervention other than data collection for pattern analysis and observing the results. In this article, we explain the ASSL specification models for the autonomic properties of DMARF.
This work was supported in part by an IRCSET postdoctoral fellowship grant (now termed as EMPOWER) at University College Dublin, Ireland, by the Science Foundation Ireland grant 03/CE2/I303_1 to Lero (the Irish Software Engineering Research Centre), and by the Faculty of Engineering and Computer Science of Concordia University, Montreal, Canada.
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Vassev, E., Mokhov, S.A. (2012). Developing Autonomic Properties for Distributed Pattern-Recognition Systems with ASSL. In: Gavrilova, M.L., Tan, C.J.K., Phan, CV. (eds) Transactions on Computational Science XV. Lecture Notes in Computer Science, vol 7050. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-28525-7_5
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