DocumentCode
1957241
Title
A Tripartite Analytic Framework for Characterising Awareness and Self-Awareness in Autonomic Systems Research
Author
Schaumeier, J. ; Pitt, Jeremy ; Cabri, Giacomo
Author_Institution
Dept. of Electr. & Electron. Eng., Imperial Coll. London, London, UK
fYear
2012
fDate
10-14 Sept. 2012
Firstpage
157
Lastpage
162
Abstract
Autonomic systems exhibiting self-* properties are composed of inter-connected computational elements with increasingly sophisticated instrumentation for perception of the environment in which they are embedded. In realising these self-* properties, satisfying functional requirements, or meeting performance metrics, these components need to have, and are often said to display, some form of `awareness´ and/or `self-awareness´. Rather than giving a specific definition of these terms, in this paper we propose instead a tripartite analytic framework to characterise and categorise forms of awareness and self-awareness in autonomic systems research. The three aspects are the level of `awareness´ being addressed, the field of computer science in which the system has been developed, and the research themes being addressed. By applying the analytic framework to the articles in the online Awareness Magazine, and the collected opinions from the Awareness Research Agenda, we aim to promote knowledge transfer and scientific dialogue across research communities and disciplines, and promote a common agenda for awareness research.
Keywords
fault tolerant computing; Awareness Magazine; autonomic system research; functional requirement; interconnected computational element; knowledge transfer; performance metrics; scientific dialogue; self-* property; self-awareness; tripartite analytic framework; autonomic systems; awareness; self-awareness;
fLanguage
English
Publisher
ieee
Conference_Titel
Self-Adaptive and Self-Organizing Systems Workshops (SASOW), 2012 IEEE Sixth International Conference on
Conference_Location
Lyon
Print_ISBN
978-1-4673-5153-9
Type
conf
DOI
10.1109/SASOW.2012.35
Filename
6498396
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