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A Knowledge Network Toolkit for Autonomic Componentware

Biomedical Sciences Research Institute Computer Science Research Institute Environmental Sciences Research Institute Nanotechnology & Advanced Materials Research Institute

Baumgarten, Matthias, Bicocchi, Nicola, Curran, K, Greer, KRC, Kusber, Rico, Mamei, Marco, Mulvenna, Maurice, Nugent, CD and Zambonelli, Franco (2008) A Knowledge Network Toolkit for Autonomic Componentware. In: First Tutorial and Workshop on Autonomic Communications and Component-ware (TACC 2008), Budapest, Hungary. Scientific Association for Info-communications. 6 pp. [Conference contribution]

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Abstract

With the dawn of smart world infrastructures on a global scale, the need for fully autonomous operating systems and services has never been more urgent. A key aspect for such systems is the availability of relevant contextual information so that they can autonomously configure, adapt and optimize their behavior towards changing conditions. This is known as context or situation awareness, which is of fundamental importance for successful autonomic computing and services. However, acquiring relevant information from the real, virtual or operational environment is only the first step to facilitate such contextual awareness. Additional processing is required to pre-organize, correlate or simply reformat such data so that they are readily accessible as well as usable by a multitude of services. Within a distributed environment, this translates directly into a diverse network of knowledge, where individual views correspond to specific contexts and situations that are ultimately understandable yet manageable in real time. This paper, discusses a Knowledge Network (KN) approach that has been developed as part of an Autonomous Componentware toolkit, called ACE-Toolkit (Autonomic Communication Elements). The reference based KN framework provides the means for the ACE-Toolkit and its components to acquire a higher degree of contextual awareness where knowledge from various sources can be utilized efficiently at various levels of granularity. On the other hand the KN components themselves are realized as ACE’s thus taking full advantage of the autonomic features offered by the toolkit.

Item Type:Conference contribution (Paper)
Faculties and Schools:Faculty of Computing & Engineering
Faculty of Computing & Engineering > School of Computing and Intelligent Systems
Faculty of Computing & Engineering > School of Computing and Mathematics
Research Institutes and Groups:Computer Science Research Institute
Computer Science Research Institute > Intelligent Systems Research Centre
Computer Science Research Institute > Smart Environments
ID Code:16513
Deposited By:Professor Maurice Mulvenna
Deposited On:26 Nov 2010 09:46
Last Modified:26 Nov 2010 09:46

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