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Istituto di Scienza e Tecnologie dell'Informazione     
Dazzi P., Nidito F., Pasquali M. New perspectives in autonomic design patterns for stream-classification-systems. In: Workshop on Automating service quality. Held at the International Conference on Automated Software Engineering, ASE (Atlanta Georgia, Novembre 2007). Proceedings, pp. 34 - 37. ACM, 2007.
 
 
Abstract
(English)
Nowadays, systems are growing in size and are becoming more ad more complex. Such a complexity outline a new need for mechanisms enabling the system self-management, freeing administrators of low-level task management whilst delivering an optimized system. The autonomic systems sense their operating environment and automatically take action to change the environment or their own behavior. They are able to achieve it with a minimum human effort. They have the following properties: self-configuring, self- healing, self-optimizing and self-protecting. Current auto- nomic systems are ad hoc solutions: each system is designed and implemented from scratch i.e. there are not standard (or well-established) methodologies that autonomic system de- signers and/or programmers can exploit to drive their work. In this paper, we propose a design pattern that can be eas- ily exploited by the stream-classification-systems designer to achieve autonomicity with a minimal effort. The pattern is described using a java-like notation for the classes and interfaces. A simple UML class diagram is depicted.
URL: http://portal.acm.org/citation.cfm?id=1314483.1314490&coll=GUIDE&dl=GUIDE
Subject Autonomic
Pattern
F.1.1 Models of Computation
D.2.11 Software Architectures


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