Service-context knowledge-based solution for autonomic adaptation

Authors:
Marcel Cremene;Michel Riveill
Affiliations:
Technical University of Cluj-Napoca, Cluj-Napoca, Romania;University of Nice, Sophia-Antipolis, France
Venue:
ATC'07 Proceedings of the 4th international conference on Autonomic and Trusted Computing
Year:
2007

Citing 6
Cited 0

An architectural support for self-adaptive software for treating faults

WOSS '02 Proceedings of the first workshop on Self-healing systems
Understanding and Using Context

Personal and Ubiquitous Computing
Ontology Based Context Modeling and Reasoning using OWL

PERCOMW '04 Proceedings of the Second IEEE Annual Conference on Pervasive Computing and Communications Workshops
Rainbow: Architecture-Based Self-Adaptation with Reusable Infrastructure

Computer
Research challenges of autonomic computing

Proceedings of the 27th international conference on Software engineering
Using Architecture Models for Runtime Adaptability

IEEE Software

Quantified Score

Hi-index	0.00

Visualization

Abstract

In most adaptive systems, the adaptation control is based on developer-made rules and strategies that are specific for each service and context. Our proposal for autonomic computing is to replace this mechanism with a machine-based reasoning. The key element in making this possible is a service-context model that offers a knowledge support for the adaptive platform, which can diagnose the service adequacy to the context and search for solutions. We have tested our model using a prototype that adapts a service by inserting the 'right' component at the 'right' place into the service architecture.