The Vision of Autonomic Computing
Computer
Using components for architecture-based management: the self-repair case
Proceedings of the 30th international conference on Software engineering
A framework for adaptive real-time applications: the declarative real-time OSGi component model
Proceedings of the 7th workshop on Reflective and adaptive middleware
Self-adaptive software: Landscape and research challenges
ACM Transactions on Autonomous and Adaptive Systems (TAAS)
An Architecture-Based Framework for Managing Adaptive Real-Time Applications
SEAA '09 Proceedings of the 2009 35th Euromicro Conference on Software Engineering and Advanced Applications
ACCADA: A Framework for Continuous Context-Aware Deployment and Adaptation
SSS '09 Proceedings of the 11th International Symposium on Stabilization, Safety, and Security of Distributed Systems
Challenges in building service-oriented applications for OSGi
IEEE Communications Magazine
Robust-and-evolvable resilient software systems: open problems and lessons learned
Proceedings of the 8th workshop on Assurances for self-adaptive systems
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Autonomous Robots normally perform tasks in unstructured environments, with little or no continuous human guidance. This calls for context-aware, self-adaptive software systems. This paper aims at providing a flexible adaptive middleware platform to seamlessly integrate multiple adaptation logics during the run-time. To support such an approach, a reconfigurable middleware system "ACCADA" was designed to provide compositional adaptation. During the run-time, context knowledge is used to select the most appropriate adaptation modules so as to compose an adaptive system best-matching the current exogenous and endogenous conditions. Together with a structure modeler, this allows robotic applications' structure to be autonomously (re)-constructed and (re)-configured. This paper applies this model on a Lego NXT robot system. A remote NXT model is designed to wrap and expose native NXT devices into service components that can be managed during the run-time. A dynamic UI is implemented which can be changed and customized according to system conditions. Results show that the framework changes robot adaptation behavior during the run-time.