Applying case-based reasoning: techniques for enterprise systems
Applying case-based reasoning: techniques for enterprise systems
Conversational Case-Based Reasoning
Applied Intelligence
Interactive Case-Based Reasoning in Sequential Diagnosis
Applied Intelligence
Research challenges of autonomic computing
Proceedings of the 27th international conference on Software engineering
Standard Exemplars for Autonomic Computing Concepts
EASE '06 Proceedings of the Third IEEE International Workshop on Engineering of Autonomic & Autonomous Systems
Advances in conversational case-based reasoning
The Knowledge Engineering Review
Retrieval, reuse, revision and retention in case-based reasoning
The Knowledge Engineering Review
Integrations with case-based reasoning
The Knowledge Engineering Review
Achieving Self-Healing in Autonomic Software Systems: a Case-Based Reasoning Approach
Proceedings of the 2005 conference on Self-Organization and Autonomic Informatics (I)
Case-based reasoning for autonomous service failure diagnosis and remediation in software systems
ECCBR'06 Proceedings of the 8th European conference on Advances in Case-Based Reasoning
Conversational Case-Based Reasoning in Self-healing and Recovery
ECCBR '08 Proceedings of the 9th European conference on Advances in Case-Based Reasoning
Using a teleo-reactive approach in building self-managing systems
International Journal of Autonomous and Adaptive Communications Systems
| Hi-index | 0.00 |
An important goal of autonomic computing is the development of computing systems that are capable of self healing with a minimum of human intervention. Typically, recovery from even a simple fault will require knowledge of the environment in which a computing system operates. To meet this need, we present an approach to self healing and recovery informed by environment knowledge that combines case based reasoning (CBR) and rule based reasoning. Specifically, CBR is used for fault diagnosis and rule based reasoning for fault remediation, recovery, and referral. We also show how automated information gathering from available sources in a computing system's environment can increase problem solving efficiency and help to reduce the occurrence of service failures. Finally, we demonstrate the approach in an intelligent system for fault management in a local printer network.