The Vision of Autonomic Computing
Computer
Model-Based Diagnosis or Reasoning from First Principles
IEEE Intelligent Systems
Knowledge Representation and Reasoning
Knowledge Representation and Reasoning
Advanced fault analysis in web service composition
WWW '05 Special interest tracks and posters of the 14th international conference on World Wide Web
Introduction to Probability Models, Ninth Edition
Introduction to Probability Models, Ninth Edition
QoS management in service-oriented architectures
Performance Evaluation
A Survey of Autonomic Computing Systems
ICAS '07 Proceedings of the Third International Conference on Autonomic and Autonomous Systems
Soa: principles of service design
Soa: principles of service design
Static and dynamic adaptations for service-based systems
Information and Software Technology
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Service-Oriented Computing reveals features which are not commonly found in conventional computing paradigms; loose coupling, dynamism, black box, evolvability, and heterogeneity. These features make diagnosing and healing faults found in deployed services and service-related elements more challenging than managing conventional systems. Hence, service-oriented systems management often results in problems of increased cost/effort, decreased effectiveness, and irresolvable service faults. Applying key disciplines of autonomic computing to services management would effectively resolve these problems and automate the task. This paper presents a comprehensive framework, for managing service faults in autonomous manner, called Symptom-Cause-Actuator Framework (SCAF). We first present a 5-phase process for autonomic service management. Then, we define functionality of SCAF and present the system architecture of the framework. Then, we propose formal reasoning system to diagnose services faults and actuate causes for the framework. The framework is not limited to providing a theoretical basis for service management, but it can be practically applied with current service-oriented architecture standards.