Model-based adaptation for self-healing systems
WOSS '02 Proceedings of the first workshop on Self-healing systems
Architectural style requirements for self-healing systems
WOSS '02 Proceedings of the first workshop on Self-healing systems
An instrumentation and control-based approach for distributed application management and adaptation
WOSS '02 Proceedings of the first workshop on Self-healing systems
An Architecture-Based Approach to Self-Adaptive Software
IEEE Intelligent Systems
From Component-Based to Service-Based Distributed Applications Assembly and Management
EUROMICRO '03 Proceedings of the 29th Conference on EUROMICRO
Computing System Failure Frequencies and Reliability Importance Measures Using OBDD
IEEE Transactions on Computers
Fault Monitoring and Detection of Distributed Services over Local and Wide Area Networks
ICPADS '06 Proceedings of the 12th International Conference on Parallel and Distributed Systems - Volume 2
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Distributed applications, based on internet worked services, provide users with more flexible and varied services and developers with the ability to incorporate a vast array of services into their applications. Such applications are difficult to develop and manage due to their inherent dynamics and heterogeneity. One desirable characteristic of distributed applications is self-healing, or the ability to reconfigure themselves "on the fly" to circumvent failure. In this paper, we discuss our middleware for developing self-healing distributed applications. We present the model we adopted for self-healing behaviour and show as case study the reconfiguration of an application that uses networked sorting services and an application for networked home appliances. We discuss the performance benefits of self-healing property by analysing the elapsed time for automatic reconfiguration without user intervention. Our results show that a distributed application developed with our self-healing middleware will be able to perform smoothly by quickly reconfiguring its services upon detection of failure. We also consider the performance impact of a number of fault-detection mechanisms, including pre-emptive detection and on-use detection.