Abstract
There is increasing demand for the self-diagnosis and self-healing of problems or errors arising in systems operating in the ubiquitous computing environment. In this paper, we propose a self-healing system that monitors, diagnoses and heals its own problems. The proposed system consists of multi agents that analyze the log context in order to perform self-diagnosis and self-healing. To minimize the resources used by the Adapters in an existing system, we place a single process in memory. By this, we mean that a single Monitoring Agent monitors the context of the logs that are generated by the different components of the system. For rapid and efficient self-healing, we use a 6-step process. The effectiveness of the proposed system is confirmed through experiments conducted with a prototype system.
Keywords
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
This work was supported by the Ubiquitous Autonomic Computing and Network Project, 21st Century Frontier R&D Program in Korea and the Brain Korea 21 Project in 2004. Dr. E. Lee is the corresponding author
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
References
IBM: Autonomic Computing: IBM’s Perspective on the State of Information Technology, http://www-1.ibm.com/industries/government/doc/content/resource/thought/278606109.html
Kephart, J.O., Chess, D.M.: The Vision of Autonomic Computing, January 2003. IEEE Computer Society, Los Alamitos (2003)
Oreizy, P., Gorlick, M.M., Taylor, R.N., Heimbigner, D., Hohnson, G., Medvidovic, N., Quilici, A., Rosenblum, D.S., Wolf, A.L.: An Architecture-Based Approach to Self- Adaptive Software. IEEE Intelligent Systems 14(3), 54–62 (1999)
Garlan, D., Schmerl, B.: Model-based Adaptation for Self-Healing Systems. In: Proceedings of the First ACM SIGSOFT Workshop on Self-Healing Systems (WOSS), South Carolina, November 2002, pp. 27–32 (2002)
Abowd, G.D., Allen, R., Garlan, D.: Formalizing style to understand descriptions of software architecture. ACM Transactions on Software Engineering and Methodology 4(4), 319–364 (1995)
Batory, D., O’Malley, S.: The Design and Implementation of Hierarchical Software Systems with Reusable Components. ACM Transactions on Software Engineering and Methodology 1(4), 355–398 (1992)
Bernardo, M., Ciancarni, P., Donatiello, L.: On the formalization of architectural types with process algebras. In: Proceedings of the 8th International Symposium on Foundations of Software Engineering, November 2000, pp. 140–148 (2000)
Topol, B., Ogle, D., Pierson, D., Thoensen, J., Sweitzer, J., Chow, M., Hoffmann, M.A., Durham, P., Telford, R., Sheth, S., Studwell, T.: Automating problem determination: A first step toward self-healing computing system. IBM white paper (October 2003)
Baekelmans, J., Brittenham, P., Deckers, T., DeLaet, C., Merenda, E., Miller, B., Ogle, D., Rajaraman, B., Sinclair, K., Sweitzer, J.: Adaptive Services Framework CISCO white paper (October 2003)
Hillman, J., Warren, I.: Meta-adaptation in Autonomic systems. In: Proceedings of the 10th International Workshop on Future Trends in Distributed Computer Systems (FTDCS), Sozhou, China, May 26-28 (2004)
Garlan, D., Cheng, S., Schmerl, B.: Increasing System Dependability through Architec- ture-based Self-repair. In: de Lemos, Gacek, Romanovsky (eds.) Appears in Architecting Dependable Systems. ©Springer, Heidelberg (2003)
Bellifemine, F., Caire, G., Trucco, T. (TILAB, formerly CSELT) Giovanni Rimassa (University of Parma): JADE PROGRAMMER’S GUIDE
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2005 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Park, J., Youn, H., Lee, E. (2005). A Multi-agent Based Context Aware Self-healing System. In: Gallagher, M., Hogan, J.P., Maire, F. (eds) Intelligent Data Engineering and Automated Learning - IDEAL 2005. IDEAL 2005. Lecture Notes in Computer Science, vol 3578. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11508069_67
Download citation
DOI: https://doi.org/10.1007/11508069_67
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-26972-4
Online ISBN: 978-3-540-31693-0
eBook Packages: Computer ScienceComputer Science (R0)