Self-adapting Strategies guided by Diagnosis and Situation Assessment in Collaborative Communicating Systems

##plugins.themes.bootstrap3.article.main##

##plugins.themes.bootstrap3.article.sidebar##

A. Subias E. Exposito C. Chassot L. Travé-Massuyes K. Drira

Abstract

Coping with context changes in networked systems requires considering self-adaptive communication protocols in the design of the future generation of communication systems. The communication system configuration then dynamically changes according to the user’s requirements and to the load of the communication resources. Dealing with this problem requires the capacity of detecting the possible degradations of the Quality of Service (QoS) and of dynamically modifying the behavior of the communication protocols for each new context situation. This requires in turn both monitoring the QoS values, detecting the degradations, identifying their origins through appropriate diagnosis and executing reconfiguration actions. We propose to implement such functions by considering an event-based model-driven diagnosis approach leading the dynamic composition of communication protocols for the execution of the reconfiguration. We consider a chronicle-based diagnosis approach and we apply our ideas to the Transport layer of communication systems. In this position paper, we show the relevance of our ideas and present preliminary ideas towards an integrated automated approach.

How to Cite

Subias, A., Exposito, E., Chassot, C., Travé-Massuyes, L., & Drira, K. (2010). Self-adapting Strategies guided by Diagnosis and Situation Assessment in Collaborative Communicating Systems. Annual Conference of the PHM Society, 2(2). https://doi.org/10.36001/phmconf.2010.v2i1.1928
Abstract 10 | PDF Downloads 17

##plugins.themes.bootstrap3.article.details##

Keywords

Model-based diagnosis, communication protocols, self-adapting stategies, QoS, situation assessment, chronicle

References
( Allen, 1983 ) James F. Allen. Maintaining knowledge about temporal intervals. Communications of the ACM, 26(11):832 – 843, 1983.
(Allen, 1984 ) James F. Allen. Towards a general theory of action and time. Artificial Intelligence, 23(2):123–154, 1984.
(Bertrand et al., 2008 ) O. Bertrand, P. Carle, and C. Choppy. Towards a coloured petri nets semantics of a chronicle language for distributed simulation processing. In In CHINA 2008 Workshop (Concurrency metHods: Issues aNd Applications), pages 105–119, 2008.
(Carle et al., 1998 ) P. Carle, P. Benhamou, M. Ornato, and FX. Dolbeau. Building dynamic organizations using intentions recognition. Technical Report ONERA-TP - 99-136, Office national d’études et de recherches aérospatiales, Châtillon, France, 1998.
(Carrault et al., 1999 ) G. Carrault, M.-O. Cordier, R. Quiniou, M. Garreau, J.-J. Bellanger, and A. Bardou. A model-based approach for learning to identify cardiac arrhythmias. In G. Lindberg S. Andreassen W. Horn, Y. Shahar and J. Wyatt, editors, Proceedings of AIMDM-99 : Artificial Intelligence in Medicine and Medical Decision Making, 1999.
(Cordier and Dousson, 2000 ) MO Cordier and C Dousson. Alarm driven monitoring based on chronicles. In 4th Sumposium on Fault Detection Supervision and Safety for Technical Processes (SafeProcess), pages 286–291, Budapest, Hungary, june 2000.
(Cordier et al., 2007 ) M.-O. Cordier, X. Le Guillou, S. Robin, L. Rozé, and T. Vidal. Distributed chronicles for on-line diagnosis of web services. In
(G. Biswas, X. Koutsoukos, and S. Abdelwahed, editors, 18th International Workshop on Principles of Diagnosis, pages 37–44, May 2007.
(Dousson and Duong, 1999 ) C. Dousson and T. Vu Duong. Discovering chronicles with numerical time constraints from alarm logs for monitoring dynamic systems. In IJCAI 99: Proceedings of the Sixteenth International Joint Conference on Artificial Intelligence, pages 620–626, San Francisco, CA, USA, June 1999.
(Dousson et al., 1993 ) C. Dousson, P. Gaborit, and M. Ghallab. In IJCAI: International Joint Conference on Artificial Intelligence, pages 166–172, Chambéry, France, august 1993.
(Guerraz and Dousson, 2004 ) B. Guerraz and C. Dousson. Chronicles construction starting from the fault model of the system to diagnose. In International Workshop on Principles of Diagnosis (DX04), pages 51–56, Carcassonne, France, 2004.
(Kowalski and Sergot, 1986 ) Robert Kowalski and Marek Sergot. A logic-based calculus of events. New Generation Computing, 4(1):67–95, 1986.
(Laborie and Krivine, 1997 ) P. Laborie and J.-P. Krivine. Automatic generation of chronicles and its application to alarm processing in power distribution systems. In 8th international workshop of diagnosis (DX97), Mont Saint-Michel, France, 1997.
(Mayer, 1998 ) E. Mayer. Inductive learning of chronicles. In European Conference on Artificial Intelligence, pages 471–472, 1998.
(McCarthy and Hayes, 1969 ) J. McCarthy and P. J. Hayes. Some philosophical problems from the standpoint of artificial intelligence. Machine Intelligence, 4, 1969.
(Morin and Debar, 2003 ) Benjamin Morin and Hervé Debar. Correltaion on intrusion: an application od chronicles. In 6th International Conference on recent Advances in Intrusion Detection RAID, Pittsburgh, USA, september 2003.
(Pencolé and Subias, 2009 ) Y. Pencolé and A. Subias. A chronicle-based diagnosability approach for discrete timed-event systems: Application to webservices. Journal of Universal Computer Science, 15(17):3246–3272, 2009.
(Rota and Thonnat, 2000 ) N. Rota and M. Thonnat. Activity recognition from video sequences using declarative models. In 14th International Workshop on Principles of Diagnosis (DX00), Morelia, Michoacen, Mexico, June 2000.
(VanWambeke et al., 2007 ) N. VanWambeke, E. Exposito, and M. Diaz. Transport layer qos protocols: the micro-protocol approach. March 2007.
(VanWambeke et al., 2008 ) N. VanWambeke, F. Armando, C. Chassot C, and E. Exposito. A modelbased approach for self-adaptive transport protocols. Elsevier Computer Communications, Special issue on end-to-end support over heterogeneous wired and wireless network, 31(11):26992705, July 2008.
(Zimmermann, 1980 ) H. Zimmermann. Osi reference model: the iso model of architecture for open systems interconnection. IEEE transactions on communication, 28(4), 1980.
Section
Poster Presentations