AN INTELLIGENT MAINTENANCE BASED ON MACHINE LEARNING APPROACH FOR WIRELESS AND MOBILE SYSTEMS

Amine Chohra, Felicita Di Giandomenico, Stefano Porcarelli, Andrea Bondavalli

Abstract

To enhance wireless and mobile system dependability, audit operations are necessary, to periodically check the database consistency and recover in case of data corruption. Consequently, how to tune the database audit parameters and which operation order and frequency to apply becomes important aspects, to optimize performance and satisfy a certain degree of Quality of Service, over system life-cycle. The aim of this work is then to suggest an intelligent maintenance system based on reinforcement Q-Learning approach, built of a given audit operation set and an audit manager, in order to maximize the performance (performability and unreliability). For this purpose, a methodology, based on deterministic and stochastic Petri nets, to model and analyze the dependability attributes of different scheduled audit strategies is first developed. Afterwards, an intelligent (reinforcement Q-Learning) software agent approach is developed for planning and learning to derive optimal maintenance policies adaptively dealing with the highly dynamic evolution of the environmental conditions. This intelligent approach, is then implemented with feedforward artificial neural networks under the supervised gradient back-propagation learning to guarantee the success even with large state spaces, exploits intelligent behaviors traits (learning, adaptation, generalization, and robustness) to derive optimal actions in different system states in order to achieve an intelligent maintenance system.

References

  1. Adgar, A., Addison, J. F. D., and Yau, C.-Y., 2007. Applications of RFID technology in maintenance systems. 2nd World Congress on Engineering Asset Management, Harrogate, UK.
  2. Bagchi, S., Liu, Y., Whisnant, K., Kalbarczyk, Z., Iyer, R., Levendel, Y., and Votta, L., 2001. A framework for database audit and control flow checking for a wireless telephone network controller. Int. Conf. on Dependable Systems and Networks, pp. 225-234, Göteborg, Sweden.
  3. Chohra, A., 2001. Embodied cognitive science, intelligent behavior control, machine learning, soft computing, and FPGA integration: Towards fast, cooperative and adversarial robot team (RoboCup), Technical GMD (currently Fraunhofer) Report, No. 136, pp. 01-59, Sankt Augustin, Germany.
  4. Costa, D., Rilho, T., and Madeira, H., 2000. Joint evaluation of performance and robustness of a COTS DBMS through fault-injection. Int. IEEE Conf. on Dependable Systems and Networks, pp. 251-260, New York, USA.
  5. Haugk, G., Lax, F. M., Royer, R. D., Williams, J. R., 1985. The 5ESS switching system, maintenance capabilities. AT&T Technical Journal, Vol. 64, No. 6, pp. 1385-1416.
  6. Irigaray, A. A., Gilabert, E., Jantunen, E., Adgar, A., 2009. Ubiquitous computing for dynamic conditionbased maintenance. Journal of Quality in Maintenance Engineering, Vol. 15 Iss: 2, pp.151 - 166.
  7. Pfeifer, R., and Scheier, C., 1999. Understanding intelligence, MIT press.
Download


Paper Citation


in Harvard Style

Chohra A., Di Giandomenico F., Porcarelli S. and Bondavalli A. (2011). AN INTELLIGENT MAINTENANCE BASED ON MACHINE LEARNING APPROACH FOR WIRELESS AND MOBILE SYSTEMS . In Proceedings of the International Conference on Wireless Information Networks and Systems - Volume 1: WINSYS, (ICETE 2011) ISBN 978-989-8425-73-7, pages 115-118. DOI: 10.5220/0003611001150118


in Bibtex Style

@conference{winsys11,
author={Amine Chohra and Felicita Di Giandomenico and Stefano Porcarelli and Andrea Bondavalli},
title={AN INTELLIGENT MAINTENANCE BASED ON MACHINE LEARNING APPROACH FOR WIRELESS AND MOBILE SYSTEMS},
booktitle={Proceedings of the International Conference on Wireless Information Networks and Systems - Volume 1: WINSYS, (ICETE 2011)},
year={2011},
pages={115-118},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003611001150118},
isbn={978-989-8425-73-7},
}


in EndNote Style

TY - CONF
JO - Proceedings of the International Conference on Wireless Information Networks and Systems - Volume 1: WINSYS, (ICETE 2011)
TI - AN INTELLIGENT MAINTENANCE BASED ON MACHINE LEARNING APPROACH FOR WIRELESS AND MOBILE SYSTEMS
SN - 978-989-8425-73-7
AU - Chohra A.
AU - Di Giandomenico F.
AU - Porcarelli S.
AU - Bondavalli A.
PY - 2011
SP - 115
EP - 118
DO - 10.5220/0003611001150118