QoS Adaptive ISHM Systems

  • Authors:
  • Yansheng Zhang;Jicheng Fu;I-Ling Yen;Farokh Bastani;Ann T. Tai;Savio Chau;Farrokh Vatan;Amir Fijany

  • Affiliations:
  • University of Texas at Dallas, USA;University of Texas at Dallas, USA;University of Texas at Dallas, USA;University of Texas at Dallas, USA;IA Tech., Inc.;Jet Propulsion Laboratory, USA;Jet Propulsion Laboratory, USA;Jet Propulsion Laboratory, USA

  • Venue:
  • ICTAI '06 Proceedings of the 18th IEEE International Conference on Tools with Artificial Intelligence
  • Year:
  • 2006

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Abstract

Embedded systems are becoming highly complex and increasingly being used in critical applications. Integrated system health management (ISHM) techniques have therefore been developed to ensure the proper operation of these systems. However, some ISHM systems are relatively complex and may consume a significant amount of resources. In some situations, activating the full ISHM system may cause resource contention and prevents the target system from timely completing critical tasks. Thus, it is imperative to introduce the notion of adaptivity into ISHM systems. This paper systematically discusses the issues that need to be addressed in an adaptive ISHM system with a focus on adaptation in terms of QoS aspects. A novel model, Adaptive Diagnosis Quality-Oriented System Model (ADQSM), is proposed to model the QoS specification and fault diagnosis quality measurement issues as well as the abstraction of the adaptation problem. We then present the method to evaluate various diagnosability attributes based on a modified fault signature matrix. We further map the ADQSM model to the Particle Swarm Optimization (PSO) problem model and use PSO for rapid configuration decision making.