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Software Health Management with Bayesian NetworksMost modern aircraft as well as other complex machinery is equipped with diagnostics systems for its major subsystems. During operation, sensors provide important information about the subsystem (e.g., the engine) and that information is used to detect and diagnose faults. Most of these systems focus on the monitoring of a mechanical, hydraulic, or electromechanical subsystem of the vehicle or machinery. Only recently, health management systems that monitor software have been developed. In this paper, we will discuss our approach of using Bayesian networks for Software Health Management (SWHM). We will discuss SWHM requirements, which make advanced reasoning capabilities for the detection and diagnosis important. Then we will present our approach to using Bayesian networks for the construction of health models that dynamically monitor a software system and is capable of detecting and diagnosing faults.
Document ID
20110015016
Acquisition Source
Ames Research Center
Document Type
Conference Paper
Authors
Mengshoel, Ole
(Carnegie-Mellon Univ. Moffett Field, CA, United States)
Schumann, JOhann
(SGT, Inc. Moffett Field, CA, United States)
Date Acquired
August 25, 2013
Publication Date
August 2, 2011
Subject Category
Computer Programming And Software
Report/Patent Number
ARC-E-DAA-TN3714
Meeting Information
Meeting: 4th International Conference on Space Mission Challenges for Information Technology (SMC-IT 2011)
Location: Palo Alto, CA
Country: United States
Start Date: August 2, 2011
Sponsors: Vanderbilt Univ.
Funding Number(s)
CONTRACT_GRANT: NNX08AY50A
CONTRACT_GRANT: NNA08CG83C
Distribution Limits
Public
Copyright
Public Use Permitted.
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