Fault Management Framework and Multi-layer Recovery Methodology for Resilient System

• Fault management is a key function to guarantee the quality of the service. Research has done a lot to improve fault supervision, and investigation is ongoing in fault prediction, thanks to the potentials of artificial intelligence and machine learning. In this study, we propose a fault management framework that puts an emphasis on fault recovery: a framework developed on multi-layer function and a fault recovery methodology distributed over several technological layers. The basic principle of our proposal is that the system's complexity exposes it to a higher probability of temporary error. Newfound attention to the fault recovery phase is the key to keeping the service's quality high and saving maintenance costs by decreasing the return rate. 

Ämnesord

NATURVETENSKAP  -- Data- och informationsvetenskap -- Datavetenskap (hsv//swe)

NATURAL SCIENCES  -- Computer and Information Sciences -- Computer Sciences (hsv//eng)

Nyckelord

Fault Management

Recovery methodology

Resilient system

Artificial intelligence

Artificial intelligence learning

Fault prediction

Fault recovery

Machine-learning

Management frameworks

Management IS

Multi-layers

Resilient systems

Failure analysis

Publikations- och innehållstyp

ref (ämneskategori)

kon (ämneskategori)