Machine Learning Approach for Smart Self-diagnosing Autonomic Computing Systems

Titre	Machine Learning Approach for Smart Self-diagnosing Autonomic Computing Systems
Publication Type	Journal Article
Year of Publication	2020
Authors	Kamri, H, Bounabat, B
Journal	Advances in Intelligent Systems and Computing
Volume	1105 AISC
Pagination	298-307
Mots-clés	Autonomic Computing, Autonomic computing system, Diagnosing system, Intelligent systems, Learning systems, Machine learning, Machine learning approaches, Machine learning techniques, planning, Research initiatives, Self management, Self-diagnosing, Sustainable development, wireless networks
Abstract	While modern systems and networks are continuously growing in size, complexity and diversity, the monitoring and diagnosing of such systems is becoming a real challenge. Technically and economically, more automation of the classical diagnosing tasks is needed. This has triggered a considerable research initiative, grouped under the terms self-management and Autonomic Computing. In this paper we propose a new model for smart self-diagnosing systems based on Autonomic Computing principles and Machine Learning techniques. © 2020, Springer Nature Switzerland AG.
URL	https://www.scopus.com/inward/record.uri?eid=2-s2.0-85080896883&doi=10.1007%2f978-3-030-36674-2_31&partnerID=40&md5=3dce8bc657338047166fb3ded16c10c8
DOI	10.1007/978-3-030-36674-2_31