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A proposal to apply inductive logic programming to self‐healing problem in grid computing: How will it work?
Author(s) -
Ferro Mariza,
Mury Antonio Roberto,
Schulze Bruno
Publication year - 2011
Publication title -
concurrency and computation: practice and experience
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.309
H-Index - 67
eISSN - 1532-0634
pISSN - 1532-0626
DOI - 10.1002/cpe.1714
Subject(s) - computer science , casual , autonomic computing , inductive logic programming , component (thermodynamics) , grid , distributed computing , artificial intelligence , root (linguistics) , computation , software engineering , complex system , control (management) , grid computing , cloud computing , programming language , linguistics , philosophy , materials science , physics , geometry , mathematics , composite material , thermodynamics , operating system
SUMMARY As computation systems get extremely large and complex, failure diagnosis becomes even more complex. To cope with this ever increasing complexity of managing heterogeneous systems—such as grids and nowadays clouds—systems should manage their own behavior themselves. This vision of self‐managing systems also referred to as autonomic computing (AC) aims to allow systems to recover themselves from various failures or malfunctions. This is known as self‐healing (SH) and is one of the requirements of AC. However, dealing with these complex failure scenarios is always an open challenge. Dealing with this challenge requires prediction and control through a number of automated learning and proactive actions. In this work, we present the usage of a relational learning method known as inductive logic programming, for prediction and root casual analysis, and the development of an SH component. Copyright © 2011 John Wiley & Sons, Ltd.