Files in this item
A survey of self-healing systems frameworks
Item metadata
dc.contributor.author | Schneider, Christopher | |
dc.contributor.author | Barker, Adam David | |
dc.contributor.author | Dobson, Simon Andrew | |
dc.date.accessioned | 2015-01-20T00:01:26Z | |
dc.date.available | 2015-01-20T00:01:26Z | |
dc.date.issued | 2015-10 | |
dc.identifier | 93684879 | |
dc.identifier | 2129008f-a60f-482a-b588-3a06c2b532a8 | |
dc.identifier | 84941168239 | |
dc.identifier | 000360814800004 | |
dc.identifier.citation | Schneider , C , Barker , A D & Dobson , S A 2015 , ' A survey of self-healing systems frameworks ' , Software: Practice and Experience , vol. 45 , no. 10 , pp. 1375-1398 . https://doi.org/10.1002/spe.2250 | en |
dc.identifier.issn | 0038-0644 | |
dc.identifier.other | ORCID: /0000-0001-9633-2103/work/70234166 | |
dc.identifier.uri | https://hdl.handle.net/10023/6026 | |
dc.description.abstract | Rising complexity within multi-tier computing architectures remains an open problem. As complexity increases, so do the costs associated with operating and maintaining systems within these environments. One approach for addressing these problems is to build self-healing systems (i.e. frameworks) that can autonomously detect and recover from faulty states. Self-healing systems often combine machine learning techniques with closed control loops to reduce the number of situations requiring human intervention. This is particularly useful in situations where human involvement is both costly to develop, and a source of potential faults. Therefore, a survey of self-healing frameworks and methodologies in multi-tier architectures is provided to the reader. Uniquely, this study combines an overview of the state of the art with a comparative analysis of the computing environment, degree of behavioural autonomy, and organisational requirements of these approaches. Highlighting these aspects provides for an understanding of the different situational benefits of these self-healing systems. We conclude with a discussion of potential and current research directions within this field. | |
dc.format.extent | 236656 | |
dc.language.iso | eng | |
dc.relation.ispartof | Software: Practice and Experience | en |
dc.subject | Autonomic computing | en |
dc.subject | Self-healing systems | en |
dc.subject | Survey | en |
dc.subject | Artificial intelligence | en |
dc.subject | Machine learning | en |
dc.subject | Evolutionary programming | en |
dc.subject | QA75 Electronic computers. Computer science | en |
dc.subject | T-NDAS | en |
dc.subject.lcc | QA75 | en |
dc.title | A survey of self-healing systems frameworks | en |
dc.type | Journal article | en |
dc.contributor.institution | University of St Andrews. School of Computer Science | en |
dc.identifier.doi | https://doi.org/10.1002/spe.2250 | |
dc.description.status | Peer reviewed | en |
dc.date.embargoedUntil | 2015-01-20 |
This item appears in the following Collection(s)
Items in the St Andrews Research Repository are protected by copyright, with all rights reserved, unless otherwise indicated.