Bennaceur, Amel; Issarny, Valérie; Sykes, Daniel; Howar, Falk; Isberner, Malte; Steffen, Bernhard; Johansson, Richard and Moschitti, Alessandro
(2013).
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| DOI (Digital Object Identifier) Link: | https://doi.org/10.1007/978-3-642-45260-4_2 |
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| Google Scholar: | Look up in Google Scholar |
Abstract
Highly dynamic and heterogeneous distributed systems are challenging today's middleware technologies. Existing middleware paradigms are unable to deliver on their most central promise, which is offering interoperability. In this paper, we argue for the need to dynamically synthesise distributed system infrastructures according to the current operating environment, thereby generating "Emergent Middleware'' to mediate interactions among heterogeneous networked systems that interact in an ad hoc way. The paper outlines the overall architecture of Enablers underlying Emergent Middleware, and in particular focuses on the key role of learning in supporting such a process, spanning statistical learning to infer the semantics of networked system functions and automata learning to extract the related behaviours of networked systems.
| Item Type: | Conference or Workshop Item | ||||||
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| Copyright Holders: | 2012 Springer | ||||||
| ISBN: | 3-642-45260-4, 978-3-642-45260-4 | ||||||
| ISSN: | 1865-0929 | ||||||
| Project Funding Details: |
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| Extra Information: | Communications in Computer and Information Science
Volume 379, 2013 |
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| Keywords: | machine learning; natural language processing; automata learning; interoperability; automated mediation | ||||||
| Academic Unit/School: | Faculty of Science, Technology, Engineering and Mathematics (STEM) > Computing and Communications Faculty of Science, Technology, Engineering and Mathematics (STEM) |
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| Item ID: | 39468 | ||||||
| Depositing User: | Amel Bennaceur | ||||||
| Date Deposited: | 10 Feb 2014 09:54 | ||||||
| Last Modified: | 07 Dec 2018 23:02 | ||||||
| URI: | http://oro.open.ac.uk/id/eprint/39468 | ||||||
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