Conference proceeding
Combining Self-Organisation and Autonomic Computing in CASs with Aggregate-MAPE
2016 IEEE 1st International Workshops on Foundations and Applications of Self Systems (FASW), pp.186-191
09/2016
DOI: 10.1109/FAS-W.2016.49
Abstract
Aggregate computing is a recently proposed framework to build CASs (collective adaptive systems) by focussing on direct programming of ensembles so as to abstract away from individual devices and their single interaction acts: this approach is shown to streamline the identification of highly reusable block components, and support reasoning about their resiliency properties. Following this paradigm, in this paper we present a framework for bridging the gap between the MAPE (Monitor-Analyse-Plan-Execute) loop of autonomic computing managers, and fully-distributed self-organising CASs. This is achieved by seeing the collection of M components of each agent as an aggregate, amenable to a direct specification as overall CAS Monitoring behaviour, and similarly for A, P and E. As a result, a self-organising CAS can be programmed by clearly separating the M, A, P, and E parts of it, though each is expressed in terms of a collective behaviour. The proposed approach is exemplified with an application scenario of crowd dispersal in a large-scale smart-mobility application.
Details
- Title: Subtitle
- Combining Self-Organisation and Autonomic Computing in CASs with Aggregate-MAPE
- Creators
- Mirko Viroli - University of BolognaAntonio Bucchiarone - Fondazione Bruno KesslerDanilo Pianini - University of BolognaJacob Beal - RTX
- Resource Type
- Conference proceeding
- Publication Details
- 2016 IEEE 1st International Workshops on Foundations and Applications of Self Systems (FASW), pp.186-191
- Publisher
- IEEE
- DOI
- 10.1109/FAS-W.2016.49
- Language
- English
- Date published
- 09/2016
- Academic Unit
- Electrical and Computer Engineering
- Record Identifier
- 9984627301402771
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