A state machine-based approach for reliable adaptive distributed systems.

Mostarda, Leonardo and Sykes, Daniel and Dulay, Naranker (2010) A state machine-based approach for reliable adaptive distributed systems. In: Engineering of Autonomic and Autonomous Systems (EASe), 2010. Sterritt, Roy and McCann, Julie, eds. IEEE International Conference and Workshops (7). IEEE, pp. 91-100. ISBN 9781424465354

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Abstract

Adaptive systems are often composed of distributed components that co-operate in order to achieve a global behaviour, and yet many approaches for adaptive systems are centralised or make strong assumptions about the distributed aspects of the problem. However, if insufficient attention is paid to the problem of decentralisation, especially in the difficult and unpredictable environments in which adaptive systems are commonly deployed, it can introduce inefficiencies, and even cause catastrophic failure. An adaptive system is either required to implement subtle synchronisation and consensus protocols or accept certain types of failure from which the system cannot recover. A major goal of our research is to facilitate the development of adaptive, reliable and distributed applications. We provide a framework in which a state machine language is used to define logically centralised behaviour. This is automatically translated into a reliable and efficient distributed implementation that enforces the correct co-ordination in the presence of unpredictable failures.

Item Type:Book Section
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Conference details: International Conference and Workshop on Engineering of Autonomic and Autonomous Systems (EASe), 2010 Held 22-26 March 2010 • Oxford, England.

Research Areas:Middlesex University Schools and Centres > School of Science and Technology > Computer and Communications Engineering
Middlesex University Schools and Centres > School of Science and Technology > Computer Science > SensoLab group
Middlesex University Schools and Centres > School of Science and Technology > Computer Science > Intelligent Environments group
ID Code:7380
Deposited On:04 Apr 2011 12:12
Last Modified:06 Nov 2014 13:02

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