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Emergence: a paradigm for robust and scalable distributed applications

Emergence: a paradigm for robust and scalable distributed applications

Anthony, Richard (2004) Emergence: a paradigm for robust and scalable distributed applications. In: Proceedings. International Conference on Autonomic Computing. IEEE Computer Society, Los Alamitos, California, USA, pp. 132-139. ISBN 0769521142 (doi:10.1109/ICAC.2004.1301356)

Full text not available from this repository.

Abstract

Natural distributed systems are adaptive, scalable and fault-tolerant. Emergence science describes how higher-level self-regulatory behaviour arises in natural systems from many participants following simple rulesets. Emergence advocates simple communication models, autonomy and independence, enhancing robustness and self-stabilization.

High-quality distributed applications such as autonomic systems must satisfy the appropriate nonfunctional requirements which include scalability, efficiency, robustness, low-latency and stability. However the traditional design of distributed applications, especially in terms of the communication strategies employed, can introduce compromises between these characteristics.

This paper discusses ways in which emergence science can be applied to distributed computing, avoiding some of the compromises associated with traditionally-designed applications.

To demonstrate the effectiveness of this paradigm, an emergent election algorithm is described and its performance evaluated. The design incorporates nondeterministic behaviour. The resulting algorithm has very low communication complexity, and is simultaneously very stable, scalable and robust.

Item Type: Conference Proceedings
Title of Proceedings: Proceedings. International Conference on Autonomic Computing
Additional Information: [1] This paper was first presented at the [1st] International Conference on Autonomic Computing 2004 (ICAC 2004) held from 17-18 May 2004 in New York, USA.
Uncontrolled Keywords: emergence, distributed systems, fault tolerance, scalability, self-stabilisation, election algorithm
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Pre-2014 Departments: School of Computing & Mathematical Sciences
School of Computing & Mathematical Sciences > Computer & Computational Science Research Group
School of Computing & Mathematical Sciences > Department of Computer Systems Technology
Related URLs:
Last Modified: 14 Oct 2016 09:01
Selected for GREAT 2016: None
Selected for GREAT 2017: None
Selected for GREAT 2018: None
URI: http://gala.gre.ac.uk/id/eprint/712

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