Anthony, Richard John (2005) An autonomic election algorithm based on emergence in natural systems. Integrated Computer-Aided Engineering, 13 (1). pp. 3-22. ISSN 1069-2509 (Print), 1875-8835 (Online)

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Abstract

This paper examines some of the emergence behaviours of natural distributed systems, with respect to identifying ways in which the highly successful strategies and mechanisms found in these systems can be employed in autonomic distributed computer systems. Particular emphasis is placed on communications aspects.
The relative effectiveness of deterministic behaviour found in traditionally designed distributed applications and non-deterministic behaviour found in natural systems are explored. Ways in which deterministic design can lead to increases in complexity and conflicts between the non-functional requirements of distributed applications; that include scalability, efficiency, robustness, low-latency and stability; are identified. Deterministic design is contrasted with non-deterministic approaches, and ways in which the latter can avoid such conflicts and reduce the interaction and communication complexity are discussed.
This paper proposes that we look to natural systems for inspiration when designing architecture and selecting communications strategies. To demonstrate the effectiveness of this paradigm, a nature-inspired election algorithm is presented. The design and communication strategy are described. The election algorithm encapsulates non-deterministic behaviour internally to achieve the non-functional requirements described above. Externally the algorithm exhibits deterministic behaviour in meeting its functional requirements. The performance and complexity are critically evaluated through a simulation model and an implementation.

Item Type:	Article
Uncontrolled Keywords:	autonomic distributed computer systems, natural distributed systems, nature-inspired election algorithm, communication complexity, deterministic design
Subjects:	Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Pre-2014 Departments:	School of Computing & Mathematical Sciences School of Computing & Mathematical Sciences > Department of Computer Systems Technology
Related URLs:	Publisher Organisation
Last Modified:	14 Oct 2016 09:09
URI:	http://gala.gre.ac.uk/id/eprint/3597

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