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Quality-of-context driven autonomicity

Quality-of-context driven autonomicity

Breza, Michael, Anthony, Richard and McCann, Julie (2007) Quality-of-context driven autonomicity. In: De Wolf, Tom, Saffre, Fabrice and Anthony, Richard, (eds.) Proceedings of the 2nd International Workshop on Engineering Emergence in Decentralised Autonomic Systems EEDAS 2007. CMS Press, University of Greenwich, pp. 42-51. ISBN 9781904521433

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Abstract

Optimisation in wireless sensor networks is necessary due to the resource constraints of individual devices, bandwidth limits of the communication channel, relatively high probably of sensor failure, and the requirement constraints of the deployed applications in potently highly volatile environments. This paper presents BioANS, a protocol designed to optimise a wireless sensor network for resource efficiency as well as to meet a requirement common to a whole class of WSN applications - namely that the sensor nodes are dynamically selected on some qualitative basis, for example the quality by which they can provide the required context information. The design of BioANS has been inspired by the communication mechanisms that have evolved in natural systems. The protocol tolerates randomness in its environment, including random message loss, and incorporates a non-deterministic ’delayed-bids’ mechanism. A simulation model is used to explore the protocol’s performance in a wide range of WSN configurations. Characteristics evaluated include tolerance to sensor node density and message loss, communication efficiency, and negotiation latency .

Item Type: Book Section
Additional Information: This paper forms part of the published proceedings from 2nd International Workshop on Engineering Emergence in Decentralised Autonomic Systems, EEDAS 2007, June 11th, 2007
Uncontrolled Keywords: wireless sensor networks, BioANS, randomness, delayed-bids, node density, message loss,
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 09:03
Selected for GREAT 2016: None
Selected for GREAT 2017: None
Selected for GREAT 2018: None
URI: http://gala.gre.ac.uk/id/eprint/1083

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