Embryonic Stream processing using Morphogens

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dc.contributor.author Sabir, Kenneth en_US
dc.contributor.author Lowe, David en_US
dc.contributor.editor Hideyuki Takagi, Ajith Abraham, Mario Koppen, Kaori Yoshida, Andre de Carvalho en_US
dc.date.accessioned 2012-02-02T11:08:07Z
dc.date.available 2012-02-02T11:08:07Z
dc.date.issued 2010 en_US
dc.identifier 2009007510 en_US
dc.identifier.citation Sabir Kenneth and Lowe David 2010, 'Embryonic Stream processing using Morphogens', , IEEE, Piscataway, NJ, USA, , pp. 603-610. en_US
dc.identifier.issn 978-1-4244-7377-9 en_US
dc.identifier.other E1 en_US
dc.identifier.uri http://hdl.handle.net/10453/16275
dc.description.abstract Abstract-Stream processing has been shown to be a computing paradigm that is well suited to the distributed processing of massive amounts of continuous real-time data. In stream processing, tasks are distributed across processing nodes and the information flow passes from task to task. The allocation of tasks to nodes has typically been carried out by a centralized task manager. Whilst this allocation approach has allowed optimization of the task allocation for constrained domains, it is likely to suffer problems as the complexity of the processing tasks and the scale of the network rise and the network becomes more dynamic. In this paper we explore the potential for a distributed autonomous task allocation based on an embryonic approach combined with a node differentiation that uses reaction-diffusion techniques. In this approach each processing node contains a full description of the processing tasks, and determines its own optimal role based on interactions with its neighbors. We describe the approach and provide preliminary results that indicate that it is likely to provide elegant scalability and therefore warrants further consideration. en_US
dc.language English en_US
dc.publisher IEEE en_US
dc.relation.isbasedon http://dx.doi.org/10.1109/NABIC.2010.5716321 en_US
dc.title Embryonic Stream processing using Morphogens en_US
dc.parent Second World Congress on Nature and Biologically Inspired Computing (NaBIC2010) en_US
dc.journal.volume en_US
dc.journal.number en_US
dc.publocation Piscataway, NJ, USA en_US
dc.identifier.startpage 603 en_US
dc.identifier.endpage 610 en_US
dc.cauo.name FEIT.Faculty of Engineering & Information Technology en_US
dc.conference Verified OK en_US
dc.for 080100 en_US
dc.personcode 94079807 en_US
dc.personcode 930311 en_US
dc.percentage 100 en_US
dc.classification.name Artificial Intelligence and Image Processing en_US
dc.classification.type FOR-08 en_US
dc.edition en_US
dc.custom World Congress on Nature and Biologically Inspired Computing en_US
dc.date.activity 20101215 en_US
dc.location.activity Kitakyushi, Japan en_US
dc.description.keywords Amorphous Computing; Embryonic Computing; Distributed Dataflow; Morphogenics; Stream Processing en_US
dc.staffid 930311 en_US

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