Embryonic Stream processing using Morphogens

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dc.contributor.author Sabir, KS
dc.contributor.author Lowe, DB
dc.contributor.editor Takagi, H
dc.contributor.editor Abraham, A
dc.contributor.editor Koppen, M
dc.contributor.editor Yoshida, K
dc.contributor.editor Carvalho, AD
dc.date.accessioned 2012-02-02T11:08:07Z
dc.date.issued 2010-01
dc.identifier.citation Second World Congress on Nature and Biologically Inspired Computing (NaBIC2010), 2010, pp. 603 - 610
dc.identifier.isbn 978-1-4244-7377-9
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.
dc.publisher IEEE
dc.relation.isbasedon 10.1109/NABIC.2010.5716321
dc.title Embryonic Stream processing using Morphogens
dc.type Conference Proceeding
dc.parent Second World Congress on Nature and Biologically Inspired Computing (NaBIC2010)
dc.journal.number en_US
dc.publocation Piscataway, NJ, USA en_US
dc.publocation Piscataway, NJ, USA
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.conference World Congress on Nature and Biologically Inspired Computing
dc.for 0801 Artificial Intelligence and Image Processing
dc.personcode 930311
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.date.activity 2010-12-15
dc.location.activity Kitakyushi, Japan en_US
dc.description.keywords Amorphous Computing; Embryonic Computing; Distributed Dataflow; Morphogenics; Stream Processing en_US
dc.description.keywords Amorphous Computing
dc.description.keywords Embryonic Computing
dc.description.keywords Distributed Dataflow
dc.description.keywords Morphogenics
dc.description.keywords Stream Processing
pubs.embargo.period Not known
pubs.organisational-group /University of Technology Sydney
pubs.organisational-group /University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group /University of Technology Sydney/Faculty of Engineering and Information Technology/School of Computing and Communications
pubs.organisational-group /University of Technology Sydney/Strength - Realtime Information Networks
utslib.copyright.status Closed Access
utslib.copyright.date 2015-04-15 12:17:09.805752+10
utslib.collection.history Closed (ID: 3)


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