Please use this identifier to cite or link to this item: http://hdl.handle.net/20.500.12188/25343
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dc.contributor.authorRoig, Pedro Juanen_US
dc.contributor.authorAlcaraz, Salvadoren_US
dc.contributor.authorGilly, Katjaen_US
dc.contributor.authorBernad, Cristinaen_US
dc.contributor.authorFiliposka, Sonjaen_US
dc.date.accessioned2023-01-10T08:30:28Z-
dc.date.available2023-01-10T08:30:28Z-
dc.date.issued2022-
dc.identifier.urihttp://hdl.handle.net/20.500.12188/25343-
dc.description.abstractEdge AI environments are ever increasing as the amount of IoT-connected devices grow, thus rising the level of carbon emissions of such ecosystems. Therefore, sustainable AI cloud/edge systems are a must in order to minimize all those emissions, where AI plays its part in gaining efficiency. In this paper, a scheme to easily organize and optimize the computing resources in an edge data center is going to be proposed, based on a specific toroidal grid topology which minimizes distance between any pair of hosts being part of it, thus reducing energy needs. That architecture may be dynamically adjusted according to the current traffic conditions and their expected variations so as to further save power consumption by using just the necessary computing assets.en_US
dc.subjectdata center design · edge AI · internet of things · resource migration · toroidal topologyen_US
dc.titleAn efficient architecture for edge data center networksen_US
dc.typeProceedingsen_US
dc.relation.conferenceICT Innovationsen_US
item.grantfulltextopen-
item.fulltextWith Fulltext-
crisitem.author.deptFaculty of Computer Science and Engineering-
Appears in Collections:Faculty of Computer Science and Engineering: Conference papers
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