DC Field | Value | Language |
---|---|---|
dc.contributor.author | NGUYEN, HOANG MINH | ko |
dc.contributor.author | Kim, Seong Hoon | ko |
dc.contributor.author | Le, Dinh Tuan | ko |
dc.contributor.author | Heo, Sehyeon | ko |
dc.contributor.author | Im, Janggwan | ko |
dc.contributor.author | Kim, Daeyoung | ko |
dc.date.accessioned | 2016-07-13T02:01:04Z | - |
dc.date.available | 2016-07-13T02:01:04Z | - |
dc.date.created | 2016-01-06 | - |
dc.date.created | 2016-01-06 | - |
dc.date.created | 2016-01-06 | - |
dc.date.issued | 2015-06-27 | - |
dc.identifier.citation | IEEE Cloud 2015 | - |
dc.identifier.uri | http://hdl.handle.net/10203/210822 | - |
dc.description.abstract | To ensure global interoperability in today’s fast-moving trading networks, EPCglobal Network (EPC Network) architecture has been at the core of Electronic Product Code (EPC) as a universal identifier for objects’ virtual representations. While Cloud technology has largely been used for EPC Network’s real world deployment for thousands of vendors, an optimized Cloud solution has yet to be provided. Therefore, in this paper, we explore the challenges of EPC Network deployment, and propose our own Cloud solution with optimizations in load prediction and migration management. As proof of concept, we have conducted experiments with regard to prediction accuracy and migration performance. | - |
dc.language | English | - |
dc.publisher | IEEE Computer Society | - |
dc.title | EPCloudFlow: Load Prediction and Migration Optimizations for EPC Network on Cloud | - |
dc.type | Conference | - |
dc.identifier.wosid | 000380473600124 | - |
dc.identifier.scopusid | 2-s2.0-84960145690 | - |
dc.type.rims | CONF | - |
dc.citation.publicationname | IEEE Cloud 2015 | - |
dc.identifier.conferencecountry | US | - |
dc.identifier.conferencelocation | Millennium Broadway Hotel, New York | - |
dc.embargo.liftdate | 9999-12-31 | - |
dc.embargo.terms | 9999-12-31 | - |
dc.contributor.localauthor | Kim, Daeyoung | - |
dc.contributor.nonIdAuthor | Le, Dinh Tuan | - |
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