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dc.contributor.authorZeinalipour-Yazdi, Constantinos D.en
dc.contributor.authorNeema, S.en
dc.contributor.authorKalogeraki, Vanaen
dc.contributor.authorGunopulos, Dimitriosen
dc.contributor.authorNajjar, W.en
dc.creatorZeinalipour-Yazdi, Constantinos D.en
dc.creatorNeema, S.en
dc.creatorKalogeraki, Vanaen
dc.creatorGunopulos, Dimitriosen
dc.creatorNajjar, W.en
dc.date.accessioned2019-11-13T10:43:04Z
dc.date.available2019-11-13T10:43:04Z
dc.date.issued2005
dc.identifier.isbn0-7695-2657-8
dc.identifier.isbn978-0-7695-2657-7
dc.identifier.urihttp://gnosis.library.ucy.ac.cy/handle/7/55192
dc.description.abstractSensor Networks will soon become ubiquitous, making them essential tools for monitoring the activity and evolution of our surrounding environment. However such environments are expected to generate vast amounts of temporal data that needs to be processed in a power-effective manner. To this date sensor nodes feature small amounts of memory which mostly limits their capabilities to queries that only refer to the current point in time. In this paper we initiate a study on the deployment of large memories at sensor nodes. Such an approach gives birth to an array of new temporal and top-k queries which have been extensively studied by the database community. Our discussion is in the context of the RISE (Riverside SEnsor) hardware platform, in which sensor nodes feature external flash card memories that provides them several Megabytes of storage. © 2005 IEEE.en
dc.sourceProceedings - International Workshop on Biomedical Data Engineering, BMDE2005en
dc.source21st International Conference on Data Engineering Workshops 2005en
dc.source.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-33947123707&doi=10.1109%2fICDE.2005.209&partnerID=40&md5=f64ef1817b2a31d5fbade5e8fd63e717
dc.subjectSensor networksen
dc.subjectSensor nodesen
dc.subjectData acquisitionen
dc.subjectData storage equipmenten
dc.subjectDatabase systemsen
dc.subjectFlash memoryen
dc.subjectFlash card memoriesen
dc.subjectRiverside Sensors (RISE)en
dc.subjectTemporal dataen
dc.titleData acquisition in sensor networks with large memoriesen
dc.typeinfo:eu-repo/semantics/conferenceObject
dc.identifier.doi10.1109/ICDE.2005.209
dc.description.volume2005
dc.author.faculty002 Σχολή Θετικών και Εφαρμοσμένων Επιστημών / Faculty of Pure and Applied Sciences
dc.author.departmentΤμήμα Πληροφορικής / Department of Computer Science
dc.type.uhtypeConference Objecten
dc.description.notes<p>Conference code: 69335en
dc.description.notesCited By :17</p>en
dc.contributor.orcidZeinalipour-Yazdi, Constantinos D. [0000-0002-8388-1549]
dc.gnosis.orcid0000-0002-8388-1549


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