A Scalable and Energy-Efficient Context Monitoring Framework for Mobile Personal Sensor Networks

Cited 43 time in webofscience Cited 0 time in scopus
  • Hit : 582
  • Download : 0
DC FieldValueLanguage
dc.contributor.authorKang, Seung-Wooko
dc.contributor.authorLee, Jin-Wonko
dc.contributor.authorJang, Hyuk-Jaeko
dc.contributor.authorLee, Young-Kiko
dc.contributor.authorPark, Sun-Eilko
dc.contributor.authorSong, June-Hwako
dc.date.accessioned2013-03-11T22:46:51Z-
dc.date.available2013-03-11T22:46:51Z-
dc.date.created2012-02-06-
dc.date.created2012-02-06-
dc.date.issued2010-05-
dc.identifier.citationIEEE TRANSACTIONS ON MOBILE COMPUTING, v.9, no.5, pp.686 - 702-
dc.identifier.issn1536-1233-
dc.identifier.urihttp://hdl.handle.net/10203/100561-
dc.description.abstractThe key feature of many emerging pervasive computing applications is to proactively provide services to mobile individuals. One major challenge in providing users with proactive services lies in continuously monitoring users' context based on numerous sensors in their PAN/BAN environments. The context monitoring in such environments imposes heavy workloads on mobile devices and sensor nodes with limited computing and battery power. We present SeeMon, a scalable and energy-efficient context monitoring framework for sensor-rich, resource-limited mobile environments. Running on a personal mobile device, SeeMon effectively performs context monitoring involving numerous sensors and applications. On top of SeeMon, multiple applications on the mobile device can proactively understand users' contexts and react appropriately. This paper proposes a novel context monitoring approach that provides efficient processing and sensor control mechanisms. We implement and test a prototype system on two mobile devices: a UMPC and a wearable device with a diverse set of sensors. Example applications are also developed based on the implemented system. Experimental results show that SeeMon achieves a high level of scalability and energy efficiency.-
dc.languageEnglish-
dc.publisherIEEE COMPUTER SOC-
dc.titleA Scalable and Energy-Efficient Context Monitoring Framework for Mobile Personal Sensor Networks-
dc.typeArticle-
dc.identifier.wosid000275652900007-
dc.identifier.scopusid2-s2.0-77949874130-
dc.type.rimsART-
dc.citation.volume9-
dc.citation.issue5-
dc.citation.beginningpage686-
dc.citation.endingpage702-
dc.citation.publicationnameIEEE TRANSACTIONS ON MOBILE COMPUTING-
dc.identifier.doi10.1109/TMC.2009.154-
dc.contributor.localauthorSong, June-Hwa-
dc.type.journalArticleArticle-
dc.subject.keywordAuthorContext monitoring-
dc.subject.keywordAuthorshared and incremental processing-
dc.subject.keywordAuthorsensor control-
dc.subject.keywordAuthorenergy efficiency-
dc.subject.keywordAuthorpersonal computing-
dc.subject.keywordAuthorportable devices-
dc.subject.keywordAuthorubiquitous computing-
dc.subject.keywordAuthorwireless sensor network-
dc.subject.keywordAuthorpervasive computing-
Appears in Collection
CS-Journal Papers(저널논문)
Files in This Item
There are no files associated with this item.
This item is cited by other documents in WoS
⊙ Detail Information in WoSⓡ Click to see webofscience_button
⊙ Cited 43 items in WoS Click to see citing articles in records_button

qr_code

  • mendeley

    citeulike


rss_1.0 rss_2.0 atom_1.0