Scenario-based energy estimation for continuous mobile sensing applications: Poster abstract

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dc.contributor.authorChoi, Seungpyoko
dc.contributor.authorKim, Seonghoonko
dc.contributor.authorLee, Taegyeongko
dc.contributor.authorSong, Junehwako
dc.date.accessioned2023-07-27T03:01:50Z-
dc.date.available2023-07-27T03:01:50Z-
dc.date.created2023-07-07-
dc.date.issued2020-11-
dc.identifier.citation18th ACM Conference on Embedded Networked Sensor Systems, SenSys 2020, pp.715 - 716-
dc.identifier.urihttp://hdl.handle.net/10203/310844-
dc.description.abstractContinuous mobile sensing applications (CMSAs) run 24 hours in the background, consuming a significant amount of energy. Due to CMSA's dynamic behavior according to the users' context, it is very difficult to predict the energy consumption of CMSA. User trace-based solutions have been proposed to effectively estimate the energy consumption of CMSA, but they suffer burdensome user trace collection. We propose Scenethesizer, a scenario-based energy estimation system, which generates and augments the user traces for unseen application usage scenarios and estimate the energy consumption of CMSA based on the generated user traces.-
dc.languageEnglish-
dc.publisherAssociation for Computing Machinery, Inc-
dc.titleScenario-based energy estimation for continuous mobile sensing applications: Poster abstract-
dc.typeConference-
dc.identifier.scopusid2-s2.0-85097524674-
dc.type.rimsCONF-
dc.citation.beginningpage715-
dc.citation.endingpage716-
dc.citation.publicationname18th ACM Conference on Embedded Networked Sensor Systems, SenSys 2020-
dc.identifier.conferencecountryJA-
dc.identifier.conferencelocationVirtual-
dc.identifier.doi10.1145/3384419.3430405-
dc.contributor.localauthorSong, Junehwa-
dc.contributor.nonIdAuthorChoi, Seungpyo-
dc.contributor.nonIdAuthorKim, Seonghoon-
dc.contributor.nonIdAuthorLee, Taegyeong-
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CS-Conference Papers(학술회의논문)
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