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CG-E2S2: Consistency-guaranteed and energy-efficient sleep scheduling algorithm with data aggregation for IoT

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dc.contributor.authorKo, Haneul-
dc.contributor.authorLee, Jaewook-
dc.contributor.authorPack, Sangheon-
dc.date.accessioned2021-09-01T18:13:50Z-
dc.date.available2021-09-01T18:13:50Z-
dc.date.created2021-06-19-
dc.date.issued2019-03-
dc.identifier.issn0167-739X-
dc.identifier.urihttps://scholar.korea.ac.kr/handle/2021.sw.korea/67187-
dc.description.abstractIn data acquisition (DAQ)-based services of Internet of things (IoT), IoT devices sense and transmit data to the application server through IoT gateway (GW). Due to the energy limitation of IoT devices, it is important to increase their energy efficiency. Further, when data from a very large number of IoT devices is individually transmitted, the data traffic volume can be significant. To resolve these issues, IoT devices and IoT GW can use sleep mode and data aggregation, respectively. However, when the IoT devices are in sleep mode for a long time and/or data are aggregated in IoT GW for a long time without any transmissions, data can become inconsistent. In this paper, we propose a consistency-guaranteed and energy efficient sleep scheduling algorithm (CG-E2S2) with data aggregation. In CG-E2S2, the optimal sleep duration of IoT devices and aggregation duration in IoT GW are jointly determined by means of a Markov decision process (MDP) with the consideration of energy efficiency of IoT devices, data traffic in networks, and data consistency. The evaluation results demonstrate that CG-E2S2 with the optimal policy outperforms the comparison schemes in terms of energy efficiency, data traffic volume, and data consistency. (C) 2017 Elsevier B.V. All rights reserved.-
dc.languageEnglish-
dc.language.isoen-
dc.publisherELSEVIER SCIENCE BV-
dc.subjectWIRELESS SENSOR NETWORKS-
dc.subjectINTERNET-
dc.subjectTHINGS-
dc.subjectPERFORMANCE-
dc.titleCG-E2S2: Consistency-guaranteed and energy-efficient sleep scheduling algorithm with data aggregation for IoT-
dc.typeArticle-
dc.contributor.affiliatedAuthorKo, Haneul-
dc.contributor.affiliatedAuthorPack, Sangheon-
dc.identifier.doi10.1016/j.future.2017.08.040-
dc.identifier.scopusid2-s2.0-85029724801-
dc.identifier.wosid000454370600095-
dc.identifier.bibliographicCitationFUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE, v.92, pp.1093 - 1102-
dc.relation.isPartOfFUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE-
dc.citation.titleFUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE-
dc.citation.volume92-
dc.citation.startPage1093-
dc.citation.endPage1102-
dc.type.rimsART-
dc.type.docTypeArticle-
dc.description.journalClass1-
dc.description.journalRegisteredClassscie-
dc.description.journalRegisteredClassscopus-
dc.relation.journalResearchAreaComputer Science-
dc.relation.journalWebOfScienceCategoryComputer Science, Theory & Methods-
dc.subject.keywordPlusWIRELESS SENSOR NETWORKS-
dc.subject.keywordPlusINTERNET-
dc.subject.keywordPlusTHINGS-
dc.subject.keywordPlusPERFORMANCE-
dc.subject.keywordAuthorInternet of things (IoT)-
dc.subject.keywordAuthorMarkov decision process (MDP)-
dc.subject.keywordAuthorSleep-
dc.subject.keywordAuthorEnergy-
dc.subject.keywordAuthorData aggregation-
dc.subject.keywordAuthorData consistency-
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공과대학 (전기전자공학부)
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