Smart Collaborative Tracking for Ubiquitous Power IoT in Edge-Cloud Interplay Domain
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Song, Fei | - |
dc.contributor.author | Zhu, Mingqiang | - |
dc.contributor.author | Zhou, Yutong | - |
dc.contributor.author | You, Ilsun | - |
dc.contributor.author | Zhang, Hongke | - |
dc.date.accessioned | 2021-08-11T08:34:21Z | - |
dc.date.available | 2021-08-11T08:34:21Z | - |
dc.date.issued | 2020-07 | - |
dc.identifier.issn | 2327-4662 | - |
dc.identifier.uri | https://scholarworks.bwise.kr/sch/handle/2021.sw.sch/2680 | - |
dc.description.abstract | Ubiquitous power Internet of Things (IoT) is suffering unprecedented constraints and reliable tracing is a typical example. Motivated by software-defined and function virtualization capabilities of edge-cloud interplay, we propose a smart collaborative tracking scheme by investigating advanced parameter prediction skills and improved particle filter approaches. First, the range-based positioning issues are transformed into the vector nonlinear suboptimal estimation problem based on information fusion. Second, the importance of density function is provisioned to calculate locations and trajectories of the mobile node by obtaining cubature points, updating state estimation, and revising vector estimation. The Gauss-Newton iterative method has been utilized to achieve higher accuracy. Third, we implement our scheme into the simulation platform and prototype system. The practical deployment has been validated from multiple perspectives. Comparing with existing candidates, experimental results illustrate that the proposed algorithm is able to enhance the performance and demonstrate acceptable reliability. Potential usages are being expected in dynamic surveillance, equipment maintenance, and other emerging IoT scenarios. | - |
dc.format.extent | 10 | - |
dc.language | 영어 | - |
dc.language.iso | ENG | - |
dc.publisher | Institute of Electrical and Electronics Engineers Inc. | - |
dc.title | Smart Collaborative Tracking for Ubiquitous Power IoT in Edge-Cloud Interplay Domain | - |
dc.type | Article | - |
dc.publisher.location | 미국 | - |
dc.identifier.doi | 10.1109/JIOT.2019.2958097 | - |
dc.identifier.scopusid | 2-s2.0-85089310959 | - |
dc.identifier.wosid | 000548817900033 | - |
dc.identifier.bibliographicCitation | IEEE Internet of Things Journal, v.7, no.7, pp 6046 - 6055 | - |
dc.citation.title | IEEE Internet of Things Journal | - |
dc.citation.volume | 7 | - |
dc.citation.number | 7 | - |
dc.citation.startPage | 6046 | - |
dc.citation.endPage | 6055 | - |
dc.type.docType | Article | - |
dc.description.isOpenAccess | N | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
dc.relation.journalResearchArea | Computer Science | - |
dc.relation.journalResearchArea | Engineering | - |
dc.relation.journalResearchArea | Telecommunications | - |
dc.relation.journalWebOfScienceCategory | Computer Science, Information Systems | - |
dc.relation.journalWebOfScienceCategory | Engineering, Electrical & Electronic | - |
dc.relation.journalWebOfScienceCategory | Telecommunications | - |
dc.subject.keywordPlus | INDUSTRIAL INTERNET | - |
dc.subject.keywordPlus | PARTICLE FILTER | - |
dc.subject.keywordPlus | LOCALIZATION | - |
dc.subject.keywordPlus | NETWORKS | - |
dc.subject.keywordPlus | AOA | - |
dc.subject.keywordAuthor | Mathematical model | - |
dc.subject.keywordAuthor | Internet of Things | - |
dc.subject.keywordAuthor | Mobile nodes | - |
dc.subject.keywordAuthor | Collaboration | - |
dc.subject.keywordAuthor | Reliability | - |
dc.subject.keywordAuthor | Particle filters | - |
dc.subject.keywordAuthor | Edge-cloud interplay | - |
dc.subject.keywordAuthor | smart collaborative tracking | - |
dc.subject.keywordAuthor | ubiquitous power Internet of Things (IoT) | - |
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