A Software-Defined Surveillance System With Energy Harvesting: Design and Performance Optimization
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Ko, Haneul | - |
dc.contributor.author | Pack, Sangheon | - |
dc.date.accessioned | 2021-09-02T11:15:16Z | - |
dc.date.available | 2021-09-02T11:15:16Z | - |
dc.date.created | 2021-06-16 | - |
dc.date.issued | 2018-06 | - |
dc.identifier.issn | 2327-4662 | - |
dc.identifier.uri | https://scholar.korea.ac.kr/handle/2021.sw.korea/75419 | - |
dc.description.abstract | Even though energy harvesting is a promising technology for energy-efficient surveillance systems, energy harvesting levels are highly dynamic depending on the time and location. Thus, the deployment of nonenergy-harvesting sensor nodes (NHSs) and sophisticated sleep scheduling of sensor nodes are necessary for performance guaranteed surveillance systems. In this paper, we present a software-defined surveillance system (SDSS) in which a centralized controller determines the sleep schedules of energy harvesting and NHSs on the basis of the collected information such as the spatial distribution of targets and the energy levels of sensor nodes. To derive the optimal sleep schedules minimizing the number of active sensor nodes while providing sufficient surveillance performance, a constraint Markov decision process problem is formulated and the optimal policy on sleep scheduling is obtained by linear programming. The evaluation results demonstrate that the SDSS with the optimal policy can reduce energy consumption by employing fewer active sensor nodes while providing the required level of target monitoring probability. | - |
dc.language | English | - |
dc.language.iso | en | - |
dc.publisher | IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC | - |
dc.subject | LIFETIME MAXIMIZATION | - |
dc.subject | TARGET COVERAGE | - |
dc.subject | WIRELESS | - |
dc.subject | NETWORKS | - |
dc.subject | STRATEGIES | - |
dc.subject | ALGORITHM | - |
dc.title | A Software-Defined Surveillance System With Energy Harvesting: Design and Performance Optimization | - |
dc.type | Article | - |
dc.contributor.affiliatedAuthor | Ko, Haneul | - |
dc.contributor.affiliatedAuthor | Pack, Sangheon | - |
dc.identifier.doi | 10.1109/JIOT.2018.2797174 | - |
dc.identifier.scopusid | 2-s2.0-85040966911 | - |
dc.identifier.wosid | 000435182100003 | - |
dc.identifier.bibliographicCitation | IEEE INTERNET OF THINGS JOURNAL, v.5, no.3, pp.1361 - 1369 | - |
dc.relation.isPartOf | IEEE INTERNET OF THINGS JOURNAL | - |
dc.citation.title | IEEE INTERNET OF THINGS JOURNAL | - |
dc.citation.volume | 5 | - |
dc.citation.number | 3 | - |
dc.citation.startPage | 1361 | - |
dc.citation.endPage | 1369 | - |
dc.type.rims | ART | - |
dc.type.docType | Article | - |
dc.description.journalClass | 1 | - |
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 | LIFETIME MAXIMIZATION | - |
dc.subject.keywordPlus | TARGET COVERAGE | - |
dc.subject.keywordPlus | WIRELESS | - |
dc.subject.keywordPlus | NETWORKS | - |
dc.subject.keywordPlus | STRATEGIES | - |
dc.subject.keywordPlus | ALGORITHM | - |
dc.subject.keywordAuthor | Constraint Markov decision process (CMDP) | - |
dc.subject.keywordAuthor | energy harvesting | - |
dc.subject.keywordAuthor | Internet of Things (IoT) | - |
dc.subject.keywordAuthor | sleep scheduling | - |
dc.subject.keywordAuthor | surveillance system | - |
dc.subject.keywordAuthor | target monitoring | - |
Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.
(02841) 서울특별시 성북구 안암로 14502-3290-1114
COPYRIGHT © 2021 Korea University. All Rights Reserved.
Certain data included herein are derived from the © Web of Science of Clarivate Analytics. All rights reserved.
You may not copy or re-distribute this material in whole or in part without the prior written consent of Clarivate Analytics.