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Exploiting Mobile Plus in-situ Deployments in Community IoT Systems.- [electronic resource]
Exploiting Mobile Plus in-situ Deployments in Community IoT Systems.- [electronic resource]
상세정보
- 자료유형
- 학위논문(국외)
- 자관 청구기호
- 기본표목-개인명
- 표제와 책임표시사항
- Exploiting Mobile Plus in-situ Deployments in Community IoT Systems. - [electronic resource] / Zhu, Qiuxi.
- 발행, 배포, 간사 사항
- 발행, 배포, 간사 사항
- 형태사항
- 1 online resource(178 p.)
- 일반주기
- Source: Dissertations Abstracts International, Volume: 81-04, Section: B.
- 일반주기
- Advisor: Venkatasubramanian, Nalini.
- 학위논문주기
- Thesis (Ph.D.)--University of California, Irvine, 2019.
- 이용제한주기
- This item must not be sold to any third party vendors.
- 요약 등 주기
- 요약Improvements in Internet connectivity and advances in smart personal devices have enabled the rise of the Internet of Things (IoT) in real-world communities.Community IoT deployments utilize low-cost devices, often deployed in-situ in a relatively stable environment, to create real-time situation awareness. Our experience in operating and maintaining prototype IoT systems in real-world testbeds indicates that integrating mobile devices with in-situ platforms is a promising approach to increase the reliability and sustainability of commonplace community IoT applications. In particular, mobile devices can be leveraged to compensate for the non-uniform availability of infrastructure efficiently. Realizing the potential of the combined "mobile and in-situ'' deployments requires us to address a new set of challenges for data collection in dynamic settings.In this thesis, we propose planning-based approaches to the efficient operation and maintenance of community-scale IoT deployments that consist of both mobile and in-situ devices.Our proposed techniques leverage the prior knowledge of data characteristics, device heterogeneity, community infrastructure, and application needs.The goal is to optimize the activities of the devices under data budgets and timeliness constraints and seek a balance between data utility (i.e., accuracy, importance, and timeliness) and operational cost.We explore our solution within the context of urban environmental sensing and address three major research problems regarding IoT data generation, data upload, and sensor calibration (i.e., maintenance), respectively. First, we propose a spatiotemporal scheduling framework that regulates the data generation activities of participating devices. The framework employs online planning algorithms that optimize the spatiotemporal coverage of collected data to meet the application requirements of heterogeneous data types.Second, in the case of non-uniform network availability, we design a two-phase upload planning approach that creates data upload plans (i.e., when, where, and what to upload) for mobile data collectors before their departure (i.e., the static planning phase)
- 주제명부출표목-일반주제명
- 주제명부출표목-일반주제명
- 부출표목-단체명
- 기본자료저록
- Dissertations Abstracts International. 81-04B.
- 기본자료저록
- Dissertation Abstract International
- 전자적 위치 및 접속
- 원문정보보기
MARC
008200317s2019 ulk s 00 eng■001000015491785
■00520200217181416
■007cr
■020 ▼a9781085654593
■040 ▼d225006
■08204▼a621.3
■090 ▼a전자도서(박사논문)
■1001 ▼aZhu, Qiuxi.
■24510▼aExploiting Mobile Plus in-situ Deployments in Community IoT Systems.▼h[electronic resource]▼cZhu, Qiuxi.
■260 ▼a[S.l.]▼bUniversity of California, Irvine. ▼c2019
■260 1▼aAnn Arbor▼bProQuest Dissertations & Theses▼c2019
■300 ▼a1 online resource(178 p.)
■500 ▼aSource: Dissertations Abstracts International, Volume: 81-04, Section: B.
■500 ▼aAdvisor: Venkatasubramanian, Nalini.
■5021 ▼aThesis (Ph.D.)--University of California, Irvine, 2019.
■506 ▼aThis item must not be sold to any third party vendors.
■520 ▼aImprovements in Internet connectivity and advances in smart personal devices have enabled the rise of the Internet of Things (IoT) in real-world communities.Community IoT deployments utilize low-cost devices, often deployed in-situ in a relatively stable environment, to create real-time situation awareness. Our experience in operating and maintaining prototype IoT systems in real-world testbeds indicates that integrating mobile devices with in-situ platforms is a promising approach to increase the reliability and sustainability of commonplace community IoT applications. In particular, mobile devices can be leveraged to compensate for the non-uniform availability of infrastructure efficiently. Realizing the potential of the combined "mobile and in-situ'' deployments requires us to address a new set of challenges for data collection in dynamic settings.In this thesis, we propose planning-based approaches to the efficient operation and maintenance of community-scale IoT deployments that consist of both mobile and in-situ devices.Our proposed techniques leverage the prior knowledge of data characteristics, device heterogeneity, community infrastructure, and application needs.The goal is to optimize the activities of the devices under data budgets and timeliness constraints and seek a balance between data utility (i.e., accuracy, importance, and timeliness) and operational cost.We explore our solution within the context of urban environmental sensing and address three major research problems regarding IoT data generation, data upload, and sensor calibration (i.e., maintenance), respectively. First, we propose a spatiotemporal scheduling framework that regulates the data generation activities of participating devices. The framework employs online planning algorithms that optimize the spatiotemporal coverage of collected data to meet the application requirements of heterogeneous data types.Second, in the case of non-uniform network availability, we design a two-phase upload planning approach that creates data upload plans (i.e., when, where, and what to upload) for mobile data collectors before their departure (i.e., the static planning phase)
■650 4▼aComputer science.
■650 4▼aElectrical engineering.
■71020▼aUniversity of California, Irvine▼bComputer Science - Ph.D..
■7730 ▼tDissertations Abstracts International▼g81-04B.
■773 ▼tDissertation Abstract International
■791 ▼aPh.D.
■792 ▼a2019
■793 ▼aEnglish
■85640▼uhttp://www.riss.kr/pdu/ddodLink.do?id=T15491785▼nKERIS
