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    Hierarchical cloud-fog platform for data import from network-edge applications

    Jiang, Duo
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    [PDF] public.pdf (2.220Kb)
    [PDF] research.pdf (11.37Mb)
    Date
    2016
    Format
    Thesis
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    Abstract
    [ACCESS RESTRICTED TO THE UNIVERSITY OF MISSOURI AT REQUEST OF AUTHOR.] Communication and coordination in a mass casualty disaster scenario is limited and difficult for medical personnel in the absence of necessary cyber infrastructure and technologies that enable situation awareness. This leads to misdirected and delayed triage of scene-wide critically injured patients, especially when there are large numbers of patients needing diverse care levels. A hierarchical cloud-fog architecture involving a core cloud and edge clouds (i.e., fogs) can help the patient triage related real-time data movement challenges for creating visual situational awareness and overcome infrastructure limitations at the wireless network edge. In this MS Thesis, we study the architecture requirements of "Panacea's Cloud" [3], [4], a hierarchical cloud-fog platform that provides augmented reality benefits with real-time human communication and geolocation services. The platform integrates a standardized Incident Command System (ICS) with smart devices such as heads-up displays (HUDs), virtual beacons, and wireless mesh network elements. We show how the ICS back-end system can run using an infrastructure design that involves a core cloud leveraging fog resources and secure data collection close to the incident scenes. In addition, we describe experiment results from field evaluations of Panacea's Cloud platform that show benefits and issues in hierarchical cloud-fog service management in support of ICS communication during disaster incident coordination. Specifically, our results highlight hierarchical cloud-fog performance in terms of data communication throughput in HUD-to-virtual beacons, HUD-to-router and router-to-router communication cases.
    URI
    https://hdl.handle.net/10355/62571
    Degree
    M.S.
    Thesis Department
    Computer science (MU)
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    • 2016 MU theses - Access restricted to MU
    • Computer Science electronic theses and dissertations (MU)

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