Supporting device-to-device search and sharing of hyper-localized data

dc.contributor.advisorJulien, Christineen
dc.contributor.committeeMemberGarg, Vijayen
dc.contributor.committeeMemberLam, Simonen
dc.contributor.committeeMemberde Veciana, Gustavoen
dc.contributor.committeeMemberVishwanath, Sriramen
dc.creatorMichel, Jonas Reinhardten
dc.date.accessioned2015-09-08T19:36:17Zen
dc.date.accessioned2018-01-22T22:28:05Z
dc.date.available2018-01-22T22:28:05Z
dc.date.issued2015-05en
dc.date.submittedMay 2015en
dc.date.updated2015-09-08T19:36:17Zen
dc.descriptiontexten
dc.description.abstractSupporting emerging mobile applications in densely populated environments requires connecting mobile users and their devices with the surrounding digital landscape. Specifically, the volume of digitally-available data in such computing spaces presents an imminent need for expressive mechanisms that enable humans and applications to share and search for relevant information within their digitally accessible physical surroundings. Device-to-device communications will play a critical role in facilitating transparent access to proximate digital resources. A wide variety of approaches exist that support device-to-device dissemination and query-driven data access. Very few, however, capitalize on the contextual history of the shared data itself to distribute additional data or to guide queries. This dissertation presents Gander, an application substrate and mobile middleware designed to ease the burden associated with creating applications that require support for sharing and searching of hyper-localized data in situ. Gander employs a novel trajectory-driven model of spatiotemporal provenance that enriches shared data with its contextual history -- annotations that capture data's geospatial and causal history across a lifetime of device-to-device propagation. We demonstrate the value of spatiotemporal data provenance as both a tool for improving ad hoc routing performance and for driving complex application behavior. This dissertation discusses the design and implementation of Gander's middleware model, which abstracts away tedious implementation details by enabling developers to write high-level rules that govern when, where, and how data is distributed and to execute expressive queries across proximate digital resources. We evaluate Gander within several simulated large-scale environments and one real-world deployment on the UT Austin campus. The goal of this research is to provide formal constructs realized within a software framework that ease the software engineering challenges encountered during the design and deployment of several applications in emerging mobile environments.en
dc.description.departmentElectrical and Computer Engineeringen
dc.format.mimetypeapplication/pdfen
dc.identifier.urihttp://hdl.handle.net/2152/31018en
dc.language.isoenen
dc.subjectPervasive computingen
dc.subjectDistributed systemsen
dc.subjectMobile computingen
dc.subjectDynamic networksen
dc.subjectSearch algorithmsen
dc.subjectData modelingen
dc.subjectGraph databasesen
dc.subjectMobile applicationsen
dc.subjectTime varying graphsen
dc.subjectMobile middlewareen
dc.subjectDevice-to-device communicationen
dc.subjectSpatiotemporal trajectoriesen
dc.titleSupporting device-to-device search and sharing of hyper-localized dataen
dc.typeThesisen

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