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dc.contributorDimitris Padosen_US
dc.contributorThyagarajan Nandagopal Program Manageren_US
dc.contributor.authorTommaso Melodia Principal Investigatoren_US
dc.datestart 09/01/2011en_US
dc.dateexpiration 08/31/2014en_US
dc.date.accessioned2014-04-02T18:15:22Z
dc.date.available2014-04-02T18:15:22Z
dc.date.issued2014-04-02
dc.identifier1117121en_US
dc.identifier.urihttp://hdl.handle.net/10477/22270
dc.descriptionGrant Amount: $ 450000en_US
dc.description.abstractWhile there has been progress in recent years in solving numerous wireless sensor networking challenges, the key problem of enabling real-time quality-aware video streaming in large-scale wireless networks of resource-constrained devices is still open and largely unexplored. Existing wireless networking protocol stacks based on transmitting predictively-encoded video are computationally expensive, have limited resilience to wireless channel errors, and use available network resources inefficiently. This project is attempting a new approach based: (a) On the development of a novel wireless streaming framework for resource-constrained devices rooted in the theory of compressed sensing (CS) and (b) co-design/optimization of the video encoder and key wireless networking functionalities. <br/><br/>The new networked wireless streaming system being developed is referred to as Compressive Video Streaming (CVS) and has the potential to significantly reduce power consumption for a given target video quality for resource-constrained sensing devices. New network control algorithms are designed and integrated with the video encoder that, unlike TCP and TCP-friendly approaches, use the estimated received video quality as the basis for resource allocation decisions. Project implementation and extensive testing is being carried out on several experimental platforms.<br/><br/>The technology to be developed has the potential to strongly impact the state of the art in resource-constrained wireless video sensor networks. Important educational objectives of the program include mentoring of minority graduate and undergraduate students, and development of new interdisciplinary course materials.en_US
dc.titleNeTS: Small: Towards Ubiquitous Multimedia Sensing through Compressive Video Streamingen_US
dc.typeNSF Granten_US


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