{"@context":"http://iiif.io/api/presentation/2/context.json","@id":"https://repo.library.stonybrook.edu/cantaloupe/iiif/2/manifest.json","@type":"sc:Manifest","label":"ON SELECTED PROBLEMS IN BACKSCATTER NETWORKS AND QUALITY OF EXPERIENCE IN NETWORKED APPLICATIONS","metadata":[{"label":"dc.description.sponsorship","value":"This work is sponsored by the Stony Brook University Graduate School in compliance with the requirements for completion of degree"},{"label":"dc.format","value":"Monograph"},{"label":"dc.format.medium","value":"Electronic Resource"},{"label":"dc.format.mimetype","value":"Application/PDF"},{"label":"dc.identifier.uri","value":"http://hdl.handle.net/11401/78361"},{"label":"dc.language.iso","value":"en_US"},{"label":"dcterms.abstract","value":"Wireless communication uses valuable energy especially because it is primarily done through battery-driven mobile devices. How we use energy revenue is a vital issue because people depend on this mode of communication for a variety of reasons, including personal, social, economic, and educational. When devices use energy inefficiently, they drain resources too quickly, resulting in network disconnection. In conventional wireless networks that continue to be the norm, devices transmit information through active radio, costing the major portion of energy in the transmission. To remove energy hungry active radio, the industry introduced RFID (radio frequency identification) systems which built on the backscatter communication mechanism. Through the backscatter mechanism, a power greedy active transmission is simplified to a passive reflection \u2013 ride on the existing carrier signal. Building on passive backscattering approach, the first half of the dissertation makes two main contributions. First, it presents the first multi-hop backscatter tags that can successfully communicate in the presence of structural obstacles, and this backscattered signal utilized in the form of RF sensor. Therefore, the new system resolves scalability issue in RFID and ultimately provide activity signatures for human motion analytic. Second, we introduce an adequate localization technique for the backscatter based devices. The new system presented a phase-based ranging technique and demonstrated on application to shopping cart localization. In the latter half of the dissertation, human\u2019s perception on web applications is investigated toward identifying the best quality of service and experience (QoS/QoE), the best satisfaction under the given network revenue. We, humans, see only a tiny region at the center of their visual field with the highest visual acuity, a behavior known as foveation. Visual acuity reduces drastically towards the visual periphery. Even the contents are served on its highest quality; humans cannot perceive as it served. Humans only perceive and recognize the small portion of contents. Because of human\u2019s characteristics, resources are oversupplied or misused. We prioritize the contents for the best use of the same given network resource, yet serve better service and experience. Essentially, we prioritize the web contents based on the user\u2019s gaze information, in terms of the real-time gaze feedback and previously learned scan path patterns. Through our prioritized system, we can achieve to the quality level that contemporary service unable to reach. Our system demonstrated higher resolution where contemporary service can only serve medium or low resolution for the Internet streaming service, and validate the faster web page perception than contemporary web page service. Thus, the latter part of the dissertation concludes by highlighting two major achievements. We first present layered Internet video streaming service which serves the best quality in terms of user perception yet save Internet traffic. Next, we introduce a reprioritized web page service in learned user\u2019s visual scan paths. The user\u2019s perception of page load time reduced 17 percent on average. In this dissertation, we propose technical solutions to realize communication in lean resource environment in the first two chapters, then propose the best use of tightly given resources in the latter two chapters."},{"label":"dcterms.available","value":"2018-07-09T14:18:44Z"},{"label":"dcterms.contributor","value":"Djuri'c, Petar M."},{"label":"dcterms.creator","value":"Ryoo, Jihoon"},{"label":"dcterms.dateAccepted","value":"2018-07-09T14:18:44Z"},{"label":"dcterms.dateSubmitted","value":"2018-07-09T14:18:44Z"},{"label":"dcterms.description","value":"Department of Computer Science."},{"label":"dcterms.extent","value":"167 pg."},{"label":"dcterms.format","value":"Monograph"},{"label":"dcterms.identifier","value":"http://hdl.handle.net/11401/78361"},{"label":"dcterms.issued","value":"2017-08-01"},{"label":"dcterms.language","value":"en_US"},{"label":"dcterms.provenance","value":"Submitted by Jason Torre (fjason.torre@stonybrook.edu) on 2018-07-09T14:18:44Z\nNo. of bitstreams: 1\nRyoo_grad.sunysb_0771E_13360.pdf: 5737464 bytes, checksum: 5f4aa2c8b19537c0c6bdeeb57f1588f9 (MD5)"},{"label":"dcterms.subject","value":"page load time"},{"label":"dcterms.title","value":"ON SELECTED PROBLEMS IN BACKSCATTER NETWORKS AND QUALITY OF EXPERIENCE IN NETWORKED APPLICATIONS"},{"label":"dcterms.type","value":"Dissertation"},{"label":"dc.type","value":"Dissertation"}],"description":"This manifest was generated dynamically","viewingDirection":"left-to-right","sequences":[{"@type":"sc:Sequence","canvases":[{"@id":"https://repo.library.stonybrook.edu/cantaloupe/iiif/2/canvas/page-1.json","@type":"sc:Canvas","label":"Page 1","height":1650,"width":1275,"images":[{"@type":"oa:Annotation","motivation":"sc:painting","resource":{"@id":"https://repo.library.stonybrook.edu/cantaloupe/iiif/2/82%2F93%2F96%2F82939634641168591297483434812778947495/full/full/0/default.jpg","@type":"dctypes:Image","format":"image/jpeg","height":1650,"width":1275,"service":{"@context":"http://iiif.io/api/image/2/context.json","@id":"https://repo.library.stonybrook.edu/cantaloupe/iiif/2/82%2F93%2F96%2F82939634641168591297483434812778947495","profile":"http://iiif.io/api/image/2/level2.json"}},"on":"https://repo.library.stonybrook.edu/cantaloupe/iiif/2/canvas/page-1.json"}]}]}]}