{"id":{"repo_id":"uiuc","oai_identifier":"oai:www.ideals.illinois.edu:2142/44181"},"canonical_url":"https://search.dev.ndltd.org/etd/uiuc/oai:www.ideals.illinois.edu:2142/44181","repository":{"repo_id":"uiuc","name":"University of Illinois - Urbana-Champaign","base_url":"https://www.ideals.illinois.edu/oai-pmh"},"display":{"title":"Wireless sensor network implementations on a testbed platform","abstract":"Wireless sensor network implementations are developed for three different problems: data efficient quickest change detection, energy efficient sleep control for application to the tracking problem, and diffusing point source localization and tracking. For each of these three problems work in the field is briefly examined before simulations and implementations are presented. Particular emphasis is placed on the tracking problem where a small extension is made to previous work in the field. A sub-optimal algorithm is developed that is computationally feasible for implementation purposes. This solution is compared to the more optimal solution already derived, and is then implemented on a testbed network of wireless sensors. Results from the testbed are compared, and shown to be superior in performance, to duty cycling, which is the current standard for power efficiency in a sensor network. The implementations of the data efficient quickest change detection and the energy efficient sleep control for tracking algorithms both work well, and encourage immediate development for applied use. The implementation for the diffusing point source localization and tracking algorithm is by comparison less ready for deployment, and requires further development before applied use can be seriously considered.","abstract_html":"Wireless sensor network implementations are developed for three different problems: data efficient quickest change detection, energy efficient sleep control for application to the tracking problem, and diffusing point source localization and tracking. For each of these three problems work in the field is briefly examined before simulations and implementations are presented. Particular emphasis is placed on the tracking problem where a small extension is made to previous work in the field. A sub-optimal algorithm is developed that is computationally feasible for implementation purposes. This solution is compared to the more optimal solution already derived, and is then implemented on a testbed network of wireless sensors. Results from the testbed are compared, and shown to be superior in performance, to duty cycling, which is the current standard for power efficiency in a sensor network. The implementations of the data efficient quickest change detection and the energy efficient sleep control for tracking algorithms both work well, and encourage immediate development for applied use. The implementation for the diffusing point source localization and tracking algorithm is by comparison less ready for deployment, and requires further development before applied use can be seriously considered.","abstract_has_math":false,"creators":["Harris, Kyle"],"institution":"University of Illinois at Urbana-Champaign","degree_name":"M.S.","degree_level":"Thesis","degree_discipline":"Electrical & Computer Engr","degree_department":null,"school":null,"contributors":["Veeravalli, Venugopal V."],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2013,"date_issued":"2013-05-24T21:53:33Z","date_published":"2013-05-24T21:53:33Z","updated_at":"2026-07-22T22:25:33Z","subjects":["wireless sensor network","testbed","tracking network","quickest change detection","partially observable Markov decision process (POMDP)","energy-efficiency"],"languages":["en"],"rights":["Copyright 2013 Kyle A. 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This solution is compared to the more optimal solution already derived, and is then implemented on a testbed network of wireless sensors. Results from the testbed are compared, and shown to be superior in performance, to duty cycling, which is the current standard for power efficiency in a sensor network. The implementations of the data efficient quickest change detection and the energy efficient sleep control for tracking algorithms both work well, and encourage immediate development for applied use. The implementation for the diffusing point source localization and tracking algorithm is by comparison less ready for deployment, and requires further development before applied use can be seriously considered.","Item withdrawn by Mark Zulauf (zulauf@illinois.edu) on 2013-04-15T18:03:50Z Item was in collections: University of Illinois Theses & Dissertations (ID: 1) No. of bitstreams: 2 Harris_Kyle.zip: 25726713 bytes, checksum: 02004b1424b3862f0dcc0e65afd702b7 (MD5) Harris_Kyle.pdf: 13135831 bytes, checksum: 0be8f1109d90e1afb517b1330f214848 (MD5)","Made available in DSpace on 2013-05-24T21:53:33Z (GMT). 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Particular emphasis is placed on the tracking problem where a small extension is made to previous work in the field. A sub-optimal algorithm is developed that is computationally feasible for implementation purposes. This solution is compared to the more optimal solution already derived, and is then implemented on a testbed network of wireless sensors. Results from the testbed are compared, and shown to be superior in performance, to duty cycling, which is the current standard for power efficiency in a sensor network. The implementations of the data efficient quickest change detection and the energy efficient sleep control for tracking algorithms both work well, and encourage immediate development for applied use. 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Harris"],"dc:subject":["wireless sensor network","testbed","tracking network","quickest change detection","partially observable Markov decision process (POMDP)","energy-efficiency"],"dc:title":["Wireless sensor network implementations on a testbed platform"],"dc:type":["text"],"thesis:degree_discipline":["Electrical & Computer Engr"],"thesis:degree_level":["Thesis"],"thesis:degree_name":["M.S."],"thesis:institution_name":["University of Illinois at Urbana-Champaign"]},"updated_at":"2026-07-22T22:25:33Z"}