Monitoring the structural health of civil infrastructures with wireless sensor networks aids in detecting failures early, but faces power challenges in ensuring reasonable network lifetimes. Recharging select nodes with Unmanned Aerial Vehicles (UAVs) provides a solution that currently can recharge a single node; however, questions arise on the effectiveness of a limited recharging system, the appropriate node to recharge, and the best sink selection algorithm for improving network lifetime given a limited recharging system. This paper simulates such a network in order to answer those questions. This thesis first determines whether or not recharging with a UAV is an effective method of delivering limited power to the network. It then determines the best way to deliver that power. Finally, this thesis explores five different sink positioning algorithms to find which optimize the network lifetime by load-balancing the energy in the network, all in combination with the added capability of a UAV.
","abstract_html":"<p>Monitoring the structural health of civil infrastructures with wireless sensor networks aids in detecting failures early, but faces power challenges in ensuring reasonable network lifetimes. Recharging select nodes with Unmanned Aerial Vehicles (UAVs) provides a solution that currently can recharge a single node; however, questions arise on the effectiveness of a limited recharging system, the appropriate node to recharge, and the best sink selection algorithm for improving network lifetime given a limited recharging system. This paper simulates such a network in order to answer those questions. This thesis first determines whether or not recharging with a UAV is an effective method of delivering limited power to the network. It then determines the best way to deliver that power. Finally, this thesis explores five different sink positioning algorithms to find which optimize the network lifetime by load-balancing the energy in the network, all in combination with the added capability of a UAV.</p>","abstract_has_math":false,"creators":["Johnson, Jennifer Nichole"],"institution":null,"degree_name":"Master of Science in Engineering (M.S.Eng.)","degree_level":"Thesis - Pacific Access Restricted","degree_discipline":"Engineering","degree_department":null,"school":null,"contributors":["Elizabeth Basha"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2014,"date_issued":"2014-01-01T08:00:00Z","date_published":"2014-01-01T08:00:00Z","updated_at":"2026-07-24T05:36:09Z","subjects":["Computer Engineering","Applied sciences","Recharging","Sink positioning","Unmanned aerial vehicles","Wireless sensor networks","Engineering"],"languages":[],"rights":[],"rights_urls":["http://rightsstatements.org/vocab/InC/1.0/"],"identifier_entries":[{"key":"dc:identifier","label":"Identifier","values":["9781303996672"],"render_values":[{"text":"9781303996672","href":null,"code":true}]}]},"links":{"outbound_url":"https://scholarlycommons.pacific.edu/uop_etds/227","outbound_label":"Repository record","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Elizabeth Basha"]},{"key":"dc:creator","label":"Author","values":["Johnson, Jennifer Nichole"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.available","label":"Dc Date Available","values":["2018-06-29T09:07:05Z"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Engineering"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Thesis - Pacific Access Restricted"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Master of Science in Engineering (M.S.Eng.)"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Computer Engineering","Applied sciences","Recharging","Sink positioning","Unmanned aerial vehicles","Wireless sensor networks","Engineering"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:rights","label":"Dc Rights","values":["http://rightsstatements.org/vocab/InC/1.0/"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["9781303996672","https://scholarlycommons.pacific.edu/uop_etds/227"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["Monitoring the structural health of civil infrastructures with wireless sensor networks aids in detecting failures early, but faces power challenges in ensuring reasonable network lifetimes. Recharging select nodes with Unmanned Aerial Vehicles (UAVs) provides a solution that currently can recharge a single node; however, questions arise on the effectiveness of a limited recharging system, the appropriate node to recharge, and the best sink selection algorithm for improving network lifetime given a limited recharging system. This paper simulates such a network in order to answer those questions. This thesis first determines whether or not recharging with a UAV is an effective method of delivering limited power to the network. It then determines the best way to deliver that power. Finally, this thesis explores five different sink positioning algorithms to find which optimize the network lifetime by load-balancing the energy in the network, all in combination with the added capability of a UAV.
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