{"id":{"repo_id":"uiuc","oai_identifier":"oai:www.ideals.illinois.edu:2142/95425"},"canonical_url":"https://search.dev.ndltd.org/etd/uiuc/oai:www.ideals.illinois.edu:2142/95425","repository":{"repo_id":"uiuc","name":"University of Illinois - Urbana-Champaign","base_url":"https://www.ideals.illinois.edu/oai-pmh"},"display":{"title":"An energy-efficient P2P protocol for validating measurements in wireless sensor networks","abstract":"Wireless sensor networks (WSNs) should collect accurate measurements to reliably capture the state of the environment that they monitor. However, measurement data collected from one or more sensors may drift or become erroneous due to hardware failures or sensor degradation. In WSNs with remote deployments, detecting those measurement errors through a centralized reporting approach can result in a large number of message transmissions, which in turn dramatically decreases the battery life of sensors in the network. In this thesis, we address this issue through three main contributions. First, we propose a protocol in which sensors detect errors in a peer-to-peer (P2P) fashion, and that extends the life of the WSN by minimizing the number of messages transmitted. Second, we propose an e ective anomaly detection approach that has low memory and processing requirements, allowing for easy deployment on low-cost sensor hardware. Third, we develop a trace-driven, discrete-event simulator that allows us to evaluate the developed protocol and approach. In doing so, we use three datasets from real WSN deployments, which include indoor air temperature, sea surface water temperature and seismic wave amplitude sensors. Our results show that our P2P protocol can accurately detect errors and simultaneously extend the e ective WSN lifetime dramatically compared to the centralized protocol.","abstract_html":"Wireless sensor networks (WSNs) should collect accurate measurements to reliably capture the state of the environment that they monitor. However, measurement data collected from one or more sensors may drift or become erroneous due to hardware failures or sensor degradation. In WSNs with remote deployments, detecting those measurement errors through a centralized reporting approach can result in a large number of message transmissions, which in turn dramatically decreases the battery life of sensors in the network. In this thesis, we address this issue through three main contributions. First, we propose a protocol in which sensors detect errors in a peer-to-peer (P2P) fashion, and that extends the life of the WSN by minimizing the number of messages transmitted. Second, we propose an e ective anomaly detection approach that has low memory and processing requirements, allowing for easy deployment on low-cost sensor hardware. Third, we develop a trace-driven, discrete-event simulator that allows us to evaluate the developed protocol and approach. In doing so, we use three datasets from real WSN deployments, which include indoor air temperature, sea surface water temperature and seismic wave amplitude sensors. Our results show that our P2P protocol can accurately detect errors and simultaneously extend the e ective WSN lifetime dramatically compared to the centralized protocol.","abstract_has_math":false,"creators":["Badrinath Krishna, Varun"],"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":["Sanders, William H."],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2017,"date_issued":"2017-03-01T15:49:36Z","date_published":"2017-03-01T15:49:36Z","updated_at":"2026-07-22T22:26:37Z","subjects":["Energy","Efficient","P2P","Distributed","Protocol","Validating","Detect","Fault","Measurement","Wireless sensor networks","Sensors","Isocontour","Bivariate","Normal","Distribution","Gaussian","Simulation","Anomaly","Detection","Error","Optimal","Message","Transmission"],"languages":["en"],"rights":["COPYRIGHT 2016 VARUN BADRINATH KRISHNA"],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"http://hdl.handle.net/2142/95425","outbound_label":"Handle","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Sanders, William H."]},{"key":"dc:creator","label":"Author","values":["Badrinath Krishna, Varun"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2017-03-01T15:49:36Z","2016-12-09","2016-12"]},{"key":"dc:type","label":"Dc Type","values":["text"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Electrical & Computer Engr"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Thesis"]},{"key":"thesis:degree_name","label":"Degree Name","values":["M.S."]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["University of Illinois at Urbana-Champaign"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Energy","Efficient","P2P","Distributed","Protocol","Validating","Detect","Fault","Measurement","Wireless sensor networks","Sensors","Isocontour","Bivariate","Normal","Distribution","Gaussian","Simulation","Anomaly","Detection","Error","Optimal","Message","Transmission"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["en"]},{"key":"dc:rights","label":"Dc Rights","values":["COPYRIGHT 2016 VARUN BADRINATH KRISHNA"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["http://hdl.handle.net/2142/95425"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["Wireless sensor networks (WSNs) should collect accurate measurements to reliably capture the state of the environment that they monitor. However, measurement data collected from one or more sensors may drift or become erroneous due to hardware failures or sensor degradation. In WSNs with remote deployments, detecting those measurement errors through a centralized reporting approach can result in a large number of message transmissions, which in turn dramatically decreases the battery life of sensors in the network. In this thesis, we address this issue through three main contributions. First, we propose a protocol in which sensors detect errors in a peer-to-peer (P2P) fashion, and that extends the life of the WSN by minimizing the number of messages transmitted. Second, we propose an e ective anomaly detection approach that has low memory and processing requirements, allowing for easy deployment on low-cost sensor hardware. Third, we develop a trace-driven, discrete-event simulator that allows us to evaluate the developed protocol and approach. In doing so, we use three datasets from real WSN deployments, which include indoor air temperature, sea surface water temperature and seismic wave amplitude sensors. Our results show that our P2P protocol can accurately detect errors and simultaneously extend the e ective WSN lifetime dramatically compared to the centralized protocol.","Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2017-02-28 without embargo terms","The student, Varun Badrinath Krishna, accepted the attached license on 2016-12-08 at 17:28.","The student, Varun Badrinath Krishna, submitted this Thesis for approval on 2016-12-08 at 17:46.","This Thesis was approved for publication on 2016-12-09 at 09:44.","DSpace SAF Submission Ingestion Package generated from Vireo submission #10497 on 2017-02-28 at 15:04:06","Made available in DSpace on 2017-03-01T15:49:36Z (GMT). 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In WSNs with remote deployments, detecting those measurement errors through a centralized reporting approach can result in a large number of message transmissions, which in turn dramatically decreases the battery life of sensors in the network. In this thesis, we address this issue through three main contributions. First, we propose a protocol in which sensors detect errors in a peer-to-peer (P2P) fashion, and that extends the life of the WSN by minimizing the number of messages transmitted. Second, we propose an e ective anomaly detection approach that has low memory and processing requirements, allowing for easy deployment on low-cost sensor hardware. Third, we develop a trace-driven, discrete-event simulator that allows us to evaluate the developed protocol and approach. In doing so, we use three datasets from real WSN deployments, which include indoor air temperature, sea surface water temperature and seismic wave amplitude sensors. Our results show that our P2P protocol can accurately detect errors and simultaneously extend the e ective WSN lifetime dramatically compared to the centralized protocol.","Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2017-02-28 without embargo terms","The student, Varun Badrinath Krishna, accepted the attached license on 2016-12-08 at 17:28.","The student, Varun Badrinath Krishna, submitted this Thesis for approval on 2016-12-08 at 17:46.","This Thesis was approved for publication on 2016-12-09 at 09:44.","DSpace SAF Submission Ingestion Package generated from Vireo submission #10497 on 2017-02-28 at 15:04:06","Made available in DSpace on 2017-03-01T15:49:36Z (GMT). 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