{"id":{"repo_id":"utc","oai_identifier":"oai:scholar.utc.edu:theses-1067"},"canonical_url":"https://search.dev.ndltd.org/etd/utc/oai:scholar.utc.edu:theses-1067","repository":{"repo_id":"utc","name":"University of Tennessee - Chattanooga","base_url":"https://scholar.utc.edu/do/oai/"},"display":{"title":"Energy efficient compressed sensing in wireless sensor networks via random walk","abstract":"In this paper, we explore the problem of data acquisition using compressive sensing (CS) in wireless sensor networks. Unique properties of wireless sensor networks require we minimize communication cost for efficient power usage. At first, a compressive distributed sensing (CDS) algorithm is proposed but is then modified to decrease communication costs. The final algorithm presented is compressive distributed sensing with random walk CDS(RW); an algorithm that combines the data gathering and projection generation process of CDS.CDS(RW) uses rateless encoding, graph algorithms, and belief propagation decoding to improve upon the communication cost associated with CDS. In the end, we show that the communication cost of CDS(RW) versus existing CS algorithms is far superior, while still having satisfactory decoding accuracy.","abstract_html":"In this paper, we explore the problem of data acquisition using compressive sensing (CS) in wireless sensor networks. Unique properties of wireless sensor networks require we minimize communication cost for efficient power usage. At first, a compressive distributed sensing (CDS) algorithm is proposed but is then modified to decrease communication costs. The final algorithm presented is compressive distributed sensing with random walk CDS(RW); an algorithm that combines the data gathering and projection generation process of CDS.CDS(RW) uses rateless encoding, graph algorithms, and belief propagation decoding to improve upon the communication cost associated with CDS. In the end, we show that the communication cost of CDS(RW) versus existing CS algorithms is far superior, while still having satisfactory decoding accuracy.","abstract_has_math":false,"creators":["Fletcher, Robert Brian"],"institution":"University of Tennessee at Chattanooga","degree_name":null,"degree_level":null,"degree_discipline":null,"degree_department":null,"school":null,"contributors":["Sartipi, Mina","Yang, Li; Cao, Yu","College of Engineering and Computer Science"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":null,"date_issued":"","date_published":null,"updated_at":"2026-07-24T05:46:02Z","subjects":["Random walks (Mathematics)","Wireless sensor networks"],"languages":["English","eng"],"rights":[],"rights_urls":["https://rightsstatements.org/page/InC/1.0/?language=en"],"identifier_entries":[]},"links":{"outbound_url":"https://scholar.utc.edu/theses/65","outbound_label":"Repository record","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Sartipi, Mina","Yang, Li; Cao, Yu","College of Engineering and Computer Science"]},{"key":"dc:creator","label":"Author","values":["Fletcher, Robert Brian"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2011-05-01T07:00:00Z"]},{"key":"dc:publisher","label":"Institution","values":["University of Tennessee at Chattanooga","Chattanooga (Tenn.)"]},{"key":"dc:relation","label":"Dc Relation","values":["Masters Theses and Doctoral Dissertations"]},{"key":"dc:type","label":"Dc Type","values":["Masters theses","Text"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Random walks (Mathematics)","Wireless sensor networks"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["English","eng"]},{"key":"dc:rights","label":"Dc Rights","values":["https://rightsstatements.org/page/InC/1.0/?language=en"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://scholar.utc.edu/theses/65"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["Dept. of Computer Science and Engineering","M. S.; A thesis submitted to the faculty of the University of Tennessee at Chattanooga in partial fulfillment of the requirements of the degree of Master of Science."]},{"key":"dc:description.abstract","label":"Abstract","values":["In this paper, we explore the problem of data acquisition using compressive sensing (CS) in wireless sensor networks. Unique properties of wireless sensor networks require we minimize communication cost for efficient power usage. At first, a compressive distributed sensing (CDS) algorithm is proposed but is then modified to decrease communication costs. The final algorithm presented is compressive distributed sensing with random walk CDS(RW); an algorithm that combines the data gathering and projection generation process of CDS.CDS(RW) uses rateless encoding, graph algorithms, and belief propagation decoding to improve upon the communication cost associated with CDS. In the end, we show that the communication cost of CDS(RW) versus existing CS algorithms is far superior, while still having satisfactory decoding accuracy."]},{"key":"dc:title","label":"Title","values":["Energy efficient compressed sensing in wireless sensor networks via random walk"]}]}],"canonical_facts":{"dc:contributor":["Sartipi, Mina","Yang, Li; Cao, Yu","College of Engineering and Computer Science"],"dc:creator":["Fletcher, Robert Brian"],"dc:date":["2011-05-01T07:00:00Z"],"dc:description":["Dept. of Computer Science and Engineering","M. S.; A thesis submitted to the faculty of the University of Tennessee at Chattanooga in partial fulfillment of the requirements of the degree of Master of Science."],"dc:description.abstract":["In this paper, we explore the problem of data acquisition using compressive sensing (CS) in wireless sensor networks. Unique properties of wireless sensor networks require we minimize communication cost for efficient power usage. At first, a compressive distributed sensing (CDS) algorithm is proposed but is then modified to decrease communication costs. The final algorithm presented is compressive distributed sensing with random walk CDS(RW); an algorithm that combines the data gathering and projection generation process of CDS.CDS(RW) uses rateless encoding, graph algorithms, and belief propagation decoding to improve upon the communication cost associated with CDS. In the end, we show that the communication cost of CDS(RW) versus existing CS algorithms is far superior, while still having satisfactory decoding accuracy."],"dc:identifier":["https://scholar.utc.edu/theses/65"],"dc:language":["English","eng"],"dc:publisher":["University of Tennessee at Chattanooga","Chattanooga (Tenn.)"],"dc:relation":["Masters Theses and Doctoral Dissertations"],"dc:rights":["https://rightsstatements.org/page/InC/1.0/?language=en"],"dc:subject":["Random walks (Mathematics)","Wireless sensor networks"],"dc:title":["Energy efficient compressed sensing in wireless sensor networks via random walk"],"dc:type":["Masters theses","Text"]},"updated_at":"2026-07-24T05:46:02Z"}