{"id":{"repo_id":"unlv","oai_identifier":"oai:oasis.library.unlv.edu:rtds-2657"},"canonical_url":"https://search.dev.ndltd.org/etd/unlv/oai:oasis.library.unlv.edu:rtds-2657","repository":{"repo_id":"unlv","name":"University of Nevada - Las Vegas","base_url":"https://oasis.library.unlv.edu/do/oai/"},"display":{"title":"Power aware broadcast trees for sensor networks","abstract":"In a sensor network with nodes distributed randomly in a two dimensional plane, the problem of constructing a power aware broadcast tree from a given source node is a difficult problem when nodes have k different levels of power. In fact, it is known that the problem of constructing a broadcast tree that minimizes total power consumption is NP-hard; We investigate the development of a good approximation algorithm for generating power reduced broadcast trees for sensor networks. We are particularly interested in the diameter of the generated broadcast tree. Both theoretical investigation and simulated results are presented. We present two approximation algorithms (one based on a partitioning approach and the other based on a cluster following approach) for constructing broadcast tRees The experimental investigation shows that the proposed algorithms are very effective in generating power-reduced and hop-count-reduced broadcast tRees","abstract_html":"In a sensor network with nodes distributed randomly in a two dimensional plane, the problem of constructing a power aware broadcast tree from a given source node is a difficult problem when nodes have k different levels of power. In fact, it is known that the problem of constructing a broadcast tree that minimizes total power consumption is NP-hard; We investigate the development of a good approximation algorithm for generating power reduced broadcast trees for sensor networks. We are particularly interested in the diameter of the generated broadcast tree. Both theoretical investigation and simulated results are presented. We present two approximation algorithms (one based on a partitioning approach and the other based on a cluster following approach) for constructing broadcast tRees The experimental investigation shows that the proposed algorithms are very effective in generating power-reduced and hop-count-reduced broadcast tRees","abstract_has_math":false,"creators":["Veeravalli, Sridhar"],"institution":"University of Nevada, Las Vegas","degree_name":"Master of Science (MS)","degree_level":"Thesis","degree_discipline":"Computer Science","degree_department":null,"school":null,"contributors":["Laxmi P. Gewali"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2004,"date_issued":"2004-01-01T08:00:00Z","date_published":"2004-01-01T08:00:00Z","updated_at":"2026-07-24T05:25:47Z","subjects":[],"languages":["English"],"rights":["IN COPYRIGHT. For more information about this rights statement, please visit http://rightsstatements.org/vocab/InC/1.0/"],"rights_urls":[],"identifier_entries":[{"key":"dc:identifier","label":"Identifier","values":["https://oasis.library.unlv.edu/rtds/1658"],"render_values":[{"text":"https://oasis.library.unlv.edu/rtds/1658","href":"https://oasis.library.unlv.edu/rtds/1658","code":true}]}]},"links":{"outbound_url":"https://doi.org/10.25669/oee7-03ty","outbound_label":"DOI","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Laxmi P. 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We are particularly interested in the diameter of the generated broadcast tree. Both theoretical investigation and simulated results are presented. We present two approximation algorithms (one based on a partitioning approach and the other based on a cluster following approach) for constructing broadcast tRees The experimental investigation shows that the proposed algorithms are very effective in generating power-reduced and hop-count-reduced broadcast tRees"]},{"key":"dc:format","label":"Dc Format","values":["pdf"]},{"key":"dc:title","label":"Title","values":["Power aware broadcast trees for sensor networks"]}]}],"canonical_facts":{"dc:contributor":["Laxmi P. Gewali"],"dc:creator":["Veeravalli, Sridhar"],"dc:description.abstract":["In a sensor network with nodes distributed randomly in a two dimensional plane, the problem of constructing a power aware broadcast tree from a given source node is a difficult problem when nodes have k different levels of power. In fact, it is known that the problem of constructing a broadcast tree that minimizes total power consumption is NP-hard; We investigate the development of a good approximation algorithm for generating power reduced broadcast trees for sensor networks. We are particularly interested in the diameter of the generated broadcast tree. Both theoretical investigation and simulated results are presented. We present two approximation algorithms (one based on a partitioning approach and the other based on a cluster following approach) for constructing broadcast tRees The experimental investigation shows that the proposed algorithms are very effective in generating power-reduced and hop-count-reduced broadcast tRees"],"dc:format":["pdf"],"dc:identifier":["10.25669/oee7-03ty","https://oasis.library.unlv.edu/rtds/1658","https://oasis.library.unlv.edu/context/rtds/article/2657/viewcontent/uc.pdf"],"dc:language":["English"],"dc:publisher":["University of Nevada, Las Vegas"],"dc:rights":["IN COPYRIGHT. For more information about this rights statement, please visit http://rightsstatements.org/vocab/InC/1.0/"],"dc:title":["Power aware broadcast trees for sensor networks"],"dc:type":["Text"],"thesis:degree_discipline":["Computer Science"],"thesis:degree_level":["Thesis"],"thesis:degree_name":["Master of Science (MS)"]},"updated_at":"2026-07-24T05:25:47Z"}