Directional virtual backbone based data aggregation scheme for Wireless Visual Sensor Networks
Data gathering is a fundamental task in Wireless Visual Sensor Networks (WVSNs). Features of directional antennas and the visual data make WVSNs more complex than the conventional Wireless Sensor Network (WSN). The virtual backbone is a technique, which is capable of constructing clusters. The versi...
Gespeichert in:
Veröffentlicht in: | PloS one 2018-05, Vol.13 (5), p.e0196705-e0196705 |
---|---|
Hauptverfasser: | , , , , |
Format: | Artikel |
Sprache: | eng |
Schlagworte: | |
Online-Zugang: | Volltext |
Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
container_end_page | e0196705 |
---|---|
container_issue | 5 |
container_start_page | e0196705 |
container_title | PloS one |
container_volume | 13 |
creator | Zhang, Jing Liu, Shi-Jian Tsai, Pei-Wei Zou, Fu-Min Ji, Xiao-Rong |
description | Data gathering is a fundamental task in Wireless Visual Sensor Networks (WVSNs). Features of directional antennas and the visual data make WVSNs more complex than the conventional Wireless Sensor Network (WSN). The virtual backbone is a technique, which is capable of constructing clusters. The version associating with the aggregation operation is also referred to as the virtual backbone tree. In most of the existing literature, the main focus is on the efficiency brought by the construction of clusters that the existing methods neglect local-balance problems in general. To fill up this gap, Directional Virtual Backbone based Data Aggregation Scheme (DVBDAS) for the WVSNs is proposed in this paper. In addition, a measurement called the energy consumption density is proposed for evaluating the adequacy of results in the cluster-based construction problems. Moreover, the directional virtual backbone construction scheme is proposed by considering the local-balanced factor. Furthermore, the associated network coding mechanism is utilized to construct DVBDAS. Finally, both the theoretical analysis of the proposed DVBDAS and the simulations are given for evaluating the performance. The experimental results prove that the proposed DVBDAS achieves higher performance in terms of both the energy preservation and the network lifetime extension than the existing methods. |
doi_str_mv | 10.1371/journal.pone.0196705 |
format | Article |
fullrecord | <record><control><sourceid>gale_plos_</sourceid><recordid>TN_cdi_plos_journals_2039224439</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><galeid>A538804335</galeid><doaj_id>oai_doaj_org_article_35dfc3dddca146bba340d003bab8bff1</doaj_id><sourcerecordid>A538804335</sourcerecordid><originalsourceid>FETCH-LOGICAL-c692t-c1703df7afd66627dc20f01e7a7a92d62cb61d416ee373e5171d3477bac654c73</originalsourceid><addsrcrecordid>eNqNk01v1DAQhiMEoqXwDxBEQkJw2MWOHXtzqVSVr5UqKlEoNyzHHme9zcaL7RT49zhsWm1QDygHW5Pnfe2Z8WTZU4zmmHD8Zu1638l2vnUdzBGuGEflvewQV6SYsQKR-3v7g-xRCGuESrJg7GF2UFScEcroYfb9rfWgonXJKr-2PvZpraW6qpNt2gTQuZZR5rJpPDRyIPOgVrCB3Diff0vyFkLIL20YpBfQhRT-BPGn81fhcfbAyDbAk3E9yr6-f_fl9OPs7PzD8vTkbKZYVcSZwhwRbbg0mjFWcK0KZBAGLrmsCs0KVTOsKWYAhBMoMceaUM7TRVlJFSdH2fOd77Z1QYylCSKlXhUFpaRKxHJHaCfXYuvtRvrfwkkr_gacb4T00aoWBCm1UURrrSSmrK4loUgjRGpZL2pjcPI6Hk_r6w1oBV30sp2YTv90diUady3KqkxlR8ng1Wjg3Y8eQhQbGxS0rezA9bt7LzhmeEBf_IPend1INTIlYDvj0rlqMBUnqekLRAkpEzW_g0qfho1VqeHGpvhE8HoiSEyEX7GRfQhiefH5_9nzyyn7co9dgWzjKri2H15XmIJ0ByrvQvBgbouMkRjG4KYaYhgDMY5Bkj3bb9Ct6Obdkz9zCwOP</addsrcrecordid><sourcetype>Open Website</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2039224439</pqid></control><display><type>article</type><title>Directional virtual backbone based data aggregation scheme for Wireless Visual Sensor Networks</title><source>DOAJ Directory of Open Access Journals</source><source>Public Library of Science (PLoS) Journals Open Access</source><source>EZB-FREE-00999 freely available EZB journals</source><source>PubMed Central</source><source>Free Full-Text Journals in Chemistry</source><creator>Zhang, Jing ; Liu, Shi-Jian ; Tsai, Pei-Wei ; Zou, Fu-Min ; Ji, Xiao-Rong</creator><contributor>Li, Lixiang</contributor><creatorcontrib>Zhang, Jing ; Liu, Shi-Jian ; Tsai, Pei-Wei ; Zou, Fu-Min ; Ji, Xiao-Rong ; Li, Lixiang</creatorcontrib><description>Data gathering is a fundamental task in Wireless Visual Sensor Networks (WVSNs). Features of directional antennas and the visual data make WVSNs more complex than the conventional Wireless Sensor Network (WSN). The virtual backbone is a technique, which is capable of constructing clusters. The version associating with the aggregation operation is also referred to as the virtual backbone tree. In most of the existing literature, the main focus is on the efficiency brought by the construction of clusters that the existing methods neglect local-balance problems in general. To fill up this gap, Directional Virtual Backbone based Data Aggregation Scheme (DVBDAS) for the WVSNs is proposed in this paper. In addition, a measurement called the energy consumption density is proposed for evaluating the adequacy of results in the cluster-based construction problems. Moreover, the directional virtual backbone construction scheme is proposed by considering the local-balanced factor. Furthermore, the associated network coding mechanism is utilized to construct DVBDAS. Finally, both the theoretical analysis of the proposed DVBDAS and the simulations are given for evaluating the performance. The experimental results prove that the proposed DVBDAS achieves higher performance in terms of both the energy preservation and the network lifetime extension than the existing methods.</description><identifier>ISSN: 1932-6203</identifier><identifier>EISSN: 1932-6203</identifier><identifier>DOI: 10.1371/journal.pone.0196705</identifier><identifier>PMID: 29763464</identifier><language>eng</language><publisher>United States: Public Library of Science</publisher><subject>Adequacy ; Agglomeration ; Algorithms ; Analysis ; Antennas ; Backbone ; Biology and Life Sciences ; Clusters ; Coding ; Computer and Information Sciences ; Construction ; Data management ; Data mining ; Data transmission ; Directional antennas ; Energy consumption ; Energy measurement ; Engineering ; Engineering and Technology ; Information management ; Information science ; Laboratories ; Management ; Physical Sciences ; Preservation ; Remote sensors ; Research and Analysis Methods ; Sensors ; Software ; Theoretical analysis ; Virtual networks ; Visual tasks ; Wireless networks ; Wireless sensor networks</subject><ispartof>PloS one, 2018-05, Vol.13 (5), p.e0196705-e0196705</ispartof><rights>COPYRIGHT 2018 Public Library of Science</rights><rights>2018 Zhang et al. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><rights>2018 Zhang et al 2018 Zhang et al</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c692t-c1703df7afd66627dc20f01e7a7a92d62cb61d416ee373e5171d3477bac654c73</citedby><cites>FETCH-LOGICAL-c692t-c1703df7afd66627dc20f01e7a7a92d62cb61d416ee373e5171d3477bac654c73</cites><orcidid>0000-0002-0677-3667</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC5953460/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC5953460/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,315,729,782,786,866,887,2104,2930,23873,27931,27932,53798,53800</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/29763464$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><contributor>Li, Lixiang</contributor><creatorcontrib>Zhang, Jing</creatorcontrib><creatorcontrib>Liu, Shi-Jian</creatorcontrib><creatorcontrib>Tsai, Pei-Wei</creatorcontrib><creatorcontrib>Zou, Fu-Min</creatorcontrib><creatorcontrib>Ji, Xiao-Rong</creatorcontrib><title>Directional virtual backbone based data aggregation scheme for Wireless Visual Sensor Networks</title><title>PloS one</title><addtitle>PLoS One</addtitle><description>Data gathering is a fundamental task in Wireless Visual Sensor Networks (WVSNs). Features of directional antennas and the visual data make WVSNs more complex than the conventional Wireless Sensor Network (WSN). The virtual backbone is a technique, which is capable of constructing clusters. The version associating with the aggregation operation is also referred to as the virtual backbone tree. In most of the existing literature, the main focus is on the efficiency brought by the construction of clusters that the existing methods neglect local-balance problems in general. To fill up this gap, Directional Virtual Backbone based Data Aggregation Scheme (DVBDAS) for the WVSNs is proposed in this paper. In addition, a measurement called the energy consumption density is proposed for evaluating the adequacy of results in the cluster-based construction problems. Moreover, the directional virtual backbone construction scheme is proposed by considering the local-balanced factor. Furthermore, the associated network coding mechanism is utilized to construct DVBDAS. Finally, both the theoretical analysis of the proposed DVBDAS and the simulations are given for evaluating the performance. The experimental results prove that the proposed DVBDAS achieves higher performance in terms of both the energy preservation and the network lifetime extension than the existing methods.</description><subject>Adequacy</subject><subject>Agglomeration</subject><subject>Algorithms</subject><subject>Analysis</subject><subject>Antennas</subject><subject>Backbone</subject><subject>Biology and Life Sciences</subject><subject>Clusters</subject><subject>Coding</subject><subject>Computer and Information Sciences</subject><subject>Construction</subject><subject>Data management</subject><subject>Data mining</subject><subject>Data transmission</subject><subject>Directional antennas</subject><subject>Energy consumption</subject><subject>Energy measurement</subject><subject>Engineering</subject><subject>Engineering and Technology</subject><subject>Information management</subject><subject>Information science</subject><subject>Laboratories</subject><subject>Management</subject><subject>Physical Sciences</subject><subject>Preservation</subject><subject>Remote sensors</subject><subject>Research and Analysis Methods</subject><subject>Sensors</subject><subject>Software</subject><subject>Theoretical analysis</subject><subject>Virtual networks</subject><subject>Visual tasks</subject><subject>Wireless networks</subject><subject>Wireless sensor networks</subject><issn>1932-6203</issn><issn>1932-6203</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2018</creationdate><recordtype>article</recordtype><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><sourceid>DOA</sourceid><recordid>eNqNk01v1DAQhiMEoqXwDxBEQkJw2MWOHXtzqVSVr5UqKlEoNyzHHme9zcaL7RT49zhsWm1QDygHW5Pnfe2Z8WTZU4zmmHD8Zu1638l2vnUdzBGuGEflvewQV6SYsQKR-3v7g-xRCGuESrJg7GF2UFScEcroYfb9rfWgonXJKr-2PvZpraW6qpNt2gTQuZZR5rJpPDRyIPOgVrCB3Diff0vyFkLIL20YpBfQhRT-BPGn81fhcfbAyDbAk3E9yr6-f_fl9OPs7PzD8vTkbKZYVcSZwhwRbbg0mjFWcK0KZBAGLrmsCs0KVTOsKWYAhBMoMceaUM7TRVlJFSdH2fOd77Z1QYylCSKlXhUFpaRKxHJHaCfXYuvtRvrfwkkr_gacb4T00aoWBCm1UURrrSSmrK4loUgjRGpZL2pjcPI6Hk_r6w1oBV30sp2YTv90diUady3KqkxlR8ng1Wjg3Y8eQhQbGxS0rezA9bt7LzhmeEBf_IPend1INTIlYDvj0rlqMBUnqekLRAkpEzW_g0qfho1VqeHGpvhE8HoiSEyEX7GRfQhiefH5_9nzyyn7co9dgWzjKri2H15XmIJ0ByrvQvBgbouMkRjG4KYaYhgDMY5Bkj3bb9Ct6Obdkz9zCwOP</recordid><startdate>20180515</startdate><enddate>20180515</enddate><creator>Zhang, Jing</creator><creator>Liu, Shi-Jian</creator><creator>Tsai, Pei-Wei</creator><creator>Zou, Fu-Min</creator><creator>Ji, Xiao-Rong</creator><general>Public Library of Science</general><general>Public Library of Science (PLoS)</general><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>IOV</scope><scope>ISR</scope><scope>3V.</scope><scope>7QG</scope><scope>7QL</scope><scope>7QO</scope><scope>7RV</scope><scope>7SN</scope><scope>7SS</scope><scope>7T5</scope><scope>7TG</scope><scope>7TM</scope><scope>7U9</scope><scope>7X2</scope><scope>7X7</scope><scope>7XB</scope><scope>88E</scope><scope>8AO</scope><scope>8C1</scope><scope>8FD</scope><scope>8FE</scope><scope>8FG</scope><scope>8FH</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABJCF</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>ARAPS</scope><scope>ATCPS</scope><scope>AZQEC</scope><scope>BBNVY</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>BHPHI</scope><scope>C1K</scope><scope>CCPQU</scope><scope>D1I</scope><scope>DWQXO</scope><scope>FR3</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>H94</scope><scope>HCIFZ</scope><scope>K9.</scope><scope>KB.</scope><scope>KB0</scope><scope>KL.</scope><scope>L6V</scope><scope>LK8</scope><scope>M0K</scope><scope>M0S</scope><scope>M1P</scope><scope>M7N</scope><scope>M7P</scope><scope>M7S</scope><scope>NAPCQ</scope><scope>P5Z</scope><scope>P62</scope><scope>P64</scope><scope>PATMY</scope><scope>PDBOC</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PTHSS</scope><scope>PYCSY</scope><scope>RC3</scope><scope>7X8</scope><scope>5PM</scope><scope>DOA</scope><orcidid>https://orcid.org/0000-0002-0677-3667</orcidid></search><sort><creationdate>20180515</creationdate><title>Directional virtual backbone based data aggregation scheme for Wireless Visual Sensor Networks</title><author>Zhang, Jing ; Liu, Shi-Jian ; Tsai, Pei-Wei ; Zou, Fu-Min ; Ji, Xiao-Rong</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c692t-c1703df7afd66627dc20f01e7a7a92d62cb61d416ee373e5171d3477bac654c73</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2018</creationdate><topic>Adequacy</topic><topic>Agglomeration</topic><topic>Algorithms</topic><topic>Analysis</topic><topic>Antennas</topic><topic>Backbone</topic><topic>Biology and Life Sciences</topic><topic>Clusters</topic><topic>Coding</topic><topic>Computer and Information Sciences</topic><topic>Construction</topic><topic>Data management</topic><topic>Data mining</topic><topic>Data transmission</topic><topic>Directional antennas</topic><topic>Energy consumption</topic><topic>Energy measurement</topic><topic>Engineering</topic><topic>Engineering and Technology</topic><topic>Information management</topic><topic>Information science</topic><topic>Laboratories</topic><topic>Management</topic><topic>Physical Sciences</topic><topic>Preservation</topic><topic>Remote sensors</topic><topic>Research and Analysis Methods</topic><topic>Sensors</topic><topic>Software</topic><topic>Theoretical analysis</topic><topic>Virtual networks</topic><topic>Visual tasks</topic><topic>Wireless networks</topic><topic>Wireless sensor networks</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Zhang, Jing</creatorcontrib><creatorcontrib>Liu, Shi-Jian</creatorcontrib><creatorcontrib>Tsai, Pei-Wei</creatorcontrib><creatorcontrib>Zou, Fu-Min</creatorcontrib><creatorcontrib>Ji, Xiao-Rong</creatorcontrib><collection>PubMed</collection><collection>CrossRef</collection><collection>Gale In Context: Opposing Viewpoints</collection><collection>Gale In Context: Science</collection><collection>ProQuest Central (Corporate)</collection><collection>Animal Behavior Abstracts</collection><collection>Bacteriology Abstracts (Microbiology B)</collection><collection>Biotechnology Research Abstracts</collection><collection>Nursing & Allied Health Database</collection><collection>Ecology Abstracts</collection><collection>Entomology Abstracts (Full archive)</collection><collection>Immunology Abstracts</collection><collection>Meteorological & Geoastrophysical Abstracts</collection><collection>Nucleic Acids Abstracts</collection><collection>Virology and AIDS Abstracts</collection><collection>Agricultural Science Collection</collection><collection>Health & Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Medical Database (Alumni Edition)</collection><collection>ProQuest Pharma Collection</collection><collection>Public Health Database</collection><collection>Technology Research Database</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>ProQuest Natural Science Collection</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>Materials Science & Engineering Collection</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>Advanced Technologies & Aerospace Collection</collection><collection>Agricultural & Environmental Science Collection</collection><collection>ProQuest Central Essentials</collection><collection>Biological Science Collection</collection><collection>ProQuest Central</collection><collection>Technology Collection</collection><collection>Natural Science Collection</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ProQuest One Community College</collection><collection>ProQuest Materials Science Collection</collection><collection>ProQuest Central Korea</collection><collection>Engineering Research Database</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Central Student</collection><collection>AIDS and Cancer Research Abstracts</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Materials Science Database</collection><collection>Nursing & Allied Health Database (Alumni Edition)</collection><collection>Meteorological & Geoastrophysical Abstracts - Academic</collection><collection>ProQuest Engineering Collection</collection><collection>ProQuest Biological Science Collection</collection><collection>Agricultural Science Database</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>Medical Database</collection><collection>Algology Mycology and Protozoology Abstracts (Microbiology C)</collection><collection>Biological Science Database</collection><collection>Engineering Database</collection><collection>Nursing & Allied Health Premium</collection><collection>Advanced Technologies & Aerospace Database</collection><collection>ProQuest Advanced Technologies & Aerospace Collection</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>Environmental Science Database</collection><collection>Materials Science Collection</collection><collection>Access via ProQuest (Open Access)</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>Engineering Collection</collection><collection>Environmental Science Collection</collection><collection>Genetics Abstracts</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><collection>DOAJ Directory of Open Access Journals</collection><jtitle>PloS one</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Zhang, Jing</au><au>Liu, Shi-Jian</au><au>Tsai, Pei-Wei</au><au>Zou, Fu-Min</au><au>Ji, Xiao-Rong</au><au>Li, Lixiang</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Directional virtual backbone based data aggregation scheme for Wireless Visual Sensor Networks</atitle><jtitle>PloS one</jtitle><addtitle>PLoS One</addtitle><date>2018-05-15</date><risdate>2018</risdate><volume>13</volume><issue>5</issue><spage>e0196705</spage><epage>e0196705</epage><pages>e0196705-e0196705</pages><issn>1932-6203</issn><eissn>1932-6203</eissn><abstract>Data gathering is a fundamental task in Wireless Visual Sensor Networks (WVSNs). Features of directional antennas and the visual data make WVSNs more complex than the conventional Wireless Sensor Network (WSN). The virtual backbone is a technique, which is capable of constructing clusters. The version associating with the aggregation operation is also referred to as the virtual backbone tree. In most of the existing literature, the main focus is on the efficiency brought by the construction of clusters that the existing methods neglect local-balance problems in general. To fill up this gap, Directional Virtual Backbone based Data Aggregation Scheme (DVBDAS) for the WVSNs is proposed in this paper. In addition, a measurement called the energy consumption density is proposed for evaluating the adequacy of results in the cluster-based construction problems. Moreover, the directional virtual backbone construction scheme is proposed by considering the local-balanced factor. Furthermore, the associated network coding mechanism is utilized to construct DVBDAS. Finally, both the theoretical analysis of the proposed DVBDAS and the simulations are given for evaluating the performance. The experimental results prove that the proposed DVBDAS achieves higher performance in terms of both the energy preservation and the network lifetime extension than the existing methods.</abstract><cop>United States</cop><pub>Public Library of Science</pub><pmid>29763464</pmid><doi>10.1371/journal.pone.0196705</doi><tpages>e0196705</tpages><orcidid>https://orcid.org/0000-0002-0677-3667</orcidid><oa>free_for_read</oa></addata></record> |
fulltext | fulltext |
identifier | ISSN: 1932-6203 |
ispartof | PloS one, 2018-05, Vol.13 (5), p.e0196705-e0196705 |
issn | 1932-6203 1932-6203 |
language | eng |
recordid | cdi_plos_journals_2039224439 |
source | DOAJ Directory of Open Access Journals; Public Library of Science (PLoS) Journals Open Access; EZB-FREE-00999 freely available EZB journals; PubMed Central; Free Full-Text Journals in Chemistry |
subjects | Adequacy Agglomeration Algorithms Analysis Antennas Backbone Biology and Life Sciences Clusters Coding Computer and Information Sciences Construction Data management Data mining Data transmission Directional antennas Energy consumption Energy measurement Engineering Engineering and Technology Information management Information science Laboratories Management Physical Sciences Preservation Remote sensors Research and Analysis Methods Sensors Software Theoretical analysis Virtual networks Visual tasks Wireless networks Wireless sensor networks |
title | Directional virtual backbone based data aggregation scheme for Wireless Visual Sensor Networks |
url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2024-12-04T11%3A44%3A37IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-gale_plos_&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Directional%20virtual%20backbone%20based%20data%20aggregation%20scheme%20for%20Wireless%20Visual%20Sensor%20Networks&rft.jtitle=PloS%20one&rft.au=Zhang,%20Jing&rft.date=2018-05-15&rft.volume=13&rft.issue=5&rft.spage=e0196705&rft.epage=e0196705&rft.pages=e0196705-e0196705&rft.issn=1932-6203&rft.eissn=1932-6203&rft_id=info:doi/10.1371/journal.pone.0196705&rft_dat=%3Cgale_plos_%3EA538804335%3C/gale_plos_%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2039224439&rft_id=info:pmid/29763464&rft_galeid=A538804335&rft_doaj_id=oai_doaj_org_article_35dfc3dddca146bba340d003bab8bff1&rfr_iscdi=true |