A Survey of Compressive Data Gathering in WSNs for IoTs
Internet of Things (IoTs) are increasingly widespread in the field of health care, smart city and smart home application, industrial and agricultural monitoring, automation, etc. With its growing scale of networks, there are a large amount of data in IoTs needing to be sensed, transmitted, and proce...
Gespeichert in:
| Veröffentlicht in: | Wireless communications and mobile computing 2022-01, Vol.2022, p.1-14 |
|---|---|
| Hauptverfasser: | , |
| Format: | Artikel |
| Sprache: | eng |
| Schlagworte: | |
| Online-Zugang: | Volltext |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| container_end_page | 14 |
|---|---|
| container_issue | |
| container_start_page | 1 |
| container_title | Wireless communications and mobile computing |
| container_volume | 2022 |
| creator | Wang, Xun Chen, Hongbin |
| description | Internet of Things (IoTs) are increasingly widespread in the field of health care, smart city and smart home application, industrial and agricultural monitoring, automation, etc. With its growing scale of networks, there are a large amount of data in IoTs needing to be sensed, transmitted, and processed. Resource-limited Wireless Sensor Networks (WSNs) as a perceptual layer of IoTs are hard to handle massive uncompressed sensing data. Compressive data gathering (CDG), which applies compressive sensing theory to data gathering, is a perfectly matching method for data compressing and gathering in WSNs. This promising method has attracted lots of researchers’ attention. In this paper, we attempt to survey substantial references about CDG in WSNs. According to their technology schemes, we classify the published references into three categories, i.e., routing protocol of CDG, clustering scheme of CDG, and CDG combined with other technologies. The merits and defects of each method are highlighted. Our work aims to provide an insight into CDG and promote improvements of this technology. |
| doi_str_mv | 10.1155/2022/4490790 |
| format | Article |
| fullrecord | <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_journals_2625916651</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2625916651</sourcerecordid><originalsourceid>FETCH-LOGICAL-c337t-b498d8284b0e178185aa275c3814b98e635d2d3c193eceb31f76017d8b5a03413</originalsourceid><addsrcrecordid>eNp90E1PAjEQgOHGaCKiN39AE4-6MtNuv44EFUmMHsB4bLq7XVkiW2wXDP9eCMSjp5nDk5nkJeQa4R5RiAEDxgZ5bkAZOCE9FBwyLZU6_dulOScXKS0AgAPDHlFDOl3Hjd_SUNNRWK6iT6nZePrgOkfHrpv72LSftGnpx_Q10TpEOgmzdEnOaveV_NVx9sn70-Ns9Jy9vI0no-FLVnKuuqzIja4003kBHpVGLZxjSpRcY14Y7SUXFat4iYb70hccayUBVaUL4YDnyPvk5nB3FcP32qfOLsI6truXlkkmDEop9uruoMoYUoq-tqvYLF3cWgS7T2P3aewxzY7fHvi8aSv30_yvfwHnbV-f</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2625916651</pqid></control><display><type>article</type><title>A Survey of Compressive Data Gathering in WSNs for IoTs</title><source>Wiley-Blackwell Open Access Titles</source><source>Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals</source><source>Alma/SFX Local Collection</source><creator>Wang, Xun ; Chen, Hongbin</creator><contributor>Fernandez-Veiga, Manuel ; Manuel Fernandez-Veiga</contributor><creatorcontrib>Wang, Xun ; Chen, Hongbin ; Fernandez-Veiga, Manuel ; Manuel Fernandez-Veiga</creatorcontrib><description>Internet of Things (IoTs) are increasingly widespread in the field of health care, smart city and smart home application, industrial and agricultural monitoring, automation, etc. With its growing scale of networks, there are a large amount of data in IoTs needing to be sensed, transmitted, and processed. Resource-limited Wireless Sensor Networks (WSNs) as a perceptual layer of IoTs are hard to handle massive uncompressed sensing data. Compressive data gathering (CDG), which applies compressive sensing theory to data gathering, is a perfectly matching method for data compressing and gathering in WSNs. This promising method has attracted lots of researchers’ attention. In this paper, we attempt to survey substantial references about CDG in WSNs. According to their technology schemes, we classify the published references into three categories, i.e., routing protocol of CDG, clustering scheme of CDG, and CDG combined with other technologies. The merits and defects of each method are highlighted. Our work aims to provide an insight into CDG and promote improvements of this technology.</description><identifier>ISSN: 1530-8669</identifier><identifier>EISSN: 1530-8677</identifier><identifier>DOI: 10.1155/2022/4490790</identifier><language>eng</language><publisher>Oxford: Hindawi</publisher><subject>Accuracy ; Algorithms ; Clustering ; Data compression ; Data transmission ; Energy consumption ; Energy efficiency ; Internet of Things ; Protocol ; Sensors ; Smart buildings ; Wavelet transforms ; Wireless networks ; Wireless sensor networks</subject><ispartof>Wireless communications and mobile computing, 2022-01, Vol.2022, p.1-14</ispartof><rights>Copyright © 2022 Xun Wang and Hongbin Chen.</rights><rights>Copyright © 2022 Xun Wang and Hongbin Chen. This work is licensed under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c337t-b498d8284b0e178185aa275c3814b98e635d2d3c193eceb31f76017d8b5a03413</citedby><cites>FETCH-LOGICAL-c337t-b498d8284b0e178185aa275c3814b98e635d2d3c193eceb31f76017d8b5a03413</cites><orcidid>0000-0003-4008-3704</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,776,780,27901,27902</link.rule.ids></links><search><contributor>Fernandez-Veiga, Manuel</contributor><contributor>Manuel Fernandez-Veiga</contributor><creatorcontrib>Wang, Xun</creatorcontrib><creatorcontrib>Chen, Hongbin</creatorcontrib><title>A Survey of Compressive Data Gathering in WSNs for IoTs</title><title>Wireless communications and mobile computing</title><description>Internet of Things (IoTs) are increasingly widespread in the field of health care, smart city and smart home application, industrial and agricultural monitoring, automation, etc. With its growing scale of networks, there are a large amount of data in IoTs needing to be sensed, transmitted, and processed. Resource-limited Wireless Sensor Networks (WSNs) as a perceptual layer of IoTs are hard to handle massive uncompressed sensing data. Compressive data gathering (CDG), which applies compressive sensing theory to data gathering, is a perfectly matching method for data compressing and gathering in WSNs. This promising method has attracted lots of researchers’ attention. In this paper, we attempt to survey substantial references about CDG in WSNs. According to their technology schemes, we classify the published references into three categories, i.e., routing protocol of CDG, clustering scheme of CDG, and CDG combined with other technologies. The merits and defects of each method are highlighted. Our work aims to provide an insight into CDG and promote improvements of this technology.</description><subject>Accuracy</subject><subject>Algorithms</subject><subject>Clustering</subject><subject>Data compression</subject><subject>Data transmission</subject><subject>Energy consumption</subject><subject>Energy efficiency</subject><subject>Internet of Things</subject><subject>Protocol</subject><subject>Sensors</subject><subject>Smart buildings</subject><subject>Wavelet transforms</subject><subject>Wireless networks</subject><subject>Wireless sensor networks</subject><issn>1530-8669</issn><issn>1530-8677</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2022</creationdate><recordtype>article</recordtype><sourceid>RHX</sourceid><sourceid>BENPR</sourceid><recordid>eNp90E1PAjEQgOHGaCKiN39AE4-6MtNuv44EFUmMHsB4bLq7XVkiW2wXDP9eCMSjp5nDk5nkJeQa4R5RiAEDxgZ5bkAZOCE9FBwyLZU6_dulOScXKS0AgAPDHlFDOl3Hjd_SUNNRWK6iT6nZePrgOkfHrpv72LSftGnpx_Q10TpEOgmzdEnOaveV_NVx9sn70-Ns9Jy9vI0no-FLVnKuuqzIja4003kBHpVGLZxjSpRcY14Y7SUXFat4iYb70hccayUBVaUL4YDnyPvk5nB3FcP32qfOLsI6truXlkkmDEop9uruoMoYUoq-tqvYLF3cWgS7T2P3aewxzY7fHvi8aSv30_yvfwHnbV-f</recordid><startdate>20220125</startdate><enddate>20220125</enddate><creator>Wang, Xun</creator><creator>Chen, Hongbin</creator><general>Hindawi</general><general>Hindawi Limited</general><scope>RHU</scope><scope>RHW</scope><scope>RHX</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7SC</scope><scope>7SP</scope><scope>7XB</scope><scope>8FD</scope><scope>8FE</scope><scope>8FG</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>ARAPS</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>GNUQQ</scope><scope>HCIFZ</scope><scope>JQ2</scope><scope>K7-</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope><scope>M0N</scope><scope>P5Z</scope><scope>P62</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>Q9U</scope><orcidid>https://orcid.org/0000-0003-4008-3704</orcidid></search><sort><creationdate>20220125</creationdate><title>A Survey of Compressive Data Gathering in WSNs for IoTs</title><author>Wang, Xun ; Chen, Hongbin</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c337t-b498d8284b0e178185aa275c3814b98e635d2d3c193eceb31f76017d8b5a03413</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2022</creationdate><topic>Accuracy</topic><topic>Algorithms</topic><topic>Clustering</topic><topic>Data compression</topic><topic>Data transmission</topic><topic>Energy consumption</topic><topic>Energy efficiency</topic><topic>Internet of Things</topic><topic>Protocol</topic><topic>Sensors</topic><topic>Smart buildings</topic><topic>Wavelet transforms</topic><topic>Wireless networks</topic><topic>Wireless sensor networks</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Wang, Xun</creatorcontrib><creatorcontrib>Chen, Hongbin</creatorcontrib><collection>Hindawi Publishing Complete</collection><collection>Hindawi Publishing Subscription Journals</collection><collection>Hindawi Publishing Open Access</collection><collection>CrossRef</collection><collection>Computer and Information Systems Abstracts</collection><collection>Electronics & Communications Abstracts</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Technology Research Database</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>Advanced Technologies & Aerospace Collection</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>Technology Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>ProQuest Central Student</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Computer Science Collection</collection><collection>Computer Science Database</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><collection>Computing Database</collection><collection>Advanced Technologies & Aerospace Database</collection><collection>ProQuest Advanced Technologies & Aerospace Collection</collection><collection>Publicly Available Content Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>ProQuest Central Basic</collection><jtitle>Wireless communications and mobile computing</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Wang, Xun</au><au>Chen, Hongbin</au><au>Fernandez-Veiga, Manuel</au><au>Manuel Fernandez-Veiga</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>A Survey of Compressive Data Gathering in WSNs for IoTs</atitle><jtitle>Wireless communications and mobile computing</jtitle><date>2022-01-25</date><risdate>2022</risdate><volume>2022</volume><spage>1</spage><epage>14</epage><pages>1-14</pages><issn>1530-8669</issn><eissn>1530-8677</eissn><abstract>Internet of Things (IoTs) are increasingly widespread in the field of health care, smart city and smart home application, industrial and agricultural monitoring, automation, etc. With its growing scale of networks, there are a large amount of data in IoTs needing to be sensed, transmitted, and processed. Resource-limited Wireless Sensor Networks (WSNs) as a perceptual layer of IoTs are hard to handle massive uncompressed sensing data. Compressive data gathering (CDG), which applies compressive sensing theory to data gathering, is a perfectly matching method for data compressing and gathering in WSNs. This promising method has attracted lots of researchers’ attention. In this paper, we attempt to survey substantial references about CDG in WSNs. According to their technology schemes, we classify the published references into three categories, i.e., routing protocol of CDG, clustering scheme of CDG, and CDG combined with other technologies. The merits and defects of each method are highlighted. Our work aims to provide an insight into CDG and promote improvements of this technology.</abstract><cop>Oxford</cop><pub>Hindawi</pub><doi>10.1155/2022/4490790</doi><tpages>14</tpages><orcidid>https://orcid.org/0000-0003-4008-3704</orcidid><oa>free_for_read</oa></addata></record> |
| fulltext | fulltext |
| identifier | ISSN: 1530-8669 |
| ispartof | Wireless communications and mobile computing, 2022-01, Vol.2022, p.1-14 |
| issn | 1530-8669 1530-8677 |
| language | eng |
| recordid | cdi_proquest_journals_2625916651 |
| source | Wiley-Blackwell Open Access Titles; Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals; Alma/SFX Local Collection |
| subjects | Accuracy Algorithms Clustering Data compression Data transmission Energy consumption Energy efficiency Internet of Things Protocol Sensors Smart buildings Wavelet transforms Wireless networks Wireless sensor networks |
| title | A Survey of Compressive Data Gathering in WSNs for IoTs |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-02-01T18%3A33%3A02IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=A%20Survey%20of%20Compressive%20Data%20Gathering%20in%20WSNs%20for%20IoTs&rft.jtitle=Wireless%20communications%20and%20mobile%20computing&rft.au=Wang,%20Xun&rft.date=2022-01-25&rft.volume=2022&rft.spage=1&rft.epage=14&rft.pages=1-14&rft.issn=1530-8669&rft.eissn=1530-8677&rft_id=info:doi/10.1155/2022/4490790&rft_dat=%3Cproquest_cross%3E2625916651%3C/proquest_cross%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2625916651&rft_id=info:pmid/&rfr_iscdi=true |