Optimization of AES-128 Encryption Algorithm for Security Layer in ZigBee Networking of Internet of Things
With the rapid development of network and communication technology, the interaction of various information data is more and more frequent, and people pay more and more attention to information security. The information encryption algorithm is a research hotspot in the field of information security....
Gespeichert in:
Veröffentlicht in: | Computational intelligence and neuroscience 2022-04, Vol.2022, p.8424100-11 |
---|---|
Hauptverfasser: | , , , , |
Format: | Artikel |
Sprache: | eng |
Schlagworte: | |
Online-Zugang: | Volltext |
Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
container_end_page | 11 |
---|---|
container_issue | |
container_start_page | 8424100 |
container_title | Computational intelligence and neuroscience |
container_volume | 2022 |
creator | Luo, Zhonghua Shen, Keyong Hu, Rongqun Yang, Yuhan Deng, Rongchun |
description | With the rapid development of network and communication technology, the interaction of various information data is more and more frequent, and people pay more and more attention to information security. The information encryption algorithm is a research hotspot in the field of information security. The Advanced Encryption Standard (AES) algorithm has been widely used in the field of information security with its high security and encryption efficiency. This paper mainly introduces the optimization of the AES-128 encryption algorithm of the security layer in ZigBee networking of the Internet of Things. By analyzing the principles of ZigBee networking and the AES encryption algorithm, the changes are optimized. In this paper, the new S-box cryptographic properties are used after analysis and calculation. The affine transformation period, the number of iteration cycles, and the algebraic expression of the S-box are improved. Its cryptographic properties are better than the S-box of the original algorithm, and the security of the algorithm is improved. In the theory of column hybrid algorithm, the computational complexity is reduced by changing the fixed polynomial, and the efficiency of the column hybrid algorithm is improved. In this paper, the performance of the improved AES algorithm is tested. The results show that, in the power consumption curve experiment, the recovery success rate of the original algorithm is about 42%, and the recovery success rate of the improved algorithm is nearly 60%. The improved algorithm is faster than the original algorithm in achieving a recovery success rate of 100%. Experimental results show that the design can accurately complete the encryption and decryption of the AES algorithm, and the performance is better than the original algorithm, which proves the overall superiority of the algorithm. |
doi_str_mv | 10.1155/2022/8424100 |
format | Article |
fullrecord | <record><control><sourceid>gale_pubme</sourceid><recordid>TN_cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_9042606</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><galeid>A702230084</galeid><sourcerecordid>A702230084</sourcerecordid><originalsourceid>FETCH-LOGICAL-c476t-55582d7449362af47321ac88f26ea4b72456d00915b4eddd8f91ae3a212a6a983</originalsourceid><addsrcrecordid>eNp9kc1v0zAYhy0EYmNw44wscUFiYf6Oc0EqU_chVeywceFiuYmTuiR2ZztM5a_HWUs1OHCy_frRY7_vD4C3GH3CmPMzggg5k4wwjNAzcIyFLAtOSvr8sBf8CLyKcY0QLzkiL8ER5aySWIhjsL7ZJDvYXzpZ76Bv4Wx-W2Ai4dzVYbt5rM76zgebVgNsfYC3ph7zaQsXemsCtA5-t90XY-BXkx58-GFdN3muXTLBmTTt71a5GF-DF63uo3mzX0_At4v53flVsbi5vD6fLYqalSIVnHNJmpKxigqiW1ZSgnUtZUuE0WxZEsZFg1CF-ZKZpmlkW2FtqCaYaKErSU_A5513My4H09TGpaB7tQl20GGrvLbq7xtnV6rzP1WFGBFIZMGHvSD4-9HEpAYba9P32hk_RpUHKgXjvKIZff8PuvZjcLm9RwohRtETqtO9Uda1Pr9bT1I1K3N8FCHJMnW6o-rgYwymPXwZIzVFraao1T7qjL972uYB_pNtBj7ugDz9Rj_Y_-t-Aw0Lrrg</addsrcrecordid><sourcetype>Open Access Repository</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2658004303</pqid></control><display><type>article</type><title>Optimization of AES-128 Encryption Algorithm for Security Layer in ZigBee Networking of Internet of Things</title><source>Wiley-Blackwell Open Access Titles</source><source>Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals</source><source>PubMed Central</source><source>Alma/SFX Local Collection</source><source>PubMed Central Open Access</source><creator>Luo, Zhonghua ; Shen, Keyong ; Hu, Rongqun ; Yang, Yuhan ; Deng, Rongchun</creator><contributor>Chaudhary, Gopal ; Gopal Chaudhary</contributor><creatorcontrib>Luo, Zhonghua ; Shen, Keyong ; Hu, Rongqun ; Yang, Yuhan ; Deng, Rongchun ; Chaudhary, Gopal ; Gopal Chaudhary</creatorcontrib><description>With the rapid development of network and communication technology, the interaction of various information data is more and more frequent, and people pay more and more attention to information security. The information encryption algorithm is a research hotspot in the field of information security. The Advanced Encryption Standard (AES) algorithm has been widely used in the field of information security with its high security and encryption efficiency. This paper mainly introduces the optimization of the AES-128 encryption algorithm of the security layer in ZigBee networking of the Internet of Things. By analyzing the principles of ZigBee networking and the AES encryption algorithm, the changes are optimized. In this paper, the new S-box cryptographic properties are used after analysis and calculation. The affine transformation period, the number of iteration cycles, and the algebraic expression of the S-box are improved. Its cryptographic properties are better than the S-box of the original algorithm, and the security of the algorithm is improved. In the theory of column hybrid algorithm, the computational complexity is reduced by changing the fixed polynomial, and the efficiency of the column hybrid algorithm is improved. In this paper, the performance of the improved AES algorithm is tested. The results show that, in the power consumption curve experiment, the recovery success rate of the original algorithm is about 42%, and the recovery success rate of the improved algorithm is nearly 60%. The improved algorithm is faster than the original algorithm in achieving a recovery success rate of 100%. Experimental results show that the design can accurately complete the encryption and decryption of the AES algorithm, and the performance is better than the original algorithm, which proves the overall superiority of the algorithm.</description><identifier>ISSN: 1687-5265</identifier><identifier>EISSN: 1687-5273</identifier><identifier>DOI: 10.1155/2022/8424100</identifier><identifier>PMID: 35498166</identifier><language>eng</language><publisher>United States: Hindawi</publisher><subject>Affine transformations ; Algorithms ; Computer applications ; Critical path ; Cryptography ; Data encryption ; Efficiency ; Encryption ; Information technology ; Internet ; Internet of Things ; Iterative methods ; Monitoring systems ; Network security ; Network topologies ; Optimization ; Polynomials ; Power consumption ; Protocol ; Recovery ; Safety and security measures ; Security ; Software ; Wireless communications ; Wireless networks</subject><ispartof>Computational intelligence and neuroscience, 2022-04, Vol.2022, p.8424100-11</ispartof><rights>Copyright © 2022 Zhonghua Luo et al.</rights><rights>COPYRIGHT 2022 John Wiley & Sons, Inc.</rights><rights>Copyright © 2022 Zhonghua Luo et al. This is an open access article distributed under the Creative Commons Attribution License (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. https://creativecommons.org/licenses/by/4.0</rights><rights>Copyright © 2022 Zhonghua Luo et al. 2022</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c476t-55582d7449362af47321ac88f26ea4b72456d00915b4eddd8f91ae3a212a6a983</citedby><cites>FETCH-LOGICAL-c476t-55582d7449362af47321ac88f26ea4b72456d00915b4eddd8f91ae3a212a6a983</cites><orcidid>0000-0002-5355-2613</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/PMC9042606/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC9042606/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,723,776,780,881,27901,27902,53766,53768</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/35498166$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><contributor>Chaudhary, Gopal</contributor><contributor>Gopal Chaudhary</contributor><creatorcontrib>Luo, Zhonghua</creatorcontrib><creatorcontrib>Shen, Keyong</creatorcontrib><creatorcontrib>Hu, Rongqun</creatorcontrib><creatorcontrib>Yang, Yuhan</creatorcontrib><creatorcontrib>Deng, Rongchun</creatorcontrib><title>Optimization of AES-128 Encryption Algorithm for Security Layer in ZigBee Networking of Internet of Things</title><title>Computational intelligence and neuroscience</title><addtitle>Comput Intell Neurosci</addtitle><description>With the rapid development of network and communication technology, the interaction of various information data is more and more frequent, and people pay more and more attention to information security. The information encryption algorithm is a research hotspot in the field of information security. The Advanced Encryption Standard (AES) algorithm has been widely used in the field of information security with its high security and encryption efficiency. This paper mainly introduces the optimization of the AES-128 encryption algorithm of the security layer in ZigBee networking of the Internet of Things. By analyzing the principles of ZigBee networking and the AES encryption algorithm, the changes are optimized. In this paper, the new S-box cryptographic properties are used after analysis and calculation. The affine transformation period, the number of iteration cycles, and the algebraic expression of the S-box are improved. Its cryptographic properties are better than the S-box of the original algorithm, and the security of the algorithm is improved. In the theory of column hybrid algorithm, the computational complexity is reduced by changing the fixed polynomial, and the efficiency of the column hybrid algorithm is improved. In this paper, the performance of the improved AES algorithm is tested. The results show that, in the power consumption curve experiment, the recovery success rate of the original algorithm is about 42%, and the recovery success rate of the improved algorithm is nearly 60%. The improved algorithm is faster than the original algorithm in achieving a recovery success rate of 100%. Experimental results show that the design can accurately complete the encryption and decryption of the AES algorithm, and the performance is better than the original algorithm, which proves the overall superiority of the algorithm.</description><subject>Affine transformations</subject><subject>Algorithms</subject><subject>Computer applications</subject><subject>Critical path</subject><subject>Cryptography</subject><subject>Data encryption</subject><subject>Efficiency</subject><subject>Encryption</subject><subject>Information technology</subject><subject>Internet</subject><subject>Internet of Things</subject><subject>Iterative methods</subject><subject>Monitoring systems</subject><subject>Network security</subject><subject>Network topologies</subject><subject>Optimization</subject><subject>Polynomials</subject><subject>Power consumption</subject><subject>Protocol</subject><subject>Recovery</subject><subject>Safety and security measures</subject><subject>Security</subject><subject>Software</subject><subject>Wireless communications</subject><subject>Wireless networks</subject><issn>1687-5265</issn><issn>1687-5273</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2022</creationdate><recordtype>article</recordtype><sourceid>RHX</sourceid><sourceid>BENPR</sourceid><recordid>eNp9kc1v0zAYhy0EYmNw44wscUFiYf6Oc0EqU_chVeywceFiuYmTuiR2ZztM5a_HWUs1OHCy_frRY7_vD4C3GH3CmPMzggg5k4wwjNAzcIyFLAtOSvr8sBf8CLyKcY0QLzkiL8ER5aySWIhjsL7ZJDvYXzpZ76Bv4Wx-W2Ai4dzVYbt5rM76zgebVgNsfYC3ph7zaQsXemsCtA5-t90XY-BXkx58-GFdN3muXTLBmTTt71a5GF-DF63uo3mzX0_At4v53flVsbi5vD6fLYqalSIVnHNJmpKxigqiW1ZSgnUtZUuE0WxZEsZFg1CF-ZKZpmlkW2FtqCaYaKErSU_A5513My4H09TGpaB7tQl20GGrvLbq7xtnV6rzP1WFGBFIZMGHvSD4-9HEpAYba9P32hk_RpUHKgXjvKIZff8PuvZjcLm9RwohRtETqtO9Uda1Pr9bT1I1K3N8FCHJMnW6o-rgYwymPXwZIzVFraao1T7qjL972uYB_pNtBj7ugDz9Rj_Y_-t-Aw0Lrrg</recordid><startdate>20220419</startdate><enddate>20220419</enddate><creator>Luo, Zhonghua</creator><creator>Shen, Keyong</creator><creator>Hu, Rongqun</creator><creator>Yang, Yuhan</creator><creator>Deng, Rongchun</creator><general>Hindawi</general><general>John Wiley & Sons, Inc</general><general>Hindawi Limited</general><scope>RHU</scope><scope>RHW</scope><scope>RHX</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7QF</scope><scope>7QQ</scope><scope>7SC</scope><scope>7SE</scope><scope>7SP</scope><scope>7SR</scope><scope>7TA</scope><scope>7TB</scope><scope>7TK</scope><scope>7U5</scope><scope>7X7</scope><scope>7XB</scope><scope>8AL</scope><scope>8BQ</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>AZQEC</scope><scope>BBNVY</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>BHPHI</scope><scope>CCPQU</scope><scope>CWDGH</scope><scope>DWQXO</scope><scope>F28</scope><scope>FR3</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>H8D</scope><scope>H8G</scope><scope>HCIFZ</scope><scope>JG9</scope><scope>JQ2</scope><scope>K7-</scope><scope>K9.</scope><scope>KR7</scope><scope>L6V</scope><scope>L7M</scope><scope>LK8</scope><scope>L~C</scope><scope>L~D</scope><scope>M0N</scope><scope>M0S</scope><scope>M1P</scope><scope>M7P</scope><scope>M7S</scope><scope>P5Z</scope><scope>P62</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>PSYQQ</scope><scope>PTHSS</scope><scope>Q9U</scope><scope>7X8</scope><scope>5PM</scope><orcidid>https://orcid.org/0000-0002-5355-2613</orcidid></search><sort><creationdate>20220419</creationdate><title>Optimization of AES-128 Encryption Algorithm for Security Layer in ZigBee Networking of Internet of Things</title><author>Luo, Zhonghua ; Shen, Keyong ; Hu, Rongqun ; Yang, Yuhan ; Deng, Rongchun</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c476t-55582d7449362af47321ac88f26ea4b72456d00915b4eddd8f91ae3a212a6a983</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2022</creationdate><topic>Affine transformations</topic><topic>Algorithms</topic><topic>Computer applications</topic><topic>Critical path</topic><topic>Cryptography</topic><topic>Data encryption</topic><topic>Efficiency</topic><topic>Encryption</topic><topic>Information technology</topic><topic>Internet</topic><topic>Internet of Things</topic><topic>Iterative methods</topic><topic>Monitoring systems</topic><topic>Network security</topic><topic>Network topologies</topic><topic>Optimization</topic><topic>Polynomials</topic><topic>Power consumption</topic><topic>Protocol</topic><topic>Recovery</topic><topic>Safety and security measures</topic><topic>Security</topic><topic>Software</topic><topic>Wireless communications</topic><topic>Wireless networks</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Luo, Zhonghua</creatorcontrib><creatorcontrib>Shen, Keyong</creatorcontrib><creatorcontrib>Hu, Rongqun</creatorcontrib><creatorcontrib>Yang, Yuhan</creatorcontrib><creatorcontrib>Deng, Rongchun</creatorcontrib><collection>Hindawi Publishing Complete</collection><collection>Hindawi Publishing Subscription Journals</collection><collection>Hindawi Publishing Open Access</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Aluminium Industry Abstracts</collection><collection>Ceramic Abstracts</collection><collection>Computer and Information Systems Abstracts</collection><collection>Corrosion Abstracts</collection><collection>Electronics & Communications Abstracts</collection><collection>Engineered Materials Abstracts</collection><collection>Materials Business File</collection><collection>Mechanical & Transportation Engineering Abstracts</collection><collection>Neurosciences Abstracts</collection><collection>Solid State and Superconductivity Abstracts</collection><collection>Health & Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Computing Database (Alumni Edition)</collection><collection>METADEX</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>ProQuest Central Essentials</collection><collection>Biological Science Collection</collection><collection>ProQuest Central</collection><collection>Technology Collection</collection><collection>Natural Science Collection</collection><collection>ProQuest One Community College</collection><collection>Middle East & Africa Database</collection><collection>ProQuest Central Korea</collection><collection>ANTE: Abstracts in New Technology & Engineering</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>Aerospace Database</collection><collection>Copper Technical Reference Library</collection><collection>SciTech Premium Collection</collection><collection>Materials Research Database</collection><collection>ProQuest Computer Science Collection</collection><collection>Computer Science Database</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Civil Engineering Abstracts</collection><collection>ProQuest Engineering Collection</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>ProQuest Biological Science Collection</collection><collection>Computer and Information Systems Abstracts Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><collection>Computing Database</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>Medical Database</collection><collection>Biological Science Database</collection><collection>Engineering 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 One Psychology</collection><collection>Engineering Collection</collection><collection>ProQuest Central Basic</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>Computational intelligence and neuroscience</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Luo, Zhonghua</au><au>Shen, Keyong</au><au>Hu, Rongqun</au><au>Yang, Yuhan</au><au>Deng, Rongchun</au><au>Chaudhary, Gopal</au><au>Gopal Chaudhary</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Optimization of AES-128 Encryption Algorithm for Security Layer in ZigBee Networking of Internet of Things</atitle><jtitle>Computational intelligence and neuroscience</jtitle><addtitle>Comput Intell Neurosci</addtitle><date>2022-04-19</date><risdate>2022</risdate><volume>2022</volume><spage>8424100</spage><epage>11</epage><pages>8424100-11</pages><issn>1687-5265</issn><eissn>1687-5273</eissn><abstract>With the rapid development of network and communication technology, the interaction of various information data is more and more frequent, and people pay more and more attention to information security. The information encryption algorithm is a research hotspot in the field of information security. The Advanced Encryption Standard (AES) algorithm has been widely used in the field of information security with its high security and encryption efficiency. This paper mainly introduces the optimization of the AES-128 encryption algorithm of the security layer in ZigBee networking of the Internet of Things. By analyzing the principles of ZigBee networking and the AES encryption algorithm, the changes are optimized. In this paper, the new S-box cryptographic properties are used after analysis and calculation. The affine transformation period, the number of iteration cycles, and the algebraic expression of the S-box are improved. Its cryptographic properties are better than the S-box of the original algorithm, and the security of the algorithm is improved. In the theory of column hybrid algorithm, the computational complexity is reduced by changing the fixed polynomial, and the efficiency of the column hybrid algorithm is improved. In this paper, the performance of the improved AES algorithm is tested. The results show that, in the power consumption curve experiment, the recovery success rate of the original algorithm is about 42%, and the recovery success rate of the improved algorithm is nearly 60%. The improved algorithm is faster than the original algorithm in achieving a recovery success rate of 100%. Experimental results show that the design can accurately complete the encryption and decryption of the AES algorithm, and the performance is better than the original algorithm, which proves the overall superiority of the algorithm.</abstract><cop>United States</cop><pub>Hindawi</pub><pmid>35498166</pmid><doi>10.1155/2022/8424100</doi><tpages>11</tpages><orcidid>https://orcid.org/0000-0002-5355-2613</orcidid><oa>free_for_read</oa></addata></record> |
fulltext | fulltext |
identifier | ISSN: 1687-5265 |
ispartof | Computational intelligence and neuroscience, 2022-04, Vol.2022, p.8424100-11 |
issn | 1687-5265 1687-5273 |
language | eng |
recordid | cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_9042606 |
source | Wiley-Blackwell Open Access Titles; Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals; PubMed Central; Alma/SFX Local Collection; PubMed Central Open Access |
subjects | Affine transformations Algorithms Computer applications Critical path Cryptography Data encryption Efficiency Encryption Information technology Internet Internet of Things Iterative methods Monitoring systems Network security Network topologies Optimization Polynomials Power consumption Protocol Recovery Safety and security measures Security Software Wireless communications Wireless networks |
title | Optimization of AES-128 Encryption Algorithm for Security Layer in ZigBee Networking of Internet of Things |
url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-30T19%3A16%3A47IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-gale_pubme&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Optimization%20of%20AES-128%20Encryption%20Algorithm%20for%20Security%20Layer%20in%20ZigBee%20Networking%20of%20Internet%20of%20Things&rft.jtitle=Computational%20intelligence%20and%20neuroscience&rft.au=Luo,%20Zhonghua&rft.date=2022-04-19&rft.volume=2022&rft.spage=8424100&rft.epage=11&rft.pages=8424100-11&rft.issn=1687-5265&rft.eissn=1687-5273&rft_id=info:doi/10.1155/2022/8424100&rft_dat=%3Cgale_pubme%3EA702230084%3C/gale_pubme%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2658004303&rft_id=info:pmid/35498166&rft_galeid=A702230084&rfr_iscdi=true |