Edge Intelligence Empowered Metaverse: Architecture, Technologies, and Open Issues
Recently, the metaverse has emerged as a focal point of widespread interest, capturing attention across various domains. However, the construction of a pluralistic, realistic, and shared digital world is still in its infancy. Due to the ultra-strict requirements in security, intelligence, and real-t...
Gespeichert in:
Veröffentlicht in: | IEEE network 2023-11, Vol.37 (6), p.1-1 |
---|---|
Hauptverfasser: | , , , , |
Format: | Artikel |
Sprache: | eng |
Schlagworte: | |
Online-Zugang: | Volltext bestellen |
Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
container_end_page | 1 |
---|---|
container_issue | 6 |
container_start_page | 1 |
container_title | IEEE network |
container_volume | 37 |
creator | Xu, Yanan Feng, Daquan Zhao, Mingxiong Sun, Yao Xia, Xiang-Gen |
description | Recently, the metaverse has emerged as a focal point of widespread interest, capturing attention across various domains. However, the construction of a pluralistic, realistic, and shared digital world is still in its infancy. Due to the ultra-strict requirements in security, intelligence, and real-time, it is urgent to solve the technical challenges existed in building metaverse ecosystems, such as ensuring the provision of seamless communication and reliable computing services in the face of a dynamic and time-varying complex network environment. In terms of digital infrastructure, edge computing (EC), as a distributed computing paradigm, has the potential to guarantee computing power, bandwidth, and storage. Meanwhile, artificial intelligence (AI) is regarded as a powerful tool to provide technical support for automated and efficient decision-making for metaverse devices. In this context, this paper focuses on integrating EC and AI to facilitate the development of the metaverse, namely, the edge intelligence-empowered metaverse. Specifically, we first outline the metaverse architecture and driving technologies and discuss EC as a key component of the digital infrastructure for metaverse realization. Then, we elaborate on two mainstream classifications of edge intelligence in metaverse scenarios, including AI for edge and AI on edge. Finally, we identify some open issues. |
doi_str_mv | 10.1109/MNET.2023.3317477 |
format | Article |
fullrecord | <record><control><sourceid>proquest_RIE</sourceid><recordid>TN_cdi_crossref_primary_10_1109_MNET_2023_3317477</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><ieee_id>10273380</ieee_id><sourcerecordid>3015029677</sourcerecordid><originalsourceid>FETCH-LOGICAL-c246t-34dfddd3d862da12cdd223fca27afef05ea9ba7fd24a8adbab86accccc339aca3</originalsourceid><addsrcrecordid>eNpNkE1Lw0AURQdRsFZ_gOBiwG1T5yPJJO5KiVpoLUgFd8PrzEubkiZxJrX4701oF77N25x7LxxC7jkbc87Sp8V7thoLJuRYSq5CpS7IgEdREvAo_rokA5akLEhYGF6TG-93jPEwkmJAPjK7QTqrWizLYoOVQZrtm_qIDi1dYAs_6Dw-04kz26JF0x4cjugKzbaqy3pToB9RqCxdNljRmfcH9LfkKofS4935D8nnS7aavgXz5etsOpkHRoRxG8jQ5tZaaZNYWODCWCuEzA0IBTnmLEJI16ByK0JIwK5hncRg-pMyBQNySB5PvY2rv7vdVu_qg6u6SS0Zj5hIY6U6ip8o42rvHea6ccUe3K_mTPfqdK9O9-r0WV2XeThlCkT8xwslZcLkH-9RbMs</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>3015029677</pqid></control><display><type>article</type><title>Edge Intelligence Empowered Metaverse: Architecture, Technologies, and Open Issues</title><source>IEEE Electronic Library (IEL)</source><creator>Xu, Yanan ; Feng, Daquan ; Zhao, Mingxiong ; Sun, Yao ; Xia, Xiang-Gen</creator><creatorcontrib>Xu, Yanan ; Feng, Daquan ; Zhao, Mingxiong ; Sun, Yao ; Xia, Xiang-Gen</creatorcontrib><description>Recently, the metaverse has emerged as a focal point of widespread interest, capturing attention across various domains. However, the construction of a pluralistic, realistic, and shared digital world is still in its infancy. Due to the ultra-strict requirements in security, intelligence, and real-time, it is urgent to solve the technical challenges existed in building metaverse ecosystems, such as ensuring the provision of seamless communication and reliable computing services in the face of a dynamic and time-varying complex network environment. In terms of digital infrastructure, edge computing (EC), as a distributed computing paradigm, has the potential to guarantee computing power, bandwidth, and storage. Meanwhile, artificial intelligence (AI) is regarded as a powerful tool to provide technical support for automated and efficient decision-making for metaverse devices. In this context, this paper focuses on integrating EC and AI to facilitate the development of the metaverse, namely, the edge intelligence-empowered metaverse. Specifically, we first outline the metaverse architecture and driving technologies and discuss EC as a key component of the digital infrastructure for metaverse realization. Then, we elaborate on two mainstream classifications of edge intelligence in metaverse scenarios, including AI for edge and AI on edge. Finally, we identify some open issues.</description><identifier>ISSN: 0890-8044</identifier><identifier>EISSN: 1558-156X</identifier><identifier>DOI: 10.1109/MNET.2023.3317477</identifier><identifier>CODEN: IENEET</identifier><language>eng</language><publisher>New York: IEEE</publisher><subject>Artificial intelligence ; Cloud computing ; Computer architecture ; Computer networks ; Distributed processing ; Edge computing ; Infrastructure ; Internet of Things ; Metaverse ; Production ; Rendering (computer graphics)</subject><ispartof>IEEE network, 2023-11, Vol.37 (6), p.1-1</ispartof><rights>Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2023</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-c246t-34dfddd3d862da12cdd223fca27afef05ea9ba7fd24a8adbab86accccc339aca3</cites><orcidid>0000-0001-9499-5456 ; 0000-0002-5599-7683 ; 0000-0002-0667-1150 ; 0000-0002-5767-5020 ; 0000-0002-4391-377X</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/10273380$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>314,776,780,792,27903,27904,54737</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/10273380$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Xu, Yanan</creatorcontrib><creatorcontrib>Feng, Daquan</creatorcontrib><creatorcontrib>Zhao, Mingxiong</creatorcontrib><creatorcontrib>Sun, Yao</creatorcontrib><creatorcontrib>Xia, Xiang-Gen</creatorcontrib><title>Edge Intelligence Empowered Metaverse: Architecture, Technologies, and Open Issues</title><title>IEEE network</title><addtitle>NET-M</addtitle><description>Recently, the metaverse has emerged as a focal point of widespread interest, capturing attention across various domains. However, the construction of a pluralistic, realistic, and shared digital world is still in its infancy. Due to the ultra-strict requirements in security, intelligence, and real-time, it is urgent to solve the technical challenges existed in building metaverse ecosystems, such as ensuring the provision of seamless communication and reliable computing services in the face of a dynamic and time-varying complex network environment. In terms of digital infrastructure, edge computing (EC), as a distributed computing paradigm, has the potential to guarantee computing power, bandwidth, and storage. Meanwhile, artificial intelligence (AI) is regarded as a powerful tool to provide technical support for automated and efficient decision-making for metaverse devices. In this context, this paper focuses on integrating EC and AI to facilitate the development of the metaverse, namely, the edge intelligence-empowered metaverse. Specifically, we first outline the metaverse architecture and driving technologies and discuss EC as a key component of the digital infrastructure for metaverse realization. Then, we elaborate on two mainstream classifications of edge intelligence in metaverse scenarios, including AI for edge and AI on edge. Finally, we identify some open issues.</description><subject>Artificial intelligence</subject><subject>Cloud computing</subject><subject>Computer architecture</subject><subject>Computer networks</subject><subject>Distributed processing</subject><subject>Edge computing</subject><subject>Infrastructure</subject><subject>Internet of Things</subject><subject>Metaverse</subject><subject>Production</subject><subject>Rendering (computer graphics)</subject><issn>0890-8044</issn><issn>1558-156X</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2023</creationdate><recordtype>article</recordtype><sourceid>RIE</sourceid><recordid>eNpNkE1Lw0AURQdRsFZ_gOBiwG1T5yPJJO5KiVpoLUgFd8PrzEubkiZxJrX4701oF77N25x7LxxC7jkbc87Sp8V7thoLJuRYSq5CpS7IgEdREvAo_rokA5akLEhYGF6TG-93jPEwkmJAPjK7QTqrWizLYoOVQZrtm_qIDi1dYAs_6Dw-04kz26JF0x4cjugKzbaqy3pToB9RqCxdNljRmfcH9LfkKofS4935D8nnS7aavgXz5etsOpkHRoRxG8jQ5tZaaZNYWODCWCuEzA0IBTnmLEJI16ByK0JIwK5hncRg-pMyBQNySB5PvY2rv7vdVu_qg6u6SS0Zj5hIY6U6ip8o42rvHea6ccUe3K_mTPfqdK9O9-r0WV2XeThlCkT8xwslZcLkH-9RbMs</recordid><startdate>20231101</startdate><enddate>20231101</enddate><creator>Xu, Yanan</creator><creator>Feng, Daquan</creator><creator>Zhao, Mingxiong</creator><creator>Sun, Yao</creator><creator>Xia, Xiang-Gen</creator><general>IEEE</general><general>The Institute of Electrical and Electronics Engineers, Inc. (IEEE)</general><scope>97E</scope><scope>RIA</scope><scope>RIE</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7SC</scope><scope>7SP</scope><scope>8FD</scope><scope>JQ2</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope><orcidid>https://orcid.org/0000-0001-9499-5456</orcidid><orcidid>https://orcid.org/0000-0002-5599-7683</orcidid><orcidid>https://orcid.org/0000-0002-0667-1150</orcidid><orcidid>https://orcid.org/0000-0002-5767-5020</orcidid><orcidid>https://orcid.org/0000-0002-4391-377X</orcidid></search><sort><creationdate>20231101</creationdate><title>Edge Intelligence Empowered Metaverse: Architecture, Technologies, and Open Issues</title><author>Xu, Yanan ; Feng, Daquan ; Zhao, Mingxiong ; Sun, Yao ; Xia, Xiang-Gen</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c246t-34dfddd3d862da12cdd223fca27afef05ea9ba7fd24a8adbab86accccc339aca3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2023</creationdate><topic>Artificial intelligence</topic><topic>Cloud computing</topic><topic>Computer architecture</topic><topic>Computer networks</topic><topic>Distributed processing</topic><topic>Edge computing</topic><topic>Infrastructure</topic><topic>Internet of Things</topic><topic>Metaverse</topic><topic>Production</topic><topic>Rendering (computer graphics)</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Xu, Yanan</creatorcontrib><creatorcontrib>Feng, Daquan</creatorcontrib><creatorcontrib>Zhao, Mingxiong</creatorcontrib><creatorcontrib>Sun, Yao</creatorcontrib><creatorcontrib>Xia, Xiang-Gen</creatorcontrib><collection>IEEE All-Society Periodicals Package (ASPP) 2005-present</collection><collection>IEEE All-Society Periodicals Package (ASPP) 1998-Present</collection><collection>IEEE Electronic Library (IEL)</collection><collection>CrossRef</collection><collection>Computer and Information Systems Abstracts</collection><collection>Electronics & Communications Abstracts</collection><collection>Technology Research Database</collection><collection>ProQuest Computer Science Collection</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><jtitle>IEEE network</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Xu, Yanan</au><au>Feng, Daquan</au><au>Zhao, Mingxiong</au><au>Sun, Yao</au><au>Xia, Xiang-Gen</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Edge Intelligence Empowered Metaverse: Architecture, Technologies, and Open Issues</atitle><jtitle>IEEE network</jtitle><stitle>NET-M</stitle><date>2023-11-01</date><risdate>2023</risdate><volume>37</volume><issue>6</issue><spage>1</spage><epage>1</epage><pages>1-1</pages><issn>0890-8044</issn><eissn>1558-156X</eissn><coden>IENEET</coden><abstract>Recently, the metaverse has emerged as a focal point of widespread interest, capturing attention across various domains. However, the construction of a pluralistic, realistic, and shared digital world is still in its infancy. Due to the ultra-strict requirements in security, intelligence, and real-time, it is urgent to solve the technical challenges existed in building metaverse ecosystems, such as ensuring the provision of seamless communication and reliable computing services in the face of a dynamic and time-varying complex network environment. In terms of digital infrastructure, edge computing (EC), as a distributed computing paradigm, has the potential to guarantee computing power, bandwidth, and storage. Meanwhile, artificial intelligence (AI) is regarded as a powerful tool to provide technical support for automated and efficient decision-making for metaverse devices. In this context, this paper focuses on integrating EC and AI to facilitate the development of the metaverse, namely, the edge intelligence-empowered metaverse. Specifically, we first outline the metaverse architecture and driving technologies and discuss EC as a key component of the digital infrastructure for metaverse realization. Then, we elaborate on two mainstream classifications of edge intelligence in metaverse scenarios, including AI for edge and AI on edge. Finally, we identify some open issues.</abstract><cop>New York</cop><pub>IEEE</pub><doi>10.1109/MNET.2023.3317477</doi><tpages>1</tpages><orcidid>https://orcid.org/0000-0001-9499-5456</orcidid><orcidid>https://orcid.org/0000-0002-5599-7683</orcidid><orcidid>https://orcid.org/0000-0002-0667-1150</orcidid><orcidid>https://orcid.org/0000-0002-5767-5020</orcidid><orcidid>https://orcid.org/0000-0002-4391-377X</orcidid></addata></record> |
fulltext | fulltext_linktorsrc |
identifier | ISSN: 0890-8044 |
ispartof | IEEE network, 2023-11, Vol.37 (6), p.1-1 |
issn | 0890-8044 1558-156X |
language | eng |
recordid | cdi_crossref_primary_10_1109_MNET_2023_3317477 |
source | IEEE Electronic Library (IEL) |
subjects | Artificial intelligence Cloud computing Computer architecture Computer networks Distributed processing Edge computing Infrastructure Internet of Things Metaverse Production Rendering (computer graphics) |
title | Edge Intelligence Empowered Metaverse: Architecture, Technologies, and Open Issues |
url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-23T07%3A59%3A19IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_RIE&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Edge%20Intelligence%20Empowered%20Metaverse:%20Architecture,%20Technologies,%20and%20Open%20Issues&rft.jtitle=IEEE%20network&rft.au=Xu,%20Yanan&rft.date=2023-11-01&rft.volume=37&rft.issue=6&rft.spage=1&rft.epage=1&rft.pages=1-1&rft.issn=0890-8044&rft.eissn=1558-156X&rft.coden=IENEET&rft_id=info:doi/10.1109/MNET.2023.3317477&rft_dat=%3Cproquest_RIE%3E3015029677%3C/proquest_RIE%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=3015029677&rft_id=info:pmid/&rft_ieee_id=10273380&rfr_iscdi=true |