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DTSTAMP:20250301T180113Z
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DESCRIPTION:Title: Automating AI-Native 6G with Holistic Network Virtualiza
 tion\n\nAbstract: The sixth-generation (6G) communication networks are ant
 icipated to enable a variety of innovative applications and provide extrem
 e connectivity for mobile devices. To meet the evolving service demands in
  highly dynamic network environments\, artificial intelligence (AI) will b
 e a pivotal technology in 6G\, not only for network management but also fo
 r intelligent network applications. Data management will be key to empower
 ing AI within the network\, which suggests that digital twins would be a c
 rucial component in the 6G architecture\, enabling controllable and scalab
 le data collection and analysis by digitally modeling network entities. In
  this talk\, I will provide a high-level overview of digital twins for net
 work management\, reviewing how they will be created\, updated\, and opera
 ted within the existing network slicing-based architecture. Then\, I will 
 present a case study on digital twin-empowered resource allocation for col
 laborative sensing in industrial IoT\, demonstrating the effectiveness of 
 a holistic network virtualization architecture in improving data collectio
 n efficiency in network management.\n\nSpeaker(s): \, Mushu\n\nVirtual: ht
 tps://events.vtools.ieee.org/m/472249
LOCATION:Virtual: https://events.vtools.ieee.org/m/472249
ORGANIZER:wzhuang@uwaterloo.ca
SEQUENCE:11
SUMMARY:KW-Section VT Chapter Technical Seminar
URL;VALUE=URI:https://events.vtools.ieee.org/m/472249
X-ALT-DESC:Description: <br /><p class="MsoNormal" style="text-align: justi
 fy\; text-autospace: none\;"><strong><span style="font-size: 12.0pt\; font
 -family: 'Times New Roman'\,serif\; color: #212121\;">Title</span></strong
 ><span style="font-size: 12.0pt\; font-family: 'Times New Roman'\,serif\; 
 color: #212121\;">: </span><span style="font-size: 12.0pt\; font-family: '
 Times New Roman'\,serif\;">Automating AI-Native 6G with Holistic Network V
 irtualization</span></p>\n<p class="MsoNormal" style="text-align: justify\
 ; text-autospace: none\;"><span style="font-size: 12.0pt\; font-family: 'T
 imes New Roman'\,serif\;"><strong>Abstract</strong>: <span style="font-siz
 e: 12.0pt\; font-family: 'Times New Roman'\,serif\; mso-fareast-font-famil
 y: SimSun\; mso-ansi-language: EN-CA\; mso-fareast-language: ZH-CN\; mso-b
 idi-language: AR-SA\;">The sixth-generation (6G) communication networks ar
 e anticipated to enable a variety of innovative applications and provide e
 xtreme connectivity for mobile devices. To meet the evolving service deman
 ds in highly dynamic network environments\, artificial intelligence (AI) w
 ill be a pivotal technology in 6G\, not only for network management but al
 so for intelligent network applications. Data management will be key to em
 powering AI within the network\, which suggests that digital twins would b
 e a crucial component in the 6G architecture\, enabling controllable and s
 calable data collection and analysis by digitally modeling network entitie
 s. In this talk\, I will provide a high-level overview of digital twins fo
 r network management\, reviewing how they will be created\, updated\, and 
 operated within the existing network slicing-based architecture. Then\, I 
 will present a case study on digital twin-empowered resource allocation fo
 r collaborative sensing in industrial IoT\, demonstrating the effectivenes
 s of a holistic network virtualization architecture in improving data coll
 ection efficiency in network management.</span></span></p>
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