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DTSTAMP:20240307T141711Z
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DESCRIPTION:The sixth-generation (6G) communication networks are anticipate
 d to enable a variety of innovative applications and provide extreme conne
 ctivity for mobile devices. To meet the evolving service demands in highly
  dynamic network environments\, mobile edge computing (MEC) and artificial
  intelligence (AI) will be two pivotal technologies in 6G. MEC extends com
 puting and storage capabilities within radio access networks\, coping with
  the increasing computing demands from mobile users. Meanwhile\, AI facili
 tates intelligent resource management by enabling network entities to lear
 n and build knowledge about network dynamics. In this talk\, we will explo
 re AI-assisted resource management for MEC-enabled networks\, addressing t
 he computing challenges caused by device mobility and heterogeneity. We wi
 ll introduce two AI-assisted resource management approaches\, each tailore
 d to support a representative MEC use case: the Internet of Vehicles and m
 obile virtual reality video streaming. Finally\, we will outline a future 
 research plan focused on holistic network virtualization through digital t
 win technologies\, aimed at further enhancing the flexibility and efficien
 cy of AI-assisted network management towards 6G.\n\nRoom: 460\, Bldg: Engi
 neering\, ENG460 \, 245 Church Street\, Toronto\, Ontario\, Canada\, M5B 2
 K3\, Virtual: https://events.vtools.ieee.org/m/409530
LOCATION:Room: 460\, Bldg: Engineering\, ENG460 \, 245 Church Street\, Toro
 nto\, Ontario\, Canada\, M5B 2K3\, Virtual: https://events.vtools.ieee.org
 /m/409530
ORGANIZER:l5zhao@torontomu.ca
SEQUENCE:7
SUMMARY:Network Dynamics-Aware Resource Management for Mobile Edge Computin
 g
URL;VALUE=URI:https://events.vtools.ieee.org/m/409530
X-ALT-DESC:Description: <br /><div style="mso-element: para-border-div\; bo
 rder: none\; border-bottom: solid windowtext 1.0pt\; mso-border-bottom-alt
 : solid windowtext .75pt\; padding: 0cm 0cm 29.0pt 0cm\;">\n<p class="MsoN
 ormal" style="text-align: justify\; text-justify: inter-ideograph\; border
 : none\; mso-border-bottom-alt: solid windowtext .75pt\; padding: 0cm\; ms
 o-padding-alt: 0cm 0cm 29.0pt 0cm\;"><span lang="EN-US">The sixth-generati
 on (6G) communication networks are anticipated to enable a variety of inno
 vative applications and provide extreme connectivity for mobile devices. T
 o meet the evolving service demands in highly dynamic network environments
 \, mobile edge computing (MEC) and artificial intelligence (AI) will be tw
 o pivotal technologies in 6G. MEC extends computing and storage capabiliti
 es within radio access networks\, coping with the increasing computing dem
 ands from mobile users. Meanwhile\, AI facilitates intelligent resource ma
 nagement by enabling network entities to learn and build knowledge about n
 etwork dynamics. In this talk\, we will explore AI-assisted resource manag
 ement for MEC-enabled networks\, addressing the computing challenges cause
 d by device mobility and heterogeneity. We will introduce two AI-assisted 
 resource management approaches\, each tailored to support a representative
  MEC use case: the Internet of Vehicles and mobile virtual reality video s
 treaming. Finally\, we will outline a future research plan focused on holi
 stic network virtualization through digital twin technologies\, aimed at f
 urther enhancing the flexibility and efficiency of AI-assisted network man
 agement towards 6G.</span></p>\n</div>
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