BEGIN:VCALENDAR
VERSION:2.0
PRODID:IEEE vTools.Events//EN
CALSCALE:GREGORIAN
BEGIN:VTIMEZONE
TZID:Asia/Shanghai
BEGIN:STANDARD
DTSTART:19910915T010000
TZOFFSETFROM:+0900
TZOFFSETTO:+0800
TZNAME:CST
END:STANDARD
END:VTIMEZONE
BEGIN:VEVENT
DTSTAMP:20260801T020555Z
UID:D1A156CF-ED6D-46E2-AB7B-1B617DFED87B
DTSTART;TZID=Asia/Shanghai:20260804T160000
DTEND;TZID=Asia/Shanghai:20260804T173000
DESCRIPTION:Intelligent edge computing is rapidly emerging as a foundationa
 l pillar for next-generation machine learning systems\, enabling low-laten
 cy\, context-aware\, and scalable intelligence close to data sources. This
  talk offers a holistic perspective on reimagining intelligent edge comput
 ing through innovative resource deployment and service optimization strate
 gies. We first introduce a cooperative edge server deployment architecture
  to reduce infrastructure overhead. To further expand flexibility and cove
 rage in dynamic environments\, a hybrid server deployment paradigm is expl
 ored to improve both spatial adaptability and computational efficiency. In
  addition\, a task-aware service placement mechanism is proposed for servi
 ce optimization. Collectively\, these insights outline a clear pathway tow
 ard scalable\, efficient\, and adaptive edge computing infrastructures for
  the next wave of machine learning technologies and real-world application
 s.\n\nRoom: 4-7151\, Bldg: Innovation Harbor\, Xi 'an Jiaotong University(
 iHarbour Campus)\, Xi'an \, Shaanxi\, China
LOCATION:Room: 4-7151\, Bldg: Innovation Harbor\, Xi 'an Jiaotong Universit
 y(iHarbour Campus)\, Xi'an \, Shaanxi\, China
ORGANIZER:chaoshen@mail.xjtu.edu.cn
SEQUENCE:4
SUMMARY:Intelligent Edge Computing: Challenges\, Architectures\, and Optimi
 zation
URL;VALUE=URI:https://events.vtools.ieee.org/m/570610
X-ALT-DESC:Description: <br /><p class="MsoNormal" style="text-align: justi
 fy\; text-justify: inter-ideograph\; line-height: 110%\;"><span lang="EN-G
 B" style="font-size: 11.0pt\; line-height: 110%\; mso-ansi-language: EN-GB
 \; mso-fareast-language: ZH-CN\;">Intelligent edge computing is rapidly em
 erging as a foundational pillar for next-generation machine learning syste
 ms\, enabling low-latency\, context-aware\, and scalable intelligence clos
 e to data sources. This talk offers a holistic perspective on reimagining 
 intelligent edge computing through innovative resource deployment and serv
 ice optimization strategies. We first introduce a cooperative edge server 
 deployment architecture to reduce infrastructure overhead. To further expa
 nd flexibility and coverage in dynamic environments\, a hybrid server depl
 oyment paradigm is explored to improve both spatial adaptability and compu
 tational efficiency. In addition\, a task-aware service placement mechanis
 m is proposed for service optimization. Collectively\, these insights outl
 ine a clear pathway toward scalable\, efficient\, and adaptive edge comput
 ing infrastructures for the next wave of machine learning technologies and
  real-world applications.</span><span lang="EN-GB" style="font-size: 11.0p
 t\; line-height: 110%\; mso-fareast-font-family: 'Arial Unicode MS'\; mso-
 ansi-language: EN-GB\; mso-bidi-font-weight: bold\;"> </span></p>
END:VEVENT
END:VCALENDAR