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PRODID:IEEE vTools.Events//EN
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TZID:Asia/Kolkata
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DTSTART:19451014T230000
TZOFFSETFROM:+0630
TZOFFSETTO:+0530
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BEGIN:VEVENT
DTSTAMP:20240817T143541Z
UID:76E19B8F-5AB2-44E7-B856-AE6CF3746143
DTSTART;TZID=Asia/Kolkata:20240817T180000
DTEND;TZID=Asia/Kolkata:20240817T190000
DESCRIPTION:Talk on "Software-Defined Networking for Edge AI" by Dr. Ayan M
 ondal\, Assistant Professor\, IIT Indore\n\nWe plan to explore how Softwar
 e-Defined Networking (SDN) can transform Edge AI applications. SDN is capa
 ble of centralized control and programmable network infrastructure to faci
 litate dynamic resource allocation\, increased network efficiency\, and re
 duced latency\, which are important for real-time AI processing. SDN separ
 ates the control from the data plane\, thus enabling flexible and agile co
 nfigurations of networks that handle complex workloads in terms of network
  configurations. In the NEST research group\, we focus on the interaction 
 between SDNs\, edge devices\, and AI models with a view toward the optimiz
 ation of data flow and computational tasks within distributed environments
 . We are working towards improving the performance\, scalability\, and rel
 iability of SDN-driven Edge AI with real-life examples such as autonomous 
 vehicles\, smart cities\, and industrial IoT. In this talk\, I will focus 
 on how SDN eliminates hindrances to traditional networks\, leading to the 
 creation of novel AI-powered solutions and fueling rapid technological gro
 wth in industries.\n\nSpeaker(s): \, Dr. Ayan Mondal\n\nVirtual: https://e
 vents.vtools.ieee.org/m/430706
LOCATION:Virtual: https://events.vtools.ieee.org/m/430706
ORGANIZER:ieee.cs.sbc.iit.kgp@gmail.com
SEQUENCE:12
SUMMARY:Software-Defined Networking for Edge AI
URL;VALUE=URI:https://events.vtools.ieee.org/m/430706
X-ALT-DESC:Description: <br /><p>Talk on "Software-Defined Networking for E
 dge AI" by Dr. Ayan Mondal\, Assistant Professor\, IIT Indore</p>\n<p>&nbs
 p\;</p>\n<p dir="ltr">We plan to explore how Software-Defined Networking (
 SDN) can transform Edge AI applications. SDN is capable of centralized con
 trol and programmable network infrastructure to facilitate dynamic resourc
 e allocation\, increased network efficiency\, and reduced latency\, which 
 are important for real-time AI processing. SDN separates the control from 
 the data plane\, thus enabling flexible and agile configurations of networ
 ks that handle complex workloads in terms of network configurations. In th
 e NEST research group\, we focus on the interaction between SDNs\, edge de
 vices\, and AI models with a view toward the optimization of data flow and
  computational tasks within distributed environments. We are working towar
 ds improving the performance\, scalability\, and reliability of SDN-driven
  Edge AI with real-life examples such as autonomous vehicles\, smart citie
 s\, and industrial IoT. In this talk\, I will focus on how SDN eliminates 
 hindrances to traditional networks\, leading to the creation of novel AI-p
 owered solutions and fueling rapid technological growth in industries.</p>
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