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DTSTART:20260308T030000
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DTSTART:20261101T010000
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DTSTAMP:20260701T104123Z
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DTSTART;TZID=America/New_York:20260706T100000
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DESCRIPTION:Network Utility Maximization (NUM) serves as a theoretical cont
 rol framework for resource allocation problems in modern communication sys
 tems\, ranging from cellular downlinks to heterogeneous multi-hop wireless
  networks. NUM frameworks mainly seek to maximize global utility functions
  subject to system constraints arising from resource limitations (e.g.\, c
 ommunication bandwidth\, computing power\, or energy availability). To opt
 imally schedule these resources\, classical NUM frameworks couple differen
 t network layers\, utilizing feedback (e.g.\, queue length or channel stat
 e information) to solve the utility maximization problem at each slot. How
 ever\, classical NUM renders inapplicable when utility functions are unkno
 wn\, feedback from network layers are opaque or delayed\, or when joint co
 mputing/communication resource scheduling are considered.\n\nWe study the 
 fundamental challenges in NUM frameworks involving multihop wireless netwo
 rks and computing platforms\, aiming to enable in-network computing and un
 ified resource/service scheduling. Further\, we investigate NUM in wireles
 s networks characterized by unknown utility functions\, partially observab
 le routing actions\, and channels/ queue states which are subject to non-t
 rivial delays.\n\nSpeaker(s): Mahfujul Kadir\, \n\nVirtual: https://events
 .vtools.ieee.org/m/565913
LOCATION:Virtual: https://events.vtools.ieee.org/m/565913
ORGANIZER:h.mohammad@northeastern.edu
SEQUENCE:16
SUMMARY:Advancing Network Utility Maximization for Intelligent Wireless Net
 works
URL;VALUE=URI:https://events.vtools.ieee.org/m/565913
X-ALT-DESC:Description: <br /><p>Network Utility Maximization (NUM) serves 
 as a theoretical control framework for resource allocation problems in mod
 ern communication systems\, ranging from cellular downlinks to heterogeneo
 us multi-hop wireless networks. NUM frameworks mainly seek to maximize glo
 bal utility functions subject to system constraints arising from resource 
 limitations (e.g.\, communication bandwidth\, computing power\, or energy 
 availability). To optimally schedule these resources\, classical NUM frame
 works couple different network layers\, utilizing feedback (e.g.\, queue l
 ength or channel state information) to solve the utility maximization prob
 lem at each slot. However\, classical NUM renders inapplicable when utilit
 y functions are unknown\, feedback from network layers are opaque or delay
 ed\, or when joint computing/communication resource scheduling are conside
 red.&nbsp\;</p>\n<p>We study the fundamental challenges in NUM frameworks 
 involving multihop wireless networks and computing platforms\, aiming to e
 nable in-network computing and unified resource/service scheduling. Furthe
 r\, we investigate NUM in wireless networks characterized by unknown utili
 ty functions\, partially observable routing actions\, and channels/ queue 
 states which are subject to non-trivial delays.</p>
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