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DTSTAMP:20220112T041154Z
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DTSTART;TZID=Australia/Victoria:20220112T130000
DTEND;TZID=Australia/Victoria:20220112T140000
DESCRIPTION:Driven by the visions of the Internet of Things and 5G communic
 ations\, recent years have seen a paradigm shift in mobile computing\, fro
 m the centralized cloud computing toward the concept of computing at the e
 dge. This concept pushes the mobile computing\, network control and storag
 e to the network edges (e.g.\, base stations and access points)\, to enabl
 e computation-intensive and latency-critical applications at the resource-
 limited mobile devices. End devices with high mobility (e.g.\, smartphones
  and smart cars)\, various emerging applications\, and heterogeneous wirel
 ess network technologies of the edge incurs a critical challenge to the ne
 twork management and resource allocation in the edge computing platform. W
 ith the recent advance in artificial intelligence (AI)\, many AI methods\,
  like machine learning\, not only are the key enablers of emerging applica
 tions but also can be utilized to overcome solve the problems mentioned ab
 ove. The promised gains of computing at the edge and AI have motivated ext
 ensive efforts in both academia and industry on developing the technologie
 s. This talk will focus on the orchestration between AI and computing at t
 he edge. It considers AI as both the application of the edge and a techniq
 ue to solve the issues of network management and resource allocation of th
 e edge. This presentation firstly discussed current advancement in networ
 k management and resource allocation utilizing AI techniques. After that\,
  it discussed how computing the edge can provide AI service to realize eme
 rging IoT applications. Finally\, this talk elaborated further on open res
 earch challenges\n\nSpeaker(s): Prof. Ai-Chin Pang\, \n\nVirtual: https://
 events.vtools.ieee.org/m/280630
LOCATION:Virtual: https://events.vtools.ieee.org/m/280630
ORGANIZER:e.vinnal@ieee.org
SEQUENCE:6
SUMMARY:Enable AIoT Service at Edge/Fog Networks in 5G/6G
URL;VALUE=URI:https://events.vtools.ieee.org/m/280630
X-ALT-DESC:Description: <br /><p>Driven by the visions of the Internet of T
 hings and 5G communications\, recent years have seen a paradigm shift in m
 obile computing\, from the centralized cloud computing toward the concept 
 of computing at the edge. This concept pushes the mobile computing\, netwo
 rk control and storage to the network edges (e.g.\, base stations and acce
 ss points)\, to enable computation-intensive and latency-critical applicat
 ions at the resource-limited mobile devices. End devices with high mobilit
 y (e.g.\, smartphones and smart cars)\, various emerging applications\, an
 d heterogeneous wireless network technologies of the edge incurs a critica
 l challenge to the network management and resource allocation in the edge 
 computing platform. With the recent advance in artificial intelligence (AI
 )\, many AI methods\, like machine learning\, not only are the key enabler
 s of emerging applications but also can be utilized to overcome solve the 
 problems mentioned above. The promised gains of computing at the edge and 
 AI have motivated extensive efforts in both academia and industry on devel
 oping the technologies. This talk will focus on the orchestration between 
 AI and computing at the edge. It considers AI as both the application of t
 he edge and a technique to solve the issues of network management and reso
 urce allocation of the edge. This presentation firstly discussed current 
 advancement in network management and resource allocation utilizing AI tec
 hniques. After that\, it discussed how computing the edge can provide AI s
 ervice to realize emerging IoT applications. Finally\, this talk elaborate
 d further on open research challenges</p>
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