20240031235. EDGE CLOUD PLATFORM FOR MISSION CRITICAL APPLICATIONS simplified abstract (Telefonaktiebolaget LM Ericsson (publ))

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EDGE CLOUD PLATFORM FOR MISSION CRITICAL APPLICATIONS

Organization Name

Telefonaktiebolaget LM Ericsson (publ)

Inventor(s)

Zhongwen Zhu of Saint-Laurent (CA)

Qinan Qi of Saint-Laurent (CA)

[[:Category:Claes Göran Robert Edstr�m of Beaconsfield (CA)|Claes Göran Robert Edstr�m of Beaconsfield (CA)]][[Category:Claes Göran Robert Edstr�m of Beaconsfield (CA)]]

Tan Phat Nguyen of Montreal (CA)

Alec Kurkdjian of Laval (CA)

EDGE CLOUD PLATFORM FOR MISSION CRITICAL APPLICATIONS - A simplified explanation of the abstract

This abstract first appeared for US patent application 20240031235 titled 'EDGE CLOUD PLATFORM FOR MISSION CRITICAL APPLICATIONS

Simplified Explanation

The abstract describes a method for implementing a network slicing controller in an edge cloud platform. The method involves receiving policy changes from an artificial intelligence-powered smart traffic controller or an artificial intelligence-powered edge traffic controller. It then determines the validity of these policy changes based on local monitoring information and sends them to a common control network function in a 5G mobile network.

  • The method manages network slicing instances in an edge cloud platform.
  • It receives policy changes from an artificial intelligence-powered smart traffic controller or an artificial intelligence-powered edge traffic controller.
  • It determines the validity of the policy changes using local monitoring information.
  • It sends the policy changes to a common control network function in a 5G mobile network.

Potential Applications:

  • Efficient management of network slicing instances in an edge cloud platform.
  • Integration of artificial intelligence-powered traffic controllers for improved network performance.
  • Implementation in 5G mobile networks for enhanced control and management capabilities.

Problems Solved:

  • Simplifies the management of network slicing instances in an edge cloud platform.
  • Enables efficient handling of policy changes from artificial intelligence-powered traffic controllers.
  • Enhances the control and management capabilities of 5G mobile networks.

Benefits:

  • Improved network performance and efficiency.
  • Enhanced control and management capabilities in edge cloud platforms.
  • Integration of artificial intelligence for intelligent traffic control.
  • Streamlined policy change handling in 5G mobile networks.


Original Abstract Submitted

a method implements a network slicing controller to manage network slicing instances in an edge cloud platform. the method includes receiving at least one policy change from an artificial intelligence powered smart traffic controller (apstc) or an artificial intelligence powered edge traffic controller (apetc), determining whether the at least one policy change is valid based on local monitoring information, and sending the at least one policy change to a common control network function in a 5g mobile network.

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