17863576. METHOD AND ELECTRONIC DEVICE FOR MANAGING MACHINE LEARNING SERVICES IN WIRELESS COMMUNICATION NETWORK simplified abstract (Samsung Electronics Co., Ltd.)

METHOD AND ELECTRONIC DEVICE FOR MANAGING MACHINE LEARNING SERVICES IN WIRELESS COMMUNICATION NETWORK

Organization Name

Samsung Electronics Co., Ltd.

Inventor(s)

Sukhdeep Singh of Bangalore (IN)

Joseph Thaliath of Bangalore (IN)

Vivek Sapru of Bangalore (IN)

Sandeep Kumar Jaisawal of Bangalore (IN)

Naman Agarwal of Bangalore (IN)

Seungil Yoon of Suwon-si (KR)

Hoejoo Lee of Suwon-si (KR)

METHOD AND ELECTRONIC DEVICE FOR MANAGING MACHINE LEARNING SERVICES IN WIRELESS COMMUNICATION NETWORK - A simplified explanation of the abstract

This abstract first appeared for US patent application 17863576 titled 'METHOD AND ELECTRONIC DEVICE FOR MANAGING MACHINE LEARNING SERVICES IN WIRELESS COMMUNICATION NETWORK

Simplified Explanation

The abstract describes a method for managing machine learning services in a wireless communication network. Here is a simplified explanation of the abstract:

• The method involves storing multiple machine learning packages that can execute network service requests.
• When a server sends a trigger based on a network service request, the method receives it.
• The method then determines various parameters associated with the network service request upon receiving the trigger.
• Based on the trigger and the parameters, the method selects a suitable machine learning package.
• Finally, the selected machine learning package is deployed to execute the network service request.

Potential Applications

This technology can be applied in various fields where machine learning services are utilized in wireless communication networks, such as:

• Network optimization: The method can be used to optimize network performance by deploying specific machine learning packages based on network service requests.
• Resource allocation: By selecting appropriate machine learning packages, the method can help allocate network resources efficiently.
• Anomaly detection: Machine learning packages can be deployed to detect and mitigate anomalies in wireless communication networks.

Problems Solved

The method addresses the following problems:

• Efficient management of machine learning services: By storing and selecting machine learning packages based on network service requests, the method simplifies the management of these services.
• Optimization of network performance: By deploying suitable machine learning packages, the method helps improve the performance of wireless communication networks.
• Resource allocation: The method assists in allocating network resources effectively by selecting appropriate machine learning packages.

Benefits

The use of this technology offers several benefits:

• Enhanced network performance: By deploying specific machine learning packages, the method can optimize network performance and improve user experience.
• Efficient resource utilization: The method helps allocate network resources effectively, leading to better resource utilization.
• Simplified management: Storing and selecting machine learning packages based on network service requests simplifies the management of machine learning services in wireless communication networks.

Original Abstract Submitted

The embodiments herein disclose a method for managing machine learning (ML) services in a wireless communication network. The method includes: storing a plurality of ML packages, each executing a network service request; receiving a trigger based on the network service request from a server; determining a plurality of parameters corresponding to the network service request, on receiving the trigger from the server; determining an ML package based on the trigger and the plurality of parameters corresponding to the network service request; and deploying the determined at least one ML package for executing the network service request.