Apple Inc. (20240259480). Dynamic Service Discovery and Offloading Framework for Edge Computing Based Cellular Network Systems simplified abstract

Dynamic Service Discovery and Offloading Framework for Edge Computing Based Cellular Network Systems

Organization Name

Apple Inc.

Inventor(s)

Biljana Badic of Munich (DE)

Christian Drewes of Munich (DE)

Ralph Hasholzner of Munich (DE)

Krisztian Kiss of Hayward CA (US)

Teck Yang Lee of Cupertino (CA)

Matthias Sauer of Campbell CA (US)

Mikhail Vilgelm of Munich (DE)

Babar Qaisrani of Los Altos CA (US)

Vijay Venkataraman of San Jose CA (US)

Robert Zaus of Neubiberg (DE)

Dynamic Service Discovery and Offloading Framework for Edge Computing Based Cellular Network Systems - A simplified explanation of the abstract

This abstract first appeared for US patent application 20240259480 titled 'Dynamic Service Discovery and Offloading Framework for Edge Computing Based Cellular Network Systems

Simplified Explanation: The patent application describes a system where a user equipment (UE) or other device can discover edge computing resources in a cellular network system and dynamically offload UE application tasks to these resources. The device can request information about edge server site capabilities and make decisions on whether to offload tasks based on factors like application latency, energy consumption, and offloading cost.

Key Features and Innovation:

• Service discovery of edge computing resources in a cellular network system
• Dynamic offloading of UE application tasks to discovered edge computing resources
• Requesting edge server site capability information during the discovery process
• Obtaining information on channel conditions, cellular network parameters, and application requirements for dynamic offloading decisions
• Using a utility function to determine whether a task should be offloaded to an edge server or executed locally on the UE

Potential Applications: This technology can be applied in various industries such as telecommunications, IoT, smart cities, and healthcare for efficient task offloading and resource utilization.

Problems Solved: This technology addresses the challenges of optimizing application performance, reducing energy consumption, and improving overall efficiency in cellular network systems.

Benefits:

• Improved application performance and reduced latency
• Efficient resource utilization and energy consumption
• Enhanced user experience and overall system efficiency

Commercial Applications: Title: Dynamic Offloading System for Cellular Networks This technology can be commercialized by network operators, IoT service providers, and edge computing companies to offer enhanced services, improve network performance, and optimize resource utilization in cellular networks.

Prior Art: Readers can explore prior research on edge computing, dynamic offloading, and cellular network optimization to understand the existing technologies and advancements in this field.

Frequently Updated Research: Researchers are continuously working on improving edge computing technologies, dynamic offloading algorithms, and network optimization strategies to enhance the performance and efficiency of cellular networks.

Questions about Dynamic Offloading System for Cellular Networks: 1. How does the utility function help in making decisions between offloaded or local execution of tasks? 2. What are the key factors considered by the device when requesting edge server site capability information?

Original Abstract Submitted

a user equipment (ue) or other device performs service discovery of edge computing resources in a cellular network system and dynamic offloading of ue application tasks to discovered edge computing resources. as part of the discovery process, the device (e.g., the ue) may request edge server site capability information. when performing dynamic offloading, the ue may obtain (collect and/or receive) information regarding channel conditions, cellular network parameters or application requirements and dynamically determine whether a task of the application executing on the ue should be offloaded to an edge server or executed locally on the ue. in making decisions between offloaded or local execution, the ue may use a utility function that takes into account factors such as relative differences in application latency, energy consumption and offloading cost.