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 and dynamically offload application tasks to these resources. The device can request information about edge server capabilities and make decisions on whether to offload tasks based on factors like channel conditions, network parameters, and application requirements.

• Edge computing resource discovery in a cellular network system
• Dynamic offloading of UE application tasks to discovered edge computing resources
• Requesting edge server site capability information during discovery
• Obtaining information on channel conditions, network parameters, and application requirements for decision making
• Dynamically determining whether to offload tasks to an edge server or execute locally based on utility function analysis

Potential Applications: This technology could be applied in various industries such as telecommunications, IoT, smart cities, and healthcare where edge computing and efficient task offloading are crucial.

Problems Solved: This technology addresses the challenges of optimizing application performance, reducing latency, and improving energy efficiency in cellular networks by leveraging edge computing resources.

Benefits: The benefits of this technology include improved application performance, reduced latency, energy savings, and enhanced overall user experience in cellular network environments.

Commercial Applications: Title: "Dynamic Offloading System for Cellular Networks" This technology could be commercially used by network operators, IoT service providers, and application developers to enhance the efficiency and performance of applications in cellular networks.

Prior Art: Readers interested in prior art related to this technology could explore research papers, patents, and industry publications on edge computing, mobile offloading, and cellular network optimization.

Frequently Updated Research: Researchers are continually exploring advancements in edge computing, mobile offloading techniques, and network optimization strategies to further enhance the performance and efficiency of cellular networks.

Questions about Edge Computing and Dynamic Offloading: 1. How does dynamic offloading to edge computing resources improve application performance in cellular networks? 2. What are the key factors that influence the decision to offload tasks from a user equipment to an edge server in a cellular network system?

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.