Wireless Data Offloading via Server Splitting Points
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Solution Overview
Problem
Existing technologies struggle to efficiently offload data from smart devices to servers while satisfying preset requirements and adapting to changing channel conditions and server environments.
Innovation Solution
A method and apparatus for offloading data in a wireless communication system, where a user equipment (UE) determines a suitable server for data processing based on received server information, and the server processes and splits data for efficient offloading, with the ability to change or add servers during the offloading process.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If data is offloaded from smart devices to servers, then data processing efficiency is improved, but network dependency and transmission latency increase
Solution Approach 1:
The system performs preliminary actions by pre-fetching data to edge servers before actual processing is needed, and by pre-establishing communication channels between devices and servers. This reduces the effective transmission latency during actual data processing operations, as the infrastructure is already in place and data can be processed immediately upon arrival.
2Power
If data is offloaded to remote servers, then computing power is improved, but network transmission requirements and energy consumption increase
Solution Approach 1:
The patent introduces a spatial dimension to the computing architecture by deploying edge servers at multiple geographic locations closer to user devices. This dimensional change allows data to be processed at nearby edge nodes rather than being transmitted to distant centralized servers, reducing transmission distance, network requirements, and energy consumption while maintaining access to powerful computing resources.
3Reliability
If data is processed locally on smart devices, then privacy and security are improved, but processing capability is limited
Solution Approach 1:
The system segments the computing architecture into multiple layers: local device processing for sensitive operations, edge server processing for intermediate tasks, and centralized cloud processing for non-sensitive heavy computations. This segmentation allows different types of data to be processed at appropriate levels, maintaining privacy and security for sensitive data while leveraging powerful processing capabilities for other tasks.
4Productivity
If more edge servers are deployed, then data processing capacity is improved, but system complexity and deployment cost increase
Solution Approach 1:
The edge server architecture is designed with universal, multi-functional components that can handle various types of data processing tasks across different applications and services. This standardization reduces system complexity by using common hardware and software platforms that can be deployed repeatedly, rather than requiring custom-built specialized systems for each function.
Data Source
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AI summary
A method and an apparatus for offloading data in a wireless communication system are provided. The method performed by a user equipment (UE) of offloading data includes determining a server for processing at least some of the data, receiving, from the server, a list regarding splitting points at which the data is splittable, determining, based on the list, at least one of the splitting points as an offloading point, transmitting, to the server, information about the offloading point and information about requirements for offloading data corresponding to the offloading point, receiving, from the server, a response as to whether the offloading data is capable of being processed, and determining whether the offloading data is to be processed, based on the response.