Edge Cloud Functionality Split Adaptation
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Solution Overview
Problem
Existing edge computing systems face inefficiencies due to a priori assumptions about backhaul connection bandwidth and latency, leading to potential congestion, unnecessary processing, and suboptimal data usage, as these assumptions do not accurately reflect varying connection conditions.
Innovation Solution
An assessment module dynamically determines and adjusts the interface and functionality split between edge processing functions and cloud computing systems based on real-time measurements of backhaul capacity and latency, incorporating additional factors like battery costs, to optimize data processing and transmission.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If a priori assumptions about backhaul connection bandwidth and latency are used, then system configuration is simplified, but system performance and reliability deteriorate due to congestion and suboptimal data usage
Solution Approach 1:
The patent implements dynamic functionality splitting that adapts to varying backhaul connection conditions. The assessment module continuously monitors connection characteristics and adjusts the division of processing tasks between edge and cloud based on real-time conditions, transforming a static configuration into a dynamic system that maintains optimal performance across changing network environments.
Solution Approach 2:
The patent employs feedback mechanisms where the assessment module evaluates actual backhaul connection performance and uses this information to adjust functionality splitting decisions. This closed-loop control ensures that the system responds to actual connection conditions rather than relying on fixed assumptions, thereby improving reliability without requiring complex manual configuration.
2Loss of time
If more data is processed at the edge, then latency is reduced and bandwidth usage is decreased, but processing efficiency deteriorates due to unnecessary processing when connection conditions are good
Solution Approach 1:
The patent dynamically adjusts the edge-cloud functionality split based on real-time assessment of backhaul connection characteristics. When connection conditions are poor, more processing is performed at the edge to reduce latency and bandwidth consumption. When connection conditions improve, the system shifts more processing to the cloud to optimize for processing efficiency, thereby avoiding unnecessary edge processing.
Solution Approach 2:
The patent changes the operational parameters of the distributed computing system by adjusting the functionality split ratio based on measured connection parameters such as bandwidth, latency, and reliability. This allows the system to optimize performance metrics by transitioning between different operational states corresponding to different network conditions.
3Productivity
If functionality is dynamically adjusted based on connection conditions, then system performance is optimized, but system complexity increases due to assessment and adjustment mechanisms
Solution Approach 1:
The patent implements a self-service mechanism where the assessment module autonomously monitors connection conditions and adjusts functionality splitting without requiring external intervention or complex centralized control. The edge processing function and cloud backend server work together to automatically optimize their collaboration based on measured connection characteristics, reducing the need for additional complex management infrastructure.
Data Source
AI summary
An edge computing system comprises: a cloud computing system; an edge processing function; a connection between the edge processing function and the cloud computing system; a backend server within the cloud computing system. An assessment module is configured to receive information about processing goals, and processing capabilities of the backend server and the edge processing function. The assessment module derives a set of possible interfaces and corresponding functionality splits defining a division of processing activity between the backend server and the edge processing function. Based on a received measurement of bandwidth and/or of latency on the connection, the assessment module selects an interface and corresponding functionality split, and downloads them to the edge processing function and the backend server.