Client-Server Data Processing Load Balancing
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Solution Overview
Problem
Existing methods for distributing data processing tasks between client-side and server-side devices face challenges in balancing performance, security, and cost, particularly in cloud computing environments where processing costs are usage-based.
Innovation Solution
A method where a client device continuously receives data, divides it into subsets, and determines whether to process each subset locally or send it to a server based on a time ratio of processing time to capture time interval, adjusting the load sharing dynamically to prevent buffer overflow and optimize resource usage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of energy
If all processing tasks are offloaded to the server, then the server processing load increases and costs increase, but the client device can maintain simpler operation
Solution Approach 1:
The patent segments processing tasks into two categories: time-critical processing performed on the client device and non-time-critical processing performed on the server. This segmentation allows the system to offload only appropriate tasks to the server, reducing server processing load and costs while maintaining client-side responsiveness for time-sensitive operations.
Solution Approach 2:
The patent applies different processing qualities to different data subsets based on their time sensitivity. Time-critical data subsets are processed locally on the client device with high priority, while non-time-critical subsets are processed on the server with lower priority, optimizing resource allocation and reducing overall processing costs.
2Loss of energy
If processing tasks are performed on the client device, then processing costs decrease and security improves, but the client device processing load increases
Solution Approach 1:
The patent implements dynamic task allocation where the client device continuously monitors its processing capacity and buffer status. Based on real-time conditions, the system dynamically decides which data subsets to process locally and which to offload to the server, preventing client device overload while maximizing local processing benefits.
Solution Approach 2:
The system uses feedback from buffer status and processing capacity monitoring to adjust processing decisions. When the client device buffer approaches capacity or processing load increases, the system automatically reduces local processing and increases server offloading, maintaining optimal client device operation.
3Speed
If time-critical processing is performed on the client device, then responsiveness improves, but the client device buffer may overflow causing data loss
Solution Approach 1:
The patent implements preliminary buffer status checking before processing decisions. The system monitors buffer capacity in advance and proactively adjusts processing decisions to prevent overflow. By checking buffer status beforehand and adjusting task allocation accordingly, the system maintains high processing speed while preventing data loss from buffer overflow.
Data Source
AI summary
A method for processing of data by applying a first algorithm in a system comprising a server and a client device comprises at the client device: continuously receiving data; dividing the received data into M>1 subsets of data, each subset of data comprising, or being derived from, sensor data captured by a sensor during a capture time interval at a plurality of points in time; determining for each subset whether the processing of the subset should be performed by the client device or by the server, and upon determining that the processing should be performed by the client device, processing the subset into processed data by applying the first algorithm to the subset, and transmitting the processed data to the server, and upon determining that processing should be performed by the server, transmitting the subset of data to the server.