Backup Client Data Stream Adaptation
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Solution Overview
Problem
Traditional backup systems face inefficiencies in data transmission due to a fixed number of data streams, which can lead to resource wastage and performance issues, especially when dealing with varying data duplication rates and server capabilities.
Innovation Solution
Dynamically determining the number of data streams based on transmission parameters and server capabilities, adjusting the number of streams for both sending data to a buffer and from the buffer to the server to optimize performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a fixed number of data streams is set independently based on experimental data, then the backup system can operate with simple configuration, but it cannot be flexibly applied to different types and sizes of data, leading to resource wastage or slow transmission
Solution Approach 1:
The patent implements dynamic adjustment of data stream numbers based on real-time transmission parameters and server capabilities. The backup client continuously monitors transmission status and adjusts the number of data streams dynamically, transforming the static fixed configuration into a dynamic adaptive system that responds to changing conditions.
Solution Approach 2:
The system establishes a feedback mechanism where transmission parameters (such as transmission speed, data duplication rate, and server receiving capability) are continuously monitored and fed back to the backup client. Based on this feedback, the system automatically adjusts the number of data streams to optimize transmission efficiency for different data types and sizes.
2Reliability
If too many data streams are used for backup data with high duplication rate, then complete data coverage is achieved, but unnecessary context switches occur bringing resource wastage and impacting backup server performance
Solution Approach 1:
The system changes the parameter of data stream number based on transmission parameters and server capabilities. When data duplication rate is high, the system reduces the number of data streams to avoid unnecessary context switches and resource wastage, while maintaining reliable transmission through adaptive adjustment.
Solution Approach 2:
The patent applies partial action by using only the necessary number of data streams required for reliable transmission. Instead of always using maximum streams, the system calculates and uses the optimal number based on actual transmission needs, avoiding excessive resource consumption while ensuring data completeness.
3Loss of energy
If too few data streams are used for large data, then resource consumption is reduced, but data transmission speed slows down
Solution Approach 1:
The system dynamically adjusts the number of data streams based on data size and transmission requirements. For large data transmissions, the system increases the number of data streams to maintain high transmission speed, while for smaller data, it reduces streams to conserve resources, achieving optimal balance between speed and resource consumption.
4Productivity
If the maximum number of data streams is set on backup server, then server capacity is maximized, but when sum of data streams from multiple clients reaches maximum, server cannot process multiple data streams with best performance
Solution Approach 1:
The system uses feedback from server capability information to adjust the number of data streams each client uses. When the server reaches its maximum processing capacity, the feedback mechanism allows clients to reduce their data stream numbers, preventing server overload and maintaining reliable performance across multiple clients.
Solution Approach 2:
The patent creates a universal data stream management mechanism that works across multiple clients and adapts to server capacity. The same feedback-based adjustment logic is applied universally to all clients, allowing the system to optimize overall server performance rather than individual client performance.
Data Source
AI summary
According to example embodiments of the present disclosure, provided is a method, device and computer program product for backing up data. The method comprises: determining a first number of data streams for sending target data; causing the target data to be sent to a buffer via the first number of data streams; determining a second number of data streams for sending the target data from the buffer to a server based on a transmission parameter associated with transmission of the target data to the buffer and a capability of the server for receiving data from the buffer; and causing the target data to be sent from the buffer to the server via the second number of data streams. Thereby, the present solution can improve the performance of sending data in a backup client.