Backup Destination Selection via Subset Code Transformation
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Solution Overview
Problem
Current methods for selecting backup destinations in large storage device sets are inefficient due to the vast number of combinations, leading to high computational overhead and processing inefficiency when selecting suitable storage devices for data backup.
Innovation Solution
A method that generates unique subset codes for candidate subsets, allowing for the selection of a target subset as a backup destination by transforming initial subset codes, reducing the need to traverse all combinations and focusing on locally optimal solutions within a limited time and computational overhead.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If all combinations of storage device subsets are evaluated to select backup destinations, then selection accuracy is improved, but computational overhead increases exponentially
Solution Approach 1:
The patent segments the exhaustive search space by generating candidate subsets through controlled transformations of initial seed subsets. Instead of evaluating all possible combinations, the method divides the search into: (1) generating initial seed subsets, (2) transforming seeds to generate candidate subsets via code manipulation, and (3) evaluating only these transformed candidates. This segmentation reduces computational overhead while maintaining selection accuracy.
Solution Approach 2:
The patent performs preliminary action by generating initial seed subsets before the main selection process. These seed subsets serve as starting points for generating candidate subsets through transformation operations. By pre-establishing a foundation set of subsets and then systematically transforming them, the method avoids exhaustive evaluation while ensuring comprehensive coverage of promising candidates.
2Quantity of substance
If the number of storage devices increases, then backup system capacity is improved, but the number of combinations to evaluate increases exponentially
Solution Approach 1:
The patent uses copying by generating candidate subsets through transformations of initial seed subsets. Instead of creating and evaluating all possible combinations from scratch, the method copies and transforms a limited set of seed subsets using code generation operations. This copying approach maintains the ability to handle large numbers of storage devices while avoiding exponential complexity growth.
Solution Approach 2:
The patent applies parameter changes by manipulating subset codes to generate candidate subsets. The method transforms initial seed subsets by modifying their representation codes through systematic operations, generating diverse candidate subsets without exhaustively enumerating all possible combinations. This parameter-based transformation approach scales efficiently with the number of storage devices.
3Reliability
If more candidate subsets are generated to improve selection quality, then backup destination quality is improved, but processing time increases
Solution Approach 1:
The patent applies dynamics by using transformative operations that dynamically generate candidate subsets from seed subsets. The code transformation process creates a dynamic exploration of the solution space, generating candidate subsets on-demand through systematic manipulation rather than static exhaustive enumeration. This dynamic approach improves backup destination quality while controlling processing time.
Data Source
AI summary
Implementations of the present disclosure provide a method for backup destination selection, an electronic device, and a computer program product. In one method, in a storage device set, a first group of candidate subsets is obtained, and the number of storage devices included in candidate subsets in the first group of candidate subsets is determined based on the number of copies specified by a backup task. A first group of subset codes of the first group of candidate subsets is determined. A second group of subset codes is generated according to the first group of subset codes, and codes in the second group of subset codes uniquely identify the candidate subsets. Based on the first group of candidate subsets and a second group of candidate subsets corresponding to the second group of subset codes, a target subset is selected as a backup destination of the backup task. According to example implementations of the present disclosure, a corresponding apparatus, a corresponding electronic device, and a corresponding computer program product are provided. The implementations of the present disclosure can greatly reduce the amount of calculation for selecting the target subset, and thereby improving the automation level and performance of the storage system.