Plugin-Based Data Merging for Cloud Version Conflicts
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Solution Overview
Problem
Cloud-based environments face version conflicts due to simultaneous editing of data files by multiple devices, leading to potential data corruption and inefficient manual intervention to resolve these conflicts.
Innovation Solution
A computer-implemented method that determines a merging policy by identifying a plugin and using it to exclude conflicting data contents from the merge operation, prioritizing recent or high-priority edits, and including relevant changes in the merged data file.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual intervention is used to resolve version conflicts, then data corruption can be prevented, but productivity decreases due to time-consuming manual resolution
Solution Approach 1:
The system automatically resolves version conflicts using predefined merging policies and plugins without requiring manual user intervention. The conflict resolution process is self-service, where the system identifies conflicting contents, determines which contents to exclude or include based on policies, and completes the merge operation automatically, thereby maintaining data integrity while improving productivity
Solution Approach 2:
Merging policies are predetermined and configured in advance, specifying which contents should be excluded or included during merge operations. By establishing these policies beforehand, the system can automatically handle version conflicts without manual intervention, resolving the contradiction between reliability and productivity
2Loss of information
If all contents from conflicting versions are included in the merge operation, then completeness is improved, but data corruption risk increases
Solution Approach 1:
The system extracts and excludes specific conflicting contents from the merge operation based on predefined policies. By identifying and removing problematic contents that would cause corruption while preserving non-conflicting contents, the system maintains both completeness and integrity of the merged data file
Solution Approach 2:
Different merging policies are applied to different contents within the data file based on their specific characteristics and conflict types. Rather than applying a uniform approach to all contents, the system selectively excludes only the problematic portions while merging other contents, thereby maintaining overall completeness while preventing local corruption
3Reliability
If version conflicts are resolved manually, then data integrity can be maintained, but loss of time increases
Solution Approach 1:
The system automatically performs conflict resolution using predefined merging policies and plugins, eliminating the need for manual user intervention. This self-service approach maintains data integrity through policy-based rules while dramatically reducing the time required to resolve conflicts compared to manual processes
Solution Approach 2:
Merging policies are configured in advance with predefined rules for handling different types of conflicts. This preliminary setup enables the system to automatically and quickly resolve conflicts without requiring time-consuming manual analysis and decision-making, thereby reducing time loss while maintaining integrity
4Loss of information
If storage operations are performed on all version contents, then data completeness is improved, but processing resource consumption increases
Solution Approach 1:
The system extracts and excludes only the necessary conflicting contents from storage operations based on merge policies. By avoiding storage operations on contents that would be excluded from the final merged file, the system maintains data completeness for essential contents while reducing unnecessary processing resource consumption
Solution Approach 2:
Rather than performing storage operations on all contents from all versions, the system performs partial storage operations only on the contents that will actually be included in the merged file. This partial action approach maintains necessary data completeness while avoiding excessive processing resource consumption on redundant contents
Data Source
AI summary
A computer-implemented method, according to one approach, includes performing a predetermined first data merge process in response to a determination that a version conflict exists between a plurality of versions of a data file resulting from editing performed on different cloud devices. The predetermined first data merge process includes determining a first merging policy of the data file from a plurality of potential merging policies, determining a plugin associated with the data file, and calling the plugin. The first merging policy is used as an input for the plugin, and the plugin includes predetermined conditions for determining first contents of the versions of the data file to exclude from a merge operation performed on the data file and second contents of the versions of the data file to include in the merge operation.