Data Object Pooling via Metadata Grouping
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Solution Overview
Problem
Accessing data objects in an organization by a remote computer is inefficient due to the overhead of individually locating and transferring objects, which results in excessive time and communication costs.
Innovation Solution
Identifying data objects with common metadata attributes and creating a pool of resembling objects, allowing for the transfer of multiple objects en masse when one is requested, thereby reducing the need for individual retrieval and transfer.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If data objects are accessed individually from remote computer, then access precision is maintained, but time consumption and communication overhead increase significantly
Solution Approach 1:
The patent merges multiple individual data object access operations into a single bulk transfer operation. By identifying that multiple data objects share common metadata attributes (such as same creator, same classification, or same access patterns), the system combines these objects into a single transfer unit, thereby reducing the number of individual access operations and significantly decreasing time consumption and communication overhead.
Solution Approach 2:
The patent performs preliminary identification and grouping of data objects based on their metadata attributes before the actual access operation. By pre-processing and organizing data objects into groups that share common characteristics, the system prepares the data structure in advance, enabling efficient bulk transfer operations without compromising the ability to precisely identify and access specific objects when needed.
2Productivity
If bulk transfer of data objects is performed, then communication efficiency improves, but transfer of unnecessary objects increases
Solution Approach 1:
The patent applies local quality by making the bulk transfer operation selective rather than universal. Instead of transferring all data objects in a directory or storage location, the system identifies and transfers only those objects that share specific metadata attributes with the requested object. This selective approach ensures that each bulk transfer operation contains only relevant objects, maintaining high communication efficiency while avoiding unnecessary data transfer.
Solution Approach 2:
The patent changes the parameters used for data object identification from individual-specific parameters to group-based parameters. By using metadata attributes (such as creator, classification, or access patterns) as grouping parameters, the system transforms the access model from individual object retrieval to parameter-based group retrieval, thereby improving communication efficiency without significantly increasing transfer volume.
3Measurement precision
If individual object location and transfer is performed, then access accuracy is maintained, but communication overhead increases
Solution Approach 1:
The patent merges multiple individual location and transfer operations into a single consolidated operation. By identifying data objects that share common metadata attributes with the requested object, the system combines their location and transfer processes, thereby maintaining access accuracy (since all transferred objects are relevant) while significantly reducing communication overhead through reduced protocol invocations and data path traversals.
Data Source
AI summary
A computerized method for pooling objects in a computerized system having a storage for objects, comprising identifying in the computerized system objects having an at least one common metadata entity associated with the objects, and including the identified objects in a pool of objects, and a apparatus for performing the same.