Remote Differential Compression Candidate Object Identification
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Solution Overview
Problem
Existing data transfer methods over limited network bandwidth are inefficient, particularly when updating large objects, as they incur significant overhead in transferring metadata and chunk information, even when the differences between objects are small.
Innovation Solution
The method employs recursive remote differential compression and local maximum-based chunking to minimize bandwidth utilization by reducing the amount of metadata transferred and optimizing chunking to reduce network communication overhead, allowing devices to reuse similar objects and transfer only the necessary differences.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of energy
If traditional remote differential compression is used to transfer large objects, then data can be transferred across the network, but significant overhead is incurred in transferring metadata and chunk information
Solution Approach 1:
The patent extracts only the essential information needed for compression - specifically file attributes (size, modification time, permissions) and small portions of file content - while leaving out the traditional bulky metadata structures. This selective extraction reduces the overhead transferred over the network while maintaining the ability to perform differential compression.
Solution Approach 2:
Instead of transferring complete metadata and chunk information as in traditional RDC, the patent inverts the approach by transferring minimal metadata and having the receiving device perform local analysis to identify reusable content. This reverses the traditional flow of information and reduces network overhead significantly.
2Productivity
If traditional RDC algorithms transfer complete metadata and chunk information, then compression can be performed, but the amount of data transferred increases network traffic
Solution Approach 1:
The patent extracts only the critical elements needed for compression decision-making - file attributes and small content samples - while omitting the transfer of complete metadata and chunk information. This extraction approach maintains compression efficiency by preserving the essential comparison data while dramatically reducing network traffic volume.
Solution Approach 2:
The patent applies partial action by transferring only a portion of the information traditionally required - specifically, minimal metadata and small content excerpts rather than complete file data. This partial transfer is sufficient for the receiving device to perform local differential analysis and achieve effective compression.
3Productivity
If local differential algorithms are used to maintain old copies of objects, then compression efficiency improves, but it becomes difficult or infeasible when old copies cannot be maintained
Solution Approach 1:
The patent introduces an intermediary approach where minimal metadata and small content excerpts act as mediators between the sender and receiver. These intermediaries enable the receiving device to perform local differential analysis without requiring complete old copies to be maintained, bridging the gap between remote and local differential compression approaches.
Solution Approach 2:
The patent applies preliminary action by having the receiving device pre-process the received minimal metadata and content excerpts to identify potential reusable portions before the actual data transfer. This preliminary local analysis enables efficient compression decisions to be made without requiring the sender to maintain or transfer complete historical versions.
Data Source
AI summary
The present invention finds candidate objects for remote differential compression. Objects are updated between two or more computing devices using remote differential compression (RDC) techniques such that required data transfers are minimized. An algorithm provides enhanced efficiencies for allowing the receiver to locate a set of objects that are similar to the object that needs to be transferred from the sender. Once this set of similar objects has been found, the receiver may reuse any chunks from these objects during the RDC algorithm.