Two-Dimensional Hash Encoding for Data Set Synchronization
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Solution Overview
Problem
Existing methods are inefficient in synchronizing data sets between network devices, especially in disconnect, intermittent, and low-bandwidth environments, where the symmetric difference between data sets is small and elements are related through a metric like Hamming distance.
Innovation Solution
The method involves partitioning the symmetric difference into subsets where elements are within a specified Hamming distance, using a two-dimensional hash to encode and decode the differences, minimizing information exchange by transmitting only the necessary data to reconcile the sets.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If existing synchronization methods are used, then data sets can be synchronized between network devices, but the synchronization efficiency is poor in disconnect, intermittent, and low-bandwidth environments
Solution Approach 1:
The patent extracts only the necessary information for synchronization by identifying and transmitting only the symmetric difference between data sets. Instead of transmitting entire data sets or all differences, the method extracts minimal representation of changes using encoding schemes that leverage the structured nature of differences (bounded Hamming distance), thereby reducing transmission overhead in low-bandwidth environments
Solution Approach 2:
The patent changes the representation parameters of data differences by encoding them in a compressed format that exploits the bounded Hamming distance property. The symmetric difference is encoded using a two-dimensional hash structure that transforms the raw difference data into a compact representation, reducing the number of bits transmitted while preserving full synchronization information
2Loss of information
If the symmetric difference between data sets is encoded using traditional methods, then all differences can be transmitted, but the amount of information transmitted is excessive
Solution Approach 1:
The patent segments the encoding process into two independent dimensions: a first dimension encoding the symmetric difference structure and a second dimension encoding the actual difference values. This segmentation allows each dimension to be optimized independently, with the first dimension providing structural context and the second dimension providing precise values, thereby reducing overall information volume while maintaining completeness
Solution Approach 2:
The patent introduces a two-dimensional hash structure as an intermediary representation between the raw symmetric difference and the transmitted data. This intermediary compresses the difference information by leveraging the bounded Hamming distance property, acting as a mediator that reduces information volume while preserving all necessary synchronization data
Data Source
AI summary
A method synchronizes related data across networked host devices. At each of a first and a second host device, string vectors are created for each document stored within the host device. The respective set of string vectors are encoded using a two-dimensional hash, where a first dimension of the two-dimensional hash stores string vector differences between all elements that reside in a symmetric difference and a second dimension of the two-dimensional hash stores one string vector from the symmetric difference. The respective encoded set of string vectors is transmitted to the other host device, which then decodes the respective encoded set of string vectors received to arrive at the symmetric difference. The host device determines which string vectors it is missing and requests from the other host device the missing documents pertaining to the missing string vectors. The missing documents are received by the requesting host device.