Network Node Data Synchronization Under Packet Loss
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Solution Overview
Problem
In unreliable networks with high packet loss and low data rates, existing data synchronization methods face challenges in ensuring data replication consistency, scalability, fault tolerance, and security due to inefficient acknowledgement mechanisms, network congestion, and increased computational overhead.
Innovation Solution
A computer-implemented method and system using a data exchange platform with a messaging API, transport plugins, and a synchronization protocol, including an AMQ filter and Merkle tree, to efficiently synchronize data across multiple network nodes by fragmenting data, applying hash functions, and utilizing metadata for targeted delivery and encryption.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional acknowledgement mechanisms are used to ensure data delivery, then data replication reliability is improved, but network traffic increases and network congestion occurs
Solution Approach 1:
The patent extracts the essential verification function from conventional acknowledgement mechanisms by using Merkle tree roots and selective fragment verification. Instead of requiring full acknowledgements for each data fragment, the system only transmits and verifies critical hash root values, thereby maintaining reliability while dramatically reducing network traffic.
Solution Approach 2:
The patent changes the verification parameter from individual fragment acknowledgements to Merkle tree root hash comparisons. This parameter transformation allows the system to verify data integrity with minimal network communication, as nodes only need to exchange and compare compact hash values rather than full data fragments or detailed acknowledgements.
2Reliability
If data is retransmitted immediately upon acknowledgement loss, then data delivery reliability is improved, but unnecessary traffic and network congestion increase
Solution Approach 1:
The patent implements intelligent feedback mechanisms where nodes use Merkle tree root comparisons to determine actual data state differences before retransmission. This feedback loop prevents unnecessary retransmissions by allowing nodes to verify whether data is actually missing or if only the acknowledgement was lost, thereby reducing redundant network traffic while maintaining delivery reliability.
3Stability of the object's composition
If periodic state comparison between nodes is performed, then data consistency is improved, but data rate requirements increase causing network congestion
Solution Approach 1:
The patent extracts only the essential state information (Merkle tree root hashes) for comparison rather than transmitting or comparing complete data sets. This extraction approach allows periodic consistency verification with minimal data rate requirements, as nodes only need to exchange compact hash values to detect state differences.
Solution Approach 2:
The patent transforms the state comparison parameter from complete data sets to compact Merkle tree root hashes. This parameter change enables efficient periodic consistency checks that consume minimal bandwidth, allowing nodes to verify data consistency even in low data rate networks without causing congestion.
4Reliability
If encryption is applied to secure data during synchronization, then data security is improved, but computational overhead and latency increase
Solution Approach 1:
The patent segments the encryption/verification process into two stages: lightweight hashing of data fragments during synchronization, and full cryptographic verification only when necessary (e.g., upon connection establishment or suspected tampering). This segmentation reduces computational overhead during routine synchronization while maintaining security through selective application of heavier cryptographic operations.
Solution Approach 2:
The patent performs preliminary hashing of data fragments into Merkle tree structures during the synchronization process itself, rather than applying full encryption to every transmission. This preliminary action creates verifiable data representations that can be efficiently transmitted and verified, reducing computational overhead while maintaining security through the cryptographic properties of the hash functions.
Data Source
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AI summary
Disclosed is a computer-implemented method for synchronizing data messages between multiple network nodes of a network. The multiple network nodes comprise a first network node (104) and second network nodes (106a, 106b). The method comprises installing a data exchange platform (102) in the first network node and in the second network nodes, wherein the data exchange platform comprises, a messaging API (108), a transport plugin interface (110), and a synchronization protocol (112); providing a set of transport plugins (114), to at least one network node of the multiple network nodes; identifying second network nodes requesting to synchronize the one or more data messages and the data messages to be synchronized; and implementing the synchronization protocol for synchronizing the data messages between the first network node and the second network nodes by transferring the data messages from the first network node to the second network nodes.