Blockchain Data Network with Fusion Nodes for Integrity
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Solution Overview
Problem
Processing and organizing vast amounts of data from diverse sources into meaningful information and knowledge is complex, and maintaining data integrity is crucial for ensuring the quality of the resulting information and knowledge, especially in contexts like IoT devices and blockchain systems.
Innovation Solution
A network architecture with collecting nodes that process data into meta-data blocks, encrypt them, and send them through a communication structure to fusion nodes for fusion and storage in a blockchain structure, ensuring data integrity and enabling efficient search and visualization of data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If data is collected from multiple diverse sources and processed into information and knowledge, then the usefulness and value of the data increases, but the complexity of processing and maintaining data integrity increases
Solution Approach 1:
The system segments data processing across multiple specialized nodes: collecting nodes gather and encrypt data, fusion nodes process and fuse data from multiple sources, and storage nodes maintain data in blockchain structures. This segmentation distributes the complex processing task while maintaining data integrity through specialized functions at each node.
Solution Approach 2:
Encryption algorithms act as intermediaries between data collection and processing/storage. The encryption layer protects data integrity during transmission and storage, while allowing authorized processing. This intermediary mechanism enables complex multi-source data processing without compromising integrity.
2Reliability
If encryption is applied to protect data security, then data security and integrity are improved, but processing speed and efficiency deteriorate
Solution Approach 1:
The system separates encryption operations from processing operations. Data is encrypted at collecting nodes before transmission, then fusion nodes process the encrypted data without needing to decrypt it for all operations. This segmentation maintains security while improving processing efficiency by avoiding repeated decryption/encryption cycles.
Solution Approach 2:
Encryption is performed as a preliminary action at the data collection stage, before data enters the processing pipeline. This preliminary encryption protects data throughout its lifecycle without requiring continuous encryption operations during processing, thereby maintaining security while improving overall system efficiency.
3Adaptability or versatility
If data is divided into chunks and distributed across multiple nodes, then data security and scalability are improved, but system complexity and coordination overhead increase
Solution Approach 1:
Data is segmented into chunks and distributed across multiple specialized nodes (collecting, fusion, and storage nodes). Each node type has a defined function, reducing the complexity of coordination compared to a fully distributed system where every node must perform every function. This structured segmentation enables scalability while managing system complexity.
Solution Approach 2:
Not all nodes perform all functions - each node type performs only its specific function (collecting, fusing, or storing). This partial action approach reduces coordination overhead and system complexity compared to requiring full functionality at each node, while still achieving scalable distributed processing.
4Reliability
If blockchain structure is used to ensure data integrity, then data quality and trustworthiness are improved, but storage overhead and processing time increase
Solution Approach 1:
The blockchain structure is implemented in a segmented manner where only critical integrity information (hashes, metadata) is stored in blockchain format, while actual data chunks are stored distributed across nodes. This segmentation reduces storage overhead and processing time compared to storing entire data sets in blockchain structures, while maintaining data integrity through cryptographic verification.
Data Source
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AI summary
Collecting nodes (110, 111) receive data (D) from multiple data sources (DS) via a communication structure (N). The data (D) is processed to generate meta data blocks (B) reflecting information about objects of interest (Ol) represented by the data content. The meta data blocks (B) are encrypted (Be). The data (D) is divided into data chunks (DC) of a respective predefined size, and encrypted (DCe). The encrypted data chunks and meta blocks (DCe; Be) are sent over the communication structure (N) to fusion nodes (120, 121), where, after decryption, meta data blocks (B) are fused into a new meta data block if an object-of-interest (Ol) criterion is fulfilled. The new meta data blocks (B) are encrypted (Be) and sent over the communication structure (N). Data storage nodes (130) store copies of the encrypted data chunks and meta data blocks (DCe; Be) in an information structure (BN) of block chains of encrypted meta data blocks (OI-1, OI-12, OI-2, OI-23. OI-3) organized in one chain per object of interest (Ol). A user interface (140) forwards any search query (SQ) to an information processing unit (120p); which, in response thereto, presents resulting information (SR) retrieved from the data storage nodes (130).