IoT Data Hashing and Blockchain Storage Segmentation
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Solution Overview
Problem
Managing large volumes of IoT data efficiently and securely, particularly in preventing data tampering, is a significant challenge due to the limited capacity of blockchain systems and the need for efficient querying and storage.
Innovation Solution
A method involving IoT data aggregation patterns, hashing, and storage in a blockchain system, where data is reorganized based on hierarchical structures to generate hash values, allowing for secure and efficient storage and retrieval, with hash indexes facilitating quick data access and tamper detection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If all IoT data is stored directly in the blockchain system, then data security and integrity are improved, but the blockchain system becomes overwhelmed due to its limited capacity
Solution Approach 1:
The patent segments IoT data into two parts: hash values are stored in the blockchain system while the actual IoT data is stored in an external database. This segmentation allows the blockchain to maintain security guarantees without being overwhelmed by the full volume of IoT data, resolving the contradiction between data security and blockchain capacity.
2Productivity
If hash values of IoT data are stored in the blockchain system, then storage efficiency is improved, but data retrieval becomes more complex
Solution Approach 1:
The patent implements a feedback mechanism where the system continuously monitors data access patterns and dynamically adjusts the aggregation granularity and hash indexing strategies. This feedback loop optimizes the balance between storage efficiency and retrieval complexity by adapting to actual usage patterns.
Solution Approach 2:
The patent introduces dynamic aggregation patterns that can adjust the level of data aggregation based on access frequency and data types. Frequently accessed data maintains finer granularity while less accessed data is aggregated more aggressively, making the retrieval complexity adaptive rather than static.
3Productivity
If data aggregation patterns are applied to IoT data, then storage scalability is improved, but the system complexity increases
Solution Approach 1:
The patent changes key parameters such as aggregation granularity, hash function selection, and indexing depth based on data characteristics and access patterns. By dynamically adjusting these parameters, the system achieves scalability without requiring a complete redesign of the architecture for different scenarios.
Data Source
AI summary
Blockchain based IoT data management can include receiving IoT data are with one or more processing units. At least one aggregation pattern of the IoT data can be determined by one or more processing units. The IoT data can be hashed, based upon the at least one aggregation pattern to obtain hash values of the IoT data by one or more processing units. The hash values can be sent to a blockchain system for storing by one or more processing units.