Pure blockchain solution for time series data.
The lab explores a non-intrusive method which is used to expand the storage and processing capabilities of the existing blockchain platform for time series data without damaging the decentralization feature of the blockchain, so that the blockchain can support more service scenarios, including IoT scenarios.
The current blockchain platform or implementation has the following problems: Most blockchain platforms in the industry support only KV data storage, but not complex data storage. (relational data, streaming data, time series data, etc.); Currently, the smart contract of most blockchain platforms in the industry support only KV-type data storage and read interfaces, or enhanced query capabilities for pre-specified data types. (relational data, streaming data, time series data, etc.) OLTP (basic operation) and OLAP (advanced analysis) capabilities; If you need to support complex types of data processing and analysis capabilities, you need to intrusively modify the code of the blockchain platform, which is a very difficult development task and faces the problem of open source maintainence.
The lab provides the solution to support timepoint data stored based on IoT time series database convergence with blockchain, thus the data can be written, read, aggregated, and analyzed through smart contract. For data aggregation and analysis tasks with a long time line and a large amount of data, parallel computing can be used to accelerate task execution based on the multi-point storage feature of blockchain. Supports latency-sensitive service scenarios (such as traffic governance). Finally, a pure on-link solution can be implemented for IoT time series data, which does not depend on off-link components. Data storage, aggregation, computing, and query can be completely decentralized. It is not bound to a blockchain platform or time series database. You can use plug-ins to flexibly expand the application scenarios (such as Hyperledger Fabric and GaussDB).
Enter the Github IDs for the set of initial committers.