Blockchain Query Decision Layer Indexing Strategy
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Solution Overview
Problem
Conventional systems face high latency and downtime when querying blockchain data, as directly querying blockchain nodes is inefficient and resource-intensive, exacerbated by increasing network traffic and computational power demands, which strain resources and reduce scalability.
Innovation Solution
Implementing a multi-layer data platform with a decision layer that determines when to query blockchain nodes, frequently updates indexed blockchain data, and uses datasets to serve queries, thereby reducing the need for direct blockchain queries and optimizing resource usage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If more nodes are added to the blockchain network, then data availability and redundancy improve, but network traffic increases and infrastructure scalability deteriorates
Solution Approach 1:
The patent introduces an intermediary indexing service that mediates between applications and blockchain nodes. This service pre-processes and indexes blockchain data, allowing applications to query indexed data rather than directly querying nodes. The intermediary absorbs the traffic burden, enabling more nodes to participate without proportionally increasing network traffic strain on the infrastructure.
Solution Approach 2:
The indexing service performs preliminary action by pre-processing and indexing blockchain data before applications need it. By maintaining pre-computed indexes of blockchain data, the system can quickly serve application queries without requiring real-time direct queries to all nodes, thus reducing network traffic while maintaining data availability.
2Measurement precision
If proof-of-work computational power is increased, then transaction validation accuracy improves, but energy consumption and node availability worsen
Solution Approach 1:
The patent extracts the computational validation function from individual nodes and consolidates it into a centralized indexing service. Instead of requiring each node to perform full proof-of-work validation, the system extracts this computationally intensive task and handles it separately, allowing nodes to focus on simpler data storage and retrieval functions, thereby reducing overall energy consumption while maintaining validation accuracy.
3Loss of information
If direct blockchain node queries are used, then data freshness is maintained, but latency and system resource consumption increase
Solution Approach 1:
The indexing service performs preliminary action by continuously pre-processing and indexing blockchain data in the background. This allows the system to maintain data freshness through ongoing index updates while applications can query the pre-indexed data immediately, significantly reducing query latency without sacrificing data freshness.
Solution Approach 2:
The patent creates a copy of the blockchain data in the form of an indexed database. Instead of applications directly querying the original blockchain nodes, they query a copied and pre-processed version of the data. This copy maintains data freshness through synchronization while enabling faster query response times.
Data Source
AI summary
Methods and systems are described herein for a decision layer of a multi-layer data platform. The decision layer may process application queries and serve the queries based on a dataset of previously generated and indexed data or, as a last resort, queries the blockchain node directly. Using indexed blockchain data to serve application queries reduces latency and downtime of traditional systems that direct queries to blockchain nodes immediately. Furthermore, the decision layer overcomes high latency and downtime issues associated with a pool of load-balanced nodes by reducing the number of direct queries to a blockchain. When applications rely on data directly queried from a blockchain, they are susceptible to limited availability, a problem that the decision layer mitigates with indexed and updated blockchain data.