Linked Blockchain Instances for Multi-Process Tracking
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Solution Overview
Problem
Current blockchain systems lack an efficient method to track and align multi-step processes across multiple blockchain instances, leading to suboptimal execution times and resource utilization.
Innovation Solution
The creation of instance blockchains linked to a generic blockchain, allowing for parallel or serial execution of processes through the use of linking operations and change evidence data to update blockchain instances, facilitating cascading blockchains and alignment of equivalent blocks.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If multiple blockchain instances are used to track multi-step processes, then tracking capability and process monitoring are improved, but system complexity and resource consumption increase
Solution Approach 1:
The system divides the blockchain tracking function into multiple independent blockchain instances, where each instance is dedicated to tracking a specific multi-step process. This segmentation allows each instance to operate independently with optimized resource allocation, improving process tracking reliability while managing system complexity through modular architecture.
Solution Approach 2:
The blockchain system implements universal linking operations that can connect any blockchain instance to any other instance or to a generic blockchain, creating a multi-functional framework. This universality allows the same blockchain infrastructure to serve multiple different process tracking purposes simultaneously, improving reliability without proportionally increasing complexity.
2Manufacturing precision
If blockchain instances execute processes serially, then execution accuracy is maintained, but overall execution time increases
Solution Approach 1:
The system dynamically adjusts the execution mode of blockchain instances based on process requirements and resource availability. Instances can switch between serial execution (for accuracy-critical processes) and parallel execution (for time-sensitive processes), with the linking operations coordinating state transitions to maintain accuracy while reducing overall execution time through adaptive scheduling.
Solution Approach 2:
The system performs preliminary alignment of equivalent blocks across blockchain instances before process execution begins. This preliminary action establishes the correct initial state relationships between instances, enabling them to execute in parallel with confidence that accuracy will be maintained, thereby reducing execution time without sacrificing precision.
3Productivity
If blockchain instances execute in parallel, then execution speed increases, but resource conflicts and synchronization issues arise
Solution Approach 1:
The generic blockchain serves as an intermediary layer between multiple instance blockchains, mediating resource allocation and synchronization. The linking operations use this intermediary to coordinate state changes across parallel instances, ensuring that resource conflicts are resolved through a centralized arbitration mechanism while maintaining high execution speed through parallel processing.
Solution Approach 2:
The system implements feedback mechanisms where the state of each blockchain instance is continuously monitored and reported to the linking operation layer. This feedback enables dynamic adjustment of parallel execution parameters, resource allocation, and synchronization timing, allowing the system to maintain high productivity while preventing resource conflicts through real-time coordination.
4Measurement precision
If change evidence data is frequently updated across blockchain instances, then data accuracy is improved, but network overhead and processing load increase
Solution Approach 1:
The system merges change evidence data updates across multiple blockchain instances by identifying and consolidating redundant updates. When equivalent blocks in different instances require the same type of update, the system performs a single update operation and propagates it to all relevant instances, maintaining data accuracy while significantly reducing network overhead and processing load.
Solution Approach 2:
The system applies local quality optimization by updating only the specific portions of blockchain instances that require changes based on received evidence data, rather than performing blanket updates across all instances. The linking operations intelligently determine which instances and which blocks within instances need updates, minimizing unnecessary network traffic and processing while maintaining data accuracy where needed.
Data Source
AI summary
A system, method, and computer-readable storage medium is provided for creating first and second blockchain instances, each comprising representative blocks corresponding to steps in first and second multistep processes, respectively; performing a linking operation to link a block in the first blockchain instance to a block in the second blockchain instance; receiving change evidence data pertaining to steps in one of the first and second multi-step processes; and performing an update operation comprising updating one of the first and second blockchain instances based on said change evidence data.