Functional Transactions for Blockchain Audit and Latency
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Solution Overview
Problem
Conventional blockchain processing systems face issues such as loss of transaction semantics, high bandwidth and latency costs, and wasted transactions due to overlapping state changes, as they only record state transitions and rely on a 'frozen state' for consensus, leading to inefficiencies in audit requirements and disaster recovery scenarios.
Innovation Solution
Implementing a distributed computing and storage network that uses functional transactions (FTs) and a blockchain naming system (BNS) to represent transactions as function closures, allowing for parallel processing and optimized block ordering, which encapsulates transaction logic and reduces reliance on a frozen state for consensus.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If conventional blockchain systems record only state transitions without transaction logic, then data storage is minimized, but transaction semantics are lost causing problems for audit requirements and disaster recovery
Solution Approach 1:
The patent segments transaction information into two distinct components: (1) state transitions (read-write sets) that are recorded on the blockchain ledger, and (2) transaction logic/semantics that are captured separately through functional transactions. This segmentation allows minimal storage of state changes while preserving complete transaction semantics in the functional representation, enabling both efficient storage and comprehensive audit capabilities.
Solution Approach 2:
The patent introduces functional transactions as an intermediary mechanism that bridges the gap between state transitions and transaction semantics. The functional transaction captures the logic and reasoning behind state changes without requiring storage of all raw transaction data, serving as a mediator that preserves semantic information in a compact form for audit and recovery purposes.
2Reliability
If large transactions cause widespread updates to data in the state store, then comprehensive state tracking is achieved, but bandwidth and latency costs increase significantly
Solution Approach 1:
The patent extracts the essential transaction logic from large-scale state update operations. By representing transactions as functional transactions that capture the core logic and dependencies, the system can track state changes reliably without transmitting and processing entire large datasets across the network, thereby reducing bandwidth consumption and latency while maintaining comprehensive state tracking.
Solution Approach 2:
The patent changes the parameter representation from raw state data to functional parameters that describe state transitions. This parameter transformation allows the system to track comprehensive state changes using compact functional representations, reducing the amount of data that needs to be transmitted and processed while maintaining reliability of state tracking.
3Stability of the object's composition
If all endorsing peers must achieve consensus on an identical read-write set before commitment, then data consistency is ensured, but overlapping state changes waste good transactions due to network latency
Solution Approach 1:
The patent introduces dynamic transaction representation through functional transactions that can adapt to overlapping state changes. Instead of requiring static consensus on identical read-write sets, the system uses functional representations that can express dependencies and conflicts more flexibly, allowing concurrent transactions to be processed and validated dynamically, thereby improving throughput while maintaining consistency through the functional validation framework.
4Productivity
If transaction logic is not captured in the read-write set, then processing speed is improved, but subsequent audit requirements and replay scenarios cannot be fulfilled
Solution Approach 1:
The patent creates a functional copy or representation of transaction logic that is separate from the raw read-write set. This functional copy captures the essential logic and semantics needed for auditing and replay scenarios without requiring storage and processing of complete transaction details in the main ledger, thus maintaining processing speed while preserving necessary information through the functional representation.
Data Source
AI summary
An example operation may include one or more of constructing a transaction proposal, by a computing system, wherein inputs to the transaction proposal are named using a blockchain naming system (BNS) that comprises ledger state addressing, oracles for addressing external data values, and user state addressing, the BNS providing a standard mechanism to name all blockchain resources using a universal resource indicator (URI).