Machine Resource Forward Purchasing for Ledger Energy Volatility
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Solution Overview
Problem
The increasing complexity and energy intensity of distributed ledger transactions, particularly in markets for energy, compute, and other resources, pose challenges in optimizing energy and compute resource management due to volatility, uncertainty, and variability in resource availability and market conditions.
Innovation Solution
A transaction-enabling system that includes a smart contract wrapper to access distributed ledgers, aggregate data for resource requirements, and utilize intelligent agents to configure and automatically solicit purchases of machine-related resources in forward markets, optimizing resource allocation through machine learning and AI.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If distributed ledger transactions are used for resource management, then transparency and trust are improved, but energy consumption and computational complexity increase
Solution Approach 1:
The system performs forward market purchases of energy and compute resources in advance before they are needed for distributed ledger transactions. By pre-acquiring resources when market conditions are favorable and demand is lower, the system reduces the energy and computational intensity of on-demand transactions while maintaining the reliability benefits of distributed ledgers.
2Productivity
If forward market purchases are implemented, then resource allocation efficiency is improved, but system complexity increases
Solution Approach 1:
The patent introduces specialized intermediary components including a forward market access circuit that connects to external forward markets, an intelligent agent circuit that analyzes market conditions and makes purchasing decisions, and a resource allocation circuit that manages the acquired resources. These intermediary components handle the complexity of forward market operations, allowing the core distributed ledger system to benefit from improved resource allocation without bearing the full burden of market interaction complexity.
3Speed
If automated resource procurement is used, then transaction speed is improved, but adaptability to market conditions deteriorates
Solution Approach 1:
The system incorporates an intelligent agent circuit that continuously monitors market conditions, resource prices, and availability in forward markets. This agent provides feedback to the resource acquisition circuit, enabling dynamic adjustment of purchasing strategies based on real-time market conditions. The feedback loop allows the automated system to adapt its behavior to changing markets while maintaining high transaction speeds through algorithmic decision-making rather than human intervention.
Data Source
AI summary
Systems and methods for forward market purchase of machine resources are disclosed. An example transaction-enabling system may include a fleet of machines, each one of the fleet of machines having a resource requirement comprising at least one of a plurality of machine-related resources and a controller. The controller may include an intelligent agent circuit to aggregate data for the plurality of machine-related resources from at least one data source comprising an external data source or an internal data source; an expert system circuit to configure a purchase of at least one of the plurality of machine-related resources; and a machine resource acquisition circuit to automatically solicit the configured purchase of the at least one of the plurality of machine-related resources in a forward market for at least one resource of the plurality of machine-related resources.