Unified Resource Allocation Dashboard for Cross-Network Optimization
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Solution Overview
Problem
Entities face inefficiencies in managing and optimizing resource allocations across multiple disparate network-based resource store systems, leading to wasted network and computational resources, and sub-optimal strategies due to lack of comprehensive comparison data.
Innovation Solution
A resource allocation optimization system that provides a unified interface to view and optimize resource allocations across multiple systems, utilizing entity grouping and machine learning to suggest adjustments based on similar entities' strategies.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If entities monitor and update resource allocations across multiple disparate network-based resource store systems using separate interfaces, then comprehensive resource allocation data can be obtained, but interface navigation time and network resource waste increase
Solution Approach 1:
The patent combines multiple disparate resource store interfaces into a single unified interface that displays resource allocation data from multiple resource stores simultaneously. This allows entities to view and manage allocations across Bitcoin, Ethereum, and other networks in one location, eliminating the need to navigate multiple separate interfaces and reducing time loss while maintaining comprehensive data access.
2Loss of information
If entities access multiple separate resource allocation systems to view resource allocations, then complete allocation information is available, but network and computational resources are wasted
Solution Approach 1:
The system merges multiple resource allocation queries into a single unified interface access point. By consolidating the display of allocation data from multiple resource stores (Bitcoin, Ethereum, etc.) into one interface, the system reduces redundant network requests and computational overhead while maintaining complete information availability.
Solution Approach 2:
The unified interface acts as an intermediary layer between entities and multiple resource store systems. It aggregates data from various sources and presents it through a single access point, reducing the number of direct connections needed and minimizing network and computational resource consumption while preserving data completeness.
3Ease of operation
If entities implement resource allocation strategies without comparison data from similar entities, then autonomous decision-making is maintained, but optimization effectiveness decreases
Solution Approach 1:
The system implements feedback by comparing an entity's resource allocation strategy with strategies from similar entities (e.g., other whales or institutions). The unified interface provides this comparative data, allowing entities to see how their allocations compare to peers and make informed adjustments while maintaining autonomous decision-making authority.
Solution Approach 2:
The system enables entities to copy or replicate successful allocation strategies from similar entities. By displaying comparative data and successful strategies from peer entities, users can replicate proven approaches while maintaining the flexibility to adapt to their specific circumstances, thereby improving optimization effectiveness without losing autonomous decision-making.
Data Source
AI summary
Disclosed in some examples are methods, systems, devices, and machine-readable mediums for resource allocation optimization systems that provide one or more interfaces that display an entity's resource allocation data from multiple sources in a single interface. Also disclosed in some examples are resource allocation optimization systems which provide resource allocation adjustments for an entity to optimize resources toward a resource optimization goal. The resource allocation optimization system groups similar entities using rule-based or artificial intelligence algorithms acting upon entity description data (including in some examples, resource allocation data) obtained from the entity and/or from external network-based services. The resource allocation optimization system uses resource allocation data of entities within a group to provide resource allocation adjustments to entities within the group via improved user interfaces. The resource allocation adjustments are selected to meet one or more resource optimization goals.