Multi-Tier Resource Orchestration for Adaptive Load Allocation
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Solution Overview
Problem
Existing systems face limitations in optimizing resource allocation due to varied reliability, speed, efficiency, and accuracy, leading to sub-optimal process performance and results.
Innovation Solution
A system and method for multi-tier resource and load orchestration that includes interfaces for receiving electronic communications, processing them to identify digital identifiers, and mapping resource and load profiles, allowing access to resource and load specifications via a control interface, with features for visualization and user-selectable interface elements to manage allocations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If resources are allocated based on fixed capacities and capabilities, then resource allocation is simple and predictable, but process performance becomes sub-optimal due to inability to adapt to varying loads and conditions
Solution Approach 1:
The patent implements dynamic resource allocation by continuously monitoring resource states and load conditions, then adjusting assignments in real-time. The system transitions from static fixed-capacity allocation to dynamic adaptive allocation where resources can be reassigned based on changing performance conditions, availability, and load requirements to optimize overall process performance.
Solution Approach 2:
The system incorporates feedback mechanisms that monitor resource performance, load conditions, and allocation effectiveness. This feedback loop enables the system to learn from actual performance data and adjust resource assignments accordingly, transforming the allocation system from a closed-loop fixed model to an open-loop adaptive model that continuously improves based on observed outcomes.
2Adaptability or versatility
If resource capacities and capabilities are fixed and limited, then resource management is straightforward and predictable, but availability for handling varying process loads becomes insufficient
Solution Approach 1:
The system dynamically adjusts resource allocation based on real-time monitoring of resource states and load conditions. Resources can be reassigned from lower-priority to higher-priority processes based on changing conditions, enabling the system to adapt capacity allocation rather than relying on fixed predetermined assignments.
Solution Approach 2:
The system changes allocation parameters such as resource assignment, capacity allocation, and priority levels based on monitored conditions. By adjusting these parameters dynamically rather than maintaining fixed values, the system can optimize resource utilization for varying loads while managing the complexity through automated parameter adjustment rules.
3Productivity
If resource allocation is optimized dynamically, then process performance improves, but system complexity and computational requirements increase
Solution Approach 1:
The system performs preliminary actions by pre-establishing allocation rules, priority frameworks, and monitoring thresholds before actual resource assignment occurs. This preparation enables more efficient real-time decision-making by reducing the computational burden during dynamic allocation events, as the system only needs to evaluate pre-defined criteria rather than optimizing from scratch.
Data Source
AI summary
Electronic communications received via a network from a plurality of electronic devices may include signals of device interactions or data changes that correspond to process performances by process-performing resources, signals of conditions of loads, or signals of processes associated with the process-performing resources and the loads. Data composites may be formed from the electronic communications, with data portions collected and mapped to resource profile records and load profile records that may be updated with the collected data portions. For each load, at least one of the one or more resource profile records and/or the one or more load profile records may be used to map the process-performing resources to the load. Content nodes may be linked in a network of content nodes, including respective linked content, resource specifications or load specifications. Access to the network of content nodes may be allowed via a control interface.