Target Allocation Parameters for Timed Resource Communications
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Solution Overview
Problem
Efficient allocation of limited resources in complex computing networks is crucial for successful execution of operations, as resources such as material, energy, and computing power are often finite and time-limited.
Innovation Solution
A method and system for determining target allocation parameters involves establishing communication channels with computing devices, receiving and processing data on execution events, generating allocation graphs, and determining target parameters for initiating targeted communications based on instantaneous and remaining available allocations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If resources are allocated to multiple execution events simultaneously, then resource utilization efficiency improves, but resource availability for individual events decreases
Solution Approach 1:
The system dynamically adjusts resource allocation parameters based on real-time execution event data and allocation graphs. Allocation parameters are not fixed but adapt to changing conditions, allowing the system to optimize resource utilization while maintaining adequate availability for individual events through continuous adjustment of timing, frequency, and quantity parameters
Solution Approach 2:
The system changes allocation parameters (timing, frequency, quantity) based on analyzed execution event data and allocation graphs. By modifying these parameters dynamically, the system achieves improved resource utilization efficiency while ensuring sufficient resource availability for each execution event through parameter optimization
2Productivity
If resource allocation is optimized for future periods, then operational efficiency improves, but flexibility to respond to immediate resource needs decreases
Solution Approach 1:
The system performs preliminary analysis of execution events and generates allocation graphs that forecast resource needs for future periods. This preliminary action enables optimized resource allocation planning while maintaining flexibility through the ability to adjust parameters based on actual conditions as they arise, balancing advance planning with adaptive response
Solution Approach 2:
The system uses feedback from analyzed execution event data to continuously refine allocation parameters. By incorporating feedback loops that analyze actual resource consumption and execution outcomes, the system maintains operational efficiency through optimized allocation while preserving flexibility to adapt to immediate needs based on real-time feedback
Data Source
AI summary
This disclosure is directed to systems and methods for determining target allocation parameters for initiating targeted communications in complex computing networks, which may be associated with the allocation of allocatables in execution events over a period of time. The systems and methods may include receiving a desired allocation; determining a first available allocation at a first time; generating allocation information for a second period comprising the first time; determining a second available allocation at a second time; determining a remaining available allocation, based on the allocation information and the second available allocation; and determining one or more target allocation parameters for initiating a targeted communication to a computing device after the second time.