Target Allocation Parameters Using Time-Based Resource Graphs
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Solution Overview
Problem
Efficient allocation of limited resources in complex computing networks is challenging due to finite availability and time constraints, necessitating improved methods for determining target allocation parameters for targeted communications.
Innovation Solution
A method involving establishing network communication channels with computing devices to receive and analyze execution event data, generate allocation graphs, and determine target allocation parameters for initiating targeted communications based on instantaneous and remaining available allocations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If resources are allocated in complex computing networks, then resource utilization improves, but resource availability constraints worsen
Solution Approach 1:
The system performs preliminary actions by generating allocation graphs that predict future resource availability before actual allocation decisions are made. This allows the system to plan resource distribution in advance, considering time-dependent availability constraints, and make informed allocation decisions that maximize utilization while respecting resource limits.
Solution Approach 2:
The system dynamically adjusts resource allocation parameters based on real-time network conditions and changing resource availability. The allocation graphs are continuously updated with new execution event data, allowing the system to adapt to dynamic constraints and optimize resource utilization as conditions evolve.
2Productivity
If allocation parameters are determined for targeted communications, then communication efficiency improves, but system complexity worsens
Solution Approach 1:
The system segments the complex resource allocation problem into manageable components by creating allocation graphs that separate time-dependent availability data from communication parameter optimization. This segmentation allows independent analysis and optimization of each component, reducing overall system complexity while maintaining communication efficiency.
Solution Approach 2:
The allocation graph serves as an intermediary data structure that mediates between raw execution event data and final communication parameter decisions. This intermediary layer simplifies the complexity by providing a structured representation of resource availability that can be easily queried and used to determine optimal communication parameters.
3Measurement precision
If instantaneous available allocation is calculated for each execution event, then allocation accuracy improves, but computational overhead worsens
Solution Approach 1:
The system performs preliminary calculations by pre-computing allocation graphs that capture resource availability trends before actual allocation decisions are needed. This preliminary action reduces the computational overhead during real-time operations, as the system can query pre-computed data rather than performing full calculations for each execution event.
Solution Approach 2:
The system calculates allocation information at different levels of detail depending on the specific needs of each query. Rather than performing complete instantaneous available allocation calculations for every possible parameter, the system computes only the necessary portion of allocation data required for each specific decision, reducing overall computational overhead while maintaining necessary accuracy.
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.