Configurable Computing Resource Allocation via Dynamic Valuation
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Solution Overview
Problem
Configurable computing environments face inefficiencies in resource allocation, leading to performance degradation due to inadequate distribution of resources among jobs, resulting in memory depletion, processing errors, and increased latency.
Innovation Solution
A system that analyzes various configurations of resource levels to determine the optimal allocation by combining lower-level resources into intermediate and higher-level resources based on availability and job valuations, ensuring the highest aggregate valuation and efficient job execution.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If resources are repeatedly reassigned or reallocated dynamically to jobs based on job characteristics, then job performance is improved, but resource allocation efficiency deteriorates due to inadequate distribution
Solution Approach 1:
The system dynamically determines resource configurations by evaluating multiple factors including job characteristics, resource availability, and valuation metrics. The resource allocation is not static but adapts based on real-time conditions, allowing the system to optimize both job performance and allocation efficiency simultaneously through dynamic decision-making processes.
Solution Approach 2:
The system changes multiple parameters simultaneously including resource aggregation levels, valuation weights, and allocation strategies. By adjusting these parameters based on computed valuations and availability data, the system resolves the contradiction between improving job performance and maintaining allocation efficiency.
2Adaptability or versatility
If lower-level resources are aggregated into intermediate and higher-level resources, then resource flexibility is improved, but system complexity increases
Solution Approach 1:
The system segments resources into distinct hierarchical levels (lower-level, intermediate-level, higher-level) with clear aggregation rules. This segmentation allows the system to manage complexity by treating each level independently while maintaining overall flexibility through defined aggregation relationships between levels.
Solution Approach 2:
The resource aggregation system serves multiple functions simultaneously: it provides flexibility for different job requirements, enables efficient allocation through hierarchical management, and maintains simplified control through standardized aggregation rules. The same aggregation mechanism handles both resource consolidation and flexibility provision.
3Reliability
If optimal resource configuration is determined through analyzing various configurations, then aggregate valuation is maximized, but processing time increases
Solution Approach 1:
The system performs preliminary analysis of resource configurations and computes valuations in advance before actual job execution. By determining optimal configurations beforehand based on available data, the system reduces real-time processing requirements while maintaining high aggregate valuation decisions.
Solution Approach 2:
The system uses available data and computed valuations to automatically determine optimal configurations without requiring extensive external input or manual intervention. The self-service approach enables rapid configuration determination while maximizing aggregate valuation through algorithmic decision-making.
Data Source
AI summary
In one example, a system can receive configuration data indicating how resources can be combined, identify availability data indicating the total number of various resources that are available, and determine maximum-capacity data using the availability data and the configuration data. The system can also receive distribution data having probability distributions for jobs to be implemented using the resources, determine capacity valuations using the distribution data and the availability data, and determine a configuration of resources using the capacity valuations and the maximum-capacity data. Thereafter, the system can receive a job and determine that a valuation for the job exceeds a predefined threshold associated with using the configuration of resources. In response to determining that the valuation exceeds the predefined threshold, the system can assign the resources to the job in the configuration. The system can then cause the job to be performed using the configuration of resources assigned to the job.