Weighted Resource Allocation to Prevent Over- and Under-Subscription
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Solution Overview
Problem
Existing methods for distributing resources among multiple entities do not consider minimization of overall resource usage, leading to potential wastage and increased costs.
Innovation Solution
A method for optimizing resource allocation by computing weights for each consumer and determining the least upper bound of resources needed, ensuring efficient distribution based on relative requirements of parallel entities.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of energy
If resources are divided among requesting entities using existing methods, then resource distribution is achieved, but overall resource usage is not minimized leading to wastage and increased costs
Solution Approach 1:
The patent changes the allocation parameters by computing weights for each resource consumer based on their relative requirements and computing total resource usage to determine the least upper bound. This parameter-based optimization approach minimizes overall resource usage while ensuring adequate distribution to all consumers, directly resolving the contradiction between resource usage efficiency and distribution effectiveness
Solution Approach 2:
The patent implements a feedback mechanism by computing total resource usage and comparing it against the least upper bound determination. This feedback loop allows the system to adjust allocations dynamically, ensuring that resources are distributed effectively while minimizing wastage, thereby resolving the technical contradiction
2Ease of operation
If resources are allocated without optimization, then allocation is simple, but over- and under-subscription occurs leading to inefficiency
Solution Approach 1:
The patent performs preliminary actions by computing weights for each resource consumer and determining the least upper bound of total resource usage before actual allocation. This preliminary computation ensures that the subsequent allocation is both accurate and reliable, preventing over- and under-subscription while maintaining a systematic approach that balances simplicity with precision
3Ease of manufacture
If traditional resource division is used, then implementation is straightforward, but resource wastage and increased costs occur
Solution Approach 1:
The patent enables the resource allocation system to self-optimize by automatically computing weights, determining least upper bounds, and allocating resources based on computed parameters. This self-service approach minimizes resource wastage through intelligent optimization while keeping implementation relatively straightforward by automating the optimization process, thereby resolving the contradiction between implementation ease and resource wastage prevention
Data Source
AI summary
A method for resource allocation optimization. The method includes: selecting a resource type from resources on a host system; computing, based on the resource type, a plurality of weights including a weight for each resource consumer of a plurality of resource consumers on the host system; computing, of the resource type, a total resource usage based on the plurality of weights and a division of available resource type units; making a determination that the total resource usage equals one; and allocating, based on the determination, a number of available resource type units of the resource type amongst the plurality of resource consumers.


