Multidimensional Resource Allocation for Computing Tasks
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Solution Overview
Problem
Current resource allocation systems in computing environments face challenges in efficiently allocating limited resources, as they often require inflexible modeling of resources and lack effective monitoring of resource performance over time, making it difficult to adapt to changing conditions.
Innovation Solution
A method that uses a multidimensional coordinate system to model computing resources, where each coordinate point represents a combination of attributes and is associated with a weight, allowing for dynamic selection of resources based on task constraints and recent performance, ensuring optimal allocation of computing tasks.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If computing resources are modeled in a flexible fashion using multidimensional coordinate systems with weights, then adaptability to changing conditions improves, but device complexity increases
Solution Approach 1:
The patent transitions from traditional flat resource modeling to a multidimensional coordinate system where resources are represented as points in n-dimensional space. Each dimension corresponds to a specific attribute (CPU speed, memory size, storage capacity, etc.), enabling flexible adaptation to changing conditions by adjusting weights and coordinates without fundamental system redesign
Solution Approach 2:
The system dynamically changes parameters (weights associated with each coordinate point) based on monitored resource performance over time. This allows the modeling framework to adapt to changing conditions by modifying parameter values rather than changing the underlying structure, balancing adaptability with manageable complexity
2Productivity
If resource performance is monitored and used to dynamically select resources, then task execution efficiency improves, but loss of time for monitoring and processing increases
Solution Approach 1:
The system pre-calculates and stores weight values for each coordinate point representing resource performance characteristics. By preparing this information in advance and organizing it in a structured multidimensional framework, the system enables rapid resource selection when tasks arrive, minimizing real-time processing delays while maintaining efficient task execution through informed resource allocation
Data Source
AI summary
Described herein are methods and related apparatus for the allocation of computing resources to perform computing tasks. The methods described herein may be used to allocate computing tasks to many different types of computing resources, such as processor cores, individual computers, and virtual machines. Characteristics of the available computing resources, as well as other aspects of the computing environment, are modeled in a multidimensional coordinate system. Each coordinate point in the coordinate system corresponds to a unique combination of attributes of the computing resources/computing environment, and each coordinate point is associated with a weight that indicates the relative desirability of the coordinate point. To allocate a computing resource to execute a task, the weights of the coordinate points, as well as other related factors, are analyzed.