Resource Label Forest Scheduling for Balanced Multi-Tenant Utilization
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Solution Overview
Problem
Traditional resource scheduling methods fail to meet the differential requirements of tenants and tasks in a multi-tenant scene, leading to inefficiencies and secondary scheduling due to resource utilization imbalances.
Innovation Solution
A resource scheduling method that selects an optimal path through a pre-constructed resource label forest, considering the weights of nodes representing physical and virtual resources, to efficiently allocate tasks and manage resource utilization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional resource scheduling methods are used, then the scheduling process is simple, but the resource utilization is unbalanced and secondary scheduling occurs frequently
Solution Approach 1:
The patent segments the resource scheduling problem into multiple dimensions by introducing a multi-dimensional resource label forest structure. Each dimension (tenant, user, virtual resource, physical resource) is represented as a separate label tree, allowing independent optimization of each dimension while maintaining overall resource allocation efficiency. This segmentation enables balanced resource utilization without requiring complex global optimization algorithms.
Solution Approach 2:
The patent transforms the traditional single-dimension resource scheduling into a multi-dimensional scheduling problem by constructing a resource label forest with multiple label trees representing different dimensions (tenant dimension, user dimension, virtual resource dimension, physical resource dimension). This dimensional transformation allows the system to consider multiple factors simultaneously and achieve better resource utilization efficiency.
2Adaptability or versatility
If multi-tenant differential requirements are not considered, then the scheduling method is simple, but the requirements of different tenants and tasks cannot be met
Solution Approach 1:
The patent applies local quality by assigning different weights to resource labels at different positions in the resource label forest based on their importance and characteristics. Each node in the label forest can have customized weights that reflect local requirements, allowing the system to meet differential requirements of different tenants and tasks while maintaining a unified scheduling framework.
Solution Approach 2:
The patent uses parameter changes by dynamically adjusting the weights of resource labels in the label forest based on tenant requirements, task characteristics, and resource status. This allows the scheduling system to adapt to different scenarios and meet diverse requirements without requiring fundamentally different scheduling algorithms for each case.
3Productivity
If resource allocation does not consider path optimization, then the scheduling decision is fast, but resource utilization efficiency is low
Solution Approach 1:
The patent applies preliminary action by pre-constructing the resource label forest structure and pre-calculating path weights before actual scheduling decisions. This preparation work is done in advance, so when a scheduling decision is needed, the system can quickly query and compare pre-computed paths without performing complex calculations in real-time, thus achieving both high resource utilization and fast decision-making.
Solution Approach 2:
The patent replaces complex mechanical optimization algorithms with a more efficient information-based approach. By representing resources and their relationships in a labeled forest structure with weighted paths, the system substitutes traditional iterative optimization methods with a more direct path-querying mechanism, reducing computational overhead and decision time.
Data Source
AI summary
The present application provides a resource scheduling method and apparatus, an electronic device, and a computer readable storage medium. The method includes: selecting an optimal path from a pre-constructed resource label forest according to a weight of a path in a resource label tree in the resource label forest; and scheduling a task to a third node through which the optimal path passes. The resource label forest includes the at least one resource label tree, and each path of which includes a first node, a second node and the third node in an order from a root node to leaf nodes.