Cloud Resource Allocation via Segmented Classification

The patent segments cloud resources into distinct categories based on their functional properties (storage capacity, operating speed, upload/download limits). By dividing the heterogeneous resource pool into segmented groups with similar characteristics, the system simplifies the selection process while maintaining access to diverse resource types, thus resolving the contradiction between versatility and allocation complexity.

The patent changes the parameters used for resource identification and allocation by introducing a multi-dimensional classification framework. Instead of treating all resources uniformly, the system evaluates and allocates resources based on multiple parameters simultaneously (storage capacity, speed, bandwidth limits), enabling automated matching between task requirements and resource characteristics, thereby reducing allocation complexity while preserving resource diversity.

The patent implements self-service automation where the system automatically performs resource allocation based on predefined criteria and task requirements. The automated allocation mechanism evaluates available resources, matches them with task demands, and assigns resources without human intervention, dramatically reducing allocation time while maintaining operational flexibility through configurable allocation rules.

The patent applies preliminary action by pre-classifying and organizing cloud resources into categories based on their properties before allocation is needed. This advance preparation creates a structured resource inventory that can be quickly queried and matched with incoming tasks, eliminating the need for manual evaluation during actual allocation and significantly reducing the time required while preserving selection flexibility.

The patent segments cloud resources into systematically classified groups based on functional properties such as storage capacity, operating speed, and bandwidth characteristics. This segmentation creates a structured management framework that enables efficient resource matching and load distribution across multiple resources, improving utilization efficiency while organizing complexity into manageable categories through automated classification.

The patent transforms resource management by introducing systematic classification based on multiple parameters (storage capacity, speed, upload/download limits). This parameter-based organization enables the system to evaluate and allocate resources efficiently by matching task requirements with resource characteristics, thereby improving productivity while the automated classification system manages the inherent complexity without requiring manual intervention.