Balanced Data Transfer Resource Provisioning
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Solution Overview
Problem
In cloud computing environments, existing methods for resource provisioning and data transfer optimization often result in suboptimal resource allocation and increased costs due to the lack of a holistic approach that matches resources across the entire data transfer pipeline, leading to inefficiencies and wasteful utilization of resources.
Innovation Solution
A method for provisioning resources that maps available resources across multiple segments of a data transfer path to categories based on relative capacity, ensuring that each segment has resources associated with the same category, thereby creating a balanced data transfer pipeline with closely matched components, and dynamically allocates resources to meet requested service levels without overcommitting higher-capacity resources.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If resources are allocated without holistic matching across the data transfer pipeline, then resource allocation speed is improved, but resource utilization efficiency deteriorates
Solution Approach 1:
The data transfer pipeline is divided into multiple segments (storage segment, network segment, etc.), and resources are matched independently within each segment while maintaining consistency across segments. This segmentation enables efficient allocation by processing each segment separately while ensuring holistic optimization through category-based matching across all segments.
Solution Approach 2:
Resources are categorized based on their capacity parameters (e.g., bandwidth, storage capacity) into different categories. The allocation system then matches resources across segments using these category parameters, ensuring that resources with comparable capacities are selected for each segment, which optimizes overall resource utilization efficiency while maintaining fast allocation through parameter-based decision making.
2Reliability
If higher-capacity resources are allocated to meet requested service levels, then service level compliance is improved, but resource waste increases
Solution Approach 1:
Each segment of the data transfer pipeline is assigned resources based on its specific requirements and the requested service level. The system matches resources locally within each segment while ensuring that the overall pipeline meets the requested service level. This local quality approach prevents allocation of excessively high-capacity resources to segments that do not require them, reducing resource waste while maintaining service level compliance.
Solution Approach 2:
The system allocates resources that are sufficient to meet service level requirements without consistently over-allocating higher-capacity resources. By using category-based matching and holistic optimization, the system applies partial action (allocating only the necessary capacity) rather than excessive action (allocating maximum capacity), thereby reducing resource waste while ensuring service level compliance.
3Loss of energy
If resources are matched across the entire data transfer pipeline, then resource utilization efficiency is improved, but allocation complexity increases
Solution Approach 1:
The complex task of matching resources across the entire data transfer pipeline is segmented into smaller, manageable sub-tasks for each segment (storage segment, network segment, etc.). The system processes each segment independently using category-based matching, which simplifies the allocation logic while achieving holistic optimization through the coordinated selection of resources across all segments.
Solution Approach 2:
The category-based resource matching mechanism serves multiple functions simultaneously: it categorizes resources by capacity, matches resources within segments, ensures consistency across segments, and optimizes overall resource utilization. This universal approach simplifies allocation complexity by using a single framework that handles multiple objectives and constraints.
Data Source
AI summary
A computer program product for provisioning resources in a balanced data transfer pipeline may associate a first requested task with a first category, allocate a first resource of a data path to the first requested task based on the first resource corresponding to the first category; and allocate a second resource as part of the data path to the first requested task based on the second resource corresponding to the first category, wherein the first resource corresponds to a first segment of the data path and the second resource corresponds to a second segment of the data path.