Volume Placement Optimization via Resource Scoring
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Solution Overview
Problem
Existing cloud storage systems face challenges in optimizing volume placement due to the complexity of combining cloud computing and storage platforms, leading to sub-optimal resource utilization and performance issues, especially in heterogeneous environments.
Innovation Solution
A system comprising a resource tracking component and a volume placement determination component that use an extensible volume placement language schema and scoring functions to determine the optimal location for creating volumes, considering various resource constraints and customer requirements, thereby improving resource utilization and performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If a simple round-robin scheme is used for volume placement, then the placement process is simple and fast, but resource utilization becomes sub-optimal and performance issues arise
Solution Approach 1:
The patent changes the placement criteria from simple sequential indexing (round-robin) to multi-parameter optimization considering network resources, storage capacity, compute availability, and latency. This transforms the placement decision from a single-parameter (index-based) to multi-parameter optimization, resolving the contradiction between simplicity and efficiency.
Solution Approach 2:
The patent introduces an intermediary optimization layer that sits between the simple round-robin placement and the actual volume creation. This intermediary evaluates multiple resource parameters and determines optimal placement, thereby improving resource utilization without requiring complete redesign of the placement system.
2Reliability
If cloud computing and storage platforms are combined, then service quality for users improves, but system complexity increases leading to sub-optimal volume placement
Solution Approach 1:
The patent segments the complex combined system into distinct resource types (network resources, storage resources, compute resources) that can be independently evaluated. By dividing the resource evaluation into separate trackable components, the system manages complexity while maintaining service quality through optimized placement decisions.
Solution Approach 2:
The patent creates a universal resource tracking and evaluation framework that handles multiple resource types (network, storage, compute) through a single multi-parameter optimization system. This universal approach manages the complexity of combined platforms while improving service quality through coordinated resource utilization.
3Device complexity
If volume placement does not consider network resources, then the placement process is simpler, but networking bottlenecks and performance issues occur
Solution Approach 1:
The patent performs preliminary evaluation of network resources and other system parameters before actual volume placement occurs. By pre-assessing network capacity, latency, and resource availability, the system avoids placement decisions that would cause bottlenecks, thereby improving networking performance without excessive complexity during the actual placement execution.
Data Source
AI summary
Systems, methods, and machine-readable media are disclosed for collecting, maintaining, and retrieving use and limit data for connected resources, as well as determining an optimal location for creating a new volume (or volumes) on a storage platform and placing the volume at the determined location. A resource tracker collects resource use and/or limits data and stores it in a database. A volume placement service receives a volume deployment specification having constraints for creating a new volume. The volume placement service retrieves the data from the database. The volume placement service identifies an optimal location for the volume based at least in part on given constraints from the specification and the resource usage data. The system places the requested volume at the determined location.