Volume Placement Scoring for Cloud Storage Optimization
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Solution Overview
Problem
Existing methods for volume placement in cloud storage systems, such as round-robin schemes, fail to optimize resource utilization due to complexity in combining cloud computing and storage platforms, leading to sub-optimal performance and storage issues, especially in heterogeneous clusters.
Innovation Solution
A system comprising a resource tracking component and a volume placement determination component that use an extensible volume placement language schema to determine optimal locations for volume creation, considering various resource constraints and user requirements, thereby improving resource utilization and performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If a simple round-robin scheme is used for volume placement, then the placement process is simple and fast, but resource utilization is sub-optimal and performance deteriorates
Solution Approach 1:
The system performs preliminary actions by pre-calculating resource usage metrics and node scores before volume placement. The resource tracking component continuously monitors and updates resource usage, and the volume placement determination component pre-evaluates candidate nodes using scoring functions, so that when placement is needed, the optimal location can be quickly identified without complex real-time calculations.
Solution Approach 2:
The patent introduces intermediary components between the simple round-robin approach and optimal placement: a resource tracking component that mediates resource usage information, a scoring function that mediates node evaluation, and a volume placement determination component that mediates final placement decisions. These intermediaries transform the simple placement request into an optimized placement while maintaining system modularity.
2Reliability
If volume placement considers multiple resource constraints and uses scoring functions, then resource utilization is optimized, but the system complexity increases
Solution Approach 1:
The system segments the volume placement problem into independent, manageable components: resource tracking (monitoring usage), scoring function evaluation (ranking nodes), and placement determination (final decision). Each component has a specific responsibility and can be implemented, tested, and maintained independently, reducing overall system complexity while achieving reliable optimized placement.
Solution Approach 2:
The scoring function serves as a universal mechanism that can evaluate multiple different resource constraints (storage capacity, network bandwidth, compute resources) through a single unified framework. By making the scoring function multi-functional and configurable, the system can adapt to different placement criteria without adding proportional complexity to each constraint handling.
3Adaptability or versatility
If cloud computing and storage platforms are combined, then service quality improves, but complexity increases leading to sub-optimal volume placement
Solution Approach 1:
The patent introduces intermediary components that bridge the cloud computing and storage platforms: the resource tracking component acts as a mediator between compute and storage resources, the scoring function mediates between different platform requirements, and the volume placement determination component mediates between user needs and platform constraints. These intermediaries enable the combined platform to function as an integrated system rather than separate silos.
Solution Approach 2:
The system performs preliminary actions by pre-establishing resource tracking, pre-defining scoring functions that understand both compute and storage metrics, and pre-evaluating placement options. This preliminary preparation allows the combined cloud computing and storage platform to handle placement decisions efficiently despite the inherent complexity of integrating multiple platform types.
Data Source
AI summary
Systems, methods, and machine-readable media are disclosed for 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, particularly including instructions relating to relationships between volumes to be created. 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.