Soft Capacity Constraints for Distributed Storage Assignment
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Solution Overview
Problem
Cloud computing systems face challenges in efficiently managing data storage across distributed data centers, as maintaining large growth buffers is costly while maintaining too small buffers can lead to storage errors.
Innovation Solution
The implementation of soft buffers to control data storage balancing among computing devices, using an assignment solver to analyze storage costs and optimize project assignments to minimize storage costs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If large growth buffers are maintained to prevent storage errors, then storage reliability is improved, but storage costs increase due to large amounts of idle storage
Solution Approach 1:
The patent applies dynamics by making growth buffers flexible rather than static. The system dynamically adjusts buffer allocation based on real-time storage conditions, allowing buffers to expand when needed and contract when not required, thus preventing storage errors while minimizing idle storage capacity.
Solution Approach 2:
The patent changes the parameter of buffer size from a fixed value to a variable that can be adjusted based on system conditions. By modifying buffer allocation parameters dynamically according to storage utilization and demand patterns, the system achieves both reliability and cost efficiency.
2Loss of energy
If small growth buffers are maintained to reduce idle storage costs, then storage costs decrease, but storage errors may occur as projects grow over time
Solution Approach 1:
The patent implements feedback mechanisms that continuously monitor storage usage and automatically adjust buffer allocation. When storage utilization approaches buffer limits, the system receives feedback and dynamically expands buffers to prevent errors, while contracting buffers when utilization is low to reduce costs.
Solution Approach 2:
The system performs self-service by automatically managing its own buffer allocation without external intervention. The storage management system monitors its own state and adjusts buffer sizes autonomously based on actual demand, eliminating the need for manual buffer configuration while maintaining both cost efficiency and reliability.
3Productivity
If strategic data storage is implemented by identifying projects with shared data sets and storing them on the same computing device, then data access efficiency is improved, but storage balancing complexity increases
Solution Approach 1:
The patent merges the objectives of improving data access efficiency and maintaining storage balance into a single unified approach. By co-locating projects with shared data sets on the same computing device while simultaneously implementing dynamic buffer management, the system achieves both goals without requiring separate complex management mechanisms.
Solution Approach 2:
The storage management system performs multiple functions simultaneously: it identifies projects with shared data sets, determines optimal storage locations for improved access efficiency, and dynamically manages buffer allocation. This multi-functionality reduces the need for separate specialized mechanisms, thereby managing complexity while achieving multiple objectives.
Data Source
AI summary
A system and method for balancing data storage among a plurality of groups of computing devices, each group comprising one or more respective computing devices, each group having an available storage capacity. The method may involve, for each group of computing devices, determining an amount of used storage at the group of computing devices exceeding a predefined first threshold value that is less than the available storage capacity and calculating a storage cost based on the determined amount of used storage exceeding the predefined first threshold value, determining a total storage cost of the plurality of groups of computing devices based on a sum of the calculated storage costs, determining a transfer of one or more projects between the groups of computing devices that reduces the total storage and directing the plurality of groups of computing devices to execute the determined transfer.