Dynamic Resource Partitioning for Storage Systems
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing resource allocation techniques in computer systems, such as data storage systems, often rely on static limits and fail to dynamically adjust resource usage based on the system's state, leading to inefficiencies and potential resource contention.
Innovation Solution
A method of dynamically determining resource limit ranges for tenants within a system, with lower and upper bounds, and adjusting current resource limits based on the system's compliance or non-compliance state, using state transition criteria to manage resource contention by either reducing or increasing limits accordingly.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If static resource limits are imposed for each storage group, then resource allocation is simple and predictable, but system adaptability to changing resource demands deteriorates
Solution Approach 1:
The patent implements dynamic resource limits that automatically adjust based on real-time system state. The storage system monitors resource usage metrics and dynamically modifies the I/O rate limits for storage groups, transitioning from static to dynamic control. This allows the system to adapt to changing resource demands while maintaining manageable complexity through automated decision-making.
Solution Approach 2:
The patent changes the parameter of resource limits from fixed static values to dynamic values that vary based on system state. By monitoring metrics such as queue depth, response time, and resource utilization, the system adjusts the I/O rate limit parameters in real-time, enabling flexible adaptation to different workload conditions without requiring manual reconfiguration.
2Adaptability or versatility
If dynamic resource limits are implemented based on system state, then system adaptability improves, but control complexity increases
Solution Approach 1:
The patent employs feedback mechanisms where the storage system continuously monitors resource usage metrics and uses this information to adjust resource limits. The system monitors metrics such as queue depth, response time, and resource utilization, and automatically modifies I/O rate limits based on this feedback. This closed-loop control enables adaptive resource management while containing complexity through systematic monitoring and adjustment protocols.
Solution Approach 2:
The storage system performs self-adjustment of resource limits without requiring external intervention. The system autonomously monitors its own state, evaluates resource usage patterns, and automatically modifies allocation parameters. This self-service capability reduces the need for complex external control mechanisms while maintaining high adaptability to changing conditions.
3Stability of the object's composition
If fixed static limits are enforced per storage group, then resource allocation is predictable and stable, but system responsiveness to changing conditions deteriorates
Solution Approach 1:
The patent transitions from static to dynamic resource limits that can change in response to real-time system conditions. The storage system monitors resource usage and dynamically adjusts I/O rate limits, enabling rapid response to changing demands. This dynamic approach maintains stability through controlled adjustment mechanisms while significantly improving responsiveness compared to fixed limits.
Solution Approach 2:
The system implements periodic monitoring and adjustment cycles where resource limits are evaluated and modified at regular intervals or when threshold conditions are met. This periodic action allows the system to maintain stability during normal operation while enabling rapid response to significant changes in resource demands through scheduled review and adjustment cycles.
4Productivity
If resource limits are dynamically adjusted to maximize utilization, then system productivity improves, but risk of resource contention increases
Solution Approach 1:
The patent uses feedback mechanisms to monitor resource usage and adjust limits accordingly. The system continuously tracks metrics such as queue depth, response time, and resource utilization, and modifies I/O rate limits based on this feedback. This enables the system to maximize productivity by increasing limits when resources are underutilized while preventing resource contention by reducing limits when utilization approaches capacity thresholds.
Solution Approach 2:
The system dynamically adjusts resource limits based on real-time conditions, increasing limits to maximize utilization during low-contention periods and reducing limits when resource contention is detected. This dynamic adjustment allows the system to pursue high productivity goals while automatically protecting against resource contention risks through continuous adaptation to system state.
Data Source
AI summary
Described are techniques for partitioning resources. A plurality of resource limit ranges are specified for a plurality of tenants of a system. Each of the plurality of resource limit ranges have a lower bound and an upper bound. A plurality of current resource limits are determined. Each of the plurality of current resource limits indicate a current resource limit for one of the plurality of tenants. Each current resource limit for one of the tenants is a value included in one of the plurality of resource limit ranges specified for the one tenant. The plurality of current resource limits are dynamically determined in accordance with a current state of the system.