Multi-Objective QoS Management for Consistent Storage Performance
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Solution Overview
Problem
Current storage systems face challenges in managing Quality of Service (QoS) due to limitations in configuring volumes based on a single QoS objective, leading to inconsistent performance and inefficient resource utilization.
Innovation Solution
A QoS management mechanism that receives multiple QoS parameters and client preferences to manage policies based on IOPS, throughput, and latency, using a management system with provisioning, monitoring, and adjustment engines to ensure compliance with defined objectives.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If QoS policies are configured based on a single QoS objective, then the configuration is simple, but the performance becomes inconsistent and resource utilization is inefficient
Solution Approach 1:
The patent segments QoS management into multiple independent objective functions (IOPS, throughput, latency) that can be configured and monitored separately. Each objective is evaluated independently through distinct monitoring mechanisms, allowing the system to manage complex multi-objective QoS policies while maintaining configurability and performance consistency.
2Device complexity
If QoS policies are configured based on a single QoS objective, then the configuration is simple, but resource utilization becomes inefficient
Solution Approach 1:
The patent implements dynamic QoS policy adjustment by continuously monitoring multiple objectives (IOPS, throughput, latency) and automatically adjusting policies based on real-time system conditions. This dynamic approach enables the system to optimize resource utilization efficiency while managing configuration complexity through automated multi-objective evaluation and adjustment mechanisms.
3Reliability
If multiple QoS parameters are managed dynamically, then performance consistency is improved, but the system complexity increases
Solution Approach 1:
The patent employs feedback mechanisms that continuously monitor multiple QoS objectives (IOPS, throughput, latency) and automatically adjust policies based on monitored performance. This feedback-driven approach improves performance consistency by dynamically responding to system conditions while managing complexity through automated control loops that eliminate the need for manual intervention in multi-objective QoS management.
4Ease of operation
If QoS policies are statically configured, then the system is easier to manage, but sluggish performance occurs when IOPS are insufficient
Solution Approach 1:
The patent implements preliminary action by pre-configuring multiple QoS objectives (IOPS, throughput, latency) and establishing monitoring mechanisms in advance. This allows the system to proactively detect when IOPS or other performance metrics fall below thresholds and automatically adjust policies before sluggish performance occurs, maintaining ease of operation through automated prevention rather than reactive manual intervention.
Data Source
AI summary
A system is described. The system includes a processing resource and a non-transitory computer-readable medium, coupled to the processing resource, having stored therein instructions that when executed by the processing resource cause the processing resource to receive a plurality of quality of service (QoS) parameters and client preferences from a client device and manage a QoS policy based on a plurality of QoS objectives included in the received QoS parameters, wherein the plurality of QoS objectives comprise input output operations per second (IOPS), throughput and latency.