Storage Bandwidth Allocation for Volume Contention
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Solution Overview
Problem
Conventional storage management systems face challenges in efficiently using bandwidth due to complex manual settings and increased contention between volumes, leading to decreased performance and inefficient resource allocation.
Innovation Solution
A storage management device that acquires load information, calculates the entire bandwidth of a storage area group, and allocates individual bandwidths to each storage area based on a minimum guarantee bandwidth to ensure efficient use and reduce contention.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual band limit settings are specified for each volume, then performance adjustment is possible, but the setting becomes complicated and bandwidth utilization efficiency decreases
Solution Approach 1:
The storage management device automatically determines and adjusts band limits for each volume based on actual load information and pool status, eliminating the need for manual administrator settings. The system serves itself by autonomously optimizing bandwidth allocation according to real-time conditions.
Solution Approach 2:
The system dynamically changes band limit parameters based on varying load conditions and pool status. Instead of fixed manual settings, the band limits are continuously adjusted according to actual usage patterns and system state, optimizing performance adaptively.
2Reliability
If bandwidth of a single volume is adjusted manually, then performance of that volume improves, but contention occurs with other volumes and overall performance decreases
Solution Approach 1:
The system merges the bandwidth allocation decisions for all volumes into a unified management approach. Instead of independently adjusting each volume's bandwidth, the system considers the entire pool status and load distribution across all volumes simultaneously, optimizing overall bandwidth utilization while maintaining individual volume performance.
Solution Approach 2:
The system dynamically adjusts band limit parameters for each volume based on real-time load information and pool status, rather than using fixed manual settings. This allows automatic optimization of both individual volume performance and overall bandwidth utilization according to actual conditions.
3Speed
If automatic band adjustment uses most recent data, then responsiveness improves, but bandwidth gradually decreases leading to inefficient utilization
Solution Approach 1:
The system uses both recent load information and historical pool status information to determine optimal band limits. By incorporating multiple time dimensions of data, the system achieves responsive adjustment while avoiding the gradual bandwidth decrease that occurs with purely recent data-based approaches.
Solution Approach 2:
The system implements feedback mechanisms that consider both current load conditions and historical pool status. This multi-dimensional feedback approach allows the system to respond quickly to changes while maintaining efficient long-term bandwidth utilization through learned patterns and trends.
Data Source
AI summary
A monitoring unit acquires load information on a Tier pool that includes therein a plurality of volumes. A maximum performance calculating unit calculates, on the basis of the load information on the volumes acquired by the monitoring unit, an entire bandwidth of the Tier pool. A bandwidth management unit calculates, on the basis of the minimum guarantee bandwidth for each of the predetermined volumes, each of individual bandwidths such that the sum total of the individual bandwidths allocated to the respective volumes corresponds to the entire bandwidth calculated by the maximum performance calculating unit 101 and allocates the calculated individual bandwidths to the respective volumes.