Adaptive Data Replication Compression for Storage Systems
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Solution Overview
Problem
Current data protection systems require system shutdowns during backups, limit recovery points, and consume significant time and resources, resulting in potential data loss and inefficiencies in data replication processes.
Innovation Solution
A data replication process that dynamically adapts settings based on link capacity, processor overhead, and operating conditions, allowing for efficient synchronous and asynchronous data replication operations, reducing latency and system resource consumption.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If data compression is applied during replication, then link capacity utilization is improved, but processor overhead increases
Solution Approach 1:
The system dynamically adapts compression settings based on real-time operating conditions, link capacity, and processor overhead measurements. Compression is applied selectively rather than uniformly, adjusting the degree of compression based on current system state to optimize the trade-off between link utilization and processor load.
Solution Approach 2:
The patent changes compression parameters dynamically based on measured system conditions. By monitoring link capacity and processor overhead, the system adjusts compression levels to achieve optimal performance, transforming fixed compression settings into adaptive variable parameters.
2Reliability
If synchronous replication is performed, then data consistency is improved, but latency increases
Solution Approach 1:
The system performs partial synchronous replication by applying compression selectively to only those data blocks that benefit from it, rather than synchronously replicating all data with uniform compression. This partial application of compression reduces overall latency while maintaining consistency for compressed blocks.
Solution Approach 2:
The patent dynamically changes replication parameters based on data characteristics and system conditions. By adjusting compression settings and replication timing based on real-time measurements, the system reduces latency for certain data blocks while maintaining data consistency through selective synchronous replication.
3Loss of time
If asynchronous replication is performed, then latency is reduced, but data consistency deteriorates
Solution Approach 1:
The system dynamically switches between synchronous and asynchronous replication modes based on data characteristics and system conditions. For data blocks where compression is applied, synchronous replication ensures consistency; for other blocks, asynchronous replication reduces latency. This dynamic mode switching resolves the contradiction between consistency and latency.
Solution Approach 2:
Different replication consistency levels are applied to different data blocks based on their characteristics and compression status. Rather than applying uniform asynchronous replication to all data, the system uses local quality differentiation to maintain high consistency for compressed blocks while allowing lower latency for non-compressed blocks.
4Productivity
If compression levels are increased, then data transfer efficiency is improved, but processor overhead increases
Solution Approach 1:
Compression levels are dynamically adjusted based on real-time measurements of link capacity and processor overhead. The system monitors system state and adapts compression intensity accordingly, using higher compression when processor resources are available and link capacity is limited, and reducing compression when processor load is high.
Solution Approach 2:
The patent transforms fixed compression levels into dynamic parameters that change based on system conditions. By measuring link capacity and processor overhead, the system adjusts compression parameters to optimize the trade-off between transfer efficiency and processor overhead, achieving adaptive compression intensity.
Data Source
AI summary
Described embodiments provide systems and processes for performing data replication in a storage system. The data replication operation replicates data from at least one source device to at least one target device of the storage system. A link capacity of a link between at least one source device and at least one target device is determined. Processor overhead associated with one or more data compression processes, and one or more operating conditions of the storage system are determined. Based at least at least in part upon the determined link capacity, the determined processor overhead, and the determined one or more operating conditions, one or more settings of a data replication operation of the storage system are adapted. The data replication operation is performed according to the adapted one or more settings.