Data Replication Feedback Mechanism for I/O Optimization
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Solution Overview
Problem
Existing high availability techniques for data management are inefficient as they require re-sending large data segments when storage or replication fails, leading to increased resource consumption and higher costs due to prolonged data retention.
Innovation Solution
Implementing a feedback mechanism that temporarily stores data copies at an alternate location until successful storage and replication are confirmed, allowing for timely removal of redundant data and reducing resource usage by controlling the lifetime of data in the dumpster.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If data is retained at remote location for longer lifetime to ensure availability, then reliability is improved, but I/O performance and storage costs deteriorate due to prolonged data retention and random operations
Solution Approach 1:
The patent implements dynamic data retention by using a feedback mechanism that continuously monitors replication status and adjusts data lifetime accordingly. Data is kept in the dumpster only as long as needed for potential replay, and is automatically removed once replication succeeds, optimizing both reliability and I/O performance through adaptive time management.
Solution Approach 2:
The system employs a feedback mechanism where the dumpster monitors replication status from the destination database and receives notifications when replication succeeds or fails. This feedback loop enables intelligent decision-making about data retention, keeping data only when necessary for recovery purposes and removing it promptly when no longer needed, thus resolving the contradiction between reliability and performance.
2Reliability
If data is re-sent when storage fails to ensure data integrity, then reliability is improved, but resource consumption and costs increase due to additional hardware and software usage
Solution Approach 1:
The patent prepares for potential storage failures by maintaining a pre-copy in the dumpster before replication occurs. This preliminary action ensures that if replication fails, the data is already available for immediate replay without needing to re-send, thus ensuring data integrity while avoiding the resource consumption of repeated transmission.
Solution Approach 2:
The system creates a copy of the data in the dumpster as a backup before replication to the destination database. This copying mechanism provides a local backup that can be replayed if needed, ensuring data integrity without requiring re-sending of data over the network, thereby reducing resource consumption.
3Reliability
If feedback mechanism is implemented to monitor replication status, then data recovery capability is improved, but device complexity increases due to additional monitoring and communication infrastructure
Solution Approach 1:
The destination database automatically sends replication status notifications to the dumpster without requiring complex external monitoring infrastructure. This self-service approach allows the system to monitor its own replication status and trigger appropriate actions, improving data recovery capability while minimizing the addition of complex monitoring devices.
Solution Approach 2:
The patent integrates the feedback mechanism into the existing replication infrastructure by having the destination database directly communicate replication status to the dumpster. This merging of monitoring functions into the existing system reduces the need for separate complex monitoring infrastructure while maintaining robust data recovery capabilities.
Data Source
AI summary
Architecture for efficiently ensuring that data is stored to the desired destination datastore such as for replication processes. A copy of data (e.g., messages) sent to a datastore for storage is stored at an alternate location until a received signal indicates that the storage and replication was successful. As soon as the feedback signal is received, the copy is removed from the alternate location, and hence, improves input/output (I/O) and storage patterns. The feedback mechanism can also be used for monitoring the status of data transport associated with log shipping, for example, and taking the appropriate actions when storage (e.g., replication) is not being performed properly.