Hierarchical Volume Tree for Granular Replication Trigger Control
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional data protection systems face challenges in efficiently managing and replicating large volumes of data across multiple storage devices, particularly in identifying and responding to failures within a hierarchical structure that supports diverse applications and granular management operations.
Innovation Solution
A method and apparatus that utilize a hierarchical volume tree to determine the smallest consistency group with a replication trigger point, allowing for the stopping of replication processes when a failure occurs, thereby ensuring data consistency and enabling management operations at various levels of the hierarchy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If conventional data protection systems use traditional backup methods (tape drives or data replication), then data protection is provided, but the systems cannot efficiently manage and respond to failures in large hierarchical storage structures with millions of devices
Solution Approach 1:
The patent segments the large hierarchical storage structure into consistency groups organized in a tree structure. Each node in the tree represents a consistency group that can be independently managed. When a failure occurs, the system identifies and isolates only the affected consistency group and its descendants, rather than managing failures across the entire storage system. This segmentation enables efficient failure response while handling the complexity of large-scale hierarchical storage.
2Reliability
If the system stops replication for the entire plurality of volumes when a failure occurs, then data consistency is maintained, but replication efficiency is reduced due to unnecessary stopping of unrelated volumes
Solution Approach 1:
The patent applies local quality by designating specific consistency groups as having 'replication trigger point' status. When a failure occurs in a volume, the system determines whether the failure affects a consistency group with trigger point status. If so, replication is stopped only for that specific consistency group and its descendants in the tree, not for the entire storage system. This localized approach maintains data consistency where needed while preserving replication efficiency for unrelated volumes.
3Adaptability or versatility
If the system uses a hierarchical volume tree with consistency groups and replication trigger points, then granular control over replication is achieved, but the complexity of determining the smallest consistency group with trigger point increases
Solution Approach 1:
The patent implements preliminary action by pre-organizing volumes into a hierarchical tree structure with consistency groups and pre-designating which groups have 'replication trigger point' status. This pre-configuration is established before failures occur. When a failure happens, the system simply traverses the pre-built tree to find the smallest consistency group with trigger point status that contains the failed volume, rather than having to compute and determine group relationships dynamically during failure response. This preliminary structuring enables granular control while simplifying the failure response process.
Data Source
AI summary
In one aspect, a method includes receiving notification that a volume in a plurality of volumes has failed, determining a smallest consistency group with a replication trigger point designation using a hierarchical volume tree that includes the failed volume, stopping replication of volumes in a first consistency group if it is determined that the first consistency group is the smallest consistency group with a replication trigger point that includes the failed volume and stopping replication of the plurality of volumes if it is not determined which is the smallest consistency group with a replication trigger point that includes the failed volume.