Inline Data Deduplication in Storage Clusters
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
The process of generating, storing, and backing up data in computing devices inefficiently utilizes computing resources, impacting overall performance due to the lack of effective deduplication and replication strategies.
Innovation Solution
A method and system for storing data in a data cluster that involves deduplicating data received from a host, replicating the deduplicated data across multiple nodes within the cluster, and storing replicas on separate nodes to optimize storage efficiency and resource utilization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If data is replicated before deduplication, then data redundancy is preserved for reliability, but computing resources and storage efficiency are wasted
Solution Approach 1:
The patent applies preliminary action by performing deduplication on data before replication. The system receives data, deduplicates it to remove redundant portions, and then replicates only the unique deduplicated data across multiple nodes. This reverses the conventional order of operations to improve storage efficiency while maintaining reliability through replication of essential unique data.
2Productivity
If deduplication is performed on all data before replication, then storage efficiency is improved, but computational resources and processing time are increased
Solution Approach 1:
The patent applies local quality by differentiating the roles of different nodes in the distributed system. High-performance nodes with greater computational resources are designated to perform deduplication operations, while lower-performance nodes are assigned to store replicas. This local specialization optimizes the overall system by matching tasks to node capabilities, reducing bottlenecks and processing time.
3Speed
If high-performance nodes are used for both deduplication and storage, then processing speed is improved, but resource utilization across the cluster is inefficient
Solution Approach 1:
The patent applies segmentation by dividing the cluster into different functional groups: high-performance nodes dedicated to deduplication operations and lower-performance nodes dedicated to storage. This segmentation allows each node type to be optimized for its specific function, improving overall resource utilization and processing efficiency while maintaining scalability.
Data Source
AI summary
A method for storing data includes receiving, by a data cluster, a request to store data from a host, deduplicating, by the data cluster, the data to obtain deduplicated data on a first data node, replicating the deduplicated data to generate a plurality of replicas, and storing a first replica of the plurality of replicas on a second data node and a second replica of the plurality of replicas on a third data node, wherein the first data node, the second data node and the third data node are in the data cluster.