Distributed Object Storage Parallel Search Zones
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Solution Overview
Problem
Current data storage systems face inefficiencies in searching and managing large volumes of data across distributed storage zones, particularly in efficiently replicating and searching metadata across geographically dispersed networks.
Innovation Solution
The implementation of a distributed data storage system with multiple storage zones that utilize object-based storage, where data is partitioned into objects with policy identifiers for replication and searchability, and an object database is used to index metadata for efficient searching, allowing parallel search operations across zones.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If data is stored in a distributed data storage system across multiple storage zones, then data resiliency is improved, but search speed deteriorates due to the need to search across geographically dispersed networks
Solution Approach 1:
The patent divides the distributed storage system into multiple storage zones, each with its own metadata database. Search operations are segmented to query only local metadata first, then proceed to remote zones only if necessary. This segmentation allows parallel search operations across zones while maintaining data resiliency through distributed storage.
2Productivity
If metadata is replicated across multiple storage zones for efficient searching, then search throughput is improved, but device complexity increases due to replication management
Solution Approach 1:
The system performs preliminary actions by pre-replicating metadata to multiple storage zones before search operations occur. Each storage zone maintains a local copy of metadata, enabling parallel search operations without requiring complex real-time coordination during actual searches. This preliminary replication reduces search throughput latency while managing complexity through standardized replication protocols.
3Ease of operation
If data is partitioned into objects with policy identifiers for replication, then ease of operation is improved, but processing load increases due to policy evaluation
Solution Approach 1:
The patent applies local quality by evaluating replication policies locally at each storage zone based on object characteristics and zone capabilities. Each zone independently determines which objects to replicate and store based on local policy interpretation, eliminating the need for centralized policy evaluation for every object. This reduces overall processing load while maintaining ease of operation through consistent policy enforcement.
Data Source
AI summary
A searchable data storage system is described herein. The storage system includes zones that are independent, and autonomous from each other. The zones include nodes that are independent and autonomous. The nodes include storage devices. When a data item is stored, a local database is updated with information about the newly stored data item. When a search for a data item meeting certain metadata criteria is received, multiple concurrent searches are conducted across all storage devices in all nodes in all zones of the storage system. The configuration of the data storage system allows a parallel concurrent search at constituent storage devices to be performed quickly.