Client-Side Intelligent Content Indexing for Backup Efficiency
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Solution Overview
Problem
Current content indexing methods in enterprise computing environments are processor and memory intensive, requiring full scanning of backup data for each client, leading to significant storage needs and inefficiencies.
Innovation Solution
Implementing an intelligent content indexing system where a client-side index engine creates an initial full index and incrementally updates it based on changes, reducing the need for full backups and minimizing storage requirements by tracking only delta changes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional content indexing is performed by scanning backed up data on the shared protection server, then complete content indexing is achieved, but processor and memory intensive operations significantly increase server load and operation time
Solution Approach 1:
The patent applies preliminary action by having the client machine create and maintain the content index before data is backed up to the shared protection server. The index is built incrementally as files are added, modified, or deleted on the client, so that when backup occurs, the indexing work has already been completed locally. This eliminates the need for intensive server-side scanning of backup data.
Solution Approach 2:
The client machine performs self-service by autonomously maintaining its own content index without requiring server intervention for indexing operations. The client monitors its own file system changes and updates the index locally, making the indexing process independent of server resources and capabilities.
2Measurement precision
If full scanning of backup data is performed for each client on the shared protection server, then accurate content indexes are created, but significant storage space is required for maintaining indexes of all backed up data
Solution Approach 1:
The patent extracts the indexing function from the centralized backup server and relocates it to the client machine. Only the essential index data (file names, paths, timestamps) is maintained on the client, while the actual backup data is stored on the server. This separation reduces the storage burden on the server.
Solution Approach 2:
The indexing responsibility is segmented from the backup server and assigned to individual client machines. Each client maintains its own independent index, eliminating the need for the server to store and manage indexes for all clients' data. This segmentation distributes the storage requirements across multiple client systems.
3Ease of operation
If centralized backup servers perform all indexing operations, then centralized control is maintained, but the servers become overloaded and indexing efficiency decreases
Solution Approach 1:
The indexing workload is segmented from the centralized backup server and distributed to individual client machines. Each client independently maintains its own content index, which dramatically reduces the processing burden on the server while maintaining centralized backup management capabilities.
Solution Approach 2:
The client machine acts as an intermediary between the file system and the backup server. It maintains a local index that mediates between the need for centralized backup management and the requirement for efficient local content tracking, eliminating the need for the server to perform intensive scanning operations.
Data Source
AI summary
Techniques for intelligent content indexing are disclosed. In one particular exemplary embodiment, the techniques may be realized as a method for performing intelligent content indexing comprising indexing by one or more processes associated with a client an initial full set of data of the client to create an index of the client data, detecting a change in the client data, and modifying the index to reflect the change in the client data.