Dell products l.p. (20240103973). LEVERAGING FILE-SYSTEM METADATA FOR DIRECT TO CLOUD OBJECT STORAGE OPTIMIZATION simplified abstract
Contents
- 1 LEVERAGING FILE-SYSTEM METADATA FOR DIRECT TO CLOUD OBJECT STORAGE OPTIMIZATION
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 LEVERAGING FILE-SYSTEM METADATA FOR DIRECT TO CLOUD OBJECT STORAGE OPTIMIZATION - A simplified explanation of the abstract
- 1.4 Simplified Explanation
- 1.5 Potential Applications
- 1.6 Problems Solved
- 1.7 Benefits
- 1.8 Potential Commercial Applications
- 1.9 Possible Prior Art
- 1.10 How does the system ensure data security and privacy in the cloud object storage optimization process?
- 1.11 What are the scalability limitations of the system in managing large volumes of unstructured data in the cloud?
- 1.12 Original Abstract Submitted
LEVERAGING FILE-SYSTEM METADATA FOR DIRECT TO CLOUD OBJECT STORAGE OPTIMIZATION
Organization Name
Inventor(s)
Shelesh Chopra of Bangalore (IN)
LEVERAGING FILE-SYSTEM METADATA FOR DIRECT TO CLOUD OBJECT STORAGE OPTIMIZATION - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240103973 titled 'LEVERAGING FILE-SYSTEM METADATA FOR DIRECT TO CLOUD OBJECT STORAGE OPTIMIZATION
Simplified Explanation
The patent application describes a method and system for optimizing cloud object storage by leveraging file-system metadata for intelligent grouping and object storing of data based on file attribute similarities.
- The system aims to reduce the cost of cloud object storage by optimizing the utilization of resources through intelligent grouping and storing of data.
- By analyzing file attributes and similarities, the system can efficiently manage and store unstructured data in the cloud as objects, providing scalability and cost-effectiveness.
- The method helps in reducing runtime costs associated with read and write operations, as well as storage costs related to disk space allocation for storing file backup copies.
- The system enhances data backup, archiving, and disaster recovery processes by optimizing cloud object storage utilization.
Potential Applications
The technology can be applied in various industries such as data storage, cloud computing, and information management for efficient and cost-effective storage solutions.
Problems Solved
1. High costs associated with cloud object storage due to frequent read and write operations and disk space allocation for storing file backup copies. 2. Inefficient utilization of resources in cloud object storage architecture leading to increased expenses.
Benefits
1. Cost-effective storage solutions for managing unstructured data in the cloud. 2. Enhanced data backup, archiving, and disaster recovery processes through optimized cloud object storage utilization.
Potential Commercial Applications
Efficient data storage solutions for businesses looking to optimize their cloud object storage utilization and reduce costs associated with storage operations.
Possible Prior Art
There may be existing technologies or methods that optimize cloud object storage utilization through intelligent grouping and storing of data based on file attribute similarities. Further research is needed to identify any prior art in this specific area.
Unanswered Questions
How does the system ensure data security and privacy in the cloud object storage optimization process?
The patent application does not provide detailed information on how data security and privacy are maintained during the optimization process. Further clarification is needed on the security measures implemented by the system.
What are the scalability limitations of the system in managing large volumes of unstructured data in the cloud?
The patent application does not address the scalability limitations of the system when managing large volumes of unstructured data. Additional information is required to understand the system's capabilities in handling significant amounts of data efficiently.
Original Abstract Submitted
a method and system for leveraging file-system metadata for direct to cloud object storage optimization. under cloud object storage architecture, any unstructured data may be managed and stored in the cloud as objects. objects thus provide an elastic, scalable format through which unstructured data may be maintained for a variety of purposes, including those directed to data backup, archiving, and/or disaster recovery. cloud object storage, however, tends to be costly—mainly stemming from factors, such as the frequency of read and write operations (also referred to as runtime costs) applied to, as well as the allocation of disk space (also referred to as storage costs) consumed by, any number of objects configured to store file backup copies. in addressing at least the aforementioned, embodiments disclosed herein optimize cloud object storage utilization through the intelligent grouping and object storing of data based on file attribute similarities.
