17936950. DYNAMIC SLICING USING A BALANCED APPROACH BASED ON SYSTEM RESOURCES FOR MAXIMUM OUTPUT simplified abstract (Dell Products L.P.)
Contents
- 1 DYNAMIC SLICING USING A BALANCED APPROACH BASED ON SYSTEM RESOURCES FOR MAXIMUM OUTPUT
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 DYNAMIC SLICING USING A BALANCED APPROACH BASED ON SYSTEM RESOURCES FOR MAXIMUM OUTPUT - 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 Unanswered Questions
- 1.11 Original Abstract Submitted
DYNAMIC SLICING USING A BALANCED APPROACH BASED ON SYSTEM RESOURCES FOR MAXIMUM OUTPUT
Organization Name
Inventor(s)
Sunil K. Yadav of Bangalore (IN)
Soumen Acharya of Bangalore (IN)
DYNAMIC SLICING USING A BALANCED APPROACH BASED ON SYSTEM RESOURCES FOR MAXIMUM OUTPUT - A simplified explanation of the abstract
This abstract first appeared for US patent application 17936950 titled 'DYNAMIC SLICING USING A BALANCED APPROACH BASED ON SYSTEM RESOURCES FOR MAXIMUM OUTPUT
Simplified Explanation
The abstract of the patent application describes a method for dynamically adjusting the size of a thread pool based on changes in system resources, crawling a filesystem, identifying crawl jobs, adding them to the thread pool, and performing the crawl jobs.
- Gathering information on filesystem resources
- Identifying thread pool size based on system resource information
- Starting a thread pool with dynamically adjustable size
- Crawling a filesystem and identifying crawl jobs
- Adding crawl jobs to the thread pool
- Performing the crawl jobs
- Slicing data in directories that have been crawled
Potential Applications
This technology could be applied in data management systems, cloud computing platforms, and file synchronization tools.
Problems Solved
This technology solves the problem of efficiently crawling and processing large filesystems while dynamically adjusting resources based on system conditions.
Benefits
The benefits of this technology include improved performance, resource optimization, and scalability in handling filesystem crawling tasks.
Potential Commercial Applications
Potential commercial applications of this technology include data backup solutions, data migration tools, and content management systems.
Possible Prior Art
One possible prior art could be existing filesystem crawling algorithms that do not dynamically adjust resources based on system conditions.
Unanswered Questions
How does this technology handle errors or failures during the crawling process?
This article does not address how the method handles errors or failures that may occur during the crawling process.
What impact does the dynamic adjustment of the thread pool size have on overall system performance?
The article does not provide information on the specific impact of dynamically adjusting the thread pool size on the overall system performance.
Original Abstract Submitted
One example method includes gathering information regarding filesystem resources, based on the system resource information, identifying a thread pool size, starting a thread pool having the thread pool size, where the thread pool size is dynamically adjustable based on changes in the system resources, crawling a filesystem and identifying crawl jobs to be performed, adding the crawl jobs to the thread pool, and performing the crawl jobs. The method may further include slicing data in one or more directories that have been crawled.
