Dell products l.p. (20240126442). DATA STORAGE SYSTEM WITH DYNAMIC WORKLOAD ADJUSTMENT BASED ON HEADROOM ESTIMATION simplified abstract
Contents
- 1 DATA STORAGE SYSTEM WITH DYNAMIC WORKLOAD ADJUSTMENT BASED ON HEADROOM ESTIMATION
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 DATA STORAGE SYSTEM WITH DYNAMIC WORKLOAD ADJUSTMENT BASED ON HEADROOM ESTIMATION - 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
DATA STORAGE SYSTEM WITH DYNAMIC WORKLOAD ADJUSTMENT BASED ON HEADROOM ESTIMATION
Organization Name
Inventor(s)
Aleksey Kabishcher of Marlborough MA (US)
Vladimir Shveidel of Pardes-Hana (IL)
Gajanan S. Natu of Cary NC (US)
DATA STORAGE SYSTEM WITH DYNAMIC WORKLOAD ADJUSTMENT BASED ON HEADROOM ESTIMATION - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240126442 titled 'DATA STORAGE SYSTEM WITH DYNAMIC WORKLOAD ADJUSTMENT BASED ON HEADROOM ESTIMATION
Simplified Explanation
The method described in the abstract involves dynamically adjusting the workload of a data storage system based on the saturation value of a saturation metric that scales with the I/O per second rate relative to the maximum IOPS rate of the system.
- The method involves calculating a saturation value while processing a workload.
- The saturation value is compared to high and low thresholds to determine if workload adjustment is needed.
- Workload adjustment operations are performed based on the saturation value being above or below the thresholds.
- The adjusted workload is then processed by the system.
Potential Applications
This technology could be applied in data centers, cloud computing environments, and any system where workload management is crucial for performance optimization.
Problems Solved
1. Efficient workload management in data storage systems. 2. Optimizing system performance based on workload saturation levels.
Benefits
1. Improved system performance. 2. Automated workload adjustment for optimal efficiency. 3. Enhanced scalability of data storage systems.
Potential Commercial Applications
Optimizing workload management in cloud computing services for better customer experience.
Possible Prior Art
Prior art may include workload management systems in data storage environments that adjust based on system performance metrics.
Unanswered Questions
How does this method handle sudden spikes in workload saturation?
The method does not specify how it handles sudden spikes in workload saturation and whether it has mechanisms in place to address such scenarios.
What impact does this workload adjustment have on system stability?
The abstract does not mention the potential impact of workload adjustment operations on the overall stability of the data storage system and whether there are safeguards in place to prevent instability.
Original Abstract Submitted
a method of dynamically adjusting workload of a data storage system includes, while processing a first workload, calculating a saturation value of a saturation metric that scales substantially linearly with an i/o per second (iops) rate relative to a maximum iops rate of the system, determining that the saturation value is one of (1) above a high threshold and (2) below a low threshold, and performing a workload adjustment operation that establishes a second workload by (1) subtracting from the first workload based on the saturation value being above the high threshold, and (2) adding to the first workload based on the saturation value being below the low threshold, then subsequently processing the second workload.
