18182861. SYSTEM AND METHOD FOR MANAGING OPERATION OF DATA PROCESSING SYSTEMS TO MEET OPERATIONAL GOALS simplified abstract (Dell Products L.P.)
Contents
SYSTEM AND METHOD FOR MANAGING OPERATION OF DATA PROCESSING SYSTEMS TO MEET OPERATIONAL GOALS
Organization Name
Inventor(s)
DEEPAGANESH Paulraj of Bangalore (IN)
ASHOK NARAYANAN Potti of Bangalore (IN)
SYSTEM AND METHOD FOR MANAGING OPERATION OF DATA PROCESSING SYSTEMS TO MEET OPERATIONAL GOALS - A simplified explanation of the abstract
This abstract first appeared for US patent application 18182861 titled 'SYSTEM AND METHOD FOR MANAGING OPERATION OF DATA PROCESSING SYSTEMS TO MEET OPERATIONAL GOALS
Simplified Explanation: The patent application discusses methods and systems for managing data processing systems by analyzing logs to predict component failures and optimize system performance.
- Key Features and Innovation:
* Data processing system manager obtains logs for components to monitor system operation. * Inference models predict future component failures and times-to-failures using log information. * Failure sequences are presented as acyclic graphs to analyze and optimize system performance. * Sets of actions are identified to achieve operational goals and reduce system impairment.
Potential Applications: This technology can be applied in various industries where data processing systems are critical, such as telecommunications, finance, healthcare, and manufacturing.
Problems Solved: The technology addresses the challenges of predicting and preventing component failures in data processing systems, ultimately improving system reliability and performance.
Benefits: The benefits of this technology include increased system uptime, reduced maintenance costs, optimized system performance, and enhanced overall operational efficiency.
Commercial Applications: Optimizing data processing systems using predictive analytics can benefit companies in improving their service delivery, reducing downtime, and enhancing customer satisfaction, leading to a competitive edge in the market.
Prior Art: Prior research in predictive maintenance and system optimization can provide valuable insights into the development and implementation of this technology.
Frequently Updated Research: Stay updated on the latest advancements in predictive analytics, machine learning, and system optimization to enhance the capabilities of this technology.
Questions about Data Processing System Management: 1. How does predictive analytics help in optimizing data processing systems? 2. What are the key components of a data processing system that can benefit from predictive maintenance strategies?
Original Abstract Submitted
Methods and systems for managing data processing systems are disclosed. A data processing system may include and depend on the operation of hardware and/or software components. To manage the operation of the data processing system, a data processing system manager may obtain logs for components of the data processing system. The logs may record actions (e.g., user actions) and other information that describes and reflects the historical and/or current operation of these components. Inference models may be implemented to predict likely future component failures (e.g., failure sequences) and their associated times-to-failures using information recorded in the logs. The failure sequences may be presented as an acyclic graph that associates component failures, their times-to-failure, and related actions. The probable failure sequences may be analyzed to identify sets of actions that optimize operational goals (e.g., maximizing system lifetime, minimizing system costs), and/or reduce the likelihood of the data processing system becoming impaired.
