18121382. CONTROLLING MONITORING ROLES OF NODES USING ARTIFICIAL INTELLIGENCE TECHNIQUES simplified abstract (Dell Products L.P.)
Contents
- 1 CONTROLLING MONITORING ROLES OF NODES USING ARTIFICIAL INTELLIGENCE TECHNIQUES
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 CONTROLLING MONITORING ROLES OF NODES USING ARTIFICIAL INTELLIGENCE TECHNIQUES - A simplified explanation of the abstract
- 1.4 Simplified Explanation
- 1.5 Key Features and Innovation
- 1.6 Potential Applications
- 1.7 Problems Solved
- 1.8 Benefits
- 1.9 Commercial Applications
- 1.10 Prior Art
- 1.11 Frequently Updated Research
- 1.12 Questions about Node Monitoring Control Technology
- 1.13 Original Abstract Submitted
CONTROLLING MONITORING ROLES OF NODES USING ARTIFICIAL INTELLIGENCE TECHNIQUES
Organization Name
Inventor(s)
Pratheek Veluswamy of Bangalore (IN)
Shibi Panikkar of Bangalore (IN)
CONTROLLING MONITORING ROLES OF NODES USING ARTIFICIAL INTELLIGENCE TECHNIQUES - A simplified explanation of the abstract
This abstract first appeared for US patent application 18121382 titled 'CONTROLLING MONITORING ROLES OF NODES USING ARTIFICIAL INTELLIGENCE TECHNIQUES
Simplified Explanation
The patent application describes methods, apparatus, and storage media for controlling monitoring roles of nodes in a distributed system using artificial intelligence processes.
- Obtaining time-series data related to transactions of system nodes in a distributed system.
- Classifying load distributions of transactions across system nodes based on the time-series data.
- Determining a monitoring node to be used as the primary monitoring role for specific time intervals based on the classification.
- Controlling transitions of the primary monitoring role between monitoring nodes based on the determination.
Key Features and Innovation
- Utilizes artificial intelligence processes to classify load distributions of transactions across system nodes.
- Determines the primary monitoring role for specific time intervals based on the classification.
- Controls transitions of the primary monitoring role between monitoring nodes.
Potential Applications
This technology can be applied in various distributed systems where monitoring roles of nodes need to be controlled efficiently.
Problems Solved
Efficiently managing monitoring roles of nodes in a distributed system. Optimizing the allocation of monitoring responsibilities based on transaction load distributions.
Benefits
Improved monitoring efficiency in distributed systems. Optimized allocation of monitoring roles based on transaction load distributions.
Commercial Applications
Title: "AI-Driven Node Monitoring Control Technology for Distributed Systems" This technology can be used in cloud computing platforms, IoT networks, and large-scale distributed systems to enhance monitoring capabilities and optimize resource allocation.
Prior Art
Readers can explore prior research on artificial intelligence-based monitoring systems in distributed environments to understand the evolution of this technology.
Frequently Updated Research
Stay updated on the latest advancements in artificial intelligence-driven monitoring systems for distributed networks to enhance your understanding of this field.
Questions about Node Monitoring Control Technology
1. How does this technology improve monitoring efficiency in distributed systems?
This technology improves monitoring efficiency by dynamically allocating monitoring roles based on transaction load distributions, ensuring optimal resource utilization.
2. What are the key benefits of using artificial intelligence processes for controlling monitoring roles in distributed systems?
Using artificial intelligence processes enables more accurate classification of load distributions and efficient determination of primary monitoring roles, leading to enhanced system performance.
Original Abstract Submitted
Methods, apparatus, and processor-readable storage media for controlling monitoring roles of nodes are provided herein. An example computer-implemented method includes obtaining time-series data related to transactions of system nodes in a distributed system, where the distributed system includes monitoring nodes, and a respective one of the monitoring nodes has a primary monitoring role responsible for monitoring operation of the system nodes; classifying, using a first artificial intelligence-based process, load distributions of the transactions across the system nodes based on the time-series data; determining, using a second artificial intelligence-based process, a respective one of the monitoring nodes to be used as the primary monitoring role for at least a 10 portion of one or more time intervals based on a result of the classifying; and controlling transitions of the primary monitoring role between the monitoring nodes for the one or more time intervals based on a result of the determining.
