View source for 18121382. CONTROLLING MONITORING ROLES OF NODES USING ARTIFICIAL INTELLIGENCE TECHNIQUES simplified abstract (Dell Products L.P.)

=CONTROLLING MONITORING ROLES OF NODES USING ARTIFICIAL INTELLIGENCE TECHNIQUES=


==Organization Name==

[[:Category:Dell Products L.P.|Dell Products L.P.]]


[[Category:Dell Products L.P.]]

==Inventor(s)==

[[:Category:Pratheek Veluswamy of Bangalore (IN)|Pratheek Veluswamy of Bangalore (IN)]][[Category:Pratheek Veluswamy of Bangalore (IN)]]

[[:Category:Shibi Panikkar of Bangalore (IN)|Shibi Panikkar of Bangalore (IN)]][[Category: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.



[[Category:G06F9/50]]
[[Category:G06N5/022]]
[[Category:CPC_G06F9/5083]]