18555994. Data Duplication simplified abstract (Nokia Technologies Oy)
Contents
Data Duplication
Organization Name
Inventor(s)
Teemu Mikael Veijalainen of Helsinki (FI)
Data Duplication - A simplified explanation of the abstract
This abstract first appeared for US patent application 18555994 titled 'Data Duplication
The abstract describes a method for optimizing a predictive model for a group of nodes in a communications network. This involves receiving data tuples containing state data of nodes, actions specifying paths for duplicating data packets, and reward data indicating quality of service. The method then determines a performance level for the network based on reward data, evaluates a predictive model predicting quality of service, and modifies the model accordingly.
- Receives data tuples with state data, actions, and reward data
- Determines performance level for the network based on reward data
- Evaluates and modifies a predictive model predicting quality of service
Potential Applications: - Network optimization - Quality of service improvement - Predictive modeling in communications networks
Problems Solved: - Enhancing network performance - Improving quality of service - Optimizing data packet duplication paths
Benefits: - Enhanced network efficiency - Improved quality of service - Predictive modeling for better network management
Commercial Applications: Title: Predictive Model Optimization for Communications Networks This technology can be used in telecommunications companies, data centers, and network infrastructure providers to optimize network performance and improve quality of service for customers.
Questions about Predictive Model Optimization for Communications Networks: 1. How does this method differ from traditional network optimization techniques? 2. What are the key factors that influence the predictive model's accuracy in this context?
Frequently Updated Research: Stay updated on the latest advancements in predictive modeling for communications networks to ensure optimal network performance and quality of service.
Original Abstract Submitted
A method for optimizing a predictive model for a group of nodes in a communications network includes receiving a tuples of data values, each tuple including state data representative of a state of a node, an action including a specification of paths for duplicating data packets from the node to a further node, and reward data that indicates a quality of service at the node subsequent to duplicating data packets through the paths specified by the action, determining a data value indicative of a performance level for the communications network on the basis of reward data of the tuples, evaluating a predictive model that outputs a set of data values for each node, the data values predicting a quality of service from duplicating data packets on the paths, and modifying the predictive model based on the predicted data values and the data value indicative of a performance level for the communications network.
