7 results about "Network strategy" patented technology

The present application belongs to the field of military command control and combat simulation, and relates to a local rapid reconstruction method for a killing network based on a complementary network strategy. The method acquires current state information of the killing network and detects failed nodes or edges, constructs a local repair area centered on the failed nodes, establishes a multi-objective optimization model in the repair area aiming to maximize task recovery benefits, minimize resource use costs and minimize task completion delays, solves to obtain a Pareto optimal solution set by using a TM-NSGA-III algorithm guided by a conversion matrix, and finally screens and executes a reconstruction scheme according to a battlefield situation. The present application reduces the search space by localized modeling, combines the conversion matrix to inherit the effective information of the original network, realizes rapid and high-quality reconstruction of the killing network, and improves the resilience and self-healing ability of the killing network in a dynamic battlefield environment.

The application discloses a large model and knowledge graph enabled intention driving network design method, comprising the following steps: S101, a user inputs a user intention through a front-end natural language interaction interface, and performs a pretreatment operation on the user intention; S102, a pretreated user intention is classified based on a few-shot learning method, and a large model cooperation method extracts key information of the user intention and constructs an intention knowledge graph based on the key information; S103, a network state knowledge graph is constructed; S104, an application program interface provided by an underlying layer is called by using intention understanding and reasoning capability of the large model, so that mapping of the user intention to an underlying network strategy and issuing are realized; and S105, the large model performs dynamic real-time adjustment based on network state knowledge graph information. The application realizes intention semantic mining, adaptation of intention demand and underlying resource capability, so as to bridge a semantic gap between the user intention, strategy management and the underlying network, and improve network operation efficiency.

The application relates to a cross-network message pushing method based on a strategy model and belongs to the technical field of computer networks. The application establishes node management, engine management, route management and application management aiming at a cross-network strategy model, establishes a cross-network route model in combination with cross-network, cross-center and cross-system application scenes, shields cross-network link construction in complex scenes only by configuration of the strategy model, solves the interconnection and interworking of various service systems in service and a system application difficulty, and achieves out-of-box use. The application can realize end-to-end message sending only by simple registration and configuration in scenes where different networks, different centers and different systems cannot directly interact.

In one embodiment, a method herein may comprise: causing, for a quality-of-experience evaluation session, one or more network impairments to be injected according to a set of predefined scenarios on application traffic for a plurality of feedback sources that are using a particular application in a computer network; obtaining experience-based feedback from the plurality of feedback sources for the quality-of-experience evaluation session; correlating the experience-based feedback with the one or more network impairments to produce an evaluation result for the quality-of-experience evaluation session; and generating a quality-of-experience-based network policy recommendation for the particular application based on the evaluation result.

This application discloses a network strategy optimization method and apparatus, and a computer-readable storage medium, comprising: acquiring network parameters and service test indicators of a first network and a second network of competitors within each competitor network region; determining the superiority index value of the first network based on the comparison results of the superiority and inferiority of the same type of service test indicators of the first network and the second network; determining network strategy classification samples and corresponding strategy superiority and inferiority labels based on the network parameters and service test indicators of the first network and the second network, as well as the superiority index value of the first network, and training a network strategy classification model for classifying the network strategy of the first network as superior or inferior; classifying the network strategy of the target network to be optimized within the target competitor network region based on the network strategy classification model; and optimizing the network parameters of the target network to be optimized based on the network parameters of the competitor networks within the target competitor network region when the network strategy classification result is inferior.

The application discloses a network packet control method and device based on three-level labels and a storage medium, and relates to the technical cross field of cloud computing and power network. The method comprises the following steps: acquiring flow direction information and application layer load of a network packet; generating a first label according to the flow direction information and a preset access control strategy; obtaining security behavior information of the network packet by detecting the application layer load, and then generating a second label according to the security behavior information; querying and matching a corresponding business scenario from a preset business knowledge graph according to the flow direction information and / or the security behavior information, and generating a third label according to the matched business scenario; and determining a network control strategy and executing the network control strategy based on the collaborative analysis results of the first label, the second label and the third label. The application solves the technical problems that the network and the power business scenario are disconnected in the traditional IAAS cloud architecture, and the network strategy cannot be dynamically adapted according to the business demand.