1713 results about "Web resource" patented technology

Systems, methods, and apparatuses for providing optimization of network resources. The system is operable to monitor the electromagnetic environment, analyze the electromagnetic environment, and extract environmental awareness of the electromagnetic environment. The system extracts the environmental awareness of the electromagnetic environment by including customer goals. The system is operable to use the environmental awareness with the customer goals and / or user defined policies and rules to extract actionable information to help the customer optimize the network resources.

Systems, methods, and apparatuses for providing optimization of network resources. The system is operable to monitor the electromagnetic environment, analyze the electromagnetic environment, and extract environmental awareness of the electromagnetic environment. The system extracts the environmental awareness of the electromagnetic environment by including customer goals. The system is operable to use the environmental awareness with the customer goals and / or user defined policies and rules to extract actionable information to help the customer optimize the network resources.

The invention discloses an intelligent operation and maintenance management and control system for an information communication network, and belongs to the technical field of communication. The system comprises the following modules: an intelligent sensing and data acquisition module which is responsible for real-time acquisition of multi-source network data, dynamic monitoring of cross-domain equipment states and conversion of heterogeneous data into a unified standard; the network intelligent analysis module integrates network performance prediction, fault risk assessment, abnormal behavior identification and security threat monitoring, and provides comprehensive network operation and maintenance insight; the intelligent resource scheduling module is used for realizing dynamic allocation of cross-domain network resources and ensuring efficient and safe utilization of the resources through multi-dimensional optimization and a real-time load balancing strategy; the intelligent decision support module is used for continuously optimizing an operation and maintenance strategy based on machine learning, analyzing a long-term operation trend and providing suggestions for management decisions; and the open integration and collaboration module provides integration of an open API interface and a third-party system, supports cross-domain collaboration management, and improves the flexibility and expansibility of the system.

Systems, methods, and apparatuses for providing optimization of network resources. The system is operable to monitor the electromagnetic environment, analyze the electromagnetic environment, and extract environmental awareness of the electromagnetic environment. The system extracts the environmental awareness of the electromagnetic environment by including customer goals. The system is operable to use the environmental awareness with the customer goals and / or user defined policies and rules to extract actionable information to help the customer optimize the network resources.

The invention discloses a nursing data sharing method and system based on the Internet of Things. The method comprises the steps that S1, multi-modal nursing data are collected in real time through a distributed Internet of Things terminal cluster, and a feature signal set is formed; s2, constructing a data coordination engine, executing federal learning preprocessing operation on the feature signal set, and forming a coordination signal flow; s3, dynamically calculating a data contribution degree weight and generating a verification signal chain; s4, monitoring vital sign abnormal indexes in the coordination signal flow in real time, and generating a trigger signal vector; and S5, updating incentive mechanism parameters according to the contribution degree voucher in the verification signal chain, optimizing a service quality strategy based on a network resource allocation scheme in the trigger signal vector, and forming a closed-loop control signal. According to the invention, the problem of data islanding effect in the medical care data sharing process can be solved.

The invention relates to the technical field of resource scheduling control, and discloses a network resource hierarchical coordination method and system based on multiple agents. The method comprises the following steps: monitoring a network node load to obtain a resource state parameter; virtually constructing a resource pool and dividing a regulation domain; deploying an intelligent agent to construct a self-adaptive control system; extracting load characteristics to generate an analysis report; executing a double-layer adjustment strategy recording execution process; and analyzing the energy consumption data to optimize control strategy parameters. According to the application, the efficient utilization of network resources and energy consumption optimization can be realized while the performance of a computer network system is guaranteed.

The invention provides a dynamic routing selection method and system, electronic equipment and a storage medium, and aims to solve the problem that a routing strategy is difficult to adapt to a dynamically changing network, the method comprises the following steps: a terminal layer collects the state of a terminal and network data, and performs lightweight feature extraction; the edge node layer receives the data of the terminal layer, carries out space-time-semantic feature aggregation, and generates a region-level resource scheduling and routing decision strategy based on fragmented reinforcement learning; the central cloud service layer gathers whole network data, generates a global optimization strategy and issues the global optimization strategy; the edge node layer fuses global optimization and a region-level strategy, and executes dynamic routing selection; and security and privacy protection are provided through the trusted chain layer. According to the invention, adaptive path selection can be realized, the network resource utilization rate is improved, and the network stability is improved.

The embodiment of the invention relates to the technical field of artificial intelligence, and provides a linkage method and system of an apartment network and intelligent equipment, and the method comprises the steps: collecting network operation data and equipment operation data of a target apartment in real time; based on the equipment operation data, determining currently achievable candidate service scenes of the target apartment; fusing the network operation data and the equipment operation data into a joint operation map of the target apartment through the space-time diagram attention network; a multi-agent depth deterministic strategy gradient algorithm is adopted to carry out network resource allocation and equipment control decision making on the joint operation map, scene adaptive optimization is realized in combination with candidate service scenes, and a linkage strategy of a target apartment is obtained; and generating a decision instruction based on the linkage strategy, and adopting the decision instruction to realize remote control of the network equipment and the intelligent equipment. Through deep fusion of the space-time diagram attention network and multi-agent reinforcement learning, dynamic collaborative management and control of the network and equipment are realized, and the resource utilization rate and the service response speed are improved.

Systems and methods for managing resources across a global and / or cloud network. In particular, systems and methods for mitigating issues related to providing services while resources are offline (or may potentially go offline). For example, the systems and methods may mitigate issues related to providing services while resources are offline (or may potentially go offline) by monitoring network services at an aggregate level.

The invention relates to the technical field of network management, in particular to an Internet of Things gateway control method and system based on AI computing power, and the method comprises the following steps: obtaining channel real-time signal intensity, noise level and occupancy proportion, monitoring protocol type and transmission condition, analyzing the relationship between retransmission times and interference, deducing protocol combination interference and throughput, and obtaining a real-time channel signal intensity, noise level and occupancy proportion. And configuring an optimal scheduling scheme, evaluating resource consumption and load states, packaging and requesting permission entrustment, and judging permission information in combination with an interaction record and an access control list. According to the method, different protocol distribution combinations are simulated and deduced, the data throughput of the whole network is further estimated and optimized, potential protocol conflicts are reduced, the use efficiency and the overall performance of network resources are effectively improved, consumption of a local computing unit and network bandwidth is comprehensively considered, packaging processing of request information is optimized, and the network performance is improved. And the real-time response capability and manageability of the network state are obviously improved.

The invention provides a heterogeneous network resource virtualization modeling and intelligent arrangement method and system based on a knowledge graph, and relates to unified modeling, dynamic retrieval and intelligent resource arrangement of heterogeneous network equipment. The method specifically comprises: 1, a unified modeling method based on a knowledge graph: integrating protocol attributes, dynamic states and topological relationships of heterogeneous devices such as a 5G base station, an SDN switch, a router, an Internet of Things gateway and the like into a structured knowledge graph, breaking the barrier of a manufacturer private data model, and realizing semantic-level collaborative scheduling of cross-domain resources; 2, designing a semantic retrieval engine: querying dynamic conditional reasoning through a natural language, replacing traditional manual rule definition, and improving retrieval response speed and accuracy; and 3, developing a graph-driven intelligent arrangement framework: combining a graph neural network (GNN) and reinforcement learning (RL), automatically generating a resource allocation strategy according to a real-time network state, reducing manual intervention and improving the resource utilization rate.

Systems, methods, and apparatuses for providing optimization of network resources. The system is operable to monitor the electromagnetic environment, analyze the electromagnetic environment, and extract environmental awareness of the electromagnetic environment. The system extracts the environmental awareness of the electromagnetic environment by including customer goals. The system is operable to use the environmental awareness with the customer goals and / or user defined policies and rules to extract actionable information to help the customer optimize the network resources.

Systems and methods for managing resources across a global and / or cloud network. In particular, systems and methods for mitigating issues related to providing services while resources are offline (or may potentially go offline). For example, the systems and methods may mitigate issues related to providing services while resources are offline (or may potentially go offline) by monitoring network services at an aggregate level.

The invention relates to the technical field of communication networks, in particular to a real-time network flow prediction and resource optimization distribution method and system based on a space-time multi-mode generation model. Multi-modal feature extraction and fusion are carried out; model prediction is generated; reinforcement learning scheduling optimization; self-supervision and feedback closed loop are realized; executing resource allocation; the method has the advantages that multiple data sources such as spatio-temporal data, user behaviors and application types are fused through the multi-modal large model, future network traffic distribution is generated through the generation model, and the accuracy and timeliness of traffic prediction are improved. The network resources of different areas and time periods are intelligently scheduled through the reinforcement learning model, real-time and automatic resource allocation is realized, and the network quality and user experience of high-demand areas are ensured.

The invention discloses a cross-domain collaborative interface dynamic configuration method and device and a computer program product. According to the cross-domain collaborative interface dynamic configuration method, service flow priorities are determined by analyzing service layer data, and an initial interface configuration scheme is generated in combination with network state information. And when the initial scheme does not meet the transmission requirements, optimizing the interface parameters by adopting a dynamic programming algorithm, generating a new configuration scheme, and issuing the new configuration scheme to the target network management system. In the service switching process, network performance is monitored in real time, interface parameters are dynamically optimized and updated to a network management system, and intelligent management of service flow and efficient utilization of network resources are achieved. The method can adapt to different manufacturer devices and network levels, guarantees the service quality of cross-domain services, and improves the operation efficiency and reliability of an electric power communication network.

The invention provides a report generation method and system based on a multi-agent architecture, and the method comprises the steps: firstly receiving and analyzing a report generation instruction, obtaining a theme demand, a framework specification and an initial reference material, then starting a multi-agent cooperation framework, generating an agent task distribution table, and generating an agent task distribution table; and the resource retrieval agent executes network resource directional retrieval according to the task allocation table to generate an associated resource set, and the content extraction agent performs structured conversion on the associated resource set and the initial reference material to obtain a structured content unit with chapter codes. The method comprises the following steps: performing module classification and logic series connection on a structured content unit by a report integration agent in combination with a framework specification to generate a report first draft, and finally performing content verification and optimization on the report first draft by a multi-agent collaborative framework to generate a final report text conforming to the framework specification, thereby realizing automation, intellectualization and high efficiency of report generation. And report quality is improved.

Systems, methods, and apparatuses for providing optimization of network resources. The system is operable to monitor the electromagnetic environment, analyze the electromagnetic environment, and extract environmental awareness of the electromagnetic environment. The system extracts the environmental awareness of the electromagnetic environment by including customer goals. The system is operable to use the environmental awareness with the customer goals and / or user defined policies and rules to extract actionable information to help the customer optimize the network resources.

Systems, methods, and apparatuses for providing optimization of network resources. The system is operable to monitor the electromagnetic environment, analyze the electromagnetic environment, and extract environmental awareness of the electromagnetic environment. The system extracts the environmental awareness of the electromagnetic environment by including customer goals. The system is operable to use the environmental awareness with the customer goals and / or user defined policies and rules to extract actionable information to help the customer optimize the network resources.

Systems, methods, and apparatuses for providing optimization of network resources. The system is operable to monitor the electromagnetic environment, analyze the electromagnetic environment, and extract environmental awareness of the electromagnetic environment. The system extracts the environmental awareness of the electromagnetic environment by including customer goals. The system is operable to use the environmental awareness with the customer goals and / or user defined policies and rules to extract actionable information to help the customer optimize the network resources.

The invention provides a multi-level service priority dynamic scheduling simulation method and device, a medium and a product. The method comprises the following steps: constructing a priority label system; establishing a dynamic binding relationship between the service flow and the priority label; when a service layer generates a data packet, embedding a priority label for the data packet based on the dynamic binding relationship; extracting a priority label carried by the data packet on a protocol stack MAC layer, and ensuring that the priority label is unvarnished to a lower layer protocol in a lossless manner; and based on the priority labels carried by the extracted data packets, classifying the data packets into logic queues with corresponding priorities, and executing a differentiated scheduling strategy. The method can adapt to diversified requirements of data services of different types and priorities for network resources, effectively improves the simulation model accuracy, improves the simulation experiment efficiency and simulation real-time performance and reliability in a multi-service priority 5G communication network simulation scene, more accurately reflects the performance of a real network, and improves the simulation experience of the 5G communication network. And meanwhile, the simulation platform has higher expansibility and flexibility.

The invention relates to the technical field of network resource allocation, and discloses a network node resource dynamic allocation method and system. The method comprises the following steps: collecting multi-dimensional resource use data of network nodes and executing preprocessing to obtain a standardized resource monitoring matrix and a topological entropy weight matrix; performing nonlinear topology perception calculation to obtain a resource demand prediction matrix; based on the resource demand prediction matrix, performing sectional progressive allocation decision on the network node resources to obtain a first resource allocation decision matrix; performing chaos disturbance fine tuning on the first resource allocation decision matrix to obtain a second resource allocation decision matrix and a resource locking time table; and performing network node resource multi-level scheduling based on the second resource allocation decision matrix and the resource locking time table, and generating a resource execution result log and performance monitoring data. According to the invention, the prediction accuracy of the real resource demand of the network node is improved, and a differentiated, multi-level and smooth transition resource scheduling execution strategy is realized.

Systems, methods, and apparatuses for providing optimization of network resources. The system is operable to monitor the electromagnetic environment, analyze the electromagnetic environment, and extract environmental awareness of the electromagnetic environment. The system extracts the environmental awareness of the electromagnetic environment by including customer goals. The system is operable to use the environmental awareness with the customer goals and / or user defined policies and rules to extract actionable information to help the customer optimize the network resources.

The invention discloses an air-space-ground caching and resource optimization method and system based on a hierarchical intelligent agent, and aims to construct a deep reinforcement learning architecture in which a high-layer DQN and a low-layer DDPG are coordinated for high dynamics and information uncertainty of an air-space-ground integrated network. The high-level intelligent agent generates a period-level content cache and access control strategy based on global states including a cache state, a task request, a node resource and the like, and the low-level intelligent agent executes time slot-level resource allocation, task unloading rate control and UAV deployment optimization under the constraint of the high-level strategy. The system triggers low-level optimization through a double-stage reward mechanism and constraint verification, evaluates a strategy effect based on time slot income and full-period income, and combines state perception and experience playback technologies to realize collaborative optimization of high and low-level decisions. A simulation result shows that compared with a traditional method, the method has remarkable advantages in the aspects of reducing content acquisition delay, reducing return communication overhead, improving task processing success rate and the like, and the space-air-ground MEC network resource utilization rate and user experience are effectively improved.

The invention discloses a TSN scheduling optimization method and device based on flow sensing autonomous learning, equipment and a medium. The method comprises the following steps: deploying a lightweight flow detection module in a switch or a router, and after a controller receives a data request, automatically identifying a newly arrived unknown service flow by using the lightweight flow detection module, and judging whether the newly arrived unknown service flow is a periodic TT flow or an unpredictable burst flow; the controller performs classification management on the identified service flow types, collects topological information and flow requirements of the whole network and issues the topological information and the flow requirements to the terminal nodes through a network management interface; the controller constructs an intelligent queue scheduling task based on the collected network topology information and traffic demand and converts the task into a Markov decision process MDP, network resources, queue states and priorities are used as a state space, a scheduling strategy is used as an action space, a reward function is designed in combination with throughput and delay indexes, and an intelligent queue scheduling task is obtained. Driving a dynamic environment through real-time data and training a DRL model; an enhanced queue scheduling mechanism Pro-CQF is adopted, different priority labels are configured according to classified flow types, and then mixed flow scheduling is carried out; the controller periodically collects time delay, packet loss rate and end-to-end transmission delay indexes and feeds back the indexes to the DRL model, and a scheduling strategy is updated online. According to the method, the traffic sensing and scheduling efficiency is greatly improved in a network environment in which multiple service flows coexist and end-side equipment functions are different, and the reliability and the expandability of the TSN in industrial Internet of Things, edge computing and other high-real-time application scenes are remarkably enhanced.

Systems, methods, and apparatuses for providing optimization of network resources. The system is operable to monitor the electromagnetic environment, analyze the electromagnetic environment, and extract environmental awareness of the electromagnetic environment. The system extracts the environmental awareness of the electromagnetic environment by including customer goals. The system is operable to use the environmental awareness with the customer goals and / or user defined policies and rules to extract actionable information to help the customer optimize the network resources.

Systems, methods, and apparatuses for providing optimization of network resources. The system is operable to monitor the electromagnetic environment, analyze the electromagnetic environment, and extract environmental awareness of the electromagnetic environment. The system extracts the environmental awareness of the electromagnetic environment by including customer goals. The system is operable to use the environmental awareness with the customer goals and / or user defined policies and rules to extract actionable information to help the customer optimize the network resources.

The invention relates to the technical field of remote control, in particular to an intelligent device remote cooperative control method and system based on the Internet of Things, and the method comprises the following steps: monitoring and adjusting the CPU utilization rate and memory usage of an intelligent device based on an Internet of Things platform, optimizing the data collection and network resource distribution, and improving the intelligent device remote cooperative control efficiency. By analyzing equipment performance and a network load balance index, equipment connection priority ranking and task load management are realized, and task execution and connection frequency is dynamically adjusted, so that real-time task requirements are met, and system efficiency is improved. According to the method, the performance index of the equipment is monitored in real time, the data transmission interval is dynamically adjusted, the data processing speed is remarkably increased, resource waste is reduced, efficient use of network resources is ensured through real-time load analysis and optimization of network nodes, the problem of data delay caused by network congestion is avoided, and in the aspect of equipment connection management, the data transmission efficiency is improved. An intelligent priority decision mechanism allows the key device to quickly access the network in an emergency.

The invention discloses a macro server system, an application method, electronic equipment and a storage medium, and relates to the technical field of computers, physical devices (equipment components) of the macro server system are modularly designed to be combined into modules with different functions, and the physical devices support hot plugging, so that the physical devices can be conveniently and quickly combined into modules with different functions. Meanwhile, a plurality of physical devices are connected through a high-speed communication network to form a distributed module cluster, so that a large number of computing resources, management resources and network resources can be packaged into an independent server environment, and the limitation of a current server in the aspects of processor performance, bandwidth, physical structure, hardware quantity, firmware resources and the like is solved; according to the technical scheme, the macro server system capable of supporting large-scale data processing, high-concurrency access and complex operation is constructed, so that the technical problem of how to improve the performance and expandability of the server can be solved, and the technical effect of constructing the macro server system capable of supporting large-scale data processing, high-concurrency access and complex operation is achieved.

The invention discloses a resource awareness and task migration method and system for industrial edge nodes. The method comprises the following steps: constructing an edge node resource dynamic monitoring system, and sensing, calculating, storing and network resource states in real time; establishing a node health degree evaluation model, and predicting a potential fault risk; designing an intelligent task migration decision-making mechanism based on a resource state; the guarantee of data consistency and service continuity in the task migration process is realized; and constructing a distributed task scheduling optimization framework. The system comprises a resource monitoring module, a health assessment module, a migration decision module, a data synchronization module and a scheduling optimization module. According to the method, the problem of unstable task execution caused by dynamic resource change in an industrial edge computing environment is solved, and intelligent resource management and efficient task migration of the edge nodes are realized.

Systems, methods, and apparatuses for providing optimization of network resources. The system is operable to monitor the electromagnetic environment, analyze the electromagnetic environment, and extract environmental awareness of the electromagnetic environment. The system extracts the environmental awareness of the electromagnetic environment by including customer goals. The system is operable to use the environmental awareness with the customer goals and / or user defined policies and rules to extract actionable information to help the customer optimize the network resources.