48 results about "Resource network" patented technology

The technology disclosed relates to a method, system, and non-transitory computer-readable media that detects malicious communication between a command and control (C2) cloud resource on a cloud application and malware on an infected host, using a network security system. The network security system reroutes the cloud traffic to the network security system. The incoming requests of the cloud traffic are directed to a cloud application in the plurality of cloud applications, and wherein the cloud application has a plurality of resources. The network security system analyzes the incoming requests, determines that the incoming requests are targeted at one or more malicious resources in the plurality of resources. Also, the network security system prevents transmission of the incoming requests to the malicious resources, by making the malicious resources unavailable for receiving future incoming requests, while keeping other resources in the plurality of resources available for receiving the future incoming requests.

A distributed system and method for compressing and restoring data across edge computing devices and cloud infrastructure is disclosed. The system dynamically adjusts compression based on available computing resources, network conditions, and now energy constraints. Edge devices monitor power consumption and battery levels, optimizing compression parameters to extend battery life while maintaining data quality. A workload scheduler prioritizes tasks based on energy availability, offloading intensive processing to cloud infrastructure when necessary. The system utilizes an energy-aware coordination layer to balance workloads across multiple devices, ensuring efficient data flow and long-term operational stability. Homomorphic operations allow secure distributed processing on compressed data, while an adaptive neural upsampler enhances reconstructed outputs. By integrating energy optimization, the system improves performance and longevity of edge devices in power-limited environments.

The invention discloses a data-intensive workflow dynamic task allocation method and system oriented to cloud-edge cooperative computing, and relates to the technical field of cloud computing and edge computing collaboration.The method comprises the steps that workflow and cloud-edge resources are modeled in a unified mode, and a comprehensive cost function containing time, economy and energy consumption is defined; analyzing the workflow to obtain a conflict task set and a maximum data path set; in combination with resources and network states monitored in real time, candidate nodes are filtered according to data privacy constraints, edges or cloud nodes with the minimum comprehensive cost are selected for tasks for allocation, and sorting is performed according to priorities during multiple tasks; the system comprises a resource monitoring module, a workflow analysis and preprocessing module, a cost evaluation module and a dynamic scheduler module, the modules cooperate to realize dynamic allocation, the problems of resource heterogeneity, network dynamic and the like under cloud edge cooperation are solved, multi-objective optimization and privacy protection are balanced, and the workflow execution efficiency is improved.

The invention discloses a smart power grid and new energy collaborative distributed energy storage optimization regulation and control system, and relates to the technical field of smart power grid and new energy collaborative control. The system comprises a central processing module, a data acquisition and monitoring module, an intelligent scheduling and optimization module and a new energy automobile collaborative scheduling module. A multi-dimensional prediction model (covering weather, equipment state and user behavior data) is constructed based on machine learning, a distributed energy storage charging and discharging strategy is optimized in combination with a genetic algorithm and dynamic programming, power grid frequency modulation, voltage regulation and standby capacity requirements are coordinated, regional energy storage resources are integrated through a virtual power plant management platform, cross-space-time deployment is realized, and the power grid energy storage capacity management system is optimized. The new energy consumption capability is remarkably improved, the fluctuation risk of the power grid is relieved, the innovatively designed vehicle network interaction center supports orderly charging and reverse discharging cooperation of the electric vehicle, the peak regulation potential of a vehicle battery is aggregated, and a flexible and adjustable mobile energy storage resource network is formed.

The invention relates to the technical field of industrial data processing and resource scheduling, and discloses a garment intelligent manufacturing process dynamic optimization management system based on a large model, comprising an unstructured load waveform semantic analysis module used for receiving a load demand data stream and analyzing to generate a discrete load pulse sequence, calculating a semantic cognitive entropy representing the certainty of the load request; the resource capacity space-time constraint dynamic reconstruction module is used for generating a capacity slack variable based on the semantic cognitive entropy and embedding the capacity slack variable into the resource network load distribution model as a hard physical safety margin parameter; according to the invention, a direct mapping channel from a probability semantic space to a physical resource space-time environment is established, so that the problem of resource allocation mismatch caused by unstructured load fluctuation is effectively solved; and the stability and the self-adaptive balancing capability of the production resource network in dealing with the high-uncertainty load are improved.

Provided are communication methods, terminal devices and network devices. A communication method comprises: a terminal device receiving first DCI sent by a network device, wherein the first DCI is used for triggering a random access procedure or indicating a first PRACH resource. A network device sends first DCI to a terminal device to trigger a random access procedure or indicate a first PRACH resource, so as to provide the terminal device with additional random access opportunities or resources, thereby facilitating the rapid recovery of uplink synchronization, and also optimizing the allocation of network resources and improving the system flexibility.

A method performed by a first network node is provided. The method is for handling Sounding Reference Signal, SRS, configurations in a wireless communications network. The first network node is comprised in a group of network nodes together with one or more second network nodes. The first network node shares (202) a set of SRS configurations in the group of network nodes. The set of SRS configurations comprises SRS resources to be used for SRS interference measurements. The set of SRS configurations is to be used by the network nodes in the group of network nodes to configure User Equipments, UEs. The UEs to be configured are UEs that are identified to be Downlink, DL, heavy traffic UEs comprising DL data, which has an estimated download time that exceeds a threshold. When the first network node obtains (203) data to be transmitted to a first UE, it measures (204) SRS interference. The SRS interference is measured on SRS transmitted by each respective UE identified to be a DL heavy traffic UE by the respective one or more second network nodes. The respective measuring of 15SRS interference is performed on resources according to an SRS configuration out of said shared SRS configuration set. The first network node then selects (205) a precoder for the data to be transmitted to the first UE, based on the measured SRS interference.

This invention discloses a novel intelligent sharing and optimization method and system for aesthetic education resources based on a cloud platform, belonging to the field of resource sharing technology. By deploying multiple types of sensors in the classroom to collect teaching environment data and construct a classroom environment feature vector, a resource environment demand vector is established, and the environmental adaptability between the classroom environment and various aesthetic education resources is calculated. The network link status between the classroom terminal and the cloud platform is detected in real time, and parameters such as bandwidth, latency, and packet loss rate are obtained. Resource network matching coefficients are calculated, and the environmental adaptability and network matching coefficients are further integrated to construct a comprehensive resource availability. A resource scheduling priority sequence is generated by combining course matching degree and concurrent call status. This achieves intelligent sharing and dynamic optimization scheduling of aesthetic education resources in multi-classroom scenarios, improving the environmental adaptability and transmission stability of resource sharing, and enhancing the utilization efficiency and teaching implementation reliability of aesthetic education resources on the cloud platform.

The application discloses a kind of based on heterogeneous computing resource network element instance deployment method, device and electronic equipment, the method is applied to cloud computing field, the method includes: receiving the computing power scheduling request of user, according to computing power scheduling request parsing the computing power configuration information and computing power scheduling operation of user required computing power;With the matching of computing power configuration information and network element metadata set, obtain matching result, wherein, network element metadata set is constructed according to the network element information corresponding to multiple heterogeneous computing resources in cluster;According to matching result and license information set, determine the computing power resources to be scheduled in cluster;According to computing power scheduling operation, the computing power resources to be scheduled are scheduled, and scheduling result is returned to user. By the present application, the problem that the network element instance deployment efficiency is low due to the different structure of computing power resources provided by different manufacturers and the dispersion of license information in the related art heterogeneous computing cloud platform environment is solved.

The application discloses an offline identity authentication and key negotiation method containing biological characteristics, and belongs to the technical field of shared resource network security. The method is completed by three parties of a user intelligent terminal device, an authentication server and a vehicle-mounted device, and contains user registration / vehicle initialization stage, user login / vehicle selection stage, user offline identity authentication and vehicle use stage, user vehicle return stage and user intelligent terminal loss and vehicle use stage. The main purpose of the application is to solve the problem that shared vehicles are scattered in different geographical spaces during use, leading to difficult management of physical vehicle keys. The core idea is to use the user's intelligent terminal as a key substitute for the shared vehicle, and through the introduction of biological characteristics, time stamps, random numbers and the like, the effects of preventing theft of the intelligent terminal attack, preventing replay attack, resisting key manipulation and the like can be achieved, so that the user experience and security are improved.

A computer-implemented method is executed using a global energy management system computer in an energy and load resource network, the energy and load resource network comprising a plurality of energy generating resources, a plurality of load resources, a plurality of energy storage resources, and a plurality of virtual energy resources, the computer-implemented method comprising receiving a plurality of energy market data and a plurality of capacity market data items; executing an inference stage of a trained machine learning model over the plurality of energy market data and the plurality of capacity market data items to output predictions of generating capacity and load requirements; executing an optimization algorithm over the predictions of generating capacity and load requirements to output a plurality of optimized generating capacity and load requirements; forming a plurality of operational instructions for a plurality of the resources in the energy and load resource network, the plurality of operational instructions being formatted to cause the plurality of the resources in the energy and load resource network to conform to the plurality of optimized generating capacity and load requirements; transmitting the plurality of operational instructions to the plurality of the resources in the energy and load resource network to instruct the plurality of the resources in the energy and load resource network to conform to the plurality of optimized generating capacity and load requirements.

Embodiments described herein can involve improved network security based on a distributed network access and logical permission architecture. In an example, a computer system can receive, by a first compute instance of the system from a user device, a request indicating an action to be performed on an element of a virtual resource. The first compute instance can be associated with a logical permission to use the virtual resource and may lack network access to the virtual resource. The first compute instance can cause a credential to be generated that enables the action to be performed on the element only and has an expiration attribute. The first compute instance can provide the credential to a second compute instance of the system which has network access to the virtual resource. The second compute instance can cause the action to be performed based on the credential and the network access.

This disclosure discloses a reference signal activation indication method and apparatus, relating to the field of communication technology. The method includes: sending activation indication information to a terminal device in a disconnected state, wherein the activation indication information indicates that a reference signal received by the terminal device within the activation time period corresponding to the activation indication information is active. This method sends activation indication information to the terminal device in a disconnected state via a network device, allowing the terminal device to receive the reference signal within the activation time period according to configuration information, thus saving power and resources. The network device can also flexibly configure the activation time period, reducing system overhead.

The application discloses a logistics cost management method and system based on shared storage resources, comprising the following steps: step one: collecting original actual operation data of each warehouse in the shared storage platform, and performing time alignment and correction processing; step two: establishing a shared storage resource network diagram; step three: obtaining multiple complete cost occurrence paths, calculating various logistics costs, and obtaining a logistics cost set; step four: inputting the shared storage resource network diagram and the logistics cost set into an improved Graphormer model, obtaining a storage cost time sequence attention result through a resource occupation coding module, a cost connection enhancement module and a storage time sequence attention module; and step five: extracting a high-cost conduction risk path according to the storage cost time sequence attention result, calculating a shared warehouse comprehensive cost, and obtaining a shared storage resource reallocation scheme. The improved Graphormer model is used to realize intelligent reallocation of shared storage.

This application provides a method, device, and storage medium for accessing a mini-program. The method includes: upon detecting an access request for a target mini-program, determining whether the underlying resource files of the target mini-program are cached; if the underlying resource files of the target mini-program are not cached, obtaining the corresponding underlying resource files from the network based on the resource network path of the underlying resource files of the target mini-program, loading the obtained underlying resource files, and caching the obtained underlying resource files; if the underlying resource files of the target mini-program are cached, loading the cached underlying resource files of the target mini-program. This improves the efficiency of mini-program access.

A software defined distributed control system (SDCS) in a process plant includes an application layer that includes a plurality of containers instantiated in a data cluster. Each of the containers is an isolated execution environment executing within the local operating system of a respective computing node. The containers cooperate to facilitate execution of a control strategy in the SDCS, and includes a hyper converged infrastructure (HCI) operating across the data cluster, which HCI is configured to communicate with the application layer via an adapter service. The HCI includes software-defined (SD) compute resources, SD storage resources, SD networking resources, and an orchestrator service. The orchestrator service is programmed to configure a first container to include a service executing within the first container. It also assigns the first container to execute on an available hardware resource to control a plurality of field devices operating in the process plant.

The invention is applicable to the technical field of wireless communication, and provides a parallel detection communication integration method for an MIMO (Multiple Input Multiple Output) channel, which comprises the following steps of: setting system parameters in a user-defined manner, carrying out all-symbol reference signaling processing on a time-frequency resource network, and carrying out comb-shaped MIMO resource mapping to obtain a frequency domain resource network; transmitting terminal preprocessing work is carried out according to the frequency domain resource network to obtain a multi-antenna transmitting waveform, the multi-antenna transmitting waveform is transmitted, after a receiving terminal receives the multi-antenna transmitting waveform, receiving terminal preprocessing work is carried out, a channel is estimated and balanced, and a channel measurement result and a channel performance index are obtained; according to the invention, channel measurement and data transmission functions are deeply integrated, and cooperative work of the two functions is realized through unified signal design and processing flow, so that the system can synchronously complete high-precision channel estimation and high-quality data transmission.

The invention relates to the technical field of communication, in particular to a link generation method and device, equipment, a medium and a product, and the method comprises the steps: obtaining a pre-constructed resource tree model; wherein the resource tree model comprises association relationships among network equipment resources, network address resources and user service resources; converting resource data in the resource tree model into layer data, and projecting the layer data to a satellite map; in response to a trigger operation of a user for any map icon in the satellite map, constructing a topological relation of resource data corresponding to the map icon based on a predefined association relation in the resource tree model; and generating a visual link on the satellite map based on the topological relation. Through a predefined resource tree model, an association relationship among three kinds of resource data of equipment, addresses and services is established, an end-to-end topological link is automatically constructed and visualized, and visual positioning of a topological relationship from a single resource point to a full link is realized.

The invention provides a knowledge graph generation method and device and related equipment, and relates to the technical field of text processing. The method comprises the following steps: taking each resource, network service and business service in a communication network as an entity to obtain a plurality of entities; generating a composite vector of each entity, and clustering the plurality of entities according to the composite vector of each entity to obtain a classification tree; cutting the classification tree according to each similarity, and evaluating the result of each similarity cutting classification tree by using the contour coefficient to obtain a target result; using a large language model to guide a target result to perform hierarchical refinement; generating a triple of any two entities having a relationship in the target result, and optimizing all triples by using a scoring function of a knowledge graph embedding model; and generating the knowledge graph of the communication network according to all the triples. Through the technical means, the problem that deep semantic association between entities is difficult to accurately describe in a communication scene in related technologies is solved.

Embodiments of the present application provide an attribute selection method and device, electronic equipment and storage medium. The method comprises: initializing a plurality of populations, each population comprising a plurality of simulation nodes; determining the fitness of each simulation node according to the values of delay, bandwidth, throughput, computing resources, storage resources, network resources and load balancing indicators contained in each simulation node, and a preset fitness function; determining the simulation node with the maximum fitness from the plurality of populations based on the fitness of each simulation node; taking the key attribute corresponding to the population to which the simulation node with the maximum fitness belongs as a target attribute, the target attribute being an input of a resource allocation algorithm in an actual application process, and obtaining a resource allocation result. The key attribute of the population to which the simulation node with the maximum fitness belongs is taken as an input of a resource allocation algorithm in an actual application, so that resource allocation is performed in the actual application through the key attribute and the resource allocation algorithm, and resource utilization efficiency is improved.

The application belongs to the technical field of computer resource scheduling, and provides a multi-level computer resource multi-target dynamic scheduling method and system under algorithm-network fusion, comprising: obtaining a task request of a user; based on the obtained task request, constructing a global resource-network state distribution view; according to the parameters of the task request and the global resource-network state distribution view, taking minimizing task completion delay, optimizing load balancing and minimizing energy consumption as the target, generating a task-to-computing resource node allocation scheme and a task data transmission path planning scheme through a multi-target optimization scheduling model; according to the generated allocation scheme and path planning scheme, distributing the task to the corresponding computing resource node, and monitoring the task execution state and resource load in real time; when it is detected that the load of the computing node or the network link exceeds the preset threshold, triggering a task migration mechanism to complete the multi-target dynamic scheduling of the multi-level computing resource under algorithm-network fusion.

The invention provides a credit data association method based on a resource network, and belongs to the technical field of credit data updating, and the method comprises the steps: inputting multi-source credit data into a target data adapter, and obtaining target credit event information corresponding to the multi-source credit data; updating a predetermined credit data graph based on the target credit event information; according to the updated credit data atlas, credit scores corresponding to related credit subjects in the credit data atlas are updated to realize association of the credit data; wherein the step of updating the credit data atlas comprises at least one of the following items: creating edges and / or nodes in the credit data atlas based on the target credit event information; and updating the edge weight based on the target moment in the target credit event information. According to the credit data association method based on the resource network, the accuracy of credit data association can be improved.

Embodiments of the present application provide a resource configuration method, an information sending method and apparatus, wherein the resource configuration method comprises: a network device configuring a plurality of resources for a terminal device to transmit uplink control information (UCI); the network device sending at least one indication information to the terminal device, the at least one indication information comprising first indication information; the first indication information being used to indicate whether to combine first UCI and second UCI; wherein the resources configured for the transmission of the first UCI and the second UCI belong to a first resource set, the first resource set being a subset of a resource set composed of the plurality of resources, any resource in the first resource set overlapping at least one resource in the first resource set other than the any resource in the first resource set in the time domain, and the resources in the first resource set being continuous in the time domain. The terminal device can determine whether to combine the first UCI and the second UCI.

The invention relates to the technical field of pipeline layout, and discloses an underground communication pipeline-oriented layout optimization method, which comprises the following steps of: determining an associated region with a spatial coupling relationship between pipe sections; determining a resource-limited pipe section region range in the pipeline network topology structure by analyzing topology constraint association between the real-time pipe section occupation data and the association region of the space coupling relationship; aiming at the spatial fluctuation characteristics of the node historical flow in the pipe section area range, performing hierarchical quantitative analysis on the pipe section network transmission sensitivity degree, and determining the pipe section resource network transmission sensitivity level; pipeline path calculation is carried out by adopting a topological path search strategy of an embedded pipe section resource network transmission sensitivity level, and an optimal underground communication pipeline layout scheme is generated; according to the invention, the overall rationality of underground communication pipeline resource utilization and the continuous stability of network operation are improved.

1. Name of the product in this design: Resource information management module for a graphical user interface for resource relationships in electronic devices. 2. Intended use of this design: for use in an electronic device. 3. The key design features of this product are its graphical user interface. 4. The image or photograph that best illustrates the design's key points: Design 2 main view. 5. Due to the conventional design of electronic devices, other views are omitted. 6. Design 2 is designated as the basic design. 7. Purpose of the graphical user interface: To display the upstream and downstream relationships of a complex resource network, as well as the relationships between its components, within the application interface. Designs 1 to 4 represent the upstream and downstream relationships of purchased resources, and users interact with them by clicking on the function tabs at the top of the interface. The graphical user interface portion shown in the red semi-transparent obscured area in the interfaces of Designs 1 to 4 does not constitute the part that is protected by this design. In the graphical user interface of this product, the gray-framed area represents the content screen, such as an image, and the X-shaped area represents text and / or numbers.

The invention discloses a mineral resource potential prediction method and system based on artificial intelligence, and relates to the technical field of mine field resource prediction.The method comprises the steps that multi-source mineral data is collected, standardized processing and vectorization conversion are conducted, and a basic data set is generated; based on the basic data set, extracting spatial features and associated features of the basic data set, constructing a mineral resource network diagram and identifying a resource center node; based on the mineral resource network diagram and the resource center node, dividing same-level resource units by adopting an intelligent algorithm, and calculating basic scores of the units; constructing a mineral resource prediction model, and performing potential scoring and grade judgment on a target area after training and cross validation; and generating a resource potential prediction map, and outputting a prediction result. According to the method, a full-process intelligent mineral resource prediction system is constructed, accurate and efficient prediction of mineral resource potential is realized through multi-dimensional data integration, feature extraction and model training, and the problems of high subjectivity, poor adaptability, insufficient precision and the like of a traditional method are solved.

Disclosed are techniques for positioning. In an aspect, a network node receives, from a location server, a first request requesting on-demand positioning reference signal (PRS) configurations supported by the network node, transmits a response to the location server, the response identifying one or more alternate PRS configurations, one or more alternate PRS parameters, or both defining one or more on-demand PRS resources the network node would prefer to transmit during a positioning session between the location server and one or more target UEs, receives, from the location server, a second request requesting on-demand PRS transmission, the second request identifying at least one alternate PRS configuration, at least one alternate PRS parameter, or both, and transmits at least one on-demand PRS resource according to the at least one alternate PRS configuration, the at least one PRS parameter, or both.

The present disclosure discloses a method, a device, and related equipment for determining occasions for candidate PDSCH receptions. The method includes: determining target time domain resources, the target time domain resources being related to at least one of the following: first time domain resources indicated by the network-side device for the terminal; second time domain resources for multicast services sent by the network-side device; third time domain resources for broadcast services sent by the network-side device; fourth time-domain resources corresponding to a not configured subcarrier spacing; according to the determined target time domain resources, determining, occasions for candidate PDSCH receptions related to Hybrid Automatic Repeat Request-Acknowledgment (HARQ-ACK) information.