34 results about "Ambient network" patented technology

The invention relates to the technical field of cloud computing, in particular to a network data encryption and privacy protection system in a cloud environment, which comprises a key management unit driven by a wolf pack algorithm, an encryption algorithm optimization unit, a privacy protection strategy dynamic adjustment unit and a safety monitoring and abnormity response unit. The invention discloses a cloud environment network data encryption and privacy protection system constructed based on a wolf pack algorithm. High-security keys are dynamically generated and distributed through a key management unit, security performance and resource consumption are balanced through an encryption algorithm optimization unit, multi-target dynamic gaming and compliance guarantee are achieved through a privacy protection strategy unit, distributed attack detection and cooperative defense are completed through a security monitoring unit, and the security performance is improved through a cooperative feedback mechanism between the units. Intelligent encryption protection, dynamic strategy adjustment and efficient attack response of the full life cycle of the data in the cloud environment are realized, and the system security, the resource utilization rate and the compliance capability are remarkably improved.

Some embodiments of this disclosure include systems, apparatuses, methods, and computer-readable media for use in a wireless network for deploying User Plane Function (UPF) and edge computing virtualized network functions (VNF). For example, some embodiments are directed to a network management system. The network management system includes processor circuitry. The processor circuitry can be configured to transmit a request to an edge computing management system to instantiate an edge computing virtualized network function (VNF). The request can include an identifier of a Network Service (NS) where a User Plane Function (UPF) VNF supporting the edge computing VNF is located. The processor circuitry can be further configured to receive, from the edge computing management system, a response indicating that the edge computing VNF is instantiated.

The invention relates to an electric power pipe network intervention generation method of a diffusion model based on auto-reflection learning, belongs to the technical field of electric power pipe network space-time prediction, and solves the problem that modeling is insufficient on the influence of dynamic external environment factors such as weather change and load disturbance in the prior art. The method comprises the following steps of: S1, acquiring initial data information of the power pipe network, and obtaining a processed space-time observation sequence set, wherein the influence of dynamic external environments such as weather, human traffic, holidays and the like on the power pipe network and the power consumption is not considered; s2, performing causal mode decomposition by using a Koopman operator to obtain a dynamic environment component; s3, establishing a learnable denoising network; s4, establishing an environment network modulated by the dynamic environment component based on the dynamic environment component and a learnable denoising network; s5, establishing an auto-reflection learning mechanism model and training the auto-reflection learning mechanism model; and S6, processing the sampled data of the power pipe network by using the trained auto-reflection learning mechanism model to obtain an intervention generation result.

A technique and method for detection and display of the cybersecurity risk context of a cloud environment initiates an inspection of cybersecurity objects within a cloud environment utilizing an inspection environment and stores information pertaining to discovered cybersecurity objects within the inspected cloud environment in a storage environment. The technique and method further generate a cybersecurity risk context for the inspected cloud environment based on the observations made concerning the cybersecurity objects contained within it. The technique and method further configure a web browser running on a client device to automatically display the generated cybersecurity risk context to a user, either through a web page overlay or through a toolbar plugin which has been installed in the web browser and configured to enable inspections of a cloud environment, once the user has navigated to a web page containing cybersecurity object identifiers.

The invention relates to the technical field of data instruction optimization, and discloses an instruction optimization method and system based on privacy protection, a terminal and a storage medium, and the method comprises the steps: obtaining information of a plurality of devices through an environment perception layer, taking each device as a node, taking other devices as neighbor nodes, and calculating truncation Q values of all neighbor nodes, according to the method, the global gradient in the strategy network corresponding to each device is replaced, so that the state and action of the device are optimized, the privacy of device information is ensured by dual network isolation during optimization, and finally closed-loop optimization is performed on the strategy parameters at the current moment. According to the method, the measured data and the environment network are transmitted in an isolated manner through dual network isolation, the data security is improved, the global gradient is replaced by the truncated Q value, the complexity and the cost of calculating the global gradient are reduced, the privacy of the data is protected, and the data accuracy is improved.

A system and method for evicting a resource from a unified network topology (UNT) of a computing environment, is disclosed. The method includes: generating a representation of a UNT for a network topology of a computing environment, the representation based on a unified data schema, wherein the unified data schema is mapped to a plurality of data schemas, each corresponding to a unique data source; receiving an event record at a first time, the event record including a resource identifier; updating in the UNT a representation corresponding to the resource based on extracted data from the event record at the first time; determining that a time period has lapsed from the first time which is greater than a threshold; detecting that a number of event records which include the resource identifier is less than a threshold value; and removing the representation of the resource from the unified network topology.

The invention discloses a deep reinforcement learning calculation system and a calculation method thereof. The calculation method comprises the following steps: initializing an environment and a model; executing the experience collection process and the network updating process in parallel, and judging whether the experience collection process and the network updating process reach termination conditions or not; continuously executing the experience collection process and the network updating process in parallel in response to the situation that neither the experience collection process nor the network updating process reaches the termination condition; and in response to one of the experience collection process and the network updating process reaching a termination condition, ending execution of the experience collection process and the network updating process. The experience collection process comprises obtaining the current state of the environment; according to a current strategy of the model, calculating based on the current observed value to determine a current action; and returning the current action to the environment. The network updating process comprises obtaining a previous state of the environment and a previous strategy of the model; deciding current data based on the previous state operation; and updating a previous policy of the model to the current policy based on the current data.

The invention belongs to the technical field of cloud native environments, and particularly relates to a cloud native environment-oriented full-flow threat sensing and tracing system, which comprises a data acquisition layer deployed on each computing node of a cloud native cluster and used for acquiring east-west network flow and north-south network flow; the data preprocessing and storage layer is connected with the data acquisition layer, and is used for performing analysis, specification and standardization processing on the acquired original traffic and storing the processed original traffic as a structured traffic log; the dynamic strategy engine is connected with the data preprocessing and storage layer and is used for generating and adjusting a security strategy based on a real-time flow analysis result; and carrying out visualization and traceability analysis. According to the invention, through multi-level data acquisition and fusion, all-around deep monitoring of network activities in a cloud native environment is realized, and specifically, an eBPF probe is deployed on a kernel layer of an operating system in a data acquisition layer, so that basic network connections and data packets of all Pods can be captured without invasion.

The embodiment of the invention provides a network switching method and device of a terminal, electronic equipment and a storage medium. The method comprises the following steps: after a to-be-switched terminal is powered on and started, obtaining network connection information of the to-be-switched terminal; wherein the network connection information comprises a cell connected to a 5G network and a cell connected to a non-5G network; if the network connection information of the to-be-switched terminal is that the to-be-switched terminal is connected to the non-5G network cell, acquiring network access parameters and environment network information of the to-be-switched terminal; wherein the network access parameter indicates a parameter of an access network supported by the terminal; the environment network information indicates network basic information of a network cell in an area range where the to-be-switched terminal is located; and performing network switching processing according to the acquired network access parameters and environment network information. The method is used for achieving the effects of improving the network switching efficiency, reducing the resource loss of network switching and improving the network use experience of a user.

This invention introduces an energy-efficient communication protocol for Ambient IoT, integrating Slotted ALOHA with RF energy harvesting to enable reliable interaction between ultra-low-power, battery-less devices and 5G / 6G base stations or relay UEs. Devices first harvest energy from a Carrier Wave (CW) signal, followed by a structured five-message exchange (Msg0–Msg4) handling synchronization, random access, data transmission, and acknowledgments. Time-frequency resources are dynamically allocated based on device energy levels and random IDs, reducing collisions and improving throughput. Control signals use differential encoding for robustness. Each message is framed with a preamble and postamble, allowing the device to detect the start and end of the signal. Padding is inserted before the preamble to ensure alignment with NR OFDM symbol boundaries. A Slotted ALOHA-based retransmission strategy enhances channel reuse. Eliminating dedicated RFID readers, this approach supports long-range, interference-managed communication, offering a scalable, low-latency, and cost-effective solution for massive machine-type communication (mMTC) in next-generation Ambient IoT networks.

The application discloses a software simulation environment building method, device, medium and program product, and relates to the field of software development. The software simulation environment building method comprises the following steps: obtaining a network resource arrangement instruction; arranging target managed resources according to the network resource arrangement instruction to obtain a target environment network topology; configuring a node image file according to the target environment network topology to obtain a network topology to be instantiated; and performing code testing and verification according to target test code, the network topology to be instantiated and topology node usage state data. The technical scheme of the embodiment of the application can improve the building efficiency of a software development simulation environment and break the strong dependence of simulation environment building and instantiation on manpower.

Relatively simple user input is used to build an entire application. Input data defines a set of specifications for an automated machine. The set of specifications includes one or more of hardware specifications, operating systems, software frameworks, runtime environments, network connectivity, and environmental considerations. The input data is analyzed to retrieve relevant information from a large corpus including a plurality of libraries. One or more prompts are generated based on the relevant information, and the one or more prompts are used to generate programmable logic controller (PLC) code including a sequence of operations for controlling the automated machine.

A wireless communication method includes sending, by a first communication node to one or more second communication nodes, one or more first downlink (DL) messages, the one or more first DL messages include at least one of ambient device assistance information and / or resource allocation assistance information; and receiving a first uplink (UL) message in response to the first DL message from second communication nodes. Another wireless communication method includes receiving, by a first communication node from a second communication nodes, a first DL message, the first DL message includes at least one of ambient device assistance information and / or resource allocation assistance information; operating the one or more ambient devices associated with the first communication node according to the first DL message; and sending, by the first communication node to the second communication node, a first UL message in response to the first DL message.

The application discloses a network data deduplication method and system in a cloud environment based on an autoregressive model, and relates to the technical field of big data processing. The method comprises the following steps: step 1, obtaining network data to be stored containing similar data in the cloud environment; step 2, establishing a cloud environment elastic space model, determining the spatial autocorrelation measurement value of the network data and performing data denoising processing; step 3, obtaining the multi-dimensional scale attribute features of the data; step 4, performing clustering processing on the network data through the multi-dimensional scale attribute features of the data; step 5, establishing a network redundant data prediction model; and step 6, inputting the denoised network data into the network redundant data prediction model and performing redundant data elimination processing. The application can not only suppress noise data in the network data, but also realize clustering of the network data in the cloud environment, improve the data deduplication efficiency, and save a large amount of storage resources and management resources of the cloud server.

The embodiment of the invention provides an informatization equipment task scene analysis and fusion modeling system and method, and the system comprises a task environment analysis module which is used for analyzing an external situation environment, a network environment influence and an internal cross-linking environment faced by informatization equipment in a task; the task rule analysis module is used for describing and analyzing actions and events in a task scene based on a rule method; the task process analysis module is used for constructing and executing a model for describing the task process of the informatization equipment; and the scene fusion modeling module is used for fusing the analysis results of the task environment, the task rule and the task process to construct a task scene fusion model. By means of the method, modeling of different task scenes such as cross-field and cross-military-type task scenes of informatization equipment can be achieved, the task scenes can be analyzed, and environment elements in the task scenes can be extracted.

The present disclosure provides methods, apparatuses, and computer program products for explicit deactivation and activation of environmental network Internet of Things devices. In the context of a method, the method includes receiving, from a user device, a first signal including a list of device identifiers, where the list of device identifiers describes at least one device to be deactivated. The method includes deactivating the device based on a determination that the device identifier is included in the device identifier list. The method includes receiving a second signal including an activation list from the user device or a second user device, wherein the activation list describes at least one device to be activated. The method includes activating the device based on a determination that the device identifier is included in the activation list.

The invention relates to a method and a system for adjusting an antenna angle of an intelligent router. The method for adjusting the antenna angle of the intelligent router comprises the steps of obtaining environment network data of an environment where the intelligent router is located, wherein the environment network data comprises signal strength, user distribution and obstacle positions; preprocessing the environment network data; analyzing the preprocessed environment network data so as to analyze a signal to-be-enhanced area; and adjusting the angle of the intelligent router antenna based on the analyzed signal to-be-enhanced area. According to the invention, the angle of the antenna of the intelligent router can be automatically adjusted according to actual needs, so that the environment where the intelligent router is located can obtain stable network signals, and the user experience is improved.

The invention relates to the technical field of network space surveying and mapping, in particular to a cloud native network space surveying and mapping method and device, computer equipment, a storage medium and a computer program product. The method comprises: in response to a network surveying and mapping instruction, determining a network surveying and mapping environment based on the network surveying and mapping instruction, the network surveying and mapping environment comprising an initial network space; acquiring a data transmission node set, other node sets, a target transmission node and a reference transmission node set in the initial network space; obtaining a known node coordinate set based on the plurality of target transmission nodes and the reference transmission node set; the known node coordinate set is analyzed to obtain a data transmission path set, and the data transmission path set comprises a plurality of data transmission paths; and generating a cyberspace surveying and mapping graph based on the other node set, the known node coordinate set, the data transmission path set and a preset surveying and mapping coordinate system. By adopting the method, the accuracy and the intelligent degree of network space drawing can be improved.

This invention discloses a radio direction finding anomaly detection method based on image segmentation, comprising: acquiring real radio data; constructing a multi-signal classification spatial spectrum estimation function to extract the azimuth angle of the UAV signal; reassembling the azimuth angle data slices into a two-dimensional matrix set, calculating the true azimuth angle of the UAV, and constructing a training dataset; constructing a radio direction finding anomaly detection network based on an encoder and decoder structure; determining the optimization objective of the radio direction finding anomaly detection network and adjusting the loss function used for the network parameters; training the radio direction finding anomaly detection network using the training dataset; inputting test data into the anomaly detection network and outputting pixel-level azimuth angle prediction results. This invention achieves higher anomaly removal accuracy than existing methods, has strong transferability, can adapt to new radio azimuth angle acquisition environments, and has strong network interpretability, enabling better application in practical communication scenarios.

Relatively simple user input is used to build an entire application. Input data defines a set of specifications for an automated machine. The set of specifications includes one or more of hardware specifications, operating systems, software frameworks, runtime environments, network connectivity, and environmental considerations. The input data is analyzed to retrieve relevant information from a large corpus including a plurality of libraries. One or more prompts are generated based on the relevant information, and the one or more prompts are used to generate programmable logic controller (PLC) code including a sequence of operations for controlling the automated machine.

The invention relates to the technical field of smart home application, in particular to a mobile terminal data dynamic caching method based on user habits and equipment resources, which comprises the following steps: establishing an association model of user operation behaviors and terminal resources by identifying a user account and binding a common mobile terminal; generating a high-frequency usage scene template based on user historical operation data, and dynamically updating the template in combination with time distribution, position environment, network environment information and a terminal resource occupancy rate; the resource occupation state of the terminal is monitored, and data preloading is triggered in an idle period or a low resource occupation state; and dynamic updating and synchronization of the data are completed through a cooperation mechanism of the cloud and the client. According to the method, user behaviors, equipment states and time factors are comprehensively considered, efficient data management and caching are realized, and the performance and user experience of the smart home system are remarkably improved.

This invention discloses a distributed multiple access system for a symbiotic radio network based on reconfigurable holographic devices, comprising: a background network (BS / UE) and an IoT network consisting of K reconfigurable holographic devices (RHDs) and IoT receivers (IRs); each RHD integrates an antenna, a load modulator, and a reconfigurable holographic surface (RHS), which converts a reference wave carrying IoT information into a target wave and radiates it into free space by activating subwavelength radiating elements, overcoming the size limitations of traditional RIS / phased arrays; the IoT receiver (IR) employs distributed decoding based on random code-based code division multiple access (CDMA), utilizing matched filter (MF) or minimum mean square error (MMSE) receivers combined with asymptotic signal-to-interference-plus-noise ratio (SINNR) theory to eliminate the need for real-time random code feedback; the radiation pattern is optimized based on the weighted minimum mean square error (WMMSE) algorithm to maximize RHD and data rate. The advantages of this invention are: device size supports integration of micro-IoT devices; IoT SINNR is improved by more than 20dB; and it enables massive IoT device access.

This invention discloses a method and device for monitoring and managing line-of-sight (VLoS) limitations of unmanned aerial vehicles (UAVs) based on a 5G network. The method includes: acquiring the location information of several UAVs in real time and calculating the actual distance between the UAVs and their controller; collecting environmental data and network coverage status of the UAVs in real time, transmitting the environmental data and network coverage status to a preset calculation model to calculate the VLoS threshold for the UAVs, and updating the VLoS threshold based on the calculation results; comparing the actual distance with the current VLoS threshold, and controlling the UAV's actions through the UAV controller when the actual distance does not exceed the VLoS threshold; and triggering a UTM (Unified Device Manager) to take over control when the actual distance exceeds the VLoS threshold, using the UTM for path control to keep the actual distance between the UAVs and their controller within the VLoS threshold. This invention can update the VLoS threshold in real time based on the environment and network, adjust the current line-of-sight range of the UAVs, flexibly switch operating modes, and ensure flight safety.

A technique and method for detection and display of the cybersecurity risk context of a cloud environment initiates an inspection of cybersecurity objects within a cloud environment utilizing an inspection environment and stores information pertaining to discovered cybersecurity objects within the inspected cloud environment in a storage environment. The technique and method further generate a cybersecurity risk context for the inspected cloud environment based on the observations made concerning the cybersecurity objects contained within it. The technique and method further configure a web browser running on a client device to automatically display the generated cybersecurity risk context to a user, either through a web page overlay or through a toolbar plugin which has been installed in the web browser and configured to enable inspections of a cloud environment, once the user has navigated to a web page containing cybersecurity object identifiers.

The invention provides a commercial password application construction method and device for a thermal power plant DCS system, and relates to the technical field of control systems, and the method comprises the steps: collecting the physical environment, network topology, equipment configuration and business data flow information of the DCS system, recognizing a password application gap, and generating a risk assessment report; building a multi-dimensional password demand model of physical access control, network communication encryption and the like based on the report, and outputting a structured list; designing a five-layer deep defense system from a physical layer to a data layer, configuring a password product cooperating with an SM2 / SM4 algorithm, and establishing a key hierarchy mechanism; abnormal login, equipment health degree and network attack intensity data are collected in real time, a comprehensive risk value is calculated, key updating is triggered according to a preset threshold value, and an emergency response plan and log auditing are synchronously executed. According to the invention, the password application security and the real-time protection capability of the DCS system of the thermal power plant are effectively improved.

A system and method for evicting a resource from a unified network topology (UNT) of a computing environment, is disclosed. The method includes: generating a representation of a UNT for a network topology of a computing environment, the representation based on a unified data schema, wherein the unified data schema is mapped to a plurality of data schemas, each corresponding to a unique data source; receiving an event record at a first time, the event record including a resource identifier; updating in the UNT a representation corresponding to the resource based on extracted data from the event record at the first time; determining that a time period has lapsed from the first time which is greater than a threshold; detecting that a number of event records which include the resource identifier is less than a threshold value; and removing the representation of the resource from the unified network topology.

A system and method for incident detection based on a unified network topology of a computing environment is presented. The method includes: generating a representation of a unified network topology for a network topology of a computing environment, the representation based on a unified data schema, wherein the unified data schema is mapped to a plurality of data schemas, each data schema corresponding to a unique data source; receiving an event record respective of a first resource, the first resource represented in the unified network topology; determining a baseline behavior of the first resource based on the unified network topology; generating a predicted incident based on the baseline behavior and the received event record; and initiating a remediation action based on the predicted incident.

The invention provides a machine learning-based plug-in WIFI chip power consumption intelligent optimization method and related equipment, and relates to the technical field of electric digital data processing. The method comprises the following steps: acquiring environment network condition information, including signal strength and channel interference condition, and historical operation time information of equipment, and the historical operation time information assists in judging the performance requirement level of the equipment; meanwhile, a WIFI chip parameter adjustment model constructed through deep learning determines adjustment parameters according to an environment network and performance demand level information, and finally adjusts working parameters. By implementing the method, the chip can meet the requirements of environment and equipment, high-power-consumption operation of the chip when unnecessary is avoided on the premise that stable networking, smooth data transmission and other performance of the equipment are guaranteed, power consumption is effectively reduced, and the energy utilization efficiency is improved.

The invention provides a power environment network hidden danger identification method and device, electronic equipment and a storage medium, and belongs to the technical field of power environment networks, and the method comprises the steps: obtaining a nameplate image of each piece of equipment in a power environment network and a label image of each terminal of each piece of equipment; identifying a device name in each nameplate image, each terminal name in each label image and a downstream device name corresponding to each terminal name; generating a topological graph of the dynamic environment network according to the device name, the terminal name and the downstream device name in each nameplate image; and identifying the routing hidden danger of the dynamic environment network according to the topological graph of the dynamic environment network. According to the method, the routing hidden danger of the dynamic environment network can be visually recognized in a graphical mode, manual troubleshooting is not needed, and the recognition efficiency of the routing hidden danger of the dynamic environment network is improved.