41 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.

The invention relates to the technical field of data security monitoring, and provides a multi-source data processing security risk analysis early warning method, which comprises the following steps: acquiring multi-source data, and constructing an ecological environment data system; wherein different ecological environment data in the ecological environment data system are configured with unique calling permissions according to asset levels; constructing a risk analysis model based on an application scene, inputting the activity data in the ecological environment data system into the risk analysis model, and determining whether target activity data of data threat exists or not; and inputting the target activity data into a preset safety risk early warning model to generate an early warning signal. The method is used for multiple links of collection, processing, analysis, early warning and the like of ecological environment data, the ecological environment network condition is evaluated, and factors and events possibly causing damage or threat to the environment network are found, analyzed and prevented.

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 processing, provides a disaster recovery network element node knowledge graph construction method based on graph structure and text fusion, solves the problem of complexity of disaster recovery network management and operation and maintenance in a modern cloud environment network, and provides a disaster recovery network element node knowledge graph construction method by collecting network topology information, network element performance indexes and state data from a plurality of network data sources. A graph structure and text data are formed through extraction and processing, then the graph structure and the text data are integrated into a fused graph structure, and disambiguation and redundancy removal processing are carried out. Then, the fusion graph structure is converted into a triple form, a complete knowledge graph is constructed, the knowledge graph comprises multi-dimensional information of network topology performance and network topology state data, and the multi-dimensional information is stored in a graph database and used for query, analysis and network operation and maintenance operation. The efficiency and accuracy of network operation and maintenance are improved, and the management cost and time are reduced.

The invention discloses a network situation information multi-dimensional linkage visualization system and method, a digital earth geographic information visualization module manages connected satellite images, electronic maps and elevation data, constructs a network space situation scene based on a digital earth by combining various network space node geographic information distribution conditions according to a service scene, and provides a multi-dimensional linkage visualization system for network situation information. Carrying out unified bearing and displaying on the geographical environment, the network platform, the network equipment and the communication link data; the multi-layer logical topology visualization module constructs a multi-layer network topology perspective view according to the data structure characteristics that network space nodes and situation information are distributed in multiple layers and multiple domains, constructs a logical relationship class view for showing the relationship among a network layer, a platform layer and an equipment layer and the internal logical topology structure of each layer, and displays the relationship among the network layer, the platform layer and the equipment layer; displaying a three-dimensional association topological structure of the node network, the network platform and the network equipment; and the Gantt chart module performs dynamic studio on the overall change process of the network situation information. According to the invention, the problem of single representation form of network space visualization at present is solved.

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.

Apparatuses, methods, and systems are disclosed for security context handling during AMF reallocation. One apparatus in a mobile communication network includes a network interface and a processor that derives a Reroute Security Context and derives a first authentication parameter for authenticating a Target AMF. The network interface receives a Key Request message from a SEAF co-located with the Target AMF following an AMF reallocation during a UE Registration procedure. The processor verifies the Key Request message by determining whether the second authentication parameter matches the first authentication parameter derived for authenticating the Target AMF. The processor derives a new security context for the Target AMF / SEAF in response to successfully verifying the Key Request message. The network interface sends a Key Response message to the Target AMF / SEAF.

The invention discloses an unmanned aerial vehicle sight distance limitation monitoring management method and device based on a 5G network, and the method comprises the steps: obtaining the position information of a plurality of unmanned aerial vehicles in real time, and calculating the actual distance between the unmanned aerial vehicle and an unmanned aerial vehicle controller; environment data and a network coverage state of the unmanned aerial vehicle are collected in real time, the environment data and the network coverage state are transmitted to a preset calculation model to calculate a VLoS threshold value of the unmanned aerial vehicle, and the VLoS threshold value is updated according to a calculation result; the actual distance is compared with a current VloS threshold value, and when the actual distance does not exceed the VloS threshold value, the unmanned aerial vehicle is controlled to act through an unmanned aerial vehicle controller; and when the actual distance of the unmanned aerial vehicle exceeds the VLoS threshold value, the UTM is triggered to take over the control right, and path control is performed through the UTM, so that the actual distance between the unmanned aerial vehicle and the unmanned aerial vehicle controller is controlled within the VLoS threshold value. According to the invention, the VLoS threshold can be updated in real time according to the environment and the network, the current visual range of the direct unmanned aerial vehicle is adjusted, the operation mode is flexibly switched, and the flight safety is ensured.

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 invention relates to the field of embedded system simulation, in particular to an embedded system high-fidelity simulation method based on distributed communication. The method comprises the following steps: constructing a virtual hardware environment of the embedded system; an embedded system virtual environment network is configured, and a distributed embedded system virtual simulation environment is constructed; constructing a distributed communication architecture based on the DDS middleware; and performing simulation verification in a virtual environment based on distributed communication. According to the method, the specific hardware environment and the operating system platform of the embedded system are simulated in the PC environment, high-fidelity simulation of the embedded system is achieved, the development efficiency of an embedded software program is improved, the testing cost is reduced, distributed communication is conducted through the DDS middleware in the virtual simulation environment, and the testing efficiency is improved. The method has the advantages of high reliability, high expandability, application program transportability and the like.

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.

Techniques and methods for detecting and displaying a cyber-security risk context of a cloud environment utilize a detection environment to initiate detection of cyber-security objects within the cloud environment and store information related to cyber-security objects found within the detected cloud environment in a storage environment. The techniques and methods also generate a cyber-security risk context for the detected cloud environment based on observation of cyber-security objects included in the detected cloud environment. The techniques and methods also configure a web browser running on the client device to enable cloud environment detection through a web page overlay or through a toolbar plug-in installed in the web browser and configured to enable cloud environment detection after the user has navigated to a web page containing a cyber-secure object identifier. And automatically displaying the generated network security risk background to a user.

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.