34 results about "Network awareness" patented technology

The invention discloses an MVPS video coding method and device based on deep learning, and a medium, and relates to the technical field of video coding. The method comprises the following steps: acquiring a video stream, performing time domain and space domain feature extraction on the video stream through a feature extraction unit, and generating a joint feature map through an adaptive weight fusion layer; carrying out bidirectional feature interaction between hierarchies on the combined feature map to obtain a multi-scale feature set; generating a frame-level quantization parameter initial value according to the multi-scale feature set in combination with current network bandwidth feedback; performing time sequence consistency correction on the quantization parameter initial value to generate a target quantization parameter; and performing block coding on the current frame according to the target quantization parameter to generate a coded data stream. According to the method, through dynamic parameter adjustment, hardware algorithm collaborative optimization, cross-frame consistency enhancement and network awareness, the problems of low efficiency, insufficient real-time performance, unstable quality and poor adaptability of a traditional scheme are solved.

A communication method and a related device are applied to the field of network awareness. In the application, a first node can obtain accumulated time delay information of N routing paths, and determine a target routing topology between the first node and a root node at least based on the accumulated time delay information of the N routing paths, the first node and the root node belong to the same network domain, and the path through which the message of the first node passes when being transmitted in the network comprises the first node and the root node. The shorter the time delay of message transmission between the nodes in the network domain is, the higher the stability of message transmission of the routing topology passing through the shorter time delay is, so that the target routing topology of the node transmission message in the same network domain is screened out from the obtained accumulated time delay information of the N routing paths, and the stability of the message transmission of the node transmission message in the network domain is improved. A low-delay message transmission routing path can be coordinated among the nodes. And the message of the node is transmitted through the target routing topology, so that the reliability of the end-to-end delay can be ensured.

The invention relates to the technical field of navigation, in particular to an end-to-end visual language navigation method and device based on occupancy network awareness and computer equipment, and the method comprises the following steps: receiving a language instruction, and obtaining a color image and a depth map collected by an RGB camera and a depth camera; performing feature extraction on the color image and the depth image through a ViT model to generate image features and depth features, and performing rotation and translation transformation on the depth features through a camera model to generate a blank 3D voxel space; mapping the image features to a blank 3D voxel space to generate 3D voxel features, and constructing the image features into a topological graph; inputting the 3D voxel features, the topological graph and the language information into a BERT model to obtain text features; and inputting the text features, the 3D voxel features and the topological graph into a cross-modal model, and predicting a navigation path. The method and the device are helpful for improving the accuracy of navigation decision.

The invention provides an aluminum substrate drilling tool wear prediction method based on reinforcement learning, and the method comprises the steps: collecting working condition parameters, such as main shaft rotation speed, feeding speed, cutting depth, material type and historical vibration energy, through the deployment of an industrial sensor network, and achieving data standardization through feature extraction and normalization processing; a dynamic cognitive map with process meaning is constructed by adopting semantic analysis and a map generation strategy, key semantic nodes are identified by utilizing a map attention network, reinforcement learning is driven through a structured reward function, and self-adaptive optimization of a wear prediction strategy is realized; according to the method, abnormal detection and working condition abrupt change increment updating are supported, map consistency optimization is achieved by fusing expert experience, the tool wear prediction precision and the environment adaptability can be improved, and the intelligent sensing and dynamic response capacity to the complex manufacturing process can be enhanced.

Aspects of the subject disclosure may include, for example, obtaining satellite data indicative of satellite communication coverage areas associated with a plurality of satellites, wherein the satellite data includes locations for the satellite communication coverage areas as well as duration times for the satellite communication coverage areas; obtaining mobile device data associated with a plurality of mobile devices that are respectively attached to a wireless network, wherein the mobile device data indicates a respective location of each of the plurality of mobile devices, and wherein the plurality of mobile devices includes a first mobile device; determining whether the wireless network has information to be sent to the first mobile device, resulting in a first determination; determining, based upon the satellite data and a first location of the first mobile device, whether a period of time that the first mobile device is predicted to be out of the communication coverage areas meets a threshold, resulting in a second determination; and responsive to the first determination being that the wireless network has information to be sent to the first mobile device and to the second determination being that the period of time meets the threshold, facilitating an action. Other embodiments are disclosed.

The invention discloses a data transmission method based on low-delay optimization, which comprises the following steps of data preprocessing, data classification, partitioning, compression and encryption preprocessing operation, transmission scheduling, multi-path selection, priority scheduling and flow shaping function realization, network transmission, actual data packet sending and receiving processing and basic transmission control. According to the data transmission method and system based on low-delay optimization and the computer readable storage medium, through real-time network awareness and machine learning technologies, the system can dynamically adjust a transmission strategy and adapt to diversified network environments, and the data transmission efficiency is improved. And a multi-dimensional priority model and an intelligent scheduling algorithm ensure that key data obtains an optimal transmission path and resources.

The invention discloses a fault diagnosis method and device for electrical equipment, electronic equipment and a storage medium. According to an electromagnetic interference index, the data acquisition frequency and range are dynamically adjusted, high-frequency acquisition is pertinently started for state abnormal equipment so as to accurately capture abnormal signals, and multi-source data such as partial discharge pulses are fused. An equipment state feature sequence is constructed in combination with historical operation data, and high-correlation sensitive features are screened, so that the limitation of a single parameter is avoided; meanwhile, early faults are recognized and early warning is output through a pre-trained long-short-term memory neural network, a protection constant value is rechecked in cooperation with a rule engine and a convolutional neural network, a standby loop is automatically switched or the constant value is adjusted when abnormity occurs, and a complete monitoring-early warning-response closed loop is formed; the technical effects of improving the equipment state evaluation comprehensiveness, enhancing the early fault recognition capability, improving the early warning accuracy, increasing the response speed of the protection system and guaranteeing the operation safety and reliability of the electrical equipment and the power grid of the power plant are achieved.

This disclosure describes methods and apparatus to perform CP based UE-side Data Collection with network awareness for wireless communication systems. The overall procedure contains the stage of data collection configuration and control, data collection, data report and transfer. The Data collection configuration and control stage contains network coordination and determines to activate data collection, network selects the UEs for data collection, network indicates the data collection activation indication and configuration to the selected UE, UE applies the configuration and activates data collection functionality to collect data. The data collection stage contains UE performs measurement based on the received configuration for data collections, UE collects UE-dependent information in the container, UE logs the collected data for data reporting. The data report and transfer stage contains data sharing over the air interface and data file transfer to the UE server.

This invention provides a route status awareness method and apparatus for distributed network probe collaborative monitoring, relating to the field of communication network monitoring technology. It includes: deploying a distributed probe device at key nodes, integrating an active detection module, a passive traffic monitoring module, a data fusion analysis unit, and a detection control module; the active detection module supports periodic and targeted detection, dynamically adjusting detection priority and path; the passive monitoring module uses deep packet inspection and machine learning models to achieve fault location and anomaly tracing; the data fusion analysis unit constructs a dynamic route status graph using a spatiotemporal correlation algorithm to characterize link health and abnormal situations; and the detection control module dynamically switches detection modes based on network load, resource consumption, and historical indicators to balance detection accuracy and overhead. This invention improves network awareness accuracy and reduces resource consumption through active-passive collaborative detection and intelligent decision-making mechanisms, supporting efficient autonomous operation and maintenance of 5G / 6G networks.

The invention discloses a heterogeneous hardware acceleration method for plant disease and insect pest image recognition based on an FPGA and an ARM, and the method comprises the steps: employing a CSPdarknet53tiny as a trunk feature extraction network of Yolov4tiny, employing a layer fusion principle during the export of operator parameters, carrying out the optimization of a data flow and an interface of a designed hardware accelerator, employing a dual-buffer structure, and enabling the hardware acceleration to be more stable and reliable. An AXI bus Central DMA is designed at an interface, and finally, prediction frame decoding after network post-processing and a non-maximum suppression algorithm are implemented at an embedded PS end, so that an identification result can be obtained in real time when an accelerator network obtains a result. According to the method, an efficient and accurate hardware accelerator is designed in an embedded application scene, particularly in the aspect of plant disease and insect pest image recognition, the network recognition accuracy is improved, meanwhile, the parameter quantity of a network and the transmission efficiency of hardware are considered, greater possibility is provided for deployment of a recognition system at a mobile terminal, and the application prospect is wide. Meanwhile, the labor cost is reduced, and a powerful technical basis is provided for subsequent plant disease and pest control.

The invention provides a shared network awareness method and device, electronic equipment and a storage medium, and relates to the field of communication. The method comprises the steps of determining a target sensing mode corresponding to an application scene based on the application scene of a target sensing task; based on the target sensing mode, identifying whether a base station in a sensing area of the target sensing task and / or a terminal signed by the first operator can be used as sensing equipment for executing the target sensing task; and under the condition that existence of the sensing equipment is identified, a first message is issued to the sensing equipment, and the first message is used for indicating execution of the target sensing task. According to the method and the device, the requirement of the sensing service can be fully considered, the sensing service implementation process in the shared network architecture can be clarified, the identified sensing equipment can be ensured to perform the subsequent sensing service, the safe and effective execution of the sensing service is ensured, and the resource waste caused by improper equipment selection is avoided.

The invention discloses a network simulation dynamic aggregation presentation method and system based on situation awareness and GIS, and relates to the technical field of communication simulation, and the method comprises the steps: obtaining a node real-time movement track and link quality parameters through a sensor and a simulation engine, and generating a simulation data flow containing network topology, a link state and geographic information; the network awareness module evaluates network topology connectivity in real time and detects abnormal links, and meanwhile, the node awareness module comprehensively calculates node degree centrality, betweenness centrality, connectivity and survivability indexes to generate a situation awareness report; screening network core nodes to form an aggregated simplified network structure; the display granularity is adaptively switched according to the GIS map zoom level, the DEM terrain elevation and the DOM satellite image are fused to realize three-dimensional situation superposition, and finally a dynamically aggregated spatialization network situation interface is presented. According to the invention, the real-time monitoring and decision-making efficiency of the mobile communication network in a complex dynamic environment can be improved.

The invention discloses a cross-data center RDMA network congestion control method and device based on in-band telemetering, and belongs to the technical field of network transmission control. The method comprises the following steps: sending a first cross-data center flow to an upstream DCI switch at an initial rate; according to a Switch-INT message returned by an upstream DCI switch, a first fair rate is calculated, a second cross-data center flow is sent to the upstream DCI switch at the first fair rate, an ACK message of a downstream data center responding to the first cross-data center flow is obtained, and the ACK message comprises a suggested rate; and generating a final rate in combination with the first fair rate and the suggested rate, and sending a third cross-data center flow to an upstream DCI switch at the final rate. According to the method, the network sensing capability of the cross-data center flow can be improved, the fairness of the flow in the data center and the cross-data center flow is improved, and the transmission delay of the datagram is optimized.

The application discloses a network simulation dynamic aggregation presentation method and system based on situation awareness and GIS, and relates to the technical field of communication simulation.The method comprises the following steps: acquiring node real-time moving track and link quality parameters through a sensor and a simulation engine, and generating simulation data flow containing network topology, link state and geographic information; a network awareness module evaluates network topology connectivity and detects abnormal links in real time, while a node awareness module comprehensively calculates node degree centrality, betweenness centrality, connectivity and invulnerability indexes, and generates a situation awareness report; core nodes of the network are screened, and a simplified network structure after aggregation is formed; display granularity is adaptively switched according to GIS map zoom levels, three-dimensional situation superposition is realized by fusing DEM terrain elevation and DOM satellite images, and finally a dynamic aggregation spatialized network situation interface is presented.The application can improve the real-time monitoring and decision-making efficiency of a mobile communication network in a complex dynamic environment.

Various solutions for user equipment (UE) side data collection in mobile communications are described. A UE may receive a data collection activation indication and a data collection configuration from a network. The network may include a radio access network (RAN) node and at least one of an operations, administration, and maintenance (OAM) device and a UE server. Also, the UE may perform a data collection based on the data collection configuration. Further, the UE may report the data corresponding to the data collection configuration to the network when a reporting condition is met. The framework of control plane-based UE side data collection with network awareness provides clear and flexible procedures for data collection configuration, data collection and data reporting, such framework may efficiently supply the vast datasets demanded by artificial intelligence (AI) or machine learning (ML) model training.

The embodiment of the invention relates to a processing method and device for planning a short message retransmission strategy based on a network awareness state. The method comprises the following steps: carding a state type set S, defining a cost index C, and configuring a strategy parameter set and a strategy parameter value domain DP corresponding to the strategy parameter set; constructing an index prediction model and a strategy prediction model; constructing a first data set; training an index prediction model based on the first data set; optimizing the optimal strategy configuration corresponding to each state sample by taking the minimum cost index as an optimization target, and constructing a second data set based on all the state samples and the corresponding optimal strategies; training a strategy prediction model based on the second data set; and the strategy prediction model and the index prediction model dynamically plan the short message retransmission strategy of the server according to the real-time network state of the short message sending server and predict the cost index of the planning strategy. According to the invention, the configuration flexibility of the short message retransmission strategy can be improved, and the cost control can be optimized.

This invention relates to the field of human-computer interaction and intelligent control technology, and discloses a control method and system for an intelligent mouse. The method comprises five steps: user action acquisition, action feature encoding, semantic intent recognition, mouse behavior mapping, and feedback adjustment and optimization. The system comprises a motion acquisition and feature extraction module, an intent recognition and control signal generation module, and a behavior feedback and adaptive optimization module. By integrating an inertial measurement unit and a pressure sensor to acquire three-dimensional hand motion data, combining temporal convolutional coding and a Transformer network to recognize user operation intent, and generating mouse control signals based on context, precise control and adaptive optimization of the mouse are achieved. This invention enables complex operations without physical buttons, improving the personalization and intelligence of mouse control. It is applicable to intelligent interactive devices, auxiliary input systems, and other scenarios.

Various solutions for user equipment (UE) side data collection in mobile communications are described. A UE may receive a data collection activation indication and a data collection configuration from a network. The network may include a radio access network (RAN) node and at least one of an operations, administration, and maintenance (OAM) device and a UE server. Also, the UE may perform a data collection based on the data collection configuration. Further, the UE may report the data corresponding to the data collection configuration to the network when a reporting condition is met. The framework of control plane-based UE side data collection with network awareness provides clear and flexible procedures for data collection configuration, data collection and data reporting, such framework may efficiently supply the vast datasets demanded by artificial intelligence (AI) or machine learning (ML) model training.

The invention belongs to the field of ad hoc networks, and provides a network sensing method, device and system for an ad hoc network splitting and fusion scene, electronic equipment and a storage medium, and the method comprises the steps: carrying out the analysis of an obtained communication signal, and obtaining a shading signal superposed in the communication signal; obtaining ID information of a sender of the communication signal according to the shading signal; judging whether a sender of the communication signal belongs to a new network or not according to the ID information; determining whether to perform network convergence processing according to a judgment result; according to the method, communication bandwidth is not additionally occupied, a new sensing channel is not required to be established, link establishment between nodes is not required to be depended on, time slot synchronization is not required to be established, data content of baseband signals is not required to be analyzed, and the network node ID in the area can be sensed only by receiving and analyzing the shading signals, so that whether a sender belongs to a new network or not is identified; the method is wide in application range, has good robustness, and can guarantee the integration of communication stability and perception.

Various solutions for user plane (UP) -based data collection in mobile communications are described. A user equipment (UE) may receive a data collection activation indication and a data collection configuration from a network node through a UP tunnel. The network node may include at least one of an operations, administration, and maintenance (OAM) device and a UE server. Also, the UE may perform a data collection based on the data collection activation indication and the data collection configuration. Further, the UE may report data corresponding to the data collection configuration to the network node through the UP tunnel. The UP-based UE side data collection framework, incorporating network awareness, offers a clear, flexible, and efficient methodology for configuring, collecting, and reporting data. This framework is well-suited to efficiently deliver the large datasets required for artificial intelligence (AI) or machine learning (ML) model training.

A network awareness assisting method and a communication device are applied to the technical field of communication. The method comprises the following steps: a terminal sends first request information, wherein the first request information is used for requesting first sensing information; then, the terminal receives first sensing information from the access network equipment, and the first sensing information indicates one or more of the following items: first environment point cloud information, first environment power spectrum information or first obstacle position information; and then, the terminal performs task reasoning based on the first perception information. By adopting the method, the task execution efficiency can be improved.

This disclosure describes methods and apparatus for UE to perform UP-based data collection for UE side offline model training with network awareness for wireless communication systems, further comprising the steps of receiving data collection activation and control configurations from a UE server, performing measurement and collection based on received activation and configuration, and reporting collected data to UE server. The overall procedure contains the stage of data collection configuration and control, data collection, data report and transfer.

A network perception method, distributed device, equipment and computer readable storage medium. In the device forwarding layer, the message is not encapsulated, the device bandwidth during forwarding is guaranteed, and the device bandwidth utilization is improved; real-time detection and flow sampling reporting are performed to guarantee data accuracy and low overhead of the control layer; the control layer sends information of the control layer state table according to a sending weight, so that the management layer can receive important network state information more preferentially, and the overall overhead of the management layer is reduced; compared with the existing network perception technology based on in-band measurement, by maintaining the forwarding layer state table, the perception level is adjusted from a data packet to a data flow level, the consumption of network bandwidth resources is reduced, and the processing complexity and the consumption of computing resources of the management layer are also reduced.

Various solutions for user plane (UP) -based data collection in mobile communications are described. A user equipment (UE) may receive a data collection activation indication and a data collection configuration from a network node through a UP tunnel. The network node may include at least one of an operations, administration, and maintenance (OAM) device and a UE server. Also, the UE may perform a data collection based on the data collection activation indication and the data collection configuration. Further, the UE may report data corresponding to the data collection configuration to the network node through the UP tunnel. The UP-based UE side data collection framework, incorporating network awareness, offers a clear, flexible, and efficient methodology for configuring, collecting, and reporting data. This framework is well-suited to efficiently deliver the large datasets required for artificial intelligence (AI) or machine learning (ML) model training.

The invention provides a network security event analysis method and system through network awareness, and the method comprises the steps: obtaining channel data of a base station, the channel data comprises a physical layer channel parameter and a transmission layer channel parameter, building a first initial time domain tensor based on the historical data of the physical layer channel parameter, and transmitting the first initial time domain tensor to a second initial time domain tensor; constructing a second initial time domain tensor based on the historical data of the transmission layer channel parameters, inputting the second initial time domain tensor into a preset baseline construction model, and outputting baseline data; constructing a real-time time domain tensor based on the real-time data of the physical layer channel parameters, inputting the real-time time domain tensor into a baseline construction model, and obtaining a real-time feature vector based on the baseline construction model; calculating a network security event dynamic threshold based on the baseline information entropy of the baseline data, and calculating a real-time abnormal value based on the real-time feature vector and the baseline mean vector of the baseline data; and calculating a normalized deviation degree based on the real-time abnormal value and a security event dynamic threshold value, and judging whether a network security event occurs in the base station or not.

This disclosure describes methods and apparatus for UE to perform UP-based data collection for UE side offline model training with network awareness for wireless communication systems, further comprising the steps of receiving data collection activation and control configurations from a UE server, performing measurement and collection based on received activation and configuration, and reporting collected data to UE server. The overall procedure contains the stage of data collection configuration and control, data collection, data report and transfer.

The invention belongs to the technical field of video coding and transmission. The invention provides a video transmission intelligent control method based on network awareness. The embodiment of the invention has better adaptability under different network bandwidth environments, and has better video transmission performance under a low bandwidth condition. And the video transmission performance under different video scenes and different network bandwidths is better. According to the method, the video quality can be ensured by making full use of transmission resources, meanwhile, transmission fluctuation in different network environments can be flexibly adapted, the adaptability and robustness of video transmission in different network environments are improved, and the method has feasibility in the engineering field of unmanned aerial vehicle video transmission.

The invention discloses a customer behavior insight method, a customer behavior insight device and a marketing strategy putting method. The customer behavior insight method comprises the following steps: firstly, acquiring real-time multi-level O-domain original data; extracting target network quality data, target position trajectory data, target user behavior data and target APP behavior data corresponding to the user unique identifier from the real-time multi-level O-domain original data; then, comparing the target data with preset features to generate a network awareness tag, a position preference tag, a user preference tag, a terminal tag and an interest preference tag; and finally, summarizing the labels to form a customer behavior insight portrait. According to the method, data of multiple dimensions can be integrated, dynamic customer analysis on the basis of real-time data perception is realized, and full-link insight is provided, so that powerful technical support is provided for precision marketing, network optimization and intelligent service of enterprises.

The invention provides a multi-network integration data processing method, device and equipment, a medium and a program product. The method comprises the following steps: acquiring data traffic information in a plurality of systems, and carrying out preprocessing and time-space alignment on the data traffic information to obtain a plurality of data sequences for the plurality of systems; acquiring traffic statistical feature vectors of the plurality of data sequences, and performing feature fusion on the traffic statistical feature vectors of the plurality of systems based on an attention weighting algorithm to obtain a fused feature vector and a network state recognition result; generating a first network bandwidth resource allocation strategy based on the fusion feature vector, the corresponding network state recognition result and the flow feature vectors of the multiple systems; and executing at least one of bandwidth allocation, routing adjustment and link switching on the network bandwidth resources in the plurality of systems based on the first network bandwidth resource allocation strategy. According to the invention, dynamic resource allocation in a cross-network fusion scene can be realized, and the network awareness, intelligent scheduling and remote management capabilities of the system are significantly improved.

This disclosure describes methods and apparatus for UE to perform data collection for NW side model training with network awareness for wireless communication systems, further comprising the steps of the UE receives the data collection configuration from the serving cell, which provides the measurement configuration for the UE to perform measurement for an AI / ML-enabled feature / feature group or a functionality for the AI / ML-enabled feature / feature group; performs measurement according to the measurement configuration, logs and stores the data; receives RRCReconfiguration message from the serving cell and handles the measurement configuration and logged data according to the command. The overall procedure contains the stage of handle data collection configuration, data collection and storage, and data availability indication.