128results about How to "Reduce transmission delay" patented technology

The invention relates to the technical field of information communication, and discloses a 5G network slice resource scheduling method for a power distribution network, and the method comprises the steps: firstly collecting the geographic coordinates and priority labels of a service request, carrying out the regional division of a service based on the coordinates, and determining the cluster center of each region; then combining the priorities and the areas to which the requests belong, carrying out hierarchical sorting on all the requests to generate a global scheduling sequence; for each request in the sequence, calculating a path distance to each network resource node according to the coordinate of the request and the cluster center, and selecting a shortest path node as a target resource node; and finally, allocating resource quotas from the resource pool of the target node in sequence. According to the 5G network slice resource scheduling method provided by the invention, the resource matching accuracy and locality are effectively improved, the service transmission delay is reduced, the network flow space distribution is optimized, and the more efficient and reliable bearing of the power distribution network service is realized.

The invention provides an NoC low-delay data transmission method based on a dynamic routing algorithm, relates to the technical field of data transmission, and aims to solve the technical problems that an existing NoC routing algorithm cannot adapt to a link dynamic load, is lack of congestion trend prejudgment, is slow in path search convergence and is insufficient in QoS differential scheduling. The method comprises the following steps: constructing a dynamic sensing module containing a double-branch LSTM time sequence prediction model, collecting states such as link bandwidth and queue length in real time, and predicting a congestion trend in 50-100ms in the future; constructing a multi-objective evaluation function taking delay as a core, and dynamically adjusting the weight according to the QoS level; solving an optimal path by adopting an improved ant colony algorithm which introduces a congestion penalty and pruning strategy; during transmission, dynamic reselection is triggered through a pre-calculation + fast matching mechanism; and iteratively optimizing the prediction model based on incremental learning. According to the method, congestion is avoided in advance, the path search efficiency and the transmission reliability are improved, the delay is remarkably reduced compared with a traditional algorithm, and the method is adaptive to delay sensitive scenes such as a high-performance processor and an AI chip.

The invention discloses a voice interaction method, a user terminal, a server side, equipment, a medium and a product. The method comprises the steps that the user terminal acquires voice input of a user; the voice input is compressed and coded, first voice input is obtained, and the mode of compressed coding is dynamically selected according to the content of the voice input; performing voice recognition, text reasoning and voice synthesis on the first voice input to obtain a target synthesized voice; or, the first voice input is transmitted to the server side, the target synthetic voice obtained by the server side is received, in the transmission process, the first voice input is divided into a voice segment and a silent segment, and transmission of the voice segment is completed preferentially; and locally playing the target synthesized voice. Through the dynamic environment perception and self-adaptive noise reduction method, transmission delay is reduced, context understanding is enhanced through text reasoning, low-delay and high-naturalness real-time voice interaction is achieved, and user experience is improved.

The invention relates to the field of data processing, in particular to a data transmission quality optimization method and system for an intelligent ammeter, and the method comprises the steps: obtaining a historical sensitivity sequence and a secret key updating record of each ammeter, and constructing a transmission sensitive vector; clustering the electricity meter groups and endowing sensitive grades to the electricity meter groups; dividing a transmission period into a plurality of time slots, establishing corresponding transmission scheduling groups, and distributing the ammeters to the groups according to the sensitivity levels to form an initial scheduling scheme; collecting network and computing resource states and computing resource pressure at the beginning of the current transmission period; and comparing the resource pressure with double thresholds, taking the sum of the transmission sensitivities of the electric meters in the group as a load according to a comparison result, dynamically adjusting the corresponding sequence of each transmission scheduling group and the transmission time slot according to the load, and issuing a transmission instruction. According to the invention, through a double-layer scheduling mechanism combining historical behavior grading and real-time resource perception, peak shifting transmission of the electricity meter group is realized, and the processing efficiency of the concentrator is remarkably improved.

The application relates to the technical field of network task allocation, and discloses a heterogeneous computing power network task allocation and path optimization system based on a neural network, which comprises a graph construction module, a node task allocation module and a path optimization module.The graph construction module is used for constructing a traffic dispersion graph, modeling network topology and node data through the traffic dispersion graph, and modeling nodes and edges in combination with graph indexing and graph displacement, and extracting network communication traffic and node features.The node task allocation module is used for inputting graph indexes of all nodes into an improved graph neural network model to intelligently predict and allocate node tasks, and outputting node task allocation prediction results.The path optimization module is used for obtaining path optimization results by minimizing transmission delay and balancing node computing power in combination with node task prediction results.The system optimization module is used for optimizing the overall performance of the system based on the path optimization results and the task allocation prediction results.The application improves the task allocation and path optimization efficiency of the heterogeneous computing power network.

The invention relates to an intelligent scheduling system and method for security and protection video streams of an intelligent television. The intelligent scheduling system comprises a user, an Android TV client (TV client for short), a Web signaling server, a Relay proxy server and a camera. The user interacts with the TV client through an input device of the remote controller and initiates a watching instruction; the TV client is used for receiving a user instruction, performing signaling interaction with the Web signaling server, and establishing video stream connection with the camera or the Relay proxy server; the Web signaling server is used as a control center of the system and is used for receiving a request of the client, carrying out intelligent scheduling decision making and issuing a control instruction to the downstream camera and the client; the Relay proxy server serves as a video stream transfer node and is used for forwarding video stream data when P2P direct connection is unavailable; and the camera is used for collecting a video stream and pushing the video stream to the TV client or the Relay proxy server according to an instruction of the Web signaling server.

This invention discloses a low-latency UAV-assisted dynamic distribution method for panoramic video streams based on viewport prediction, belonging to the interdisciplinary field of mobile communication and immersive multimedia transmission. By constructing a multi-level forward-looking virtual queue model, future viewport data requests are mapped to current weighted accumulated potential energy, thereby driving the system to perform traffic temporal shaping when channel conditions are favorable. In other words, through proactive resource scheduling, future transmission tasks are shifted to the present for completion, achieving a proactive service mode for data waiting for users. Simultaneously, in conjunction with a trap-aware hierarchical backtracking optimization strategy, this invention can guide UAVs to actively avoid local optimal deadlocks, ensuring that the optimal air-to-ground transmission link is maintained in dynamic environments, thereby fundamentally eliminating queuing time and guaranteeing a low-latency, smooth playback experience for panoramic video.

The present application relates to a gas tracing method, in particular to a kind of environmental identification and tracing method, system and medium based on multi-modal cooperation, method includes: collection contains gas plume visual image and contains gas response signal olfactory signal;Visual image is preprocessed and visual feature is extracted, and visual depth feature vector is obtained;Olfactory signal is preprocessed and olfactory feature is extracted, and olfactory feature vector is obtained;Cross-modal fusion obtains fusion feature vector;Physical constraint loss function is constructed, and physical consistency correction is carried out, and modified fusion feature vector is obtained;Output gas concentration space-time distribution result.Compared with prior art, the present application solves the problem that prior art cannot realize high-precision online monitoring and tracing of multi-component gas.The scheme improves the identification accuracy of gas component, the multi-component distinguishing ability and real-time response performance in complex environment through the integration of visual monitoring and olfactory monitoring, combined with multi-modal fusion algorithm and physical consistency correction.

The present application relates to the technical field of data transmission, and specifically provides a data transmission method and system for solid waste sorting equipment, a terminal and a storage medium, comprising: adding basic classification marks and dynamic priority marks to data packets according to the function types of sorting data, and dividing the data into synchronous control flow, real-time event flow, process awareness flow and background management flow; a data source end acquires link state information before sending, and adaptively adjusts the dynamic priority of the real-time event flow; a network switch performs mixed scheduling transmission on the data packets based on time-aware shaping, credit shaping and preemption mechanism, wherein the preemption of low-priority queues is only allowed when the data packets of the highest-priority sub-queue carry the highest dynamic priority mark. Through the cooperative mechanism of basic classification and dynamic priority, the present application realizes fine classification transmission of heterogeneous data flow, solves the problem that key instructions are easily affected by network congestion, and effectively reduces transmission delay and jitter.

Embodiments of the present application provide a vehicle-mounted data transmission method, device, equipment and storage medium. The method comprises: determining a first transmission data packet from at least two transmission data packets of a vehicle; determining a network link corresponding to each first transmission data packet according to the network quality of at least two network links associated with the vehicle; and transmitting each first transmission data packet based on the network link corresponding to each first transmission data packet. Embodiments of the present application can realize multi-link transmission of vehicle-mounted data, reduce the transmission delay of vehicle-mounted data, efficiently utilize the multi-link transmission capability of the vehicle to maximize the rapid transmission of multiple transmission data packets, ensure the efficient stability of vehicle-mounted data transmission, and improve the response rate and accuracy of vehicle-mounted data transmission.

The embodiment of the invention provides a service processing method, electronic equipment, a storage medium and a program product, and relates to the technical field of federated learning, and the method comprises the steps: obtaining historical features and real-time features of a target user in response to a service processing request initiated by the target user; inputting the historical features and the real-time features of the target user into a locally-deployed portrait reasoning model, and performing risk portraying on the target user by using the locally-deployed portrait reasoning model to obtain a risk portrait label value of the target user; performing homomorphic encryption on the risk portrait label value of the target user to obtain an encrypted portrait label value; performing risk assessment on the service processing request by using a service decision engine based on the encrypted portrait label value and the encrypted label threshold to obtain a risk assessment decision result; and executing the business processing request based on the risk assessment decision result. According to the method, the accurate user portrait can be obtained in real time on the premise of protecting the privacy of the user, and the business processing risk is reduced.

The invention relates to the technical field of data transmission, and particularly provides a streaming Token double-path transmission method, system and device and a storage medium, and the method comprises the steps: responding to a streaming request, completing the initialization of a system and a session, building a bypass channel from a model to a client, and creating a session context in a control flow engine; identifying the type of each Token generated by the model, and shunting according to the type: data Token routing to a bypass channel and control Token routing to a control flow path processed by a control flow engine; data bypass transmission and control flow service processing are executed in parallel, and the states of the data bypass transmission and the control flow service processing are ensured to be consistent through a state synchronization mechanism; and the dual-path operation state is continuously monitored, and dynamic path adjustment or abnormity recovery is carried out when abnormity is detected. According to the method, the data flow and the control flow are decoupled, so that the transmission delay of the streaming Token is remarkably reduced while the state consistency is ensured.

The application discloses a smart community police management system and method based on Internet of Things security, and belongs to the technical field of smart communities, and solves the problem that existing system data processing cannot utilize edge computing nodes for low-delay real-time analysis, and cannot meet timely early warning requirements, the method comprising preprocessing of multi-source heterogeneous community monitoring information, analysis and processing of the community monitoring information based on edge computing, and generation of a risk propagation path in combination with front-end analysis results and heterogeneity characteristics; in the application, analysis and processing of the community monitoring information based on edge computing avoids the delay of centralized processing, can quickly trigger early warning in the early stage of a risk event, thereby gaining golden disposal time for risk event disposal, and a risk analysis model realizes a leap from single-node anomaly detection to composite risk quantification through multi-dimensional feature fusion and dynamic space-time reasoning, and realizes multi-dimensional feature fusion and dynamic reasoning capability of the risk event.

This invention discloses a full-body live-streaming call imaging system and method for smart glasses based on real-time correction using multiple sensors, belonging to the field of smart wearable devices and real-time audio and video communication technology. This invention integrates multiple types of sensing sensors distributed across smart glasses to collect real-time data on user facial details, clothing features, limb posture, gait, and surrounding environmental space. It then constructs a complete 3D human body model from head to toe using lightweight AI algorithms. Simultaneously, a real-time human body data correction mechanism is added, dynamically calibrating human body recognition data at the millisecond level through frame comparison, iterative compensation, and anomaly filtering, solving industry challenges of model distortion and contour offset in dynamic scenes. Combined with SLAM 3D environment reconstruction technology and an adaptive lens distance adjustment algorithm, this invention can intelligently switch between facial close-ups and full-body dual imaging modes, with no limb cropping, no image distortion, and no image jitter throughout the process, realistically reproducing the user's full-body movements and surrounding environment. This invention effectively solves the technical pain points of traditional smart glasses, such as limited imaging in video calls and live streaming, poor dynamic adaptability, and low recognition accuracy. It significantly improves imaging stability, integrity, and intelligence, and is suitable for various scenarios such as remote physical education, immersive live streaming, and virtual meetings. It has extremely high practical value and promising prospects for promotion.

This application relates to the field of natural language processing, and more particularly to a method for ultra-long context tensor parallel incremental attention and differential compression transmission. It employs a multi-level precision sliding window attention mechanism, dynamically allocating precision levels such as fp16 / int8 / int4 based on the distance between the window and the current computation position, and the information entropy of the window content. A tensor parallel incremental attention engine enables cross-GPU / node incremental attention computation and asynchronous All-Reduce synchronization, improving computational efficiency. Semantic differential compression transmission technology is used, transmitting only the differential data based on similarity detection, significantly reducing cross-node transmission overhead. Combined with an extreme performance optimization and security control strategy, a balance between performance and security is achieved through hardware monitoring and dynamic power consumption / frequency adjustment. This invention can significantly reduce memory usage and transmission overhead in ultra-long context processing, improve computational efficiency and hardware utilization, enhance the understanding ability of large models for long texts, adapt to heterogeneous hardware environments, and is suitable for large model inference and training scenarios.

According to the single-cell-oriented energy storage big data reliable transmission method and device and the storage medium provided by the embodiment of the invention, firstly, differentiated reliability levels are allocated according to the content type of a data packet, and are positively associated with coding redundancy; furthermore, the coding strategy can be dynamically optimized along with the network state by acquiring the link quality parameter in real time and positively associating the channel deterioration degree with the coding redundancy; and finally, after the acknowledgement feedback is received, selective retransmission is triggered only for the data blocks which are not successfully delivered. According to the invention, accurate retransmission control is realized, unnecessary retransmission data volume is effectively reduced, the probability of transmission delay and channel conflict is reduced, the method is especially suitable for a narrowband link or a high packet loss environment, and data delivery timeliness and link utilization efficiency are improved.

The application discloses a semiconductor structure and a manufacturing method thereof. The structure comprises a glass substrate having opposite first and second surfaces, a via hole arranged on the glass substrate and penetrating through the first and second surfaces of the glass substrate, an outer shielding layer arranged on the inner wall of the via hole, a dielectric insulation layer arranged on the side of the outer shielding layer away from the inner wall of the via hole, a first conductive seed layer arranged on the side of the dielectric insulation layer away from the inner wall of the via hole, and an internal signal conductor filled in the via hole and located in the area enclosed by the dielectric insulation layer. The semiconductor structure constitutes a vertical interconnection structure, which can greatly shorten the interconnection path between radio frequency modules, provide excellent electromagnetic shielding capability, and reduce transmission delay and loss.

The application discloses a kind of based on edge computing's distributed energy real-time monitoring system and its operating method, it is related to the technical field of energy monitoring, system includes: equipment layer, edge layer and cloud layer;Operating method includes: the original data of distributed energy equipment is collected, and original data is preprocessed;Identify the abnormal point in the data after pre-processing and the load prediction of edge node model;Based on abnormal detection result and load prediction result, according to preset rule, dynamically task scheduling is carried out to edge node, adjusts system working state;According to the current working state of system, dynamically adjust the task allocation and data interaction strategy between edge node and cloud, optimize system performance.The application can reduce data transmission delay, improve system real-time performance;Reduce the computing load of central node, improve system response speed;Optimize network bandwidth utilization, reduce operating cost;Enhance data privacy protection, improve system security.

This application provides a multi-path data transmission method, electronic device, and storage medium. It acquires communication parameters for each path in a multi-path transmission scheme and determines the replication probability of the data packet to be transmitted based on these parameters and a preset multi-armed slot machine model. This allows for the transmission of part or all of the data in the data packet across multiple paths according to the replication probability, thus saving transmission latency. In the multi-path transmission scheme, all data in the data packet is transmitted through the path with the minimum transmission latency. In each path other than the path with the minimum transmission latency, a portion of the data in the data packet is replicated according to the replication probability and transmitted. In other words, all data in the data packet is transmitted through the path with the minimum transmission latency, while the other paths replicate the portion of the data corresponding to the replication probability. This reduces the retransmission rate, decreases transmission latency, and increases the transmission rate.

The application provides a resource allocation method and device, electronic equipment and a readable storage medium, comprising: obtaining a first target function and a constraint condition corresponding to the first target function, the first target function being associated with total throughput and transmission delay of a communication channel; determining a target channel ratio of the communication channel based on the first target function and the constraint condition; determining a first ratio of an orthogonal channel and a second ratio of a shared channel in the communication channel based on the target channel ratio; determining resource allocation parameters of at least one V2I link based on the first ratio and pre-acquired communication channel parameters; and determining target transmission power of each link in the at least one V2I link and the at least one V2V link based on the first ratio, the second ratio, the resource allocation parameters and the first target function, so that the value of the first target function is minimized under the target channel ratio, the resource allocation parameters and the target transmission power. The application can reduce data transmission delay.

The disclosure relates to a communication method and system for converging a 5th-Generation (5G) communication system for supporting higher data rates beyond a 4th-Generation (4G) system with a technology for Internet of Things (IoT). The disclosure can be applied to smart services, such as smart home, smart building, smart city, smart car, connected car, health care, digital education, smart retail, security and safety services, based on 5G communication technology and IoT-related technology. The disclosure discloses a method and apparatus for reducing overhead of an Ethernet frame, a method and apparatus for efficiently performing a connection resume procedure of a terminal, and a method and apparatus for preventing data loss when performing an uplink user data compression procedure.

The application relates to an active cache routing method and system of a satellite content distribution network, the satellite content distribution network comprising at least one satellite node. The method comprises: extracting first semantic information features of distributed content and second semantic information features of historical popular content by using a deep learning model; calculating semantic similarity between the first semantic information features and the second semantic information features; calculating a satellite semantic cache priority value of a satellite node corresponding to the distributed content according to the semantic similarity; and planning an active cache routing path of the distributed content according to the satellite semantic cache priority value of each satellite node. The application can enable the satellite to automatically make a cache decision of the distributed content in the content distribution process, and improve the efficiency of active cache by combining content distribution and cache deployment.

This application provides a sensing data transmission method, an electronic device, and a computer-readable storage medium. The sensing data transmission method applied to a first device includes: accessing a network slice; sending first sensing data and a corresponding first identifier to a base station via the network slice; wherein the first identifier is used to identify the first device. The sensing data transmission method applied to a base station includes: receiving first sensing data and a corresponding first identifier sent by the first device via a network slice; wherein the first identifier is used to identify the first device; and sending the first sensing data and the first identifier to an edge cloud server. The sensing data transmission method applied to an edge cloud server includes: receiving first sensing data and a corresponding first identifier sent by a base station; wherein the first identifier is used to identify the first device; converting the format of the first sensing data to obtain third sensing data; and storing the correspondence between the first identifier and the third sensing data.

This invention relates to the field of power transmission line monitoring and early warning technology, specifically an intelligent bird monitoring device and risk warning method for power transmission lines. The device includes an intelligent bird monitoring device for power transmission lines and a risk warning method using the device. The monitoring device comprises an image acquisition module, a thermal sensing module, a sound acquisition module, a motion monitoring module, an edge computing module, and a power supply module. Each acquisition module is signal-connected to the edge computing module, and the power supply module provides power to all modules. Through the collaborative work of multiple modules, comprehensive and multi-dimensional monitoring of bird activity in power transmission line areas is achieved. The early warning method is implemented through five steps: data acquisition, data processing, intelligent analysis, risk assessment, and early warning output. This invention enables comprehensive and accurate monitoring and tiered early warning of bird activity in power transmission line areas, improving monitoring efficiency and early warning accuracy, and ensuring the safe and stable operation of power transmission lines.

This application provides a data transmission method, apparatus, device, storage medium, and program. The method includes: a first device determining target data to be transmitted to a second device through a first connection, wherein the first connection is a connection between the first device and the second device; the first device acquiring first latency requirement information corresponding to the first connection, and transmitting the target data to the second device through the first connection according to the first latency requirement information. In this process, by transmitting the target data to the second device according to the first latency requirement information corresponding to the first connection, the first device can reduce the transmission latency of the target data and meet the low latency requirement.

The application discloses a front-end data compression method, device, equipment, medium and product. The method comprises the following steps: a main thread receives service data, and when a preset compression triggering condition is met, the main thread dynamically converts a pre-embedded script code string into an executable sub-thread, and the script code string comprises compression logic of a lightweight compression engine; the main thread encodes the service data and stores the service data in a binary buffer, and transfers the memory ownership of the binary buffer to the sub-thread through a message communication interface; the sub-thread creates a typed array view based on the binary buffer, calls the lightweight compression engine to compress the typed array view, generates a compression result, and transfers the memory ownership of the compression result to the main thread; and the main thread reports the compression result or locally stores the compression result. The method can realize efficient data compression in the front end, ensure smooth running of a front-end page, and reduce memory occupation and transmission delay.

The invention belongs to the technical field of intelligent identification and detection, and discloses an intelligent identification terminal adaptive to the Internet of Things, and the terminal comprises a housing; the data acquisition module is used for synchronously acquiring behavior inertial data and visual image data of a target animal; an edge calculation module which is in communication connection with the data acquisition module and is used for operating the trained behavior identification model and visual representation identification model and performing real-time processing and identification on the acquired data; the information fusion and decision module is integrated on the edge calculation module; and the Internet of Things communication module is used for uploading the state judgment conclusion and the terminal data to a remote management platform. According to the scheme, inertial motion and visual image data are synchronously collected, and real-time processing and information fusion are carried out on the terminal locally by utilizing edge calculation and an AI model, so that the accuracy, the real-time performance and the environmental adaptability of animal state recognition are effectively improved.

This invention provides a task collaborative reasoning method, apparatus, electronic device, and medium, relating to the field of computer technology. The method includes: dividing a task arriving on a mobile device into multiple subtasks and constructing an offloading strategy for each subtask to characterize execution on the mobile device or MEC server; constructing an average overhead minimization problem for all mobile devices within a time slot for each mobile device; reconstructing the average overhead minimization problem using Lyapunov optimization theory to obtain an independent time slot policy optimization problem corresponding to the average overhead minimization problem; transforming the independent time slot policy optimization problem into a Markov decision process and solving the Markov decision process using a deep reinforcement learning algorithm to obtain the optimal offloading strategy, optimal mobile device transmission power, and optimal number of threads allocated to the MEC server for each mobile device. The invention effectively utilizes distributed computing resources and significantly improves reasoning efficiency.

The application relates to a Shenwei intelligent acceleration card system based on a Chiplet technology, a Chiplet architecture chip taking a Shenwei processor and a domestic FPGA as cores, being capable of supporting mainstream AI algorithm models and accelerating an inference process through cooperation of the powerful double-precision floating point and integer calculation power of the Shenwei processor, the powerful parallel computing capacity of the FPGA and the high-flexibility low-latency performance of the Chiplet architecture, and being applicable to domestic computers, servers, intelligent products and the like. The devices used in the application are all domestic, and have a higher self-controllable level; the Chiplet architecture designed with a PCIe interconnection bus as a core has the advantages of high transmission bandwidth, high calculation efficiency and easy realization of an inter-chip interconnection protocol; the Chiplet research and development idea based on the domestic general-purpose processor and the FPGA can be expanded according to application requirements to face different application fields.

This invention discloses a deterministic path set planning method for low-Earth orbit (LEO) satellite networks based on the spatial domain. Based on predictable LEO satellite topology information, a shortest path algorithm is used to obtain a set of lateral paths that meet the deterministic service transmission delay requirements. The lateral path set within the j-th time slice is compared with the lateral path set within the (j+1)-th time slice. The path with the most overlapping inter-satellite links is selected as the path in the (j+1)-th time slice corresponding to a path in the j-th time slice, and so on, to obtain the set of longitudinal paths within the complete service time. The impact of different longitudinal path sets on transmission delay is measured to obtain an optimal deterministic path set. This invention determines the path search range by dividing the spatial domain and extended domain, maintaining path consistency, and reducing the number of path switching times within the service transmission time while ensuring that deterministic services meet the delay threshold, thereby reducing the overall transmission delay within the complete service time and improving the deterministic service capability.