283 results about "Data transmission time" patented technology

The invention relates to a heterogeneous computing-based task scheduling method and device, a storage medium and equipment. The method comprises the following steps of: obtaining an inference task of a large language model; in the execution process of the reasoning task, at least based on the memory access intensity and the current reasoning stage, memory access intensive operators and calculation intensive operators in the reasoning task are recognized; allocating the memory access intensive operator to a first computing unit for executing a memory intensive task, and allocating a computing intensive operator to a second computing unit for executing a computing intensive task; obtaining estimated execution time of the two calculation units for executing the corresponding tasks and data transmission time between the two calculation units; according to the pre-estimated execution time and the data transmission time, the task starting moments of the first calculation unit and the second calculation unit are determined with the purpose of minimizing the overall execution delay of the reasoning task; and controlling the first calculation unit and the second calculation unit to asynchronously execute the corresponding tasks in parallel according to the task starting time.

The application provides a cache manager and a control component. The cache manager comprises an interface, an allocation module and a memory. The interface receives a cache allocation request and sends the cache allocation request to the allocation module. The interface receives first cache index information returned by the allocation module and outputs the first cache index information. In response to the cache allocation request, the allocation module allocates N idle memory blocks and generates the first cache index information. The memory blocks are located in a cache, N is a positive integer, and the first cache index information comprises indexes of the N memory blocks. The memory stores indexes of at least N memory blocks. The cache manager implemented by hardware replaces the software management cache in the prior art, thereby reducing the interaction times between software and hardware when allocating a cache in the control component, improving the information interaction speed inside the control component, and achieving the technical effect of reducing the data transmission time between the host and the flash memory chip.

The invention discloses a blasting parameter intelligent computing platform, which belongs to the field of blasting engineering, and comprises a distributed computing resource scheduling module, which adopts a distributed computing architecture to decompose a computing task into a plurality of sub-tasks, and distributes the sub-tasks to different computing nodes for parallel computing; through an intelligent scheduling algorithm, according to factors such as the load condition and the computing power of each computing node, computing tasks are dynamically allocated, dispersed computing resources in a network are fully utilized, the utilization rate of the computing resources is improved, and dependence on single high-performance computing equipment is reduced; data are processed in real time through the edge calculation preprocessing module, and the data transmission time is shortened; the lightweight calculation model library can quickly complete blasting parameter calculation; and the real-time feedback and dynamic optimization module realizes real-time adjustment and optimization of blasting parameters, so that accurate blasting parameters can be provided in time according to actual conditions in the tunnel construction process, and the construction progress is improved.

The invention discloses a self-adaptive link control method for a multi-dimensional identification system, and belongs to the technical field of link control. The method comprises the following steps: embedding an environment sensing module in a multi-dimensional identification system to obtain network state information; introducing a reinforcement learning algorithm to carry out adaptive coding; the self-adaptive waveform is realized through discrete Fourier transform (DFT) and inverse discrete Fourier transform (IDFT); a self-adaptive waveform is realized through discrete Fourier transform (DFT) and inverse discrete Fourier transform (IDFT); and establishing a link layer frame format of the multi-dimensional identification system to realize communication link management. According to the invention, through combination of a multi-dimensional identification system and an environment perception technology, a network state and channel characteristics can be perceived in real time, and a link control strategy is dynamically adjusted; the data transmission efficiency can be dynamically optimized according to the network state and the channel condition by introducing the adaptive coding modulation and adaptive waveform technology; the data transmission time delay is obviously reduced, and the data packet disorder and packet loss rate are reduced, so that the user experience is improved.

Embodiments of the present application provide a transmission control method, apparatus and system, used for a terminal device to select the data sending time, thereby reducing the data transmission time delay and releasing the storage space of satellites. The method comprises: receiving state information of at least one link, wherein the at least one link comprises a first link, the first link is a link between a first satellite and a ground station, and the state information of the first link is used for representing a reachable state of the first link over time; and sending first data at a first time, wherein the first time is determined on the basis of the state information of the at least one link.

The invention discloses a computer network security data transmission system, and relates to the technical field of network security, a core architecture of the computer network security data transmission system is formed through mutual cooperation of a plurality of groups of algorithm units, and a plurality of factors such as attack frequency, intensity, fluctuation amplitude and key length are quantized, so that the security of the computer network security data transmission system is improved. And calculating to obtain a data encryption danger value Esv, so that an encryption strategy can be dynamically adjusted to adapt to different security requirements, a self-adaptive and evolvable mathematical framework is provided for a computer network security data transmission system, and the intelligent level of the system is remarkably improved. A data transmission risk value Dtr is calculated through a transmission risk value algorithm unit in combination with a plurality of influence factors such as data transmission time Dtt and network delay Nd, so that the computer network security data transmission system can carry out comprehensive quantitative evaluation on the data transmission risk; and scientific and reliable data support is provided for adjustment of an encryption strategy in subsequent data transmission.

The invention discloses a heterogeneous cluster parallel multi-stage fuzzy job scheduling method, which comprises the following steps of: receiving a processing request which is submitted by a user and contains multi-stage jobs, and modeling task execution time, data transmission time and request deadline into triangular fuzzy numbers, constructing a scheduling model taking the minimization of the total lease cost and the minimization of the request tardiness as targets; carrying out global exploration by adopting an improved second-generation non-dominated sorting genetic algorithm to generate parent and offspring populations; based on population similarity threshold judgment, dynamically triggering local search guided by a multi-agent near-end strategy optimization algorithm, and adaptively selecting a local search operator for each individual to generate an adjacent population; combining various populations, performing non-dominated sorting and crowding distance calculation, and screening out a new generation of populations; and iterating the process until convergence, and outputting a Pareto optimal solution set. According to the method, the problem of multi-target scheduling with fuzzy time variables in a heterogeneous environment is effectively solved, and the quality of a scheduling scheme and the algorithm search efficiency are improved.

The invention discloses an intelligent data migration system based on big data, and particularly relates to the technical field of data migration. Comprising a demand analysis and strategy making module, a data source and target system access module, a data preprocessing module, a data quality evaluation module, a data version control module, a data desensitization and encryption module, a migration execution engine module, a monitoring and alarm module and a data migration visualization module. A verification and optimization module; and a data migration post-evaluation and optimization module. The data migration speed and efficiency are improved, the data transmission time and bandwidth consumption are reduced, the complexity and error rate of manual operation are reduced, the safety of sensitive data in the transmission and storage process is ensured, the traceability and restorability of the data are ensured, the data are prevented from being lost or damaged, the accuracy of the migrated data is ensured, and the data migration efficiency is improved. Meanwhile, the access of various data sources and target systems is supported, and different service requirements are met.

The application discloses a kind of high-temperature forging dynamic three-dimensional measurement-oriented sliding mode fault-tolerant control methods, and specific implementation steps include: establishing the discrete-time singular perturbation Markov jump state space model of high-temperature forging measurement system;Design probability dynamic event trigger mechanism, utilize internal dynamic variable intelligent judgment data transmission time to save bandwidth resources;For possible fraud attacks and actuator failure, build the corresponding attack model and fault model;Sliding surface and sliding control rate function are constructed;Deduce the sufficient condition for guaranteeing system reachability and closed-loop system finite time boundedness;Iterative solution controller gain and dynamic trigger parameters.The application considers network security, resource-constrained and actuator degradation and other multiple constraints under the high-temperature forging dynamic three-dimensional measurement scene, while guaranteeing the system finite time stability, significantly improves the robust cooperative control ability and operation safety of measurement system.

A method for avoiding high-frequency communication conflicts in LoRa multi-node communication includes the following steps: Step 1: Constructing a star network topology for LoRa wireless nodes; Step 2: Setting up a LoRa network for data terminal nodes; Step 3: Setting up relay nodes and agreeing on a data upload time period; Step 4: Dividing the uplink transmission period of terminal nodes into multiple time slots. Each node is assigned a corresponding transmission time slot; Step 5: Assigning priorities to each terminal node, creating a table of given node sequence lists and initial state of transmitted nodes, preprocessing the data, and uploading the data from the terminal node to the relay node. This invention achieves non-interference in uplink data transmission among terminal nodes by dividing terminal node priorities into two bits and uplink data transmission time slots. Terminal nodes listen to priority data packets and create tables, ensuring that uplink data transmission among terminal nodes does not interfere with each other, urgent data is uploaded first, and the two priority data bits guarantee the integrity of node data transmission.

This specification discloses a method, apparatus, storage medium, and electronic device for task execution. The task execution method includes: determining device information corresponding to each computing device for a computing task corresponding to each network layer in a target model; for each network layer, determining the computing time required for executing the computing task corresponding to the network layer through each computing device based on the number of calculations involved in executing the computing task corresponding to the network layer and the device information of each computing device; determining the target device corresponding to the network layer based on at least one of the computing time, the data transmission time between the computing device corresponding to the previous network layer and the other computing devices, the memory space required for the data of the network layer, and the remaining memory of each computing device; and executing the computing task through the target device corresponding to each network layer after receiving an execution request for the computing task corresponding to each network layer.

The application discloses a particle interaction calculation method and device, equipment and a storage medium. The method comprises the following steps: determining a target calculation system, grouping the particles in the target calculation system, obtaining a plurality of tasks, and using the tasks to control the calculation units to calculate the interaction between a group of particles; distributing each task to a plurality of different calculation units, wherein the number of the calculation units is a preset value; determining the total number of the calculation units used by each particle according to the correspondence between the tasks and the calculation units; if the total number of the calculation units used by each particle is less than a preset threshold, controlling each calculation unit to execute the corresponding task, and obtaining the interaction calculation result between each particle according to the execution result of each calculation unit. The application distributes different tasks to different calculation units, controls the total number of the calculation units used by each particle within a certain range, improves the calculation efficiency of each task, and reduces the data transmission time.

The application discloses a method for high-speed data synchronization transmission between boards, which adopts high-speed transceivers to realize high-speed data transmission between boards in a many-to-one mode; the data transmission time delay of each sub-board to the main board is tested, and the maximum value T0 is obtained; meanwhile, the data transmission buffer of each sub-board and the data receiving buffer of the main board are reset; after the resetting, each sub-board starts to send data, and the main board starts to receive the data of each sub-board from the local buffer after waiting for a time T greater than T0. The application realizes high-speed data transmission between boards, effectively controls the time delay of high-speed data transmission between boards, and realizes the synchronization transmission of data, which is very important in a system with complex data interaction and high data synchronization requirement.

The disclosure provides a computing power resource allocation method and device and a computer readable storage medium, and relates to the technical field of computing power network. The method comprises the following steps: receiving computing power requirements from M task nodes, M≥2; determining a transmission cost of providing computing power resources for the ith task node by the jth computing power node based on the task priority of the ith task node, a first ratio, a second ratio, and a plurality of data transmission times between the ith task node and the jth computing power node in N computing power nodes, 1≤i≤M, 1≤j≤N; and determining a global computing power resource allocation scheme based on the transmission cost, wherein the global computing power resource allocation scheme is a computing power resource allocation scheme in which the total transmission cost of providing computing power resources for the M task nodes by the N computing power nodes is less than a preset threshold.

The invention discloses a GPU-based graph vector index construction method and device and a storage medium, and relates to the technical field of graph index construction. The method comprises the following steps: fragmenting an original data set based on a clustering algorithm to obtain a first preset number of fragmented data subsets; sending the ith fragmented data subset to the GPU, wherein i is a positive integer; constructing a local graph vector index of the ith fragmented data subset in the GPU; sending the (i + 1) th fragmented data subset to the GPU until all local graph vector indexes are obtained; and constructing a hierarchical global graph vector index according to all the local graph vector indexes. According to the method, the production line of the producer-consumer model is constructed, so that the data transmission time of the PCIe bus is completely covered by the calculation time of the GPU, the I / O bottleneck is eliminated, and the construction speed of the graph index is improved.

This invention provides a circuit and method for sampling and transmitting telemetry data from a cochlear implant, belonging to the field of telemetry technology for cochlear implants. The method amplifies the analog signal under test using a programmable gain amplifier, converts the signal into a pulse width signal using a voltage ramp generator and comparator, and then generates a short-duration step signal on the coil via an output driver to form a ringing pattern. An external device detects the interval between the step signals to reconstruct the signal magnitude. This invention eliminates the need for an analog-to-digital converter, significantly reducing power consumption and chip area, and improving data transmission efficiency. It is suitable for telemetry systems in various implantable medical devices such as cochlear implants. This invention significantly reduces the power consumption and layout area of ​​the implanted chip and shortens the single data transmission time to 48μs, improving efficiency by approximately 10 times, making it suitable for low-power implantable devices such as cochlear implants.

The invention provides a user experience evaluation method and system based on multidimensional network time delay characteristics, and belongs to the field of network performance monitoring. The method comprises the following steps: receiving an original traffic data packet from a network, then receiving an original access request of a client, and decomposing the original traffic data packet into three groups of traffic, including a DNS analysis stream, a network transmission stream and an application layer request stream; calculating a DNS response time based on the DNS resolution stream; calculating network connection time and retransmission delay based on the network transport stream; calculating server response time and data transmission time based on the application layer request stream; obtaining a multi-dimensional time index; an experience evaluation model is constructed, index parameters are set according to business scenes, a comprehensive score is calculated, and then evaluation results of user experience are graded and visually displayed. According to the method, flow analysis is accurately carried out, delay sources are subdivided, and the bottleneck positioning error is smaller than 5%; the network performance problem is accurately positioned; and a client does not need to be transformed, and the compatibility is good.

According to the display content sharing method and system provided by the invention, when the display content is shared, the sharing vehicle side converts the display content resource into the resource coding configuration set through coding standardization to upload the resource coding configuration set, so that the occupation of the shared content on cloud resources is reduced. And the shared vehicle end can reproduce the display content of the sharing vehicle end only by inputting the request short code. A unique short code is used for replacing a display content file for display content sharing, conversion from file transmission to short code interaction is achieved through display content sharing, consumption of system resources in the display content sharing process is reduced, display content sharing and reproduction operation is simplified, the data transmission amount is reduced by adopting a short code sharing mechanism, and the display content sharing efficiency is improved. The data transmission time is shortened, the sharing efficiency is improved, and the user experience is improved.

The application relates to a battery data transmission method and system based on dynamic priority preemption time slots, which comprises the following steps: calculating the dynamic priority of a distributed node according to the data urgency, historical channel quality and basic priority of the distributed node; pre-empting the battery data transmission time slot according to the dynamic priority to perform battery data transmission; and performing a two-stage retransmission strategy to retransmit the battery data when the data transmission fails. The application breaks through the limitation of the fixed time slot allocation of the traditional time division multiple access communication strategy and adapts to the burst communication demand; when the wireless center node based on dynamic priority preemption performs time slot allocation and battery data retransmission, the communication conflict and real-time contradiction in the dense node scene can be effectively solved through software, the reliability, real-time performance and expandability of the system are significantly improved, and the application is suitable for intelligent battery system, electric vehicle, energy storage power station and other high-performance wireless center node application scenes.

The application discloses a data transmission method and device, a terminal device and a communication base station, and belongs to the technical field of communication. The method is applied to a terminal device of an Internet of Things, and comprises the following steps: receiving a maximum data retransmission number sent by a communication base station of the Internet of Things, wherein the maximum data retransmission number is determined based on network load conditions of the Internet of Things; determining a data transmission time slot corresponding to to-be-transmitted data based on the maximum data retransmission number, a priority of the to-be-transmitted data and position information of the terminal device; and transmitting the to-be-transmitted data to the communication base station based on the maximum data retransmission number and the data transmission time slot. The method can perceive network load by the communication base station, determine the maximum data retransmission number, determine the data transmission time slot for data transmission in combination with the priority of the to-be-transmitted data and the position information of the device, effectively improve data transmission reliability, reduce a data packet loss rate, and guarantee the priority transmission of emergency data.

The invention belongs to the technical field of frequency spectrum prediction, and particularly relates to a frequency spectrum state prediction method based on a hybrid deep learning model, the hybrid deep learning model is fused with a long short-term memory (LSTM) network and a multi-layer perceptron (MLP), and through three-dimensional frequency spectrum data sensing, self-adaptive dual-threshold energy detection and hybrid model prediction, the frequency spectrum state is predicted. And the accuracy of idle channel spectrum prediction is further improved. According to the method, the secondary user (SU) in the cognitive radio system (CRS) can quickly select the channel with the highest idle probability for access, the repeated sensing frequency is reduced, the total sensing time is reduced by 30%, and the effective data transmission time is improved by 30%. Compared with the prior art, the method provided by the invention is higher in frequency spectrum state prediction precision in a low signal-to-noise ratio (SNR) scene, the throughput of the system is remarkably improved, and the energy consumption of the system is lower.

Disclosed is an IoT device, including: a sensing circuit that obtains state values of a battery cell every time intervals; a communication circuit that establishes a wireless communication connection with a server at a transmission timing of data including the state values obtained during a designated time period; and a processor. The processor of the IoT device may be configured to: transmit the data of the state values obtained during the designated time period to the server through the communication circuit; in response to failure in transmission of the data, divide the data into sub-data of a division number based on the number of retransmissions of the data; and sequentially retransmit the sub-data through the communication circuit at a transmission time interval based on the number of retransmissions. The transmission time interval may be a time interval obtained by dividing the designated time period by the number of retransmissions.

The invention provides a hybrid expert model reasoning optimization method and device and electronic equipment. The method comprises the following steps: receiving a plurality of expert models of a hybrid expert model distributed by a terminal, and receiving operation weights of the plurality of expert models, gating weights of the hybrid expert model and feature vectors of text data sent by the terminal; based on the feature vector and the gating weight of the text data, calculating selection weights of a plurality of expert models, determining a plurality of target expert models from the plurality of expert models, and generating masks of the plurality of target expert models; based on the feature vector of the text data, the masks of the multiple target expert models and the operation weights of the multiple target expert models, sparse matrix multiplication is carried out, and multiple calculation results are obtained; and summarizing the plurality of calculation results to obtain a final calculation result. According to the hybrid expert model reasoning optimization method provided by the invention, the target expert model is determined by adopting the equipment side, and sparse matrix multiplication is performed, so that the data transmission time delay is reduced, and the calculation efficiency is improved.

The present invention discloses a method and device for end-cloud collaborative reasoning for neural network operator fusion, the method comprising converting a neural network into a directed acyclic graph; dividing the directed acyclic graph into a plurality of chain structures; fusing the network layers in each chain structure, and replacing the fused network layers with the obtained fusion blocks; predicting the inference time and output data size of each fusion block and each unfused network layer based on the data to be inferred, and calculating the intermediate data transmission time based on the output data size and the network bandwidth between the end and the cloud; segmenting the neural network based on the inference time and the intermediate data transmission time, and performing end-cloud collaborative reasoning based on the segmentation results. The present invention solves the minimum latency problem of network models with fusionable operators.

Embodiments of the present application provide a data processing method for a display device, and a display device. For each backlight driver, if dimming data of a current frame of the backlight driver is different from dimming data of a previous frame, a backlight controller sends the dimming data of the current frame to the backlight driver, and the backlight driver drives, on the basis of the dimming data of the current frame, a light-emitting unit to emit light; and if the dimming data of the current frame of the backlight driver is the same as the dimming data of the previous frame, the backlight controller does not send the dimming data of the current frame to the backlight driver, and the backlight driver drives, on the basis of the dimming data of the previous frame, the light-emitting unit to emit light. Compared with sending dimming data to all backlight drivers, sending the dimming data of the current frame only to a backlight driver of which data has changed can achieve the following effects: reducing the amount of data transmission, reducing electromagnetic interference, reducing power loss, reducing data transmission time, and increasing the response rate of the display device.

The invention relates to a distributed Internet of Things equipment authentication method based on a lightweight message, which is characterized in that a lightweight message mechanism is introduced, key information in an authentication process is packaged and transmitted in a simple and efficient manner, the data transmission quantity is greatly reduced, the communication overhead is reduced, the authentication message is transmitted more quickly in a network, and the authentication efficiency is improved. And the data transmission time in the authentication process is effectively shortened. Meanwhile, authentication is carried out by utilizing unique physical characteristics of the physical unclonable function, so that complex asymmetric encryption operation is avoided, the computing resource consumption of the terminal equipment and the authentication service equipment is reduced, and the authentication efficiency is improved. Under a large-scale Internet of Things equipment authentication scene, the authentication efficiency is greatly improved, the system load and the resource consumption are reduced, the real-time performance and the expandability of the Internet of Things system are enhanced, and the large-scale terminal equipment is ensured to be quickly and stably accessed to the network.

A GPU-based graph vector index construction method, apparatus, and storage medium are disclosed, relating to the field of graph index construction technology. The method includes: partitioning the original dataset using a clustering algorithm to obtain a first preset number of partitioned data subsets; sending the i-th partitioned data subset to the GPU, where i is a positive integer; constructing a local graph vector index for the i-th partitioned data subset on the GPU; sending the (i+1)-th partitioned data subset to the GPU, until all local graph vector indices are obtained; and constructing a hierarchical global graph vector index based on all local graph vector indices. This method, by constructing a producer-consumer model pipeline, completely masks the PCIe bus data transfer time with GPU computation time, eliminating I / O bottlenecks and improving the graph index construction speed.

The invention relates to a data continuous transmission dynamic routing calculation method for rectangular grid sequence cell elements, which comprises the following steps of: acquiring rectangular grid sequence cell element transmission parameters including the row number, the column number and the transmission period of a rectangular grid; each grid of the rectangular grid represents a cell element, and the cell element at the leftmost end of the rectangular grid is uniformly connected with a control center; dividing a transmission period according to the line number of the rectangular grid to obtain a single-line data transmission time period corresponding to each line in the rectangular grid; and in a corresponding single-row data transmission time period, according to a transmission path determination strategy, determining transmission path cells for the cells in the row sequentially through the cells in the rectangular grid along the forward direction, generating a data transmission path, and carrying out relay continuous transmission on the data of the cells in the same row. The method is suitable for a super-large-scale rectangular grid system, and an efficient and reliable routing solution is provided for a distributed system through a unique line-by-line timing transmission, dynamic local detour and path optimization and fault positioning integrated mechanism.

The invention discloses a method and a device for improving the service rate of a wireless ad hoc network. The method comprises the following steps: acquiring data to be transmitted; performing analysis according to the to-be-transmitted data, and judging whether the to-be-transmitted data can be sent through the continuous data time slots or not; if yes, calculating a first structure adjustment number q of the data time slots and an adjusted data time slot number n according to the total data volume of the to-be-transmitted data; performing time slot structure adjustment on the data time slots occupied by the data to be transmitted according to the first structure adjustment number q of the data time slots and the adjusted data time slot number n; acquiring data transmission time delay of each data time slot; calculating a risk assessment score according to the data transmission time delay of each data time slot; and dynamically adjusting the time slot structure of the subsequent data time slot according to the risk assessment score. According to the invention, the service rate is improved by dynamically adjusting the time slot structure, and the problem that the service rate has a bottleneck and cannot be broken through under a fixed time slot structure is solved.