440 results about "Bandwidth requirement" patented technology

The invention provides a bandwidth regulation and control and visitor flow routing optimization method and system for multi-scene live broadcast, and relates to the technical field of intelligent routing, and the method comprises the steps: collecting live broadcast data, constructing a feature vector, and training a scene classification model; analyzing bandwidth requirements by using a time sequence prediction algorithm, and formulating a differentiated bandwidth allocation strategy; and an edge node load monitoring mechanism is established, a multi-target routing optimization model is constructed, and real-time scheduling optimization of visitor flow is realized. The method can effectively improve the bandwidth utilization rate and the user experience quality of the live broadcast platform.

The invention relates to the technical field of network time delay scheduling, and discloses a deterministic network time delay scheduling method and device based on a TSN and a storage medium. The method comprises the following steps: carrying out graph theory analysis on a TSN network topology structure to obtain a network node connection relationship and link bandwidth information; extracting time delay requirements and bandwidth requirement characteristics of the data streams, and generating a data stream priority queue and a resource requirement index matrix; inputting a deep Q network, establishing a state-action mapping relation including a network load state and a time slice distribution action, and generating an initial time delay scheduling strategy model; calculating queuing time delay, transmission time delay and processing time delay of each data stream, and generating a time slice resource redistribution scheme; generating a global resource allocation matrix based on the time slice resource reallocation scheme; and parameter feedback updating is carried out on the initial time delay scheduling strategy model to obtain a target time delay scheduling strategy model, and the utilization efficiency of network resources is remarkably improved through bandwidth borrowing and time slice reallocation.

The invention belongs to the technical field of bandwidth access management, and particularly relates to an internet access service optimization method and system for adaptive bandwidth management. Through the distributed probe technology, network state parameters and user terminal metadata can be collected in real time, a deep learning network model such as an LSTM-Transformer hybrid neural network is utilized to process and analyze the collected data, the bandwidth requirement in a period of time in the future is predicted, time periodicity and traffic mutation characteristics are considered, and the bandwidth requirement in a period of time in the future is predicted. Equipment association characteristics are introduced, so that the prediction accuracy and reliability are improved, virtual channels are dynamically divided according to the service emergency degree and predicted bandwidth requirements, bandwidth resources are allocated to the virtual channels, it is ensured that high-priority services can obtain enough bandwidth resources in the network peak period, and the network performance is improved. Therefore, the stability and the quality of network service are ensured, and in addition, a bandwidth expansion mechanism and a bandwidth recovery strategy are introduced to cope with the dynamic change of the network bandwidth.

The invention discloses an optical transmission network hidden danger detection method and device and a computer program product, which can realize dynamic adjustment of differentiated bandwidth requirements by acquiring optical network state information in real time, evaluating service priority and establishing an optical channel resource allocation model. And when a topology anomaly is detected, constructing a service quality evaluation model by using a long-short-term memory neural network, and quantitatively analyzing the influence of the anomaly on the service. When a fault occurs, distributed link fault detection and a fault diagnosis engine based on a decision tree are adopted, and fault hidden dangers are quickly positioned and classified. And then, through an elastic recovery mechanism oriented to service sensitivity, the service quality level of a standby optical path is adjusted, and an optical layer topology connection relationship is optimized. According to the method, the resource utilization efficiency, the fault recovery capability and the service quality of the optical network are remarkably improved, and an innovative solution is provided for intelligent optical network management.

Example embodiments of the present disclosure relate to an effective mechanism for handing the scenario of discontinuous coverage. In this solution, the first terminal device receives receive a sidelink transmission on a first resource within a frequency bandwidth. Then the first terminal device determines at least one second resource within the frequency bandwidth for transmitting feedback information for the sidelink transmission, a frequency range occupied by the at least one second resource exceeding or being equal to a predefined percentage of the bandwidth, the at least one second resource comprising a common second resource and transmits the feedback information on the at least one second resource. In this way, the occupied channel bandwidth requirement for the feedback information of the sidelink transmission is ensured.

Various embodiments herein provide techniques for sidelink (SL) communication on unlicensed spectrum. For example, embodiments provide techniques for a physical sidelink feedback channel (PSFCH) and / or a SL synchronization signal block (S-SSB), such as techniques related to a listen-before-talk (LBT) procedure and / or occupied channel bandwidth (OCB) requirements. Other embodiments may be described and claimed.

The invention relates to the technical field of audio coding and decoding, and discloses an audio coding and decoding method and device based on a neural network, equipment and a storage medium. The method comprises the following steps of: firstly, gradually quantizing residual information of an audio signal by introducing an improved residual vector quantization method, and more finely retaining audio characteristics in a compression process; then, a loss function fusing reconstruction loss, perception loss, residual vector quantization loss and commitment loss is adopted, so that the reconstruction quality of the audio signal under different bit rates is remarkably improved, and efficient audio compression can be realized while high tone quality is ensured; and finally, an entropy coding module is introduced after quantization, so that the code rate of coding is further reduced, and the bandwidth requirement of audio real-time transmission is remarkably reduced.

The invention relates to the technical field of wireless communication and edge computing fusion, in particular to a wireless network resource allocation method based on edge intelligence, which comprises the following steps: S1, collecting a multi-dimensional parameter set of network edge nodes in real time; s2, converting node position coordinates into a network topological structure map, and mapping service type labels and bandwidth requirements into service requirement feature vectors; s3, generating a domain division matrix based on weight distribution of the network topological structure atlas; s4, outputting a resource block configuration tensor according to the time-frequency feature of the business demand feature vector; s5, generating a resource allocation mapping relation table; and S6, generating and executing a node-level resource scheduling instruction set. According to the invention, by constructing a resource scheduling mechanism fusing a topological structure and service features, precise resource allocation and dynamic load balancing of a cooperative domain level and a node level are realized, and the efficiency and the resource utilization rate of multi-task concurrent processing in an edge computing environment are improved.

A fault identification system and method. The system comprises an edge device and a server. The edge device can extract, from an original vibration signal, signal characteristics reflecting an abnormal vibration state of a device under test and report the signal characteristics to the server; and the server can identify a fault state of the device under test on the basis of the signal characteristics. The data volume of the signal characteristics reported in the process is small, thereby reducing the bandwidth requirement; and the signal characteristics can be used for accurate fault identification, thereby improving the accuracy of fault identification.

The invention relates to the technical field of wireless distribution network control, in particular to a high-speed low-delay distribution network three-remote system and method based on 1.4 GHz wireless communication, and the system comprises a channel management and distribution module which is based on a 1.4 GHz frequency band, reads the channel bandwidth utilization rate and interference level, counts the occupied time, divides the frequency band, and adjusts the frequency reuse proportion; and allocating a transmission frequency, optimizing spectrum allocation according to a bandwidth requirement and a transmission rate, and generating a channel frequency configuration table. According to the invention, by dynamically adjusting the frequency reuse proportion and allocating the transmission path frequency, the utilization rate of frequency spectrum resources is improved, the overload phenomenon of a channel is reduced, the high efficiency and stability of communication are ensured, and the overall transmission quality is improved by detecting interference signals and frequency spectrum fluctuation in real time, optimizing the signal transmission state and avoiding signal interference. The path interference risk is analyzed in advance through fast Fourier transform, potential transmission interruption is avoided, the stability of data transmission is ensured, and data loss is reduced.

The invention provides a dynamic wavelength allocation method based on DCI wavelength division II type equipment. The method comprises the following steps: acquiring an occupation state and a transmission quality index of each wavelength channel of a current network; establishing a wavelength channel quality evaluation model, and scoring each wavelength channel according to the transmission quality index of each wavelength channel of the network; according to the bandwidth requirement, the priority and the QoS requirement of the service request, generating a traffic characteristic matrix containing the delay sensitivity and the bandwidth requirement through a traffic prediction algorithm; based on a network state and the traffic characteristic matrix, through resource availability calculation and path quality evaluation, forming an allocable wavelength resource pool and a quality score thereof; for the allocatable wavelength resource pool, generating an optimal wavelength allocation scheme by adopting an improved heuristic algorithm and comprehensively considering the resource utilization rate, the signal quality and the service priority; and according to the performance feedback of the optimal wavelength allocation result and the network state change, continuous optimization of wavelength allocation is realized through a self-adaptive adjustment mechanism. The method can effectively deal with the dynamic flow change in the DCI network, improve the resource utilization rate, ensure the signal quality and meet the QoS requirement of the service, thereby providing an efficient and reliable wavelength allocation solution for the data center interconnection network.

The invention discloses an intelligent elevator host bearing fault diagnosis system based on AI and fault physical fusion, and belongs to the technical field of elevator diagnosis. Comprising an edge end which is connected with a cloud end; when fault diagnosis is carried out, the edge end firstly collects a high-frequency signal through a sensor, sequentially executes signal preprocessing, feature extraction, anomaly detection and data compression, and finally sends compressed feature data to the cloud end; after the cloud end receives and verifies the integrity of the data, the feature data is stored in a time series database, deep analysis is executed through a data analysis engine, a lightweight model is optimized based on historical data, an analysis result is displayed through a remote monitoring platform, and an alarm notification is sent when abnormity is detected; meanwhile, the cloud end issues the optimized lightweight model to the edge end to form a continuously optimized closed loop. Through the feature extraction and data compression technology of the edge end, the data volume needing to be transmitted is greatly reduced, and the network bandwidth requirement and the transmission delay are remarkably reduced.

A system and a method for optimizing a cable system in a telecommunication network Includes the steps of: receiving a position of each of a plurality of terminal nodes and a minimum bandwidth requirement associated with an operation of the telecommunication network including the plurality of terminal nodes and a plurality of branching nodes, wherein the telecommunication network is arranged to facilitate communication among the plurality of terminal nodes via at least one of the plurality of branching nodes; determining, between adjacent pairs of nodes of terminal nodes or branching nodes, a distance and a bandwidth capacity of a cable edge between each adjacent pair; and providing an optimized geographical location of the branching nodes and an optimized bandwidth capacity of each cable edge in which the telecommunication network being deployed with the branching nodes and the cable edges meets a quality of service associated with the minimum bandwidth requirement.

The invention relates to the technical field of communication, and discloses an OCPX-based backhaul data optimization system, which comprises a backhaul data acquisition module used for receiving and collecting backhaul data from terminal equipment or a network node, including basic information of a data packet and a network state; the backhaul data analysis module is used for analyzing backhaul data according to an OCPX protocol and identifying key features in the data packet, including importance, delay requirements, bandwidth requirements and the like of the data packet; and the optimization priority calculation module is used for calculating the optimization priority of the returned data packet according to the characteristics of the returned data and generating a priority sequence. The system can accurately calculate the optimization priority of each data packet through analysis and feature recognition of returned data in combination with factors such as importance, delay requirements and bandwidth requirements. The optimization strategy based on the multi-factor weight ensures that important and high-timeliness data packets can be transmitted preferentially, so that the overall efficiency and real-time performance of data transmission are effectively improved.

A centimeter-resolution integrated photonic millimeter-wave (mmWave) radar chip operating in the mmWave V band based on a 4-inch wafer-scale thin-film lithium niobate (TFLN) technology is provided. The fabricated TFLN photonic mmWave integrated circuit has a first electro-optic modulator (EOM) capable of generating a broadband linear frequency modulated mmWave radar waveform through optical frequency multiplication of a low-frequency input signal, and a second EOM for frequency de-chirp of the reflected echo wave, thereby greatly relieving bandwidth requirements for the digital-to-analog converter in the transmitter and analog-to-digital converter in the receiver. In the absence of optical and electrical filters, the radar chip features continuous on-demand tunability of the center frequency and bandwidth, currently only limited by the bandwidths of electrical amplifiers. The radar chip provides a promising way to achieve high resolution sensing and detection for vehicle radar, airborne radar, and smart home in the 6G era.

The invention discloses an unmanned aerial vehicle cluster cross-layer cooperative routing method based on TDMA, is applied to the field of wireless communication network resource scheduling and unmanned aerial vehicle autonomous networking cooperative control, and aims to solve the problem that the overall resource utilization rate of a system is low due to hierarchical design of a routing strategy and an MAC layer channel access control strategy in an existing TDMA network. The method comprises a dynamic collaborative framework based on routing and time slot allocation and a time slot state sensing routing algorithm based on deep reinforcement learning, the framework provides real-time time slot resource allocation state input for the algorithm, the algorithm outputs an optimal path meeting the bandwidth requirement for the framework, the problem of resource mismatching of a traditional layered framework is effectively avoided, and the routing efficiency is improved. And finally, collaborative optimization of the service bandwidth achievement rate and the network resource utilization efficiency in a high-load scene is achieved.

The invention provides a video coding method and device, electronic equipment, a chip and a medium, and relates to the field of video coding, and the method comprises the steps: determining a plurality of initial regions in each frame of picture for a plurality of frames of pictures in an original video; determining the change rate of each initial region based on the pixel points in the plurality of initial regions; determining at least one coding region and a coding strategy corresponding to each coding region based on the change rate; and performing video coding on each coding region by using the coding region corresponding to each coding region to obtain target data. According to the coding method provided by the invention, the change frequencies of different regions are identified, the regions needing to be coded are determined, and different coding modes are adopted according to the change frequencies of the coding regions, so that efficient and flexible dynamic regional coding is realized, the coding efficiency is improved, the calculation amount and the transmission amount are reduced, and the network bandwidth requirement is reduced.

The invention relates to a compression algorithm optimization method and device based on a RapidIO protocol stack and electronic equipment, and the method comprises the steps: determining an applicable compression algorithm according to the type of data transmitted by RapidIO; integrating the selected compression algorithm to a transmission layer of a RapidIO protocol stack, and creating compression and decompression functions as independent modules; dynamically adjusting a compression strategy according to a real-time network state and data characteristics; and a data integrity checking mechanism is added in the compression and decompression processes. By selecting a proper compression algorithm and integrating the compression algorithm into a protocol stack, the data transmission quantity can be remarkably reduced, so that the bandwidth utilization rate is improved, the high-bandwidth requirement is met, meanwhile, due to the modular design and the introduction of a dynamic compression strategy, the system can perform self-adaptive adjustment according to the real-time network state and data characteristics, and the real-time performance of the system is improved. The real-time requirement is met, the bandwidth can be effectively utilized conveniently when large-scale data transmission is processed, and resource waste is reduced.

The invention belongs to the technical field of wireless communication networks, and discloses a multi-modal adaptive routing equipment network optimization method based on artificial intelligence, which comprises the following steps of: extracting network flow metadata in a data link layer by adopting deep packet inspection, and analyzing and predicting bandwidth requirements in n periods of time in the future based on a time sequence; planning channel resources by adopting a Nash equilibrium algorithm according to the bandwidth requirement, and generating a channel allocation instruction; synchronously acquiring multi-band channel state data, and constructing a three-dimensional radio frequency environment signal spectrum; analyzing the three-dimensional radio frequency environment signal spectrum, searching a frequency band combination with the minimum interference, and generating a frequency band switching instruction; integrating the channel allocation instruction and the frequency band switching instruction, generating a network QoS optimization strategy, and issuing the network QoS optimization strategy to the routing equipment for execution; and the network transmission efficiency, the security and the adaptive capacity of the routing equipment are improved.

According to the automatic driving data transmission scheduling method and device, the equipment and the readable storage medium, dynamic priority weights are generated in a mode of combining reinforcement learning and a rule engine, and bandwidth demand changes, historical transmission performance and queue occupation states of all sensors can be adapted in real time; the problem that a low-priority sensor cannot acquire the bandwidth at a high load is effectively avoided, and meanwhile, efficient utilization of bandwidth resources can be realized through dynamic weight adjustment when a high-priority sensor is idle, so that the bandwidth utilization rate in a vehicle-mounted multi-sensor data transmission process is remarkably improved; the real-time performance and reliability of data transmission required by automatic driving decision making are guaranteed, and then the overall performance of an automatic driving system is improved.

The invention discloses a wireless router access management method and system and a wireless router, relates to the technical field of wireless routers, and remarkably improves network security and resource utilization efficiency through multiple authentication and a dynamic management mechanism. According to the system, first behavior characteristic data and network state data of equipment are collected, intelligent analysis is carried out in combination with a CNN model, and the security of the access equipment is judged in real time. For equipment meeting the security standard, the system automatically allocates bandwidth and provides continuous network service, and for abnormal equipment, the system blocks access of the abnormal equipment in time through multiple rounds of authentication and load evaluation, so that the security and stability of a network environment are ensured. In the aspect of bandwidth management, the system intelligently sorts and dynamically allocates bandwidth resources according to the second access safety index # imgabs0 # and bandwidth requirements of the access equipment, and low efficiency and resource waste of a traditional static allocation mode are avoided.

The invention provides a time division multiplexing-based inter-generation PON (Passive Optical Network) scheduling method and device. According to the method, modeling is carried out on association between uplink time slot resources of different intergenerational ONU terminals and total time slot resources of a PON port, a mathematical model of time slot resource allocation is obtained, the model is solved by adopting a unified scheduling algorithm, the unified scheduling algorithm can effectively coordinate bandwidth requirements of the different intergenerational ONU terminals, and the time slot resource allocation efficiency is improved. According to the method and the system, the 50G-PON terminal with high priority is ensured to obtain enough resources, meanwhile, the resource utilization rate of the whole PON network is optimized, and the service requirements of other intergenerational (such as EPON and 10G-EPON) ONU terminals are considered on the basis of ensuring that the system meets the 50G-PON priority requirements, so that the time division multiplexing coexistence of a multi-intergenerational PON system is realized. The problem that the EPON cannot coexist with the 50G-PON due to the fact that the uplink wavelength range of the EPON is too wide is solved.

The invention relates to a data transmission method and device, electronic equipment, a chip and a medium, and the method comprises the steps: obtaining a target address of a target storage region in a first memory corresponding to an application processor; according to the target address, storing at least one piece of target data acquired by the modem into a target storage area through an interface between the modem and the application processor; determining a data description sequence according to each piece of target data in the target storage area; the data description sequence comprises data description of each piece of target data; storing the data description sequence into a target storage area; the data description sequence is used for indicating a processing sequence of at least one piece of target data; according to the method and the device, read-write operation processing on the second memory corresponding to the modem is avoided, the bandwidth requirement on the second memory is reduced, and the power consumption is reduced.

The present invention relates to the technical field of computational reconstructive spectrometers, and in particular, to a spectral segment computational reconstruction method, a spectrometer, and a device, which are used for performing spectral reconstruction on an object under test, of which a wavelength range falls within a set interval X. The spectral segment computational reconstruction method comprises: performing, in order, computational reconstruction on spectral segments of set intervals x1, x2, …, xk, to respectively acquire spectral feature information sets y1, y2, …, yk of the object under test in corresponding wavelength ranges; and performing splicing and reconstruction on the spectral feature information sets y1, y2, …, yk of the corresponding wavelength ranges, to obtain complete spectral feature information Y of the wavelength range of the object under test in the set interval X. The method can greatly reduce the computing power requirements on a computing device and reduce the bandwidth requirements on a single light source, so that a spectral sensing system can be further miniaturized and low in cost. In addition, customization and non-continuous spectrum analysis are facilitated, and product power consumption is reduced.

The invention discloses a network resource scheduling method and device, equipment, a storage medium and a product, and the method comprises the steps: obtaining the network slicing demand information of a target network, carrying out the slicing operation of the target network according to the network slicing demand information, and obtaining a plurality of different types of network slicing demands; classifying network traffic of the target network according to business service quality requirements, slice priorities and traffic characteristics to obtain a traffic classification result of the target network; and performing resource scheduling on the target network according to the flow classification result and the network slicing requirement. Performing priority division of the flow based on QoS parameters such as the bandwidth requirement, the time delay requirement and the priority of the flow; according to different flow characteristics and business demand optimization classification rules, a resource allocation strategy is adjusted in real time in a dynamically changing network environment, it is ensured that high-priority flow is processed in time, and network load fluctuation and business demand changes can be coped with in real time.

The invention belongs to the technical field of short-wave radio station control, and particularly relates to a foreign trade short-wave radio station remote control method based on a WiFi link. According to the method, through multi-round data feedback and strategy optimization, the problems of frequency deviation, insufficient power or overload are automatically corrected, the signal distortion and interruption rate are effectively reduced, the high reliability of a communication link is ensured, and based on real-time calculation of an environment interference coefficient and communication compensation information, the transmitting power can be dynamically improved or a more suitable modulation mode can be switched; therefore, the influence of electromagnetic noise on the signal is reduced, the data transmission quality is ensured, flexible adjustment can be performed according to different communication distances, bandwidth requirements or frequency band limitation through a dynamic control strategy, and the rapid deployment and switching requirements of the foreign trade short-wave radio station in multiple scenes are met.

The invention discloses a communication network bandwidth control method, and particularly relates to the technical field of network bandwidth control. Flow monitoring equipment is arranged in a communication network, flow is monitored in real time, flow data of different users and applications are collected, and on the basis of historical flow data and a real-time change trend, a burst flow prediction model is constructed, and flow peak fluctuation and sudden increase characteristics are analyzed, so that the real-time response capability of a bandwidth allocation strategy is evaluated in advance, and the real-time response capability of the bandwidth allocation strategy is evaluated in advance. When the response capability is insufficient, bandwidth allocation is dynamically adjusted according to a priority strategy, bandwidth requirements of high-transmission-priority applications are preferentially guaranteed, bandwidth occupation of low-priority applications is limited so as to ensure the continuity of key services, and after bandwidth adjustment, the allocation strategy is further refined through real-time flow feedback, so that the bandwidth allocation efficiency is improved. The efficient utilization of resources and the stability of network service quality are guaranteed, so that the problem of bandwidth allocation lag in emergencies is solved, and flexible resource optimization management is realized.

The invention discloses a mirror image file transmission method and device, electronic equipment and a storage medium, and relates to the technical field of computers. According to the method, the difference comparison algorithm is preferably utilized to acquire the difference data blocks for uploading or downloading of the mirror image file, so that the data transmission quantity is reduced, the bandwidth occupation is reduced, the network state parameters are monitored in real time during data transmission, and the bandwidth requirement is predicted by adopting a mixed time sequence prediction mode according to the network state parameters, so that the data transmission efficiency is improved. And through the decision tree, the distribution action is optimized, the size of a transmission window and the sending rate of a data packet are dynamically adjusted, the transmission rate is improved, the transmission state of each data block is recorded during data transmission, a heartbeat packet is periodically sent to detect the connection state, reconnection is started after disconnection is detected, and transmission is continued from an interruption point after successful reconnection. And the integrity of the data is verified after the data block transmission is completed, so that the fault tolerance is improved.

Selective packing of small block write operations is implemented prior to compression, to improve compression efficiency and hence reduce bandwidth requirements of a Remote Data Replication (RDR) facility. Compression characteristics of write IO operations are forecast, and write IO operations with similar forecast compression characteristics are pooled. Write IO operations are also grouped according to extent, device, and storage group. Write operations from a given compression pool are then preferentially selected from the extent-level grouping, next from the device-level grouping, and then from the SG-level grouping, to create an IO package. The IO package is then compressed and transmitted on the RDR facility. By creating an IO package prior to compression, it is possible to achieve greater compression than would be possible if each individual write IO operation were to be individually compressed to thereby reduce network bandwidth of the RDR facility.

The invention discloses a video transmission and grading early warning method based on 5G and Wi-Fi hybrid networking, and relates to the technical field of network transmission and safety monitoring, and the method comprises the steps: firstly deploying fusion anchor points containing three types of core hardware modules, and determining the number of the fusion anchor points; extracting service time delay and bandwidth demand grades in an XR scene, establishing a QoS parameter mapping relation between 5G and Wi-Fi, and reading key parameters through a fusion anchor point to dynamically allocate bandwidths; based on the parameter matrix and the weight matrix, determining a sampling interval and marking a sampling frame; and finally, evaluating a sampling frame threat parameter and executing hierarchical response. According to the invention, while the collaboration of hybrid networking is improved, the accuracy of threat assessment is improved, and the continuity and security of video transmission in an XR scene are ensured.