557 results about "Bandwidth allocation" patented technology

The invention relates to the technical field of computer networks, in particular to a monitoring method and system based on industrial computer network fault data, and the method comprises the steps: collecting the heterogeneous fault data of each layer of equipment in an industrial control network in real time through distributed probe nodes; performing multi-modal normalization processing on the original fault data; constructing a fault knowledge graph, and dynamically associating an equipment topological relation, a historical fault mode and a current production task context; fault root cause analysis is carried out by adopting a hybrid inference engine, and a potential fault propagation path is predicted in combination with a rule-based expert system and an LSTM-GNN joint model; generating a grading alarm strategy, triggering a self-adaptive fault-tolerant mechanism, and dynamically adjusting network bandwidth allocation or starting redundant equipment switching according to the fault grade; according to the invention, by constructing the industrial knowledge graph and the adaptive fault-tolerant mechanism, efficient, accurate and interpretable fault diagnosis and prediction are realized, and the reliability and operation and maintenance efficiency of an industrial network are improved.

The invention relates to the technical field of communication data analysis, and discloses a communication network service health degree analysis method, system and device and a medium, and the method comprises the steps: obtaining real-time link state data, carrying out the quantitative analysis, and judging whether the link jitter exceeds a preset threshold value or not; when abnormality is detected, abnormal points can be positioned and the influence range of the abnormal points can be analyzed, so that the influence degree of nodes on the abnormal diffusion path can be identified; calculating a service quality index change value, and determining a starting point and a diffusion direction of chain degradation; by analyzing historical traffic data of the key nodes, a service traffic change trend and traffic dense area distribution characteristics are obtained. According to the method, the bandwidth allocation strategy is dynamically optimized, the bandwidth resources at the junction are reconfigured, and the regional service health degree is evaluated. And if the degradation is not effectively controlled, monitoring and detection mechanism parameters can be adaptively adjusted, and continuous analysis and control of link abnormity are realized, so that the network performance and the service quality are effectively improved.

The invention relates to the technical field of wireless high-definition audio and video transmission, and discloses a plug-and-play wireless high-definition audio and video transmission method and system.The method comprises the steps that foreground space texture features and audio and voice segments are obtained, and an initial feature set containing space and semantic features is obtained through semantic correlation analysis; a unified representation vector is output through multi-modal feature fusion, and a dynamic importance score is obtained by determining time sequence consistency, calculating an importance weight and performing normalization; and when the score exceeds a threshold value, segmenting the video frame in real time to determine an attention focus area and optimize a boundary, thereby generating an attention weight matrix, preferentially allocating bandwidth and forming a partition differentiation compression result. And in combination with a network bandwidth state, protection is enhanced for a key stream, the priority and the bit rate are dynamically adjusted, and high-quality audios and videos are output through decoding and recombination. According to the invention, the bandwidth allocation and compression strategy can be dynamically optimized, the transmission quality of a key area is guaranteed when the bandwidth fluctuates, and the audio and video transmission efficiency and experience are improved.

The invention relates to the technical field of wireless communication, in particular to a multi-orbit elastic communication method and system, and the method comprises the steps: monitoring the performance parameters of a multi-orbit satellite link in real time, and calculating the comprehensive score of each satellite link of the multi-orbit satellite link based on a preset scoring function; dynamically adjusting a configuration strategy of the main backhaul link according to the comprehensive score and a reinforcement learning model; when a network fault or congestion is detected, activating an alternative backhaul path to complete flow redirection and breakpoint resume, and executing a corresponding disaster recovery strategy according to a fault level; and dynamically adjusting bandwidth allocation according to the authorization level of the user equipment. According to the invention, the elastic communication service with wide-area coverage, low time delay and high reliability can be realized through multi-orbit satellite cooperation, efficient disaster recovery switching and priority resource guarantee in a complex scene.

The invention relates to an FTTR bandwidth management method based on a PON, and the method comprises the steps: dividing a to-be-managed region into a plurality of sub-regions according to the demands, distributing independent IP sub-networks, predicting the service of each IP sub-network, carrying out the pre-distribution, collecting the ONU flow data in real time, carrying out the feature extraction, obtaining the flow change features, dynamically adjusting the bandwidth distribution strategies of different slices, and constructing a double-layer dynamic weight model. Each network slice corresponds to an independent weight adjustment strategy, a dynamic time slot distribution field is inserted in an MPCP protocol, time slot distribution is carried out according to weight values of different network slices, burst traffic is preprocessed, demand prediction values are reported according to network slice classification, burst traffic information and traffic feature data are integrated, and the data are distributed according to the burst traffic information and the traffic feature data. And dynamically allocating bandwidth to each terminal device in the FTTR network. FTTR network bandwidth fine and dynamic management is achieved through multi-dimensional data processing, the network resource utilization rate and the user service quality are effectively improved, and the transmission requirements of diversified services are met.

The invention relates to the technical field of electric power system communication, in particular to a dynamic bandwidth allocation method and system for an electric power communication network, and the method comprises the steps: constructing a service traffic characteristic database, dividing service types, defining indexes such as a bandwidth threshold value, and predicting traffic fluctuation by adopting an LSTM-GARCH hybrid neural network; parameters such as a link bandwidth occupancy rate are obtained in real time, and a network state matrix is constructed; based on the prediction model and the network state, generating a bandwidth allocation scheme through a deep reinforcement learning algorithm optimized by a near-end strategy; a software-defined network controller is used to execute a strategy, and a gradient descent method is combined to optimize parameters to form a closed loop. By dynamically adapting the service flow and the network state, the bandwidth utilization rate is improved, the key service transmission quality is guaranteed, and efficient and stable operation of the electric power communication network is achieved.

The invention discloses a smart campus converged communication system and an information interaction method thereof, and relates to the technical field of campus communication. The system comprises a terminal access module, a protocol conversion module, a hierarchical transmission module and a cross-modal interaction module. The terminal access module acquires a terminal data stream in real time by using a multi-protocol adapter; the protocol conversion module performs protocol decoupling and standardized packaging on the data flow by using a QoS bandwidth prediction model, and generates a bandwidth allocation scheme according to a dynamic bandwidth allocation algorithm in combination with a network topology state matrix; the hierarchical transmission module extracts service information data by using a data semantic analysis model, calculates Shannon entropy and constructs a transmission queue mapping table; and the cross-modal interaction module generates an interaction protocol stack adaptive to the service by using a multi-modal feature collaborative extraction mechanism and an attention weight fusion mechanism based on the transmission queue mapping table.

The invention relates to the technical field of network communication, and discloses an AI load-oriented network topology awareness and communication optimization method, an AI load-oriented network topology awareness and communication optimization device and a related system. The method comprises the following steps: acquiring gradient transmission delay data among computing nodes in a distributed AI training system, and constructing a gradient distribution table of gradient tensors and RDMA intelligent network card queue resources; performing aggregation operation on the gradient tensor in the gradient distribution table on a programmable data plane of the RDMA intelligent network card to obtain pre-aggregated gradient data; calculating a transmission efficiency index of the pre-polymerized gradient data and solving to obtain a bandwidth allocation coefficient; and adjusting an MTU frame parameter, a WQE queue depth and a credit window of the RDMA intelligent network card according to the bandwidth allocation coefficient, and generating a hybrid execution scheme. According to the method, intelligent distribution of the gradient tensor between hardware unloading and software processing is achieved, and the performance close to the optimal performance is obtained under the condition that resources are limited.

The invention provides a network use behavior analysis and bandwidth allocation method and system based on a portable WIFI device, and the method comprises the steps: carrying out the grouping of user behaviors through employing a clustering method in machine learning according to a preliminary behavior feature set, carrying out the discrimination of use modes for different purposes, such as entertainment, work, learning, and the like, and carrying out the recognition of the user behaviors. Determining core category distribution behind the user behavior diversity; according to the resource pre-allocation instruction, obtaining an available state of a current network resource, dynamically adjusting a bandwidth allocation proportion in combination with predicted demand peak data, and determining specific execution parameters of an intelligent allocation mechanism; and obtaining real-time feedback data of the network equipment in the execution process through the adjusted resource allocation scheme, and judging whether the dynamic response speed meets the requirement of improving the service quality or not according to the fluctuation condition of the resource allocation efficiency to obtain a final optimization record.

The invention discloses a hydroelectric power station state monitoring communication method, system and device and a medium, and the method comprises the steps: carrying out the channel attenuation prediction through employing an integrated learning algorithm, and obtaining a channel attenuation prediction result; based on a channel attenuation prediction result, communication parameter optimization is carried out through a control optimization algorithm, and the optimal transmitting power and coding modulation scheme are obtained; analyzing through a deep learning framework to obtain a communication traffic prediction result; dynamically adjusting resource allocation of each service flow through a bandwidth allocation strategy based on a communication flow prediction result to obtain optimized bandwidth resource allocation; through the configuration instruction, the communication parameter setting is dynamically adjusted, and the fine management of the communication system is realized. The satellite communication system of the hydropower station is more reliable and efficient, and better support is provided for operation management of the hydropower station.

The invention discloses a data scheduling and control method based on mainboard memory straight-through, and relates to the technical field of computer hardware, the method comprises the following steps: pre-allocating a straight-through memory area for mounting equipment in a firmware initialization stage, establishing a mapping relation between equipment identification and a physical address of an exclusive memory segment, and through address translation and access control rules of a firmware layer, the device bypasses a system cache level and accesses the exclusive memory segment in a direct memory access mode. Constructing a firmware scheduling table based on the mapping relation to manage access requests of all devices, monitoring transmission delay in real time, and dynamically adjusting priority weight and bandwidth allocation in the scheduling table according to a monitoring result; and sequencing the requests according to the updated scheduling table to complete scheduling and control of the memory access behavior of the equipment. According to the method and the device, the delay bottleneck caused by multi-level copying and firmware scheduling lag in mainboard data forwarding is effectively solved.

The invention discloses a computer system based on a cross-model Internet of Things equipment access efficiency calculation model, which integrates an equipment performance sub-model, a network state sub-model and a response prediction sub-model. The identification module is used for identifying a device inherent identifier of the Internet of Things device to be accessed so as to obtain a response time statistical characteristic value and a historical communication parameter set; the prediction module is used for acquiring network state parameters in real time, calling the response prediction sub-model to calculate expected response time, and optimizing the historical communication parameter set to generate an initial communication parameter set; the comparison module is used for monitoring the actual response delay and the data packet loss rate of the current access equipment and obtaining a delay deviation value; and the adjusting module is used for dynamically adjusting the bandwidth allocation strategy in the initial communication parameter set when a preset condition is met, and synchronously updating the data analysis priority to generate a target communication parameter set. According to the invention, differentiated access control of different types of Internet of Things equipment can be realized.

The invention provides a system and a method for automatically identifying OCP network card bandwidth. According to the system for automatically identifying the bandwidth of the OCP network card, dynamic bandwidth allocation is achieved through cooperation of the multiple computing nodes, the CPLD and the OCP network card, each computing node is connected with a connector on the side of the OCP network card through a certain x8 MCIO connector in a set of x8 MCIO connectors, each computing node distinguishes the node identity through differential voltage configuration of a reserved detection pin, and therefore the bandwidth of the OCP network card can be automatically identified. And the CPLD acquires node identity detection signals to judge an access mode, determines a bandwidth allocation strategy by combining with the slot in-place detection signal group, generates a bandwidth configuration control signal group according to the bandwidth allocation strategy, and feeds back the bandwidth configuration control signal group to the OCP network card. According to the system, the OCP network card bandwidth identification and distribution are carried out by using hardware, and the application of OCP network cards with different bandwidths in various access modes can be dealt with only through a CPLD (Complex Programmable Logic Device) under the condition that firmware of each hardware is not frequently replaced.

The invention discloses a session resource scheduling method and device, equipment and a storage medium, and relates to the technical field of communication, and the method comprises the steps: carrying out the prediction through a Kalman filtering algorithm based on the current network bandwidth data and historical flow data of a target session system when a session resource request is received, and obtaining a bandwidth prediction utilization rate; according to the bandwidth prediction utilization rate, bandwidth allocation is carried out through a token bucket algorithm, and an initial interval bandwidth is obtained; determining a session activeness state according to the session resource consumption data of the user; and performing bandwidth adjustment on the initial interval bandwidth through the session activeness state to obtain a session resource allocation result. As the bandwidth prediction utilization rate of the session resource request is predicted firstly, the appropriate initial interval bandwidth is allocated in advance; and meanwhile, bandwidth adjustment is performed in real time according to the session activeness state. By performing multi-stage real-time adjustment on the session process, the situation of non-uniform allocation of session resources is avoided, and the utilization rate of the session resources is improved.

The invention discloses a disk scheduling method, and relates to the technical field of storage systems, and the method comprises the steps: collecting a historical input / output access mode of a disk array card, the mode covering access information of a disk requested to be input / output in a historical time period, and generating a disk scheduling strategy adaptive to a business rule by using a pre-trained disk scheduling model; and meanwhile, monitoring the interface traffic of the disk array card in real time, calculating the bandwidth utilization rate of the disk array card according to the interface traffic, and dynamically adjusting the number of active and dormant disks in combination with a strategy. Therefore, the disk number and bandwidth allocation are flexibly self-adapted, the problems of bandwidth imbalance, burst load response delay and the like caused by rigid configuration in the traditional technology are effectively solved, and the service continuity and the system reliability are guaranteed.

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 relates to the technical field of coal mine automation control, and discloses a coal flow windscreen wiper multi-device cooperative control method and system. The method comprises the following steps: obtaining an original environment data set of each sensor node in an underground environment, processing the original environment data set to obtain a communication quality index, calculating bandwidth demand change of each node in combination with historical transmission records of the nodes, and predicting a resource allocation proportion; when the current available network resources cannot meet the requirements, sorting the key data packets to obtain a priority transmission sequence; extracting high-priority data from the sequence, temporarily storing the high-priority data to a local cache unit, and determining the state of a buffer area; dynamically adjusting bandwidth allocation by adopting an intelligent optimization model, and updating communication resource configuration; and judging whether the resource configuration meets a load balance requirement, if so, sending a data packet through a wireless channel, determining a transmission performance index, and generating a resource management scheme of a next period. The cooperative work efficiency of multiple devices of the coal flow windscreen wiper in the high-dust and high-humidity environment is improved.

Automated communication channel selection is provided. A method, system, and computer readable storage device automatically perform a discovery process of a MoCA® network, to determine a topology of the network, perform a spectrum analysis of a DOCSIS® network of which a portion of the frequency range may be shared, apply one or more business rules to the collected network and spectrum usage data, and determine an optimized channel configuration for transmitting data to end devices in a local network. For example, the channel configuration may be configured for optimal bandwidth allocation, transmission speeds, signal quality, etc., without interferences within the shared frequency spectrum range. A gateway device may include a filter that can be reconfigured as an all-pass filter or as a variable low-pass filter based on the channel configuration determination. The MoCA® network may be reconfigured to operate within a defined frequency range based on the determined channel configuration.

The invention provides an end-network cooperative transmission system and method for a multi-mode network. The system comprises a terminal service demand layer which is used for identifying the service type of a terminal in a multi-mode network, generating structured service demand information and transmitting the service demand information to a network collaborative decision-making layer; the network cooperation decision-making layer is used for fusing the service demand information and the link state information, generating a transmission optimization strategy including path selection, priority mapping, bandwidth allocation and rate control, and transmitting the transmission optimization strategy to the transmission optimization strategy execution layer; and the transmission optimization strategy execution layer is used for executing a transmission optimization strategy, collecting link state information in the multi-mode network in real time through INT, and transmitting the link state information to the network cooperation decision layer. According to the method, efficient scheduling of heterogeneous network resources and high-reliability transmission guarantee of differentiated services are achieved, and the method is suitable for key service scenes sensitive to time delay and reliability, such as Internet of Vehicles and ultra-high-definition video transmission.

The invention relates to the technical field of data communication and artificial intelligence, and particularly discloses an intelligent data optimization system and method based on artificial intelligence, and the system comprises a characteristic curve acquisition module, a period determination module, a node grouping module, a priority calculation module, a resource distribution module and a data scheduling module. The method comprises the following steps: firstly, acquiring a flow characteristic curve of each data flow, and determining a flow fluctuation period; then, K-means clustering is combined with genetic algorithm optimization, and nodes are grouped; then, integrating hardware performance parameters and flow stability, and calculating a transmission priority weight; bandwidth resources are allocated according to the weights, basic requirements of low-priority nodes are ensured, and dynamic adjustment is carried out to adapt to network load changes; and finally, constructing a multi-objective optimization model through a deep reinforcement learning algorithm DQN, dynamically scheduling a data flow according to a bandwidth allocation result, and realizing efficient data transmission by taking delay, a packet loss rate and a bandwidth utilization rate as optimization objectives, thereby effectively improving the network transmission efficiency and performance.

The invention provides a redundant network communication device for a high-speed ship, which belongs to the technical field of communication networks and comprises a redundant link aggregation module for interconnecting network switching devices through a preset number of optical fibers to form a stacking system and enabling an LACP (Link Aggregation Control Protocol) to bind the preset number of optical fibers into a logic aggregation channel; the double-rule terminal access module is used for configuring a network card for each user terminal based on the logic aggregation channel and the stacking system and respectively connecting the network card to the network switching equipment to obtain a double-rule access channel; the intelligent routing control module is used for generating a network topological graph based on the physical connection relationship between all the user terminals and the network switching equipment, and generating a static VLAN interface routing strategy based on the network topological graph; and the security protection execution module is used for implementing a security triple mechanism on the logic aggregation channel based on a static VLAN interface routing strategy. According to the invention, the network configuration can be automatically adjusted according to the link state and the network topology change, the bandwidth allocation is optimized, and the reliability and security of network communication are improved.

The invention discloses a channel scheduling and bandwidth allocation method, system and device for cloud desktop communication, and the method comprises the steps: obtaining a data frame set, allocating a corresponding priority identifier according to a channel type to which each data frame belongs, and embedding the priority identifier of each data frame into a special field of a frame structure; the data frames are inserted into the corresponding sending queues according to the priority identifiers, each priority corresponds to one sending queue, the data frames are extracted from all the sending queues in sequence according to a preset scheduling strategy to be sent, and the preset scheduling strategy at least supports a priority preemptive mode or a weighted fair queuing mode; and collecting network state parameters in real time, and dynamically adjusting the bandwidth quota of the channel corresponding to each data frame through a feedback closed-loop mechanism based on the network state parameters. According to the invention, the rapid transmission of high-priority data frames is ensured, and the delay of real-time interaction is reduced; resources are flexibly allocated according to the network state, and the bandwidth utilization rate is improved.

The invention discloses a bandwidth allocation method and device for a namespace, and the method comprises the steps: receiving an operation request, and determining a target namespace for which the operation request aims in an SSD (Solid State Disk); obtaining the capacity of the target namespace and the total bandwidth of the NAND Flash end of the SSD, determining active namespaces when the operation request is received, and obtaining the sum of the capacities of all the active namespaces; wherein the active namespace refers to a namespace with data operation in a preset time period; obtaining a capacity ratio between the capacity of the target namespace and the determined sum of the capacities of all the active namespaces; and allocating bandwidth for the target command space according to the total bandwidth of the NAND Flash end and the obtained capacity ratio, and executing the received operation request according to the allocated bandwidth. Therefore, the overall bandwidth utilization rate is improved.

The invention discloses a digital twin data synchronization method and system fusing deep learning and the Internet of Things, and relates to the technical field of data synchronization. The method comprises the steps of calling a timestamp and a data sequence identifier through a sliding window based on digital twinborn information of Internet of Things equipment, performing time span acquisition, calculating characteristic value variation amplitudes of adjacent time slices in a data sequence, performing transmission data sparsification processing, reducing communication burden, and obtaining a sparse characteristic set. According to the method, the sliding window technology and the time sequence analysis are adopted, data features can be efficiently extracted and compressed, redundancy in data transmission is remarkably reduced, the transmission rate and efficiency are improved, the dynamic segmentation decoding and feature mapping structure application enable data fluctuation to have higher response capacity and prediction precision, and the method is suitable for large-scale popularization and application. The data flow direction and the node connection weight are intelligently adjusted, the data synchronization path is optimized according to the real-time network state and the bandwidth allocation condition, and efficient synchronization of data between multiple nodes and multiple platforms is ensured.

The invention discloses a communication method and electronic equipment, and relates to the technical field of communication, and the method adopts a two-stage QoS control strategy, and combines a bottom layer hierarchical token bucket algorithm with a top layer deficit polling algorithm. And the bottom layer QoS adopts a hierarchical token bucket to realize bandwidth allocation and traffic shaping based on traffic categories. The top layer distributes bandwidth resources by adopting deficit polling on the basis of functions, so that the problem that the waiting time of data packets in transmission queues of other functions is too long due to the fact that large data packet transmission of a certain function occupies more bandwidth in function scheduling can be solved. According to the method, end-to-end QoS guarantee can be realized, and bandwidth requirements of different traffic categories and functions are considered, so that under the scene of cross-domain sharing of PCIe equipment, the hardware resource utilization rate is maximized, fine bandwidth allocation and traffic control are performed, efficient transmission and scheduling are ensured, and bandwidth fluctuation caused by burst cross-domain access is smoothly processed.

The application relates to the field of communication and is a space-air-ground communication resource multi-target optimization method based on a Pareto optimal solution set, which solves the problem of unreasonable communication resource allocation schemes in the prior art. The application relates to a ground Internet of Things terminal, a UAV and a low-orbit satellite, and comprises the following steps: 1. calculating uplink channel capacity from the ground Internet of Things terminal to the low-orbit satellite; 2. optimizing a target function modeling: taking the minimum uplink channel capacity of each category of Internet of Things terminal in step 1 as an optimization target; 3. iterative optimization based on an evolutionary algorithm framework; the application flexibly designs the deployment position of the UAV and the bandwidth allocation scheme among the Internet of Things devices, adopts a directional resource adjustment scheme, and optimizes the uplink channel capacity of each category of ground Internet of Things terminal through the UAV relay to the low-orbit satellite in a fair manner, so that the uplink channel capacity among the same type of Internet of Things devices is as equal as possible and the uplink channel capacity of each category of Internet of Things device is as large as possible.

The invention discloses a teaching live broadcast control method, a teaching live broadcast control system, a teaching live broadcast control medium and teaching live broadcast control equipment based on multi-protocol signal flow scheduling, a multi-protocol signal source is adaptively accessed, a protocol analysis plug-in is correspondingly loaded to analyze a protocol, and different types of heterogeneous flows are converted into standardized data flows. Extracting stream features, and performing scene recognition; and dynamically adjusting the bandwidth allocation strategy based on the network state and the terminal capability. And on the basis of the multi-target reinforcement learning model, generating an optimal strategy of bandwidth allocation for live broadcast stream pushing and local distribution requirements. Stream transcoding and format conversion are carried out, and multi-signal stream timestamps are dynamically calibrated and synchronized; based on a Transform model, multi-modal content matching is carried out, knowledge chain marks are generated, and finally terminal output is carried out. The method has the advantages of full-scene protocol compatibility, dynamic scene adaptive scheduling, intelligent resource dynamic allocation, high-precision time synchronization calibration and content intelligent association matching.

The invention discloses a high-speed peripheral component interconnection bandwidth allocation system, method and device, a medium and a product, and relates to the technical field of computers. The system comprises an adapter card, an impedance circuit and a basic input and output system. The impedance circuit is integrated on the adapter card, when adapter cards of different specifications are inserted, output of different impedance signals can be achieved through the state change of the impedance circuit on the adapter card, and in the power-on self-test stage, the impedance signal output can be achieved. And the basic input and output system determines the bandwidth of each high-speed peripheral component interconnection channel according to the impedance value and a preset impedance bandwidth mapping table. Therefore, when the adapter card is replaced, operations such as circuit redesign and impedance matching element adjustment do not need to be carried out on the mainboard, and the universality of high-speed peripheral component interconnection bandwidth allocation is improved. Besides, the basic input and output system automatically obtains the impedance value and determines the bandwidth through the power-on self-test stage, firmware configuration parameters do not need to be modified manually, and the flexibility of server hardware configuration is enhanced.

Methods, systems, and devices for data management are described. A first computing node within a first set of computing nodes may receive, from a network gateway, a first replication request that is associated with a first replication job for the first cluster of computing nodes to provide copies of a first set of one or more computing snapshots to a second cluster of computing nodes. The first set of computing nodes may determine that a second computing node different from the first computing node will service the data replication request. A network bandwidth allocation may be increased for the first computing node that received the replication request directly from the network gateway while the network bandwidth allocation for the second computing node is maintained for the second computing node based on the second computing node receiving the request via an internal redirection of the request.

The invention relates to the field of data transmission, and discloses a scheduling method for parallel transmission of multi-user video streams, which comprises the following steps of: decomposing each user video stream in a frame sequence layer, a code rate layer and a network buffer layer, and establishing a mapping unit for decomposed segments in a multi-dimensional state domain; based on the initial transmission situation map, asynchronous disturbance injection is carried out on the high-priority fragments; continuously monitoring the disturbance trajectory of the dynamic dependency scheduling layer in the flow, and identifying a delay abnormal region; mapping the generated semi-adaptive bandwidth allocation factor to a transmission node corresponding to each video stream in a network topology, and performing real-time regulation and control on a shunting proportion, a caching strategy and a priority weight of the transmission node through a nonlinear regulation function; in a dynamic scheduling topology convergence stage, joint integration is performed on a local bandwidth adjustment gradient and node topology weight attenuation. The method has the advantage of improving the continuity of multi-user video playing.