743 results about "Bandwidth allocation" patented technology

The invention discloses an archive data security integration management system, which relates to the technical field of knowledge maps and comprises an archive data acquisition module, a knowledge intelligent analysis module, a knowledge map dynamic construction module, a security situation evaluation module and a security communication center module. The data acquisition module structurally acquires metadata and operation behaviors, the intelligent analysis module dynamically governs data quality, the map construction module constructs a three-dimensional security model, the situation evaluation module quantifies security influence and generates a strategy, and the communication center module realizes dynamic identity authentication and bandwidth allocation. Through the knowledge graph technology, comprehensive integration and safety management of the archive data are achieved, the data quality and utilization efficiency are improved, dynamic evaluation and coping with safety threats are achieved, and the safety and integrity of the archive data are ensured. Meanwhile, through dynamic identity authentication and bandwidth allocation, the safety and efficiency of cross-domain communication are improved.

The dynamic bandwidth allocation and resource scheduling method based on the 5G network comprises the steps that S1, a base station collects service requests, network loads and channel information of user equipment of the 5G network, and the services are divided into real-time services, big data services, key services and conventional services; s2, the real-time service calculates the bandwidth by using deep learning; the big data service is distributed according to the idle bandwidth and the data volume proportion; key service main and standby links distribute bandwidths; conventional businesses come first and then are subjected to service distribution; s3, the base station maps bandwidth resources by using a multi-carrier and dynamic subcarrier algorithm, and optimizes signal transmission in combination with a beam forming technology; s4, processing service data according to a priority scheduling queue, and verifying signal transmission according to a channel quality adjustment coding mode; and S5, updating the data and evaluating the effect according to the user feedback, and re-optimizing the scheduling strategy as required. Through intelligent dynamic bandwidth allocation and resource scheduling, efficient, flexible and reliable transmission of different types of services is realized, and the network resource utilization rate and the service quality are improved.

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 traffic management, in particular to a video monitoring traffic intelligent optimization system which comprises a time sequence fragment evaluation module, a path priority adjustment module, a traffic scheduling optimization module and a buffer strategy adaptation module. According to the invention, the transmission efficiency and quality of the video monitoring data are improved by analyzing the video stream in real time and adjusting the frame rate and the compression rate, the importance of each time sequence segment in the video stream is evaluated, the frame rate is adjusted according to the importance, more resources are ensured to be obtained by important events, unnecessary data transmission is reduced, network congestion is effectively reduced, and the transmission efficiency of the video monitoring data is improved. The network transmission path is monitored in real time, and the data transmission proportion is adjusted, so that the video stream passes through the network path with higher quality more preferentially, the stability and speed of video transmission are enhanced, the priority and bandwidth allocation are dynamically adjusted, and the video stream with high priority is protected to ensure that the video quality of a key monitoring area is not influenced by network fluctuation.

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 discloses an unmanned aerial vehicle inspection method and system based on AI visual control, and belongs to the technical field of unmanned aerial vehicle automatic control, and the method comprises the steps: carrying out the feature component extraction and compression according to discontinuous frame image data collected by an airborne camera and preset inertial navigation data, and obtaining a compressed feature flow; performing multi-mode obstacle safety level parameter analysis, generating an obstacle avoidance decision priority map, constructing a safety corridor, and generating a real-time self-correction route; semantic analysis is carried out on the deviation between the real-time flight trajectory and the real-time self-correction route, and target area abnormal mark data is generated; and dynamically adjusting the bandwidth allocation of the dual-channel communication network, and transmitting the abnormal mark data of the target area to a ground control terminal. According to the method, a non-continuous frame image and inertial navigation fusion modeling mechanism is adopted, and a multi-mode obstacle safety grading and double-channel dynamic bandwidth allocation strategy is combined, so that real-time response of dynamic obstacle avoidance, accurate judgment of anomaly detection and efficient transmission of key data can be realized.

The invention discloses an Internet of Vehicles communication resource allocation method based on federal multi-agent deep reinforcement learning, and belongs to the technical field of deep crossing of intelligent transportation, wireless communication and distributed machine learning. According to the technical scheme, in an Internet of Vehicles scene, a vehicle is taken as an agent, and local training is performed through a multi-agent depth deterministic strategy gradient algorithm: each agent decides spectrum access, power control and bandwidth allocation based on a local state; asynchronous federation learning is adopted, each agent uploads local model parameters to a global server, weights are dynamically adjusted based on model updating quality, communication quality and updating frequency, and a global model is generated through weighted aggregation; and issuing the updated global model to an intelligent agent to realize distributed privacy protection and dynamic optimization of communication resources. The method has the beneficial effects that the spectrum efficiency, the transmission success rate and the system adaptability are remarkably improved on the premise of ensuring the data security, and the method has wide application prospects and commercial values.

The invention relates to the technical field of vehicle network control, in particular to an efficient vehicle network control system and method based on CAN-FD, and the system comprises a data transmission optimization module, a bandwidth management module, a signal scheduling control module, an encryption security control module and an anomaly detection module. In the invention, the bit rate of a data frame, the length of a data packet and the proportion of filling bytes are optimized, the transmission efficiency is improved, the bandwidth occupied by invalid data is reduced, a priority screening mechanism is called, the stable transmission of high-priority signals is ensured, the bandwidth allocation is adjusted based on the flow state and node frequency monitoring, the burst flow congestion is relieved, and the resource allocation is balanced; in combination with arbitration priority and bus conflict state, non-emergency signal priority is optimized, key data blocking risk is reduced, encryption and integrity verification are adopted, data security is ensured, tampering and leakage are prevented, data abnormity score and detection are introduced, abnormal data are screened, identification capability is improved, and network potential safety hazard is reduced.

The invention provides a disaster recovery data recovery method and system of a disaster recovery system, and the method comprises the steps: adjusting a network bandwidth allocation proportion according to a priority, and if the target timeliness is higher than a preset recovery time threshold, increasing a real-time power grid alarm data bandwidth proportion, and generating a bandwidth allocation scheme; dynamically scheduling computing resource allocation according to a bandwidth allocation scheme, and if the key evaluation characteristic exceeds a set upper limit, increasing a computing resource share of a service key level, and generating a resource allocation decision; and after the priority updating scheme is obtained, monitoring a system load in concurrent request processing through a disaster recovery system, and if the system load exceeds a preset threshold value, triggering rebalance of network bandwidth allocation in combination with timeliness deviation to obtain a resource optimization result.

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 belongs to the technical field of bandwidth adjustment, and particularly relates to a distributed monitoring bandwidth adjustment method and system capable of self-adaptive scheduling, which can ensure that high-priority nodes can preferentially obtain bandwidth resources by collecting network state data in real time and dynamically adjusting the bandwidth demand priority of each node. And the central scheduling node gathers priority information of all nodes, generates a global bandwidth allocation scheme, and continuously adapts to changes of network loads and monitoring requirements through a closed-loop adjustment process. According to the method, the utilization rate of bandwidth resources is remarkably improved, the stability and reliability of the system are enhanced, the phenomena of data transmission delay and packet loss are reduced, and meanwhile, the key nodes can still obtain sufficient bandwidth support under the condition of high load or emergency, so that the flexibility and the response speed of the whole distributed monitoring system are improved.

The invention relates to the related technical field of information transmission processing, in particular to a docking station adaptive data transmission optimization system and method, and the method comprises the steps: multi-module collaborative optimization docking station transmission: dynamically collecting port data, intelligently analyzing a configuration strategy, correcting cache congestion in real time, generating a control instruction, and feeding back an adjustment protocol; the technical problems that the bandwidth allocation strategy cannot adapt to the connection state of the port equipment and the sudden change of the data transmission requirement, the power distribution of the power supply is not matched with the equipment load, and the stability and reliability of the data transmission are limited are solved, the bandwidth allocation proportion of each port is dynamically adjusted, the bandwidth waste and congestion phenomena are reduced, and the data transmission efficiency is improved. The technical effects of improving the smoothness and the real-time performance of data transmission, improving the energy efficiency by cooperatively adjusting the distribution of power supply power based on a power supply power distribution strategy of an equipment compatibility thermodynamic diagram, reducing data packet loss and transmission errors by adopting a congestion risk control and cache management strategy, and improving the stability and the reliability of data transmission are achieved.

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 device firmware upgrading method and system and a storage medium, and the method comprises the steps: taking an Android mobile terminal device as an edge node, and obtaining all to-be-upgraded devices in the node and the device information of each to-be-upgraded device through a local area network protocol; according to the equipment information and an intelligent scheduling algorithm, dynamically adjusting the upgrade task priority and the upgrade task sequence of each piece of to-be-upgraded equipment and the network bandwidth distribution among the to-be-upgraded equipment; acquiring and judging whether the current network bandwidth is sufficient or not in real time, and if yes, performing equipment firmware upgrading at least according to the dynamic adjustment result; if not, readjusting the network bandwidth allocation between the to-be-upgraded devices, and then continuing to upgrade the device firmware; and monitoring the upgrading states corresponding to all the to-be-upgraded devices and the current network bandwidth in real time, judging whether an abnormal state exists or not, if so, readjusting the upgrading task priority of the abnormal state devices or the network bandwidth distribution among the abnormal state devices, and if not, continuing real-time monitoring until all the to-be-upgraded devices are upgraded.

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 discloses a communication network bandwidth resource visualized dynamic allocation method and system based on an SDN, and relates to the technical field of communication networks, and the method comprises the steps: obtaining the channel interference intensity, the spectrum occupancy rate and the service flow priority data of each node in a wireless network based on a southbound interface of an SDN controller, and obtaining the channel interference intensity, the spectrum occupancy rate and the service flow priority data of each node through a channel resource dynamic allocation table; generating a multi-dimensional resource view; according to the multi-dimensional resource view, multi-level coverage domains of the wireless network are divided, the service load level of each coverage domain is identified, and a pre-allocation scheme of cross-domain bandwidth resources is generated; and executing a pre-allocation scheme of cross-domain bandwidth resources by using a northbound interface of the SDN controller, and adjusting bandwidth allocation parameters of each coverage domain. According to the invention, visual monitoring, accurate division and flexible scheduling of the network resource state are realized, and the utilization efficiency of network bandwidth resources is remarkably improved.

The invention discloses a vehicle-mounted equipment communication simulation system and method based on an AVCLAN protocol, and belongs to the technical field of vehicle-mounted network communication. The system comprises a data acquisition module which is used for obtaining the initial state of each vehicle-mounted device, the real-time change of a network link, the protocol parameters of an AVCLAN protocol, environment characteristics and packet loss data, and inputting the data to a complete vehicle-mounted device connection model, obtaining communication data packet size, communication link bandwidth, communication link distance, signal propagation speed and packet loss delay data among the vehicle-mounted devices; the communication delay calculation module is used for calculating the total communication delay among the vehicle-mounted equipment; and the communication simulation and optimization module is used for determining a communication performance evaluation result and a path and network optimization result. According to the scheme, the performance of the vehicle-mounted communication system can be accurately simulated and evaluated, the communication link, the bandwidth allocation and the data transmission strategy are optimized, and the reliability, the stability and the real-time performance of the system are improved.

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 relates to the technical field of computer networks, and discloses a bandwidth allocation method and device, computer equipment, a storage medium and a program product, and the method comprises the steps: determining the priority of a to-be-transmitted data packet based on the type of the to-be-transmitted data packet; based on the priority of the to-be-transmitted data packet, determining the priority of the flow formed by the to-be-transmitted data packet; pre-allocating bandwidths for the flows with different priorities; for the flow of any priority, dividing a first shared bandwidth from the bandwidths pre-allocated for the flow of the priority, dividing a second shared bandwidth from the bandwidths pre-allocated for the flow of the priority lower than the priority, and generating a shared bandwidth based on the first shared bandwidth and the second shared bandwidth; and if the bandwidth occupied by the flow of the priority reaches a first bandwidth threshold value, allocating the shared bandwidth to the flow of the priority, and performing flow transmission by utilizing the bandwidth pre-allocated for the flow of the priority and the shared bandwidth. According to the invention, the data transmission reliability of the service system is improved.

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 embodiment of the invention provides a communication method and a related device, the method is applied to a first communication device, and the method comprises the following steps: determining an offload bandwidth proportion of each port of a second communication device; sending first indication information, wherein the first indication information comprises the shunting bandwidth proportion of each port; shunt data from the second communication device is received. And multi-port transmission between the first communication equipment and the second communication equipment is realized. And furthermore, the bandwidth allocation balance of each port of the first communication equipment is realized, and the communication performance is improved.

Described herein are systems and methods for dynamically selecting network scanning rates for electronic devices. For instance, a system select a scanning rate for a mobile device to scan at. The system can access a programmable table that stores scanning rates in association with identifiers of mobile networks and / or access nodes the mobile device can connect to. The scanning rates may vary based on whether the associated mobile network is (1) associated with the mobile device (e.g., the “home” network), (2) associated with a mobile network in a partnership with the home mobile network, and (3) associated with a mobile network not in a partnership with the home mobile network. The scanning rates may also vary based on the associated access node being terrestrial (e.g., located on the surface of the earth) or extraterrestrial (e.g., located beyond the surface of the earth), such as a satellite.

The present invention is applicable to the technical field of network communication, and provides a method and device for dynamically allocating mesh sub-machine bandwidth based on FTTR. The method for dynamically allocating mesh sub-machine bandwidth can be implemented based on FTTR system, FTTR-B system or broadband fusion terminal. The method for dynamically allocating mesh sub-machine bandwidth based on FTTR includes: counting the data volume, connection volume proportion and connection time proportion of each mesh sub-machine; obtaining the current connection status and real-time network quality score of each mesh sub-machine; calculating the relative distance between each mesh sub-machine and the user terminal according to the signal strength between each mesh sub-machine and the user terminal; calculating the bandwidth allocation corresponding to each mesh sub-machine according to the weight value corresponding to each mesh sub-machine and the total FTTR bandwidth; and allocating bandwidth resources to the mesh sub-machine based on the bandwidth allocation. In summary, the technical solution can realize efficient and intelligent mesh sub-machine bandwidth allocation and improve bandwidth utilization through dynamic and multi-dimensional evaluation and calculation methods.

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.