38 results about "Bandwidth scheduling" patented technology

The invention relates to the technical field of bandwidth scheduling, and particularly discloses an intelligent bandwidth scheduling method and system for a computing power cloud platform, and the method comprises the steps: distributing a task to a computing node through a task scheduler after receiving a computing task request, and storing task metadata; and the network performance monitoring module is synchronously started to monitor the network flow of the task. And further, based on the stored task metadata and the collected task network flow data, performing deep conjoint analysis on the task metadata and the collected task network flow data by using a deep learning algorithm to identify whether the task is in a network starting stage or not. If it is determined that the task is in the network starting stage, an application enhancement strategy request is sent to an intelligent bandwidth scheduler, and a high-priority QoS label is assigned to the task for bandwidth adjustment. Through the mode, the network demand characteristics of the task in different stages of the life cycle can be captured in a fine-grained manner, and the bandwidth resource allocation is dynamically adjusted, so that the bandwidth demand in the task starting stage is ensured, and the task execution is accelerated.

The invention provides a bus bandwidth allocation method and device based on a system on chip and related equipment, and the method comprises the steps: in response to a received bandwidth scheduling instruction, determining system operation scene information corresponding to the bandwidth scheduling instruction, and a plurality of operation state dimensions corresponding to the system operation scene information; for any function module, obtaining multiple pieces of operation state data corresponding to the function module; determining a plurality of scene adjustment factors corresponding to the system operation scene information; and for any function module, performing adjustment operation on the plurality of operation state data corresponding to the function module through the scene adjustment factor corresponding to the function module, and determining the allocation priority of the function module according to the operation result, thereby allocating the bus bandwidth for the plurality of function modules. The method is based on a dynamic priority mechanism of a multi-dimensional state and a scene adjustment factor, and ensures that a high-demand task can obtain sufficient bandwidth in time.

A multimode cabinet intelligent management terminal for narrowband Internet of Things communication comprises an environment monitoring module, a load sensing module, a protocol switching module and a bandwidth scheduling module. The environment monitoring module obtains key indexes of network signal strength, delay and packet loss rate and calculates environment data; the load sensing module collects CPU usage rate and memory usage condition load data, evaluates the load state of an Internet of Things sensor node, and generates load data and environment data. The protocol switching module dynamically evaluates network environment and equipment load changes, predicts a network environment change trend by adopting a weighted decision method, and screens an optimal protocol based on a protocol switching strategy; and the bandwidth scheduling module performs optimal allocation on the bandwidth, automatically adjusts bandwidth resources, and performs release and reallocation by monitoring the network condition in real time to obtain bandwidth resource information. The invention provides a multimode cabinet intelligent management terminal for narrowband Internet of Things communication. Accurate point prediction and reliable interval prediction and probability prediction of wind power are realized.

Disclosed in the embodiments of the present application are a bandwidth scheduling method, an electronic device and a computer-readable storage medium. The method comprises: dividing a target frame into multiple subframes on the basis of a preset bandwidth requirement, wherein each subframe corresponds to a subframe configuration table and a high-priority entry configuration table; on the basis of information collected from an optical network, calculating an allocable bandwidth for the target frame; on the basis of a high-priority entry configuration table and a subframe configuration table of a target subframe among the subframes, and the allocable bandwidth, determining bandwidth entry priorities of the target subframe; on the basis of the bandwidth entry priorities of the target subframe, sequentially transferring bandwidth entries of the target subframe to a preset bandwidth mapping table; and when the target subframe is the last subframe of the target frame, transmitting to an optical network unit all bandwidth entries of the target frame that are stored in the bandwidth mapping table.

The invention discloses an internet of things card bandwidth scheduling optimization method and system, and relates to the technical field of internet of things communication. The method comprises the following steps: monitoring and acquiring equipment characteristics of target equipment monitored by an Internet of Things card, and preliminarily optimizing the bandwidth of the Internet of Things card according to the equipment characteristics to obtain an optimized bandwidth parameter space; obtaining an optimized internet of things card feature space and an optimized transmission parameter space obtained in the initial optimization process of the optimized bandwidth parameter space, and carrying out feature migration analysis in combination with equipment features to obtain a feature migration parameter space; according to the feature migration parameter space and the optimized Internet of Things card feature space, processing to obtain a compensated Internet of Things card feature space, and performing change compensation prediction of the optimized transmission parameter space to obtain a compensated transmission parameter space; and according to the compensation transmission parameter space and the compensation Internet of Things card feature space, final optimization is carried out, an optimal bandwidth parameter is obtained, and bandwidth configuration is carried out. According to the invention, accurate matching of bandwidth scheduling of the Internet of Things card is effectively improved.

The embodiment of the invention relates to the technical field of container group management, in particular to a dynamic bandwidth scheduling method and device of a K8S multi-cluster network and electronic equipment. The method comprises the following steps: determining an initial bandwidth allocation scheme, converting the initial bandwidth allocation scheme into a bandwidth allocation instruction, and issuing the bandwidth allocation instruction to each K8S cluster; service priority information of Pods in each K8S cluster and network bandwidth data of each K8S cluster are collected in real time; carrying out load state identification based on the service priority information and the network bandwidth data; if the identified load state reaches a high load condition, generating a dynamic bandwidth adjustment scheme based on the service priority information; and converting the dynamic bandwidth adjustment scheme into a bandwidth adjustment instruction, and issuing the bandwidth adjustment instruction to a corresponding K8S cluster to execute bandwidth adjustment operation. According to the method, the dynamic bandwidth collaborative scheduling based on the service priority and the multi-cluster network load can be realized.

The application discloses a traffic bandwidth scheduling method and device of a fusion CDN, and belongs to the technical field of Internet. The method comprises the following steps: in response to receiving a current access request for an acceleration domain name, acquiring a domain name and a request source area corresponding to the current access request; acquiring an uplink traffic IP resource of each CDN vendor and a bandwidth allocation ratio of planned business traffic according to the domain name and the request source area; acquiring an approaching period value according to the number of CDN vendors; acquiring a current request frequency corresponding to the current access request; and determining the uplink traffic IP resource of the CDN vendor for scheduling and responding to the current access request according to the current request frequency, the approaching period value and the bandwidth allocation ratio. According to the method, the business traffic bandwidth ratios of each fusion CDN vendor planned by the system are used for accurate scheduling, so that the business traffic bandwidth of each fusion CDN vendor is accurately allocated, and the CDN bandwidth cost of the system is saved.

This invention relates to oil and gas well surface testing video monitoring and edge intelligent transmission technology, and discloses a multimodal video intelligent transmission method driven by working condition semantic collaboration. This method spatiotemporally aligns video streams, working condition sensor data, and scene structure information; utilizes a working condition-video lead correlation model to generate risk levels and prediction lead times; drives adaptive switching between semantic messages, keyframes, and real-time video; and performs precoding enhancement, full network bandwidth scheduling, and original video backhaul retransmission before anomalies occur. A remote monitoring center uses digital twins for rendering and calibration. This method is suitable for oil and gas well surface testing sites with low bandwidth and weak networks.

The invention provides a distributed encryption fragmentation transmission method and system for big data disaster recovery and migration, and belongs to the technical field of enterprise-level data storage and cloud computing. According to the method, a neutral cache acceleration node is deployed in a core network hub, so that multi-source and multi-path parallel transmission of data fragments is realized, and the transmission efficiency and reliability are improved. A fragment version and a global transaction identification mechanism are adopted, fragment granularity breakpoint resume is supported, and data consistency is ensured. In combination with an intelligent bandwidth scheduling strategy, full fragmentation is synchronized in a service low peak period, only incremental fragmentation is synchronized in a peak period, network load is smoothed, and the influence on a production system is reduced. The system comprises a content provider, a neutral cache node, a scheduling and coordination server and an authorization terminal, safe and efficient migration and disaster recovery of mass data are achieved, the data compliance requirement is met, and the total cost is optimized.

The invention relates to an SDN (Software Defined Network)-based K8S network elastic scaling method and system, unified modeling and global visualization of a Kubernetes network are realized by introducing an SDN controller, dynamic bandwidth adjustment and QoS (Quality of Service) strategy issuing are carried out in combination with load prediction on the basis of sensing service flow in real time, the defects of fixed bandwidth and localized management of a traditional CNI (Context Network Interface) plug-in are effectively overcome, and the method and the system have the advantages that the service flow is sensed in real time; second-level elastic scaling and cross-cluster / cross-data-center deterministic bandwidth scheduling in a single cluster are realized, the phenomena of network congestion and resource waste are fundamentally eliminated, and the overall network resource utilization efficiency of the cluster and the service quality guarantee capability of key services are remarkably improved.

The application discloses a concentrator remote upgrading method and system, the method comprises the following steps: generating and storing the differential firmware to the distributed file storage module; the upgrading task is broadcasted to each concentrator node by the block chain network; the concentrator acquires task data and downloads the differential firmware; the downloaded differential firmware is verified; the new firmware is generated and installed according to the current firmware and the differential firmware. The application introduces the block chain technology to provide tamper-proof record and secure authentication mechanism for firmware upgrading, ensuring the authenticity and integrity of the firmware. At the same time, the smart contract and distributed file storage technology can effectively reduce the bandwidth and time required for firmware upgrading, improve the efficiency and reliability of upgrading. In addition, the application of dynamic bandwidth scheduling algorithm can reasonably allocate network resources when multiple concentrators upgrade at the same time, avoid network congestion and ensure that each concentrator can successfully complete firmware upgrading.

The invention discloses a multi-master-device-oriented global bandwidth scheduling and priority control method and system, and the method comprises the steps: forming a complete end-to-end scheduling system through a software marking mechanism, network-on-chip real-time monitoring, initiating end adaptive adjustment, transmission path adjustment and a master memory controller cooperation strategy; and dynamic management of multi-service flow access behaviors is realized. In the system, a software layer configures initial strategies for different data streams; the main equipment end dynamically adjusts the priority of the sent request based on the real-time load; the network-on-chip carries out secondary adjustment on the priority based on the congestion state of the transmission path; the main memory controller maps the request to different queues for execution according to the final priority; and the system feedback layer collects the overall performance state and feeds back the overall performance state to the software layer so as to dynamically update the strategy. According to the method, software and hardware collaborative and adaptive global bandwidth management is realized, and the overall performance and service quality of the complex system on chip are remarkably improved.

The invention provides a data transmission system and method for data networking, and relates to the technical field of data communication. The system comprises a data flow terminal configured with a first network interface and a second network interface; the data circulation support platform is configured to send a network demand parameter to the private network resource scheduling unit after determining a participant needing data transmission; and a private network resource scheduling unit configured to allocate network resources based on the virtual private network resource pool and the bandwidth resource pool, and communicate with another private network resource scheduling unit in a cross-management domain scene to cooperatively complete end-to-end resource allocation, an access voucher is issued to the data circulation terminal, and virtual private network configuration and a bandwidth template are issued to the private network transmission network; and the private network forwarding network establishes an isolated virtual private network channel according to the virtual private network configuration and the bandwidth template and executes bandwidth scheduling. According to the embodiment of the invention, safe isolation and efficient linkage of the control surface and the data surface can be ensured.

The present application relates to the technical field of bandwidth scheduling, and discloses a bandwidth scheduling method and device, which generates a bandwidth scheduling strategy of a current communication line of a target visitor based on broadband data of multiple communication lines and bandwidth data of the current communication line of the target visitor, and distributes the bandwidth scheduling strategy to a second CDN node, so that the second CDN node schedules the current communication line of the target visitor according to the bandwidth scheduling strategy of the current communication line of the target visitor, without modifying a linux kernel routing table, thereby avoiding risks caused by misoperations due to modification of the routing table. The disclosed embodiments automatically optimize and schedule to an optimal target scheduling line, thereby dragging high bandwidth to the target scheduling line, reducing bandwidth cost, improving network stability, and finally optimizing communication transmission quality between different visitors and node server ends.

This invention belongs to the field of communication automation technology and discloses a method for edge intelligent collaboration and dynamic security scheduling in communication automation. The invention covers the entire process of communication automation from edge collaboration and bandwidth scheduling to security protection by constructing three core modules: intelligent collaborative scheduling of edge nodes, dynamic allocation and optimization of communication bandwidth, and coordinated adaptation of security protection and communication performance. It adopts core technologies such as edge node load-aware collaborative scheduling, dynamic prediction and adaptive allocation of communication bandwidth, and security threat classification and performance-adaptive scheduling. This overcomes the industry bottlenecks of traditional communication automation, such as inefficient edge collaboration, rigid bandwidth allocation, and a disconnect between security and performance. It achieves intelligent collaboration of edge nodes, dynamic adaptation of communication bandwidth, and a coordinated balance between security protection and communication performance, significantly improving the edge processing efficiency, bandwidth utilization, and security protection capabilities of communication networks. It adapts to the needs of multiple scenarios such as edge computing communication, industrial control communication, and mobile edge communication, and particularly solves the technical problems of edge node load imbalance, mismatch between bandwidth allocation and service requirements, and the impact of security protection on communication performance.

The present disclosure provides a system-on-a-chip based bus bandwidth allocation method, device and related equipment, the method comprising: in response to the received bandwidth scheduling instruction, determining the system running scene information corresponding to the bandwidth scheduling instruction, and a plurality of running state dimensions corresponding to the system running scene information; for any functional module, obtaining a plurality of running state data corresponding to the functional module; determining a plurality of scene adjustment factors corresponding to the system running scene information; for any functional module, adjusting the operation of the plurality of running state data corresponding to the functional module through the scene adjustment factor corresponding to the functional module, determining the allocation priority of the functional module according to the operation result, and allocating the bus bandwidth to the plurality of functional modules. The method is based on the dynamic priority mechanism of multi-dimensional state and scene adjustment factor, which ensures that high demand tasks can obtain sufficient bandwidth in time.

The present application relates to a method for scheduling multiple variable paths and variable bandwidth based on a high-performance network. The method prioritizes the transmission of more urgent requests based on their priorities, and transmits more user requests within a transmission cycle. The method uses as many node-disjoint paths as possible to transmit data on the network, avoiding congestion caused by excessive load on a certain link, making more effective use of the entire network, improving overall bandwidth utilization, and increasing data transmission reliability. The method also takes into account the delay of path switching, making bandwidth scheduling more practical.

The application relates to the technical field of geological monitoring, and discloses a deep-hole geological monitoring method and system based on cloud-edge cooperation, which aims to solve the problems of poor data processing efficiency and reliability of the existing method, and mainly comprises the following steps: collecting multi-source sensor signals in a deep hole; transmitting the multi-source sensor signals to a private cloud edge based on an anti-interference transmission layer; converting differential signals into standardized digital signal streams by the private cloud edge; transmitting the standardized digital signal streams to a GPU cloud processing center based on bandwidth scheduling after real-time preprocessing of the standardized digital signal streams; generating a space-time alignment tensor and a geological monitoring task by the GPU cloud processing center; executing the geological monitoring task in a virtual machine; and triggering an active restart protection process when running to a maximum allowed time if the success probability of executing the geological monitoring task by the virtual machine is not greater than a probability threshold. The application improves the data processing efficiency and reliability, and is suitable for geological disaster early warning or engineering safety evaluation.

The application relates to a bandwidth cost scheduling method and device, computer equipment, a computer readable storage medium and a computer program product. The method comprises the following steps: acquiring a bandwidth allocation amount and an original bandwidth proportion of a first service provider; determining a unit proportion bandwidth amount of a converged content distribution network by using the bandwidth allocation amount and the original bandwidth proportion; determining a real-time cost redundant bandwidth of the first service provider according to total bandwidth cost data and total real-time bandwidth data of the first service provider; determining a bandwidth cut proportion of the first service provider relative to a second service provider according to the real-time cost redundant bandwidth and the unit proportion bandwidth amount; and performing a bandwidth scheduling operation matched with the bandwidth cut proportion. The method can realize dynamic scheduling adjustment of the bandwidth of the converged content distribution network and improve the overall resource utilization rate of the converged content distribution network.

This application relates to a bandwidth scheduling method, apparatus, computer device, storage medium, and program product. The method includes: determining the excess bandwidth of a node to be scheduled based on its cost bandwidth and current bandwidth; determining multiple associated nodes of the node to be scheduled, and determining the remaining bandwidth of each associated node based on its respective cost bandwidth and current bandwidth; determining the attribution information of the node to be scheduled and the attribution information of each associated node, and constructing a node relationship graph based on each attribution information; and generating a bandwidth scheduling path for the excess bandwidth based on the node relationship graph and the remaining bandwidth of each associated node. This method enables the scheduling of bandwidth resources.

This invention provides a method and apparatus for dynamically scheduling computing power in a high-bandwidth network within an intelligent computing center cloud platform, relating to the field of computing infrastructure technology. The method includes: a computing power main control management unit sending computing job metadata pushed by a computing job perception module to a computing power bandwidth scheduling unit; the computing power bandwidth scheduling unit determining first scheduling data for the computing job identifier based on the bandwidth requirement information and the priority information; the computing power bandwidth scheduling unit sending the first scheduling data to the GPU server indicated by the network topology information; and a link resource mapping engine sending second scheduling data to the switch indicated by the network topology information. This achieves dynamic adaptation between computing power running tasks and computing power bandwidth resources, effectively realizing a high-bandwidth network for computing power.

The invention relates to the technical field of geological monitoring, discloses a deep hole geological monitoring method and system based on cloud edge collaboration, and aims to solve the problem that an existing method is poor in data processing efficiency and reliability, and the scheme mainly comprises the following steps: collecting a multi-source sensor signal in a deep hole; transmitting a multi-source sensor signal to a private cloud side based on an anti-interference transmission layer; the private cloud side converts the differential signal into a standardized digital signal flow, and after real-time preprocessing is carried out on the standardized digital signal flow, the standardized digital signal flow is transmitted to a GPU cloud processing center based on bandwidth scheduling; the GPU cloud processing center generates a space-time alignment tensor and a geological monitoring task, and the geological monitoring task is submitted to the virtual machine for execution; and if the success probability of executing the geological monitoring task by the virtual machine is not greater than the probability threshold value, triggering an active restart protection process when the virtual machine runs to the maximum allowable time. The method improves the data processing efficiency and reliability, and is suitable for geological disaster early warning or engineering safety evaluation.

The invention discloses a bandwidth scheduling method and device, electronic equipment and a computer program product. The method relates to the field of artificial intelligence, and comprises the following steps: collecting flow sequences of M financial network points to obtain M flow sequences, each flow sequence comprising flow measurement values of each financial network point at continuous time points; performing modal decomposition on each flow sequence to obtain M groups of modal signals, and performing feature extraction on N groups of modal sub-signals in each group of modal signals to obtain M groups of sub-band features; and respectively inputting the M groups of sub-band features into a feature recognition model, processing to obtain M fusion features, determining scheduling strategies of the M financial websites based on the M fusion features, and after the scheduling strategies of the M financial websites are obtained, performing bandwidth scheduling on the M financial websites based on the scheduling strategies. Through the bandwidth scheduling method and device, the technical problem that the scheduling accuracy is low when bandwidth scheduling is carried out on the financial network in the prior art is solved.

The present application relates to the technical field of network scheduling. Provided in the embodiments of the present application are a network scheduling method and apparatus, a computer device, a storage medium and a program product, which can implement real-time bandwidth scheduling for cloud networks, and improve the bandwidth allocation quality of cloud host networks, and can further improve the accuracy, stability and reliability of cloud networks, thereby enhancing the network performance of the cloud networks. The method comprises: acquiring a target traffic bandwidth of a target tenant server (S110); acquiring network topology information of a network architecture where the target tenant server is located (S120); on the basis of the target traffic bandwidth and the network topology information, determining a traffic transmission path of the target tenant server (S130); on the basis of the traffic transmission path, determining a target cloud host server (S140); and controlling the target tenant server to access the target cloud host server (S150).

The invention relates to the technical field of communication, in particular to a mining deterministic transmission network slice bandwidth scheduling method and device and a medium thereof. The mining deterministic transmission network slice bandwidth scheduling method comprises the following steps of S1, performing network slicing on network element equipment according to a preset service requirement through a network management system, and initially allocating network slice bandwidths of all the network element equipment; s2, performing priority setting on all network slices based on service types; s3, monitoring the utilization rate of all network slices through a network management system; and S4, comparing the utilization rate of the network slices with a preset utilization rate threshold value of the network slices, and carrying out bandwidth dynamic adjustment on the network slices with high priorities. According to the mining deterministic transmission network slice bandwidth scheduling method, the slice width can be dynamically adjusted, and the slice bandwidth resource utilization rate is high.

Embodiments of the present application provide a network scheduling method and device, computer equipment, storage medium and program product, relate to the technical field of network scheduling, can carry out real-time bandwidth scheduling to cloud network, improve the bandwidth allocation quality of cloud host network, further can improve the accuracy, stability and reliability of cloud network, so that the network performance of cloud network can be improved. The method comprises: obtaining target traffic bandwidth of a target tenant server; obtaining network topology information of a network architecture in which the target tenant server is located; determining a traffic transmission path of the target tenant server based on the target traffic bandwidth and the network topology information; determining a target cloud host server according to the traffic transmission path; and controlling the target tenant server to access the target cloud host server.

This invention discloses an AI-based prediction-based dynamic bandwidth allocation system for universities across multiple scenarios, primarily relating to the field of local area network management technology. It includes: a multi-source data acquisition module for collecting multi-dimensional data and performing data cleaning, standardization, and tagging; a scenario-aware AI prediction module for constructing an AI prediction model fused with scenario tags based on the multi-dimensional data, outputting predicted bandwidth demand values ​​for each physical region within a specified future time period; a dynamic bandwidth scheduling module for generating elastic bandwidth allocation schemes for each region based on the predicted bandwidth demand values, combined with a bandwidth pool mechanism and multi-level priority scheduling logic; and an SDN controller execution module for real-time distribution and execution of the elastic bandwidth allocation schemes, dynamically adjusting the allocation strategy based on execution feedback. The beneficial effects of this invention are: it achieves accurate scenario-based bandwidth prediction for universities while improving resource utilization and ensuring the smooth operation of critical services.

The embodiment of the invention discloses a bandwidth scheduling method, electronic equipment and a computer readable storage medium, and belongs to the technical field of passive optical networks. The method comprises the following steps: dividing a target frame into a plurality of subframes according to a preset bandwidth requirement; wherein each subframe corresponds to a subframe configuration table and a high-priority entry configuration table; calculating the allocable bandwidth of the target frame according to the optical network acquisition information; determining the bandwidth entry priority of a target subframe according to the high priority entry configuration table, the subframe configuration table and the allocable bandwidth of the target subframe in the subframes, and sequentially carrying the bandwidth entries of the target subframe to a preset bandwidth mapping table according to the bandwidth entry priority of the target subframe; and under the condition that the target subframe is the last subframe of the target frame, transmitting all bandwidth entries of the target frame stored in the bandwidth mapping table to the optical network unit. According to the embodiment of the invention, the technical problem that the time delay of a broadband scheduling scheme in the related technology is too high is solved.

The invention discloses a college multi-scene bandwidth dynamic allocation system based on AI prediction, and mainly relates to the technical field of local area network management. Comprising a multi-source data acquisition module used for acquiring multi-dimensional data and carrying out cleaning, standardization and tagging processing on the data; the scene perception AI prediction module is used for constructing an AI prediction model fused with a scene label based on the multi-dimensional data and outputting a bandwidth demand prediction value of each physical region in a specified time period in the future; the dynamic bandwidth scheduling module is used for generating an elastic bandwidth allocation scheme of each region according to the bandwidth demand predicted value in combination with a bandwidth pool mechanism and a multi-level priority scheduling logic; and the SDN controller execution module issues and executes the elastic bandwidth allocation scheme in real time, and dynamically adjusts an allocation strategy according to execution feedback. The method has the beneficial effects that the resource utilization rate is improved while the college bandwidth is accurately predicted according to the scene, and the smoothness of key services is ensured.