50 results about "Bandwidth scheduling" patented technology

The invention discloses a machine room energy-saving operation and maintenance management method and system, and particularly relates to the technical field of machine room management. Computing resources are integrated in combination with a virtualization technology, virtual machine allocation is dynamically adjusted, migration flow is optimized by adopting an intelligent network bandwidth scheduling mechanism, and migration efficiency is improved; by combining a temperature and humidity control system and equipment operation temperature anomaly detection, the operation states of the air conditioner and the cooling equipment are dynamically optimized, energy consumption is reduced, early warning is performed based on the equipment operation temperature and the network load condition through a fault prediction model, equipment faults are prevented, and fuzzy logic control is adopted; based on the energy consumption efficiency and the fault prediction result, resource configuration is dynamically adjusted, the energy efficiency of the whole machine room is optimized, the utilization rate of computing resources is effectively improved, the influence of network migration on services is reduced, the energy consumption of the machine room is reduced, the equipment stability is improved, the management cost is optimized, and efficient, energy-saving and intelligent machine room operation and maintenance management is achieved.

The invention discloses an enterprise supply chain risk prediction method based on artificial intelligence, and relates to the technical field of supply chain risk management driven by artificial intelligence, and the method comprises the following steps: (a) dynamically obtaining sudden external event information in an internet unstructured data source through a heterogeneous intelligence collection network; (b) an event semantic distillation module is adopted to analyze external event information, and event ontology tags with industry correction parameters are generated; according to the enterprise supply chain risk prediction method based on artificial intelligence, through dynamic bandwidth scheduling and a multi-stage cleaning mechanism of a heterogeneous intelligence acquisition network, capture and high signal-to-noise ratio transmission of sudden unstructured events are realized, and the problem of information lag in the traditional technology is radically solved; and the event semantic distillation module is combined with dynamic correction of an industry sensitivity weight table, so that cross-industry risk misjudgment is eliminated, and the analysis accuracy of scenes such as transportation interruption of chips in the electronic manufacturing industry is improved.

The invention relates to the technical field of remote monitoring, in particular to a highway construction safety behavior intelligent remote monitoring recognition system which comprises a dispatching management module, a center detection module, a path screening module, an area monitoring module and a low-illumination monitoring module. According to the method, the priority transmission of key image data is realized by extracting the time stamp of the image data frame, the definition level and the area priority and combining the bandwidth dynamic scheduling, and the identification of the angle deviation of the camera is realized by identifying the static traffic facility, marking the image center point and recording the center track change. According to the method, the electronic fence and personnel track recognition are combined, a border crossing behavior path is extracted, the border crossing recognition continuity is enhanced, non-protection crossing detection of a dangerous area is achieved by extracting personnel distance changes and protection states, construction risk early warning coverage is optimized, and the night monitoring abnormity capture rate is increased through night light reflection track coherence and space comparison.

Large Language Model (LLM) driven proactive scheduling may be provided. First, a proactive feedback module may be used that gathers user requests and device feedback. Next, an instructive interpreter module may be used that receives the user requests and the device feedback and produces instructive prompts based on the user requests and the device feedback. Then a user-reinforced scheduling optimization module may be used that receives responses to the instructive prompts and continuously enhances bandwidth scheduling based on the receives responses.

The invention discloses a network bandwidth scheduling method and device, electronic equipment and a storage medium, and relates to the field of financial science and technology or other related fields, and the method comprises the steps: obtaining the cache region use conditions of N equipment interfaces on target network equipment in a target time period, and N is a positive integer; the cache utilization rates of the N network queues are calculated based on the cache region use conditions of the device interfaces, and each device interface corresponds to one network queue; a network bandwidth configuration strategy of the target network equipment is generated according to the cache utilization rate, and the network bandwidth configuration strategy comprises network bandwidth weights configured for the N equipment interfaces; and executing network bandwidth scheduling on the target network equipment according to the network bandwidth configuration strategy. Through application of the method and the device, the technical problem of service performance degradation caused by the fact that a traditional network bandwidth scheduling technology is not matched with flexible and changeable actual traffic in related technologies is solved.

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 cross-bandwidth scheduling method, apparatus, computer device, storage medium, and computer program product. The method includes: when a first device needs to adjust a service to a target service, determining a target partial bandwidth corresponding to the target service; the first device accessing a network access device using a target synchronization signal block; determining a second device other than the first device that accesses using the target synchronization signal block, and determining a reference frequency domain segment in the partial bandwidth where each second device is located; the reference frequency domain segment is a frequency domain segment in the partial bandwidth where the second device is located and the signal quality meets a preset condition; determining a target frequency domain segment overlapping between the target partial bandwidth and each reference frequency domain segment, and sending a scheduling instruction carrying the target frequency domain segment to the first device to instruct the first device to switch to the target partial bandwidth and perform resource scheduling in the target frequency domain segment in the target partial bandwidth. Using this method can perform resource scheduling more accurately.

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.

The embodiment of the invention provides a bandwidth scheduling method, which is applied to first network equipment comprising an output port. The flow sent to the AI training equipment connected with the output port by the output port comprises the AI training data. The output port is provided with a corresponding token bucket, and the token bucket is used for scheduling the flow of the output port. A first network device determines a first remaining token that has not been used in a token bucket. Further, the first network device determines a first bandwidth adjustment value corresponding to a preset threshold value according to the first residual token and the preset threshold value, and the first bandwidth adjustment value is used for adjusting the flow of the ingress port of the first network device. Wherein the input port is connected with a second network device. After the first network device determines the first bandwidth adjustment value, the first bandwidth adjustment value can be sent to the second network device, so that the source network device determines the bandwidth for sending traffic to the ingress port based on the first bandwidth adjustment value. According to the scheme, congestion of the outlet port can be avoided as far as possible.

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.