385 results about "Network delay" patented technology

The invention discloses a seamless switching method and system for a high-speed terminal of a ground-non-ground convergence network based on trajectory prediction and resource pre-reservation, and belongs to the technical field of space-ground convergence communication. The core of the method is that a switching area is accurately judged through bidirectional motion prediction of a terminal and an NTN node; a dynamic switching window is calculated in a self-adaptive mode by combining factors such as terminal speed and network time delay; intelligently selecting an optimal target link by using an AI enabled link scoring model; and cooperative pre-reservation and uplink and downlink synchronization of resources are completed before the window. The method has the advantages that the problem of failure of traditional RSRP judgment in an NTN dynamic environment is solved, the switching success rate and prediction accuracy in a high-speed moving scene are remarkably improved, the service interruption time and signaling overhead are greatly reduced, the continuity and reliability of communication are effectively guaranteed, and the method is suitable for large-scale popularization and application. The method is suitable for high-dynamic service scenes such as intelligent network connection vehicles and unmanned aerial vehicles in a 6G network.

The invention discloses a cross-regional computing power resource collaborative allocation method based on computing power centers, and relates to the technical field of computing power resource scheduling and optimizing.The cross-regional computing power resource collaborative allocation method comprises the steps that real-time load data, historical task execution data and network delay data of all computing power centers are collected, and a regional load feature database is constructed; predicting the load demand of each computing power center in a future time window by using a long short-term memory network model to generate a load prediction value; calculating a resource gap coefficient and a resource margin coefficient of each region according to the load prediction value and the current resource capacity, identifying a resource insufficient region and a resource surplus region, and generating a resource collaborative matching matrix between the regions; and optimizing and solving the cross-regional task allocation scheme by adopting an improved genetic algorithm to generate an optimal resource allocation strategy, and allocating the to-be-processed task to a corresponding computing power center according to the optimal resource allocation strategy. According to the method, the cooperative utilization rate and the distribution efficiency of the computing power resources in the cross-regional scene are effectively improved.

The invention discloses a storage and calculation separation key value storage delay optimization method based on prediction driving, and aims to solve the problems of performance bottleneck and high tail delay caused by passive management and high network delay in a key value storage system in a storage and calculation separation scene. The method comprises the following steps: time load prediction: deploying a time sequence prediction model at a client, and predicting a future read-write request based on a historical access sequence; active cache prefetching: according to the predicted read request, actively preloading hotspot data from a server side to a client side for caching so as to improve the cache hit rate and hide network delay; active write-in optimization: according to the predicted write request, executing maintenance at a server side through predictive pre-insertion and active node splitting, and moving high index structure adjustment overhead out of a key request path to eliminate a write delay peak; and structure sensing batch synchronization: pre-fragmenting a local write buffer by using a server index top layer model of a client cache, and combining multiple independent remote insertion operations into one efficient batch update to reduce data synchronization overhead. Compared with an existing passive management system, the characteristics of model prediction and active cooperation are fully utilized, and the average delay and the tail delay of the system are reduced.

The invention relates to the technical field of cloud computing, and particularly provides a data cache prefetching method and device, a storage medium and a program product. According to the method, file access characteristics representing file access preferences of a user are obtained based on historical access data of the user, a target file meeting a cache prefetching strategy is determined based on the file access characteristics, and the target file is cached and prefetched. By dynamically analyzing the historical access data of the user, the system can adjust the cache content in real time, actively load the data possibly required by the user and ensure that the high-frequency access data is always available, and the mechanism not only improves the data access speed, but also remarkably reduces the influence caused by network delay.

The invention discloses a large model deployment method based on heterogeneous resource scheduling and multi-model collaborative reasoning, and relates to the field of artificial intelligence and server system deployment. Comprising the following steps of: 1, calculating a deployment score of a target model by utilizing a deployment scoring function according to a GPU video memory residual rate, a CPU load, network delay and a current task quantity of each node through a heterogeneous resource sensing scheduler, and selecting a node with the highest score of the target model to load or reuse the target model; a cache index key is generated, and whether key value KV pairs supporting multiplexing of the target model exist or not is inquired; step 3, if the cache is hit, skipping a forward propagation stage, and directly decoding based on a cache result, otherwise, executing complete forward reasoning and writing the result into the cache; 4, based on a plurality of user requests, performing fusion according to user priorities, model weights, reasoning costs and cue word lengths to generate execution sorting weights, and scheduling execution models in batches according to the weights; and 5, returning the model response to the user, and releasing or updating node state information.

The invention discloses a dual-channel adaptive network stability testing method and system, and belongs to the technical field of computer network testing. The system adopts a dual-channel asynchronous communication architecture in which a control channel and a data channel are physically separated, instructions and state information are transmitted through an independent TCP control channel, and high-speed test data streams are transmitted through a UDP or TCP data channel. The method comprises the following steps: dynamically and adaptively adjusting a timeout parameter based on real-time network delay detection; nanosecond constant interval packet sending control is realized by using a high-precision monotonic clock source and busy waiting compensation mechanism; a packet loss detection, positioning and ACK confirmation mechanism based on the serial number is realized in an application layer; and real-time statistical display and idle detection automatic termination are realized through multi-thread parallel processing. According to the invention, the precision, the stability and the adaptive capability of network testing are remarkably improved, and the method is suitable for long-time stability testing in various scenes such as a high-speed Ethernet, a satellite link, an industrial Internet of Things gateway and the like.

The invention discloses a distributed file backup method for a sonar database system, which belongs to the technical field of sonar data processing and comprises the following steps: acquiring file data containing underwater acoustic signal data from the sonar database system; fragmenting the file data to generate data blocks and dynamically adjusting the sizes of the data blocks; generating a unique identifier for the data block based on the content hash value and the metadata; selecting distributed storage nodes based on availability, storage capacity, network delay and geographical distribution factors; the transmission data block uses an encryption protocol; updating the storage position and state of the backup metadata record; periodically verifying the integrity and availability of the backup data; executing a data recovery process to recover the original file data; the dynamically adjusted backup policy is based on real-time operation requirements and data importance levels. According to the method, through distributed storage and dynamic optimization, the backup efficiency, the data security and the system reliability are improved, and the method is suitable for sonar data management in an underwater detection system.

The application relates to a service scheduling and deployment method for Internet of Things edge computing node resources, which is realized based on an Internet of Things edge computing system. The system comprises a cloud data center, a convergence layer core network and a plurality of access layer switch networks connected in sequence. Each access layer switch network is in communication connection with a plurality of edge computing nodes, and each edge computing node is in communication connection with a plurality of data acquisition terminals. The application comprehensively considers the current running state of the edge computing system, network delay problems and running results after deployment, and performs service scheduling and deployment of Internet of Things edge computing node resources on each real-time data stream computing application. The application is suitable for the decision environment of the real-time computing task load and bandwidth dynamic change of the Internet of Things edge computing node, realizes global optimization from the system level, takes into account the single node load capacity, and realizes the optimal scheme and application planning and deployment decision suggestion of the long-period stable operation and real-time task flexible scheduling strategy.

The invention belongs to the field of artificial intelligence and energy power system cross control, and particularly relates to a coal-fired unit fused salt combined frequency modulation control method and device based on deep reinforcement learning. According to the method, a deep reinforcement learning agent model is constructed, and boiler fuel quantity, steam turbine valve position, fused salt heat charging and discharging power and pump starting and stopping signals are dynamically output based on state space vectors; and tracking precision, thermal stress, emission and coal consumption indexes are fused through a multi-target reward function, and strategy autonomous optimization is realized by adopting a double-Q network, experience playback and target network delay updating mechanism. After deployment, the boiler, the steam turbine and the molten salt unit can be coordinated on line, power space-time decoupling and closed-loop cooperation are achieved, on the premise that main steam parameter stability and equipment safety are guaranteed, the frequency modulation response speed and precision are remarkably improved, the thermal fatigue risk is reduced, and the unit economy and the power grid adaptability are enhanced. And a flexible adaptive adjustment capability is provided for a high-proportion new energy power system.

The invention provides a message sorting method and device, electronic equipment and a program product, original messages are obtained through a distribution thread pool, the messages of the same business process are distributed to the same to-be-sorted queue, a working thread of the sorting thread pool reads the messages and stores the messages in a thread local cache set, the sendability is judged based on the dependency relationship of the messages in the business process, and the message sorting efficiency is improved. The messages meeting the conditions are sent to the subscription queue, and the messages not meeting the conditions are reserved in the cache. According to the mechanism, the problem of disorder of messages of the same service caused by multiple switches and network delay of message middleware is effectively solved, and data inconsistency and service abnormity are avoided; unified sorting logic replaces repeated development of subscribers, so that the system complexity is reduced; through thread pool division, local cache storage and a cache strategy of messages which do not meet conditions, the interaction overhead is reduced, the message orderliness and low delay requirements are considered in a high-frequency transaction scene, and the processing throughput, the real-time performance and the resource utilization rate under high concurrency are improved.

The invention discloses a vehicle-mounted distributed data storage and management method for an intelligent vehicle, which comprises the following steps: in a dynamic election mode, acquiring performance parameters of each node by a default main storage node, calculating a comprehensive score, electing a main storage node and an alternative storage node according to the comprehensive score, and taking the rest as slave storage nodes; the main storage node formulates a differential fragmentation storage strategy and a network QoS strategy according to the data multi-dimensional label and distributes the strategies; each node stores collected data in a local designated area according to a strategy, and data aggregation and preprocessing in the nodes are completed; the alternative storage node and the slave storage node converge the preprocessed data to the main storage node at different priorities according to a preset rule; and the main and alternative storage nodes periodically synchronize data. According to the method, the distributed architecture is combined with the intelligent fragmentation, the single-point bottleneck is avoided, the data is stored and processed nearby, the network delay is effectively reduced, and the storage and network resource utilization efficiency is improved.

The invention relates to the technical field of heat supply network metering supervision, and discloses a heat supply network metering data supervision system based on edge calculation. The system comprises an edge data acquisition module, a metering task management module, an edge resource scheduling module and a heat supply network supervision execution module. The edge data acquisition module acquires original data from a heat supply network metering sensor in real time, and sends the original data to the metering task management module after verification and format conversion; the latter receives the data, generates and stores a metering task record according to the type and the supervision rule, and updates the state to be to-be-processed; the edge resource scheduling module queries a to-be-processed task, monitors the CPU utilization rate, the memory occupancy rate and the network delay of an edge node, determines an execution sequence in combination with the number of tasks and generates a resource allocation scheme; and the heat supply network supervision execution module activates a corresponding node, obtains a task record, executes data analysis and supervision logic processing, and stores a result. The system optimizes data processing and resource configuration by means of edge computing, and adapts to heat supply network metering data supervision requirements.

The invention discloses a Web end video monitoring distributed decoding method and system, and belongs to the technical field of network video playing. The method comprises the following steps of: actively initiating WebSocket connection by a browser end through a local loopback address port (127.0. 0.1: 19022), and detecting whether a distributed decoding program is installed in a user terminal or not; calling a local FFmpeg library by a distributed decoding program, decoding a video stream in real time by utilizing a terminal CPU (Central Processing Unit), and converting decoded video key frames into an image format originally supported by a browser frame by frame through OpenCV; the distributed decoding program packages binary data of each frame of image and an address identifier of the binary data into a WebSocket message, the WebSocket message is actively pushed to the browser, and the browser refreshes and displays the WebSocket message in a specified area of a page in real time according to the address identifier; according to the method, zero-plug-in, low-delay, cross-platform, safe and controllable Web end video decoding is realized, the server load and the network delay are remarkably reduced, and the user experience and the system compatibility are improved.

The invention provides a TSN time synchronization method based on dynamic jitter compensation and double-clock domain collaboration, which comprises the following steps: in a single clock domain, carrying out real-time analysis on a time difference of a synchronization message and dynamically compensating clock jitter so as to establish a high-precision local synchronization reference; based on a local synchronization reference, performing time information interaction and weighted fusion with at least one other clock domain to generate system-level global reference time, and calibrating a local clock to realize time collaboration across the clock domains; predicting a future change trend of the network delay, and pre-adjusting a dynamic compensation and / or time information interaction strategy according to a prediction result; dynamic compensation, time coordination and pre-adjustment are mutually coupled and have a synergistic effect, so that the time synchronization precision of the system is maintained in a predetermined target range, clock jitter in a single clock domain is effectively inhibited, the synchronization precision is controlled within 20ns, and the strict requirements of the fields of industrial control, automatic driving and the like on high-precision synchronization within 20ns are met.

The invention provides an intelligent control method and system for a body-equipped robot based on man-machine interaction data, and relates to the technical field of medical robots, and the method comprises the steps: building a 5G network two-way transmission channel between a control end and a surgical robot end; through a 5G network two-way transmission channel, synchronously transmitting two types of data streams between the control end and the surgical robot end, namely a control instruction data stream generated by the control end and a surgical image data stream collected by the surgical robot end; in the transmission process of the two types of data streams, real-time network time delay is continuously monitored, whether the current network time delay exceeds a preset time delay threshold value or not is judged, and the preset time delay threshold value can be dynamically corrected according to the network state; and when it is judged that the current network delay exceeds the preset delay threshold, dynamically deploying a plurality of network probes on the 5G network two-way transmission channel. According to the invention, the real-time performance, the accuracy and the safety of the remote operation can be ensured.

The invention relates to the technical field of information security, and discloses a signature verification system based on a digital certificate. The system comprises a certificate state acquisition module, a distributed verification network module, a local verification agent module and a zero-knowledge verification engine module. According to the invention, most of certificate state verification requests are locally processed by a user by constructing a distributed verification network and cooperating with a local cache and incremental synchronization mechanism, so that the real-time dependence on a centralized online certificate state protocol responder is greatly reduced; the verification performance bottleneck caused by network delay or overhigh load of the center node is effectively overcome, and the processing efficiency of the signature verification service and the service reliability of the whole system are remarkably improved. A zero-knowledge proof verification protocol is introduced, so that when remote verification is necessary, a user does not need to expose a specific serial number of a certificate to be verified to a verification node, the leakage risk of a user service behavior track is fundamentally eradicated, and stronger privacy protection capability is provided.

The invention discloses a 4K multi-frame-rate YUV422 low-delay collaborative coding and decoding method, which relates to the technical field of video coding and decoding, and comprises the following steps of: configuring coding and decoding device parameters, establishing network connection, and setting a multi-frame-rate range and a buffer area; acquiring a 4K YUV422 original frame sequence from a video source and temporarily storing the 4K YUV422 original frame sequence; analyzing the difference and texture change between the current frame and the previous frame, and calculating the comprehensive content complexity; dynamically selecting an optimal target frame rate according to the complexity value and the network delay; the codec exchanges a frame rate switching command through a control channel and realizes synchronization, adjusts a compression parameter according to a selected frame rate, and generates a bit stream; and periodically exchanging network state information while transmitting the coded data. According to the invention, by introducing a dynamic frame rate collaborative adjustment mechanism based on content complexity, adaptive matching of coding parameters, scene contents and network states can be realized, and the problem that the stability of video image quality cannot be ensured while low delay is maintained in the prior art is solved.

The invention relates to the technical field of software quality assurance, and discloses an internet-based software engineering automation test system, which comprises a test environment perception module, a test intelligent arrangement module and a test execution and optimization module, a server resource state, a network delay parameter and a code structure feature are collected in real time through an environment dynamic sensing module, a multi-dimensional environment adaptation degree evaluation model is constructed, and when it is detected that the environment adaptation degree is lower than a threshold value, container resource expansion and network strategy adjustment are automatically triggered; establishing a mapping relation between multi-level defect features and code modules through a defect root positioning system, searching an optimal diagnosis scheme in a strategy space by applying an improved particle swarm algorithm, and accurately positioning a fault point to a source code line number; finally, closed-loop control of test environment self-adaption, test path self-correction and defect positioning self-optimization is realized, and the accuracy of a test result and the fault repair efficiency are improved.

A receiver (110), a transmitter (120), a method, a computer program and a computer program product are disclosed. The receiver (110) in a network (100) for receiving a first constrained application protocol, CoAP, message, the receiver (110) receives, from a transmitter (120) in the network (100), the first CoAP message, the first CoAP message comprising a modified header field indicating a time indication value, wherein the time indication value is generated by the transmitter (120), and evaluates network latency or network load based on the time indication value. A transmitter, methods, computer programs and a computer readable storage medium is also disclosed.

A system for synchronizing and spatializing media, comprising client device and server device. A method for operation includes: tracking the real-time spatial coordinates of both devices via wireless sensors; synchronizing media playback using a timestamp-based protocol that compensates for network latency and clock offset; and applying directional audio filters, such as Head-Related Transfer Functions (HRTF), on the client device to render audio appearing to originate from server device's physical location. The method is further characterized by compensating for acoustic propagation and signal processing delays to ensure accurate spatiotemporal alignment. The system may be enhanced by a multimodal Al configured to perform operations such as real-time voice-preserving translation and the generation of synchronized, spatialized haptic feedback based on semantic event markers.

The invention discloses an e-commerce data intelligent processing method and system based on dynamic flow optimization. The method comprises the following steps: acquiring and analyzing multi-platform e-commerce data, and converting the multi-platform e-commerce data into a standardized format; constructing a matching rule by adopting a decision tree algorithm, and performing classification and priority marking on the data; the data flow is dynamically scheduled based on the priority, so that the high-priority data is executed preferentially; data are processed through parallel nodes, performance indexes such as network delay and throughput are monitored in real time, and data stream processing efficiency is optimized in combination with a dynamic scheduling algorithm. The system correspondingly comprises a data standardization module, a rule matching module, a dynamic marking module, a parallel processing module and a monitoring scheduling module, efficient and self-adaptive processing of the multi-source e-commerce data is achieved, and the data processing real-time performance and the system throughput are remarkably improved.

The invention discloses a distributed sequential logic conflict resolution method for a distributed control system, which relates to the technical field of automatic control, and can accurately calculate the queuing retention time length of an instruction in a network by acquiring the real-time load and identifier of each network node in an instruction transmission path, thereby improving the accuracy of the queuing retention time length of the instruction. The local clock of the controller is subjected to high-precision correction by combining the basic transmission delay of the link, so that the real sequential relationship of the instruction is restored, and the interference of clock asynchronization and network delay fluctuation in the distributed system on sequential judgment is fundamentally eliminated; meanwhile, on the basis of a real-time working condition self-adaptive physical constraint model, the theoretical duration needed by equipment state change is quantified, the corrected clock difference value and the theoretical duration are dynamically matched, causal instructions can be effectively distinguished from the physical level, and the accuracy and reliability of conflict resolution are remarkably improved.

The application discloses a kind of air-ground integrated mobile core network deployment method, device, terminal and medium, by constructing air-ground integrated network architecture of mobile edge computing, deployment mobile core network, with minimum service delay as target, the objective function of the mobile core network is established, the optimal solution of the objective function is obtained, and the deployment set of the mobile core network is obtained.Therefore, the embodiment of the present application can realize the fusion of the data layer of the air platform Mesh network and the ground Mesh network;Avoid the problem of unstable network performance caused by the switching of air platform node movement;While guaranteeing network delay, it can effectively reduce the average data flow establishment delay, improve the practicability of air-ground integrated network.

The invention belongs to the technical field of civil airport digitization and informatization in the civil aviation industry, and discloses an airport production data access method and system based on multi-level cache. The method comprises the following steps: a terminal responds to an interface event, constructs a local buffer interface event and query interface name combination key, and constructs a query interface name and query parameter combination key; judging whether the event time of the local buffer interface event is smaller than the retrieved buffer timestamp or not; determining specific nodes corresponding to the distributed cache region in the terminal clustering group; judging whether the event time of the local buffer interface event is smaller than the retrieved data timestamp or not; judging whether the identifier of a certain service interface is encrypted or not, and finding out a certain interface mapping relation which can be matched; and traversal of the region set needing to create the copy is completed. According to the invention, cross-regional data access is reduced, network delay is reduced, and the efficiency of data access in the region is improved.

The embodiment of the invention provides a method for evaluating network bandwidth and computing equipment. The method comprises: transmitting data packets of a plurality of streams, the plurality of streams being transmitted through one of a plurality of channels, the plurality of channels corresponding to a plurality of different receiving devices; receiving feedback information of the plurality of channels to obtain receiving time corresponding to the data packets; and offset processing is carried out on the receiving time corresponding to the data packets transmitted by other channels except the specified channel in the plurality of channels, so that the receiving time is aligned with the receiving time corresponding to the data packets transmitted by the specified channel, wherein the offset is determined according to the difference between the network delay of the channel to which the corresponding data packet belongs and the network delay of the specified channel; and evaluating the network bandwidth based on the offset reception time. By using the method, the network bandwidth can be accurately and uniformly evaluated at the sending end, so that the available bandwidth of the multiple channel data streams can be uniformly distributed, and mutual competition among the multiple channel data streams is avoided.

The invention relates to a page loading method and device, electronic equipment and a storage medium, and the method comprises the steps: responding to an access request for a target domain name, and if the target domain name is a preset domain name, intercepting the routing transmission of the access request to a source server corresponding to the target domain name; taking a page rendering resource corresponding to the preset domain name stored in a local resource library as a target resource related to the target domain name; rendering by using the target resource to obtain a target page; and displaying the target page. According to the method, the page loading is completed through the local resources without depending on network connection, so that the problems of slow page loading, untimely response and the like caused by network delay or instability can be effectively avoided, and the page loading efficiency and the user experience are remarkably improved. In addition, due to the fact that resources do not need to be loaded through a network, occupation of bandwidth can be effectively reduced, and the access pressure of the source server is reduced.

The invention provides a network traffic intelligent scheduling method and related equipment thereof. The method comprises the following steps: acquiring traffic data of a target terminal; carrying out classification identification processing on the traffic data, and determining a classification result; constructing a traffic optimization model based on the classification result; performing optimization processing on the traffic data through the traffic optimization model, and determining an optimization result; and adjusting and scheduling the network configuration corresponding to the flow data based on the optimization result. Through the steps of the method, identification and modeling of traffic of different service types can be realized, and an optimal scheduling scheme is generated in combination with a multi-objective optimization algorithm, so that dynamic resource allocation and adaptive scheduling are realized in a complex network environment, the network delay and packet loss rate are reduced, and the bandwidth utilization rate and the service quality of services are improved.

The invention belongs to the technical field of network security protection, and discloses a malicious behavior bypass interception system based on flow analysis and detection, a rule engine quickly matches known attacks based on a dynamic feature library, such as SQL injection, common port scanning, federated learning model combined multi-node cooperative training, and flow time, behavior and content features are combined to realize the flow analysis and detection of malicious behaviors. Unknown threats such as 0day vulnerability variants and low-frequency hidden attacks are accurately captured; in an enterprise mixed service traffic environment, missed judgment of traditional static detection on unknown attacks can be avoided, false alarms caused by data limitation of a single model can be reduced, energy consumption of operation and maintenance personnel for processing invalid alarms is reduced, core assets are prevented from being damaged by novel attacks, and comprehensiveness and reliability of network protection are remarkably improved; a bypass deployment mode is adopted, traffic is obtained through network TAP equipment or traffic mirror images, a service main forwarding link does not need to be intervened, and network delay and single-point failure risks introduced by traditional series deployment are avoided.

The application discloses a data processing method, device and system, and relates to the technical field of communication. The method comprises the following steps: a first device receives a first data packet from a second device; when the first data packet is an important packet, a first packet loss rate is configured for the first data packet, and the first packet loss rate is lower than a packet loss rate of a non-important packet; and the first data packet is processed according to the first packet loss rate. According to the method, the important packet is processed according to the packet loss rate which is lower than that of the non-important packet, so that the loss frequency of the important packet can be reduced. Since the important packet refers to a data packet whose loss will trigger a timeout retransmission, the loss frequency of the timeout retransmission can be reduced when the data packet is lost, and therefore, the influence of the packet loss on network delay is reduced.

The invention discloses a flow gateway vertical calling method and device, and relates to the technical field of computers. A specific embodiment of the method comprises the following steps: in response to a received call request sent by a client, analyzing target domain name information from the call request; determining a target machine room where the gateway is located, obtaining a first mapping relationship between a virtual address corresponding to the target machine room and the domain name information, and querying a target virtual address corresponding to the target domain name information according to the first mapping relationship; and querying one or more target service instances corresponding to the target virtual address according to a second mapping relationship between the virtual address corresponding to the target machine room and the one or more service instances, thereby sending the calling request to any one of the one or more target service instances. According to the embodiment, the vertical calling of the gateway is realized by configuring the virtual address of the machine room, the network delay and the cross-machine-room communication cost are reduced, the flow processing efficiency is improved, and the system stability is improved.