1312 results about "Network conditions" patented technology

The invention discloses a cloud edge cooperative control method, which comprises the following steps: establishing a cloud edge cooperative architecture, collecting data by edge nodes, and selecting a corresponding data compression strategy to compress the data; generating an edge-cloud collaborative uploading data stream; the cooperative control layer executes adaptive load balancing based on a cloud-side node state, task characteristics and a network condition which are monitored in real time so as to realize task allocation and scheduling between the cloud and the side; the cloud receives the data stream transmitted by the edge node, decompresses and processes the compressed data according to the metadata information, completes the task and feeds back an execution result; a node performance prediction model is constructed by using system state monitoring information, a task allocation strategy and a resource allocation and data compression strategy are adjusted in real time according to a prediction result, and cloud-side collaborative optimization is realized. Efficient data transmission, flexible task scheduling and self-adaptive resource management are realized, and the performance of the system in a complex and changeable environment is comprehensively improved.

The invention relates to the technical field of front-end resources, in particular to an intelligent caching method and device for loading front-end resources on demand, equipment and a medium, and the method comprises the following steps: obtaining user behavior data, predicting an access page, identifying required resources, and constructing a resource dependency graph; calculating resource use frequency and importance, and determining a target resource; selecting a resource format and a compression mode according to the user equipment type; according to the resource dependency relationship graph, loading and caching target resources required by a next page possibly accessed by the user in advance; meanwhile, the caching strategy is dynamically adjusted based on the resource use frequency and the importance index; the method comprises the following steps: monitoring a network condition, dynamically adjusting a resource loading strategy, pre-loading resources before a user requests by using a resource dependency graph and a server pushing technology, and determining a target loading mode when the user accesses. Therefore, the problems that in the prior art, resource loading is low in efficiency, a caching strategy is rigid, environment adaptability is poor, user behavior analysis is insufficient, and performance optimization automation is lack are solved.

The invention discloses a real-time interactive digital human system supporting high concurrency and an implementation method thereof, and relates to the technical field of digital human interaction.The system comprises a model instance pool module used for loading the weight of a deep learning model to a shared memory area through the memory mapping technology; the multi-thread scheduling module is used for scheduling user requests by adopting a lock-free queue and a dynamic priority algorithm; the asynchronous pipeline processing module is composed of decoupled micro-services, and the modules are connected in series through asynchronous message queues; the client SDK is used for dynamically switching a rendering mode according to terminal hardware performance and network conditions; the elastic capacity expansion and contraction module is used for monitoring resource loads in real time and automatically adjusting the number of service instances; and the audio and video synchronization calibration module is used for ensuring that the synchronization error of the audio and video frames is lower than a preset threshold value through a timestamp alignment algorithm. According to the scheme, core challenges in a high-concurrency digital human interaction scene can be systematically solved, and innovative support is provided for large-scale real-time application.

A system for the temporal ordering of multi-channel data streams, comprising the following: a multi-channel data reception module configured to receive real-time data streams from multiple sources, extract temporal metadata, and detect discrepancies in timestamps; a time synchronization module configured to align data packets using timestamp normalization, adaptive buffering, and AI-based predictive modeling; an AI-powered predictive modeling module trained to estimate missing or delayed timestamps and to reorder out-of-order data packets based on learned patterns; an adaptive buffer module configured to dynamically adjust buffer sizes based on real-time data arrival rates and network conditions; an ordering and output processing module configured to reconstruct the correct order of the data packets and transmit them to a processing or analysis system; and a module for error detection and correction that is configured to detect inconsistencies in timestamps, transmission delays and missing data points, thus ensuring increased reliability of the ordered data sequence.

The invention relates to the technical field of circuit detection, discloses a power transmission line thermochromic wire clamp heating early warning method and system, effectively solves the problem of data acquisition distortion in a strong electromagnetic environment, and improves the accuracy of state evaluation through multi-source data fusion. The dynamically adjusted early warning model reduces the risk of false alarm and missing alarm caused by equipment aging, the intelligent decision support module shortens the fault handling response time, the data closed-loop mechanism ensures the reliability of the system in the whole life cycle, and the reliability of the system in the whole life cycle is improved through multi-sensor cooperative monitoring and edge calculation processing. And the influence of environmental factors on data acquisition is reduced. The two-channel transmission architecture guarantees the data transmission integrity under different network conditions, the CRC verification mechanism effectively recognizes and corrects transmission errors, a high-quality data basis is provided for a subsequent early warning model, the abnormal data recollection mechanism avoids data missing caused by single collection failure, and continuous and stable operation of the monitoring system is ensured.

The invention provides a network state monitoring and optimization processing method and device and a readable storage medium. The method comprises the steps of obtaining network state parameters through monitoring; determining data transmission parameters according to the network state parameters; determining the transmission priority of the target data according to the importance requirement and the real-time requirement of the target data to be transmitted; and based on the data transmission parameter and the transmission priority, a target path is adopted to carry out data transmission on the target data, and the target path is a preset main path or a standby path with the highest stability when the preset main path is unavailable. According to the method, the parameters can be adjusted in real time according to the network condition, the data transmission process can be optimized according to different service requirements, the capability of flexibly coping with unexpected conditions is achieved, and the data communication quality and the user experience are remarkably improved.

The invention discloses a remote centralized control distributed data processing and analysis method based on a JMS, and the method comprises the steps: achieving the message routing and resource scheduling through the real-time monitoring of the state of a system, reinforcement of learning decision, deep learning optimization and multi-dimensional message distribution; dynamically adjusting message flow rate and queue length based on real-time network conditions, node load and flow fluctuation; through edge node intelligent task scheduling, distributed collaboration of calculation and storage is realized; adaptive compression algorithm selection is carried out by using deep learning, and the consumption of message transmission bandwidth is reduced; non-tampering storage of messages is realized through a block chain technology; based on a container arrangement technology, dynamic expansion and contraction of computing resources are realized; and dynamic resource scheduling and optimization decision are realized by utilizing reinforcement learning and multi-dimensional monitoring data. According to the invention, the bottleneck problem of the traditional message transmission system is overcome, and the system can efficiently and reliably process mass data in a high-concurrency and high-throughput scene.

The embodiment of the invention provides a dynamic allocation method and device for AI reasoning tasks, and the method comprises the steps: monitoring the workload, memory availability, network delay, bandwidth and energy consumption of each computing node in a cloud edge cooperation system in real time, the computing node comprising a local edge device, an edge server and a cloud platform; according to the delay requirement, the calculation requirement and the data privacy requirement of the task and the real-time state of each calculation node, dynamically distributing the task to different calculation nodes; adjusting the complexity of an AI model used for executing the task according to the resource use condition of the computing node; and according to the historical performance data and the real-time network condition in the task execution process, optimizing a task allocation strategy.

The invention relates to a cloud side-end cooperative processing system based on a network computing technology. A cloud computing platform is used for storage of large-scale data and training of a deep learning model; the edge computing node module is used for receiving the data stream from the end side equipment and processing the data stream in real time; the end side equipment is used for collecting environmental data and primarily processing the environmental data, and the end side equipment comprises one or more of an unmanned aerial vehicle, an unmanned vehicle and an unmanned ship; the cloud edge-end cooperation module is used for efficient communication and calculation cooperation among the cloud, the edge and the end-side equipment; and the task scheduling and resource allocation module is used for scheduling and allocating calculation tasks in real time according to current task requirements, resource states and network conditions. According to the invention, the overall operation efficiency and real-time performance of the cloud side-end cooperative processing system can be improved, and the defects of the existing system in the aspects of processing capability and task scheduling are overcome.

The present invention discloses a method and system for intelligent switching of communication protocols for an omni-channel contact center, the method comprising the steps of: evaluating the performance of each communication protocol according to user needs and the current system status, selecting the optimal communication protocol and opening the corresponding communication service for the user; continuously monitoring the communication quality under the selected current communication protocol, and triggering the reselection of the communication protocol if it is detected that the communication quality is lower than expected; re-evaluating the performance of each communication protocol under the current system state to select the target communication protocol, and switching the current communication service from the current communication protocol to the target communication protocol. The present invention realizes smooth switching between different communication protocols, can intelligently identify and automatically select the optimal communication method, while maintaining the continuity and quality of the call unaffected. In addition, the present invention also supports dynamic adjustment of the communication method according to network conditions, ensuring that users can obtain the best communication experience regardless of the network environment.

The invention relates to the technical field of multi-path information processing, and provides a multi-path optimization method, device and system for network routing, and the method comprises the steps: obtaining network node information, obtaining a plurality of available paths based on the network node information, evaluating all available paths, and obtaining network bandwidth data and an initial weight; adjusting the initial weight to obtain an initial path weight and a path priority table, distributing and identifying data packets of network flow by using the path priority table, obtaining a flow data packet with a path identifier, and adjusting the initial path weight after obtaining a flow load log and network delay data based on the flow data packet; and generating a flow scheduling scheme to update the path priority table. Through obtaining network node information and utilizing a bandwidth evaluation algorithm, initial path evaluation reflecting network conditions is generated, and through real-time data feedback of a dynamic monitoring module, a flow scheduling scheme capable of carrying out adaptive adjustment at any time is generated, so that the defects of the prior art in the aspect of dynamic adaptability are improved.

The invention relates to the technical field of audio pushing optimization, and discloses an audio stream pushing crash prevention method and system, a storage medium and equipment, and the method comprises the steps: dynamically generating a format perception pre-detection thread based on a current audio stream format, and adjusting the priority and sampling frequency of the thread according to the audio bit depth and the sampling rate; multi-level intelligent buffer area management with sound quality priority is implemented, and dynamic adjustment of the size of a buffer area and adaptive switching of the buffer area are realized according to different audio formats and input source types; establishing a cross-brand equipment coordination framework, and setting a watchdog timer with preferential tone quality to perform timed monitoring so as to process response timeout; triggering an elegant degradation strategy of sound quality priority according to the resource availability score, and reducing the audio processing quality step by step to maintain the playing continuity; the key characteristics of each transmission protocol are identified and utilized, the transmission protocols are adaptively switched according to the network condition and the processing capability of brand equipment, and real high-quality and zero-interruption audio experience is brought to users.

The present invention provides systems and methods for cellular network performance monitoring and optimization, enabling SIM-based devices to dynamically adapt to changing network conditions for improved connectivity. The invention introduces a process that includes determining baseline path performance through detailed probing of network metrics, continuously assessing current path performance via real-time monitoring, and instructing the SIM to switch from its current connected mobile network carrier to an alternate carrier when predefined performance thresholds are not met. Switching instructions are securely delivered Over-The-Air (OTA) to the SIM, ensuring seamless transitions to the most efficient and reliable network path. The system leverages both active and passive application layer observations to optimize latency, throughput, and reliability while supporting diverse applications, including IoT devices, industrial systems, and consumer devices.

The invention relates to the technical field of network set top boxes, and discloses a firmware segmented loading method and device in the starting process of a network set top box. The method comprises the following steps: performing firmware division on the network set top box to obtain a firmware segment set and an inter-segment dependency relationship matrix; determining a real-time state vector of the starting state based on hardware sensor data of the network set top box; performing starting stage identification on the network set top box according to the real-time state vector to obtain a current starting stage identifier and a time sequence optimization condition parameter; carrying out loading decision and Markov state transition analysis on the firmware segment set based on the current starting stage identifier and the inter-segment dependency relationship matrix to obtain a loading action sequence; and carrying out target path loading on the firmware segment set according to the loading action sequence and the time sequence optimization condition parameters to obtain a loading execution result. According to the method, the firmware segments can be flexibly combined and dynamically scheduled according to actual requirements, and the loading efficiency and stability under different network conditions are ensured.

The invention relates to an office process automation data analysis method based on a symmetric encryption algorithm, and the technical scheme comprises the following steps: introducing an encryption strategy generator, and dynamically adjusting the parameters of the symmetric encryption algorithm including the key length and the encryption round number through the real-time analysis of the data communication content including the data sensitivity, the frequency and the data volume; constructing a self-adaptive optimization model, and adjusting an encryption strategy according to external conditions such as a network state, equipment computing power and user behaviors; fragmenting the data packet before transmission, and allocating different transmission paths according to current network conditions and security evaluation; constructing a dynamic data recombination module at a data receiving end, and verifying and recombining data when encrypted data packets of different paths arrive; a lightweight key negotiation protocol based on symmetric encryption is adopted, and a key is generated and negotiated immediately when two communication parties initiate data exchange; a secret key life cycle management mechanism is introduced, and the service life and the number of times of limitation are set for each secret key.

The invention discloses a data transmission method and device, equipment and a storage medium, and relates to the technical field of data transmission. The method comprises the following steps: preprocessing collected initial data to obtain data to be transmitted, and monitoring network quality in a data transmission process in real time to obtain a real-time network condition; compressing the to-be-transmitted data according to the data characteristics of the to-be-transmitted data and the real-time network condition to obtain candidate data; performing feature extraction on the candidate data according to data features to obtain target feature data; and determining a data transmission strategy according to the network topology structure, the data characteristics and the real-time network condition of the edge device, and transmitting the target characteristic data to the target device based on the data transmission strategy. According to the technical scheme, data compression, feature extraction and transmission strategy determination are dynamically carried out according to the real-time network condition, the data transmission problem caused by the unstable network environment can be reduced, and the data transmission efficiency and reliability are effectively improved.

The invention discloses a reliable communication system based on a publishing and subscribing mode in a satellite-ground weak network environment, and aims to solve the problems of high round-trip delay, limited link bandwidth, high instantaneous packet loss rate, easiness in blocking and switching influence of links and the like in a data transmission process between a low-orbit satellite and a ground station. A publishing and subscribing model is introduced into an application layer to realize service logic decoupling, deep fusion with an underlying enhanced QUIC transmission protocol is realized, and mechanisms such as message persistence, breakpoint resume, forward error correction and connection migration are combined, so that stable, orderly, complete and safe transmission of service data can still be ensured under the conditions of link instability, quality fluctuation and communication interruption, and the service data transmission efficiency is improved. And high availability and continuity of a satellite-ground communication task under a weak network condition are realized.

Various embodiments comprise a wireless communication network to dynamically manage network slices. The wireless communication network comprises a Network Slice Control Function (NSCF). The NSCF retrieves network slice Key Performance Indicators (KPIs) that indicate traffic patterns and network parameters related to a wireless network slice. The NSCF generates a prediction of network conditions for the wireless network slice based on the network slice KPIs. The NSCF updates one or more network slice parameters for the wireless network slice based on the prediction. The NSCF modifies the wireless network slice based on the one or more updated network slice parameters.

The invention discloses a high-frequency data remote transmission method and system, and the method comprises the steps: dynamically adjusting the collection frequency and mode according to environment conditions, and obtaining high-frequency data in real time; based on the data type and the transmission network state, a compression algorithm, a filtering mode and a coding strategy are automatically selected; the congestion condition of the transmission network is predicted through a built-in machine learning model, and a packaging strategy and transmission parameters are dynamically adjusted according to network conditions; in the data receiving process, the bit error rate in the transmission process is monitored in real time, abnormity in transmission is automatically detected, repair is carried out through an error correction algorithm, and if repair fails, the system automatically requests the data packet again; and the recovered high-frequency data is classified and stored according to the importance, real-time performance and storage cost of the data, and automatic storage strategy adjustment is realized in a remote database. According to the technical scheme, the high efficiency, reliability and safety of remote transmission of high-frequency data are improved.

The invention discloses a network optimization method based on an online conference, which relates to the technical field of real-time audio and video transmission, and comprises the following steps: in a transnational network, deploying monitoring probes at nodes participating in the online conference for monitoring network parameters such as network delay, bandwidth, packet loss rate and jitter in real time; the method comprises the following steps: processing network parameters and predicting abnormity by using a statistical analysis algorithm and a time sequence model to obtain network condition information, and then combining global network topology and using a reinforcement learning Q-Learning model and a graph neural network GNN topology prediction algorithm; according to the method, the network condition is monitored and predicted in real time, the optimal transmission path is output by using the reinforcement learning Q-Learning model and the GNN topology prediction algorithm, the bandwidth fluctuation is predicted through the LSTM, the packet loss rate is predicted based on the Bayesian network, the data transmission strategy is optimized, the network delay, the packet loss rate and the jitter are effectively reduced, and the network performance is improved. And the smoothness and the stability of the conference are improved.

The invention discloses an AI-based automatic connection and handshake protocol for a trusted data space connector. The AI-based automatic connection and handshake protocol comprises a data supply end connector, a data demand end connector and a platform operation end, the data supply end connector is used for collecting and preprocessing data; the demand end connector is used for receiving and processing data; the platform operation end is used for connection management, authority distribution and security auditing; the method has the beneficial effects that through automatic connection and an intelligent handshake protocol, manual intervention is reduced, and the data circulation cost is reduced; multi-factor authentication, dynamic encryption and privacy protection technologies are adopted to ensure the safety of the whole life cycle of the data; aI and machine learning technologies are introduced, so that the system can intelligently select an optimal strategy according to real-time network conditions and data features; interoperation and data sharing among different data spaces are realized, and circulation and value mining of data elements are promoted.

An autonomous job scheduling system for distributed ledger technology is disclosed, leveraging photonic quantum computing and generative artificial intelligence (AI). The system collects transactional and operational data from various nodes within a distributed ledger network, focusing on transaction types, sizes, and priorities. This data is filtered for urgency and resource intensity, analyzed against real-time network conditions and business rules to ascertain job execution parameters. A photonic quantum computing system processes these parameters to optimize job scheduling strategies, including quantum annealing and simulations. The AI engine generates dynamic smart contracts deployed to distributed ledgers by a job orchestration engine. The system monitors job execution, gathering performance data and providing feedback for real-time adjustments. The job orchestration engine updates job scheduling in response to these adjustments, enhancing the efficiency and responsiveness of the blockchain network.

The invention discloses an extensible content interactive display method and system based on streaming media playing, the extensible content interactive display method based on streaming media playing belongs to the field of streaming media, and the method comprises the following steps: S1, dynamically adjusting the resolution and code rate of content under different network conditions; dynamic self-adaptive stream transmission is realized; s2, directly acquiring data through the nearest edge node when the content is requested, and caching high-frequency interaction data at the edge node; s3, the user request is routed to the optimal node; s4, adopting a predictive buffering and preloading mechanism; s5, predicting user interaction behaviors by using a deep reinforcement learning algorithm; and S6, adopting H.265, and combining the characteristics of low delay and high reliability of the QUIC protocol to carry out transmission. The extensible content interactive display system based on streaming media playing comprises a user behavior analysis module, a content management and distribution module, an interactive prediction and recommendation module, a preloading and cache management module, a network transmission and optimization module and the like.

The invention provides a fault simulation test method and device, electronic equipment and a storage medium. In the fault simulation test method, when a test instruction sent by a user is received, test parameters are configured based on the test instruction; wherein the test parameters comprise a test type, a fault parameter and a test target. And based on the test type and the fault parameter, configuring a network rule through a flow controller, and generating a fault simulation scene. And injecting the fault simulation scene into the test target, and carrying out performance test on the test target. And monitoring performance indexes of the test target in the test process, and generating a test report of the test target. Therefore, by utilizing the method provided by the invention, different types of network delays or faults, such as delay increase, packet loss and connection interruption, can be accurately injected into the target server, so that the stability and the performance of software or service under bad network conditions are effectively evaluated, and the flexibility and the expandability of the system are ensured at the same time.

A distributed system and method for compressing and restoring data across edge computing devices and cloud infrastructure is disclosed. The system preprocesses raw data at edge computing devices, compresses the data into latent space vectors using distributed encoders within a variational autoencoder spanning edge and cloud components, decompresses the vectors using decoders, and processes them through a resource-aware neural upsampler to generate enhanced reconstructed outputs. The system dynamically adapts compression based on available computing resources and network conditions, while enabling secure distributed processing through homomorphic operations on compressed data. Edge-cloud coordination layers manage data flow, compression parameters, and workload distribution, while maintaining system reliability through intelligent failover handling and resource optimization.

The invention discloses a data transmission method and device, equipment, a storage medium and a product, and relates to the technical field of information security, and the method comprises the steps: obtaining an original data packet and a current network state; embedding and packaging the original data packet to obtain a to-be-transmitted data packet; predicting according to the current network state and the to-be-transmitted data packet through the data transmission model to obtain a target encapsulation level, a target traffic shaping parameter and a sending window parameter; sending the to-be-transmitted data packet based on the target encapsulation level, the target traffic shaping parameter and the sending window parameter; according to the method, the current data packet is embedded and packaged, and the network state and the application requirement of the packaged data packet are analyzed in real time according to the data transmission model to obtain the target packaging level, the target traffic shaping parameter and the sending window parameter, so that the optimal packaging strategy, the traffic shaping parameter and the congestion control strategy are dynamically selected; flexible adjustment can be performed according to actual network conditions, and communication performance and resource utilization rate are improved.

The invention relates to the technical field related to intelligent production control, in particular to a coal mine production equipment control method and system based on remote body interaction, and the method comprises the steps: coal mine production equipment uploads parameters, analyzes the state, configures a twin architecture, and carries out local decision abnormity early warning. A remote end is communicated with an interaction device, biological characteristics are reflected as a pose instruction, time delay compensation and track deviation prediction are embedded, a multi-mode feedback unit triggers smooth control according to the pose instruction, and tactile feedback is enhanced in combination with a vibration spectrum. The technical problems that the network condition of the underground coal mine environment is poor, obvious communication delay exists in remote control, operation instruction lagging exists, and the response speed and operation safety of equipment are affected are solved, dynamic time delay is predicted through the LSTM network, track deviation is compensated, the real-time performance and stability of remote control are improved, accurate execution of instructions is ensured, and the service life of the equipment is prolonged. And the remote operation efficiency and reliability of the coal mine equipment are improved through high-precision pose control and real-time compensation.

The invention provides a network flow regulation and control system and method and a storage medium, and relates to the technical field of network communication. The network traffic regulation and control system comprises: an information collection unit, which is used for obtaining historical traffic data of all media plane network elements connected with a control plane network element and a topological relation of the media plane network elements; the AI model updating unit is used for updating the traffic regulation and control model of the control plane network element according to the historical traffic data and the topological relation, and the strategy generation unit is used for obtaining a traffic distribution strategy of the control plane network element; and the strategy execution unit is used for dynamically adjusting the media traffic of each media plane network element according to the traffic distribution strategy. According to the method, the network data is collected and analyzed in real time, and dynamic updating of the AI model is combined, so that dynamic regulation and control of the network traffic are realized, the method can quickly adapt to changes of network conditions, and the flexibility and efficiency of traffic regulation and control are improved.

The invention discloses a data stream transmission method and device, equipment and a storage medium. The method is applied to a remote USB control system, comprises a remote control end and each near-end device, and comprises the following steps: obtaining a control instruction of the remote control end, and determining a target near-end device and a corresponding device level based on the control instruction; when the equipment level is a class of non-optimal equipment, determining a target bandwidth corresponding to the target near-end equipment, and determining a bandwidth sufficiency condition according to the target bandwidth; and carrying out data stream transmission between the remote control end and the target near-end equipment according to the bandwidth sufficient condition. By clearly dividing device levels, data stream transmission resources can be more accurately allocated to different types of devices, key devices are ensured to obtain priority guarantee, target bandwidth is determined and bandwidth sufficiency is evaluated for a type of non-optimal devices, a more appropriate transmission strategy can be formulated according to actual network conditions and device requirements, and the transmission efficiency is improved. The transmission problem caused by insufficient bandwidth is reduced, and the transmission stability and smoothness are improved.

The invention discloses an efficient image transmission method based on multiple channels, and the method comprises the following steps: carrying out the fragmentation of a to-be-transmitted image, and cutting the image into a plurality of data blocks; adjusting the fragment size of the image according to the current network condition; during transmission, data blocks are distributed to different channels by identifying a network interface, and each channel independently transmits a part of fragments; a check code is added to each fragment, and whether the received data fragments are complete or not is verified through the check codes; in the data rendering process, the received complete frame is preferentially rendered, and the recombined complete image data is managed by using the cache pool, so that smooth connection between transmission and rendering is ensured. According to the invention, the image data are fragmented and transmitted concurrently on different network channels, so that the network bandwidth can be fully utilized, and the overall transmission speed is improved. The sizes of the fragments are dynamically adjusted, so that the transmission effect can be optimized under different network conditions, and the transmission delay is reduced.