39 results about "Data latency" patented technology

The invention discloses a cloud-edge collaborative intelligent storage node dynamic deployment method and system. The method comprises the following steps: monitoring performance indexes such as edge node data traffic and storage resource state in real time; a deep learning algorithm combining time sequence analysis and an LSTM neural network is adopted to analyze traffic information, and a data access demand is predicted; edge nodes and cloud storage resource configuration are dynamically adjusted based on a prediction result, and an intelligent scheduling algorithm, a data cold and hot separation strategy and a self-adaptive fragmentation technology are introduced to allocate resources; the storage node layout is optimized in real time, and an optimal data distribution path is selected through a reinforcement learning strategy; data security and access control are realized by adopting end-to-end encryption, multi-level access control and block chain technologies. The system comprises a monitoring acquisition module, a prediction analysis module, a resource scheduling module, a path optimization module and a security control module. According to the method, the utilization efficiency of storage resources is improved, data delay is reduced, system stability and data security are enhanced, and the method is suitable for a cloud edge collaborative storage scene.

The invention relates to the technical field of power system communication, in particular to a protocol conversion and communication adaptation system for an optical storage and charging grid-connected device. Comprising a protocol conversion unit used for dynamically analyzing heterogeneous protocols of a photovoltaic inverter, an energy storage converter, a charging pile and power grid side equipment; a communication adaptation unit; an energy collaboration unit; a power grid interface unit; and a man-machine interaction unit. According to the method, the protocol mapping rule base is dynamically updated through the plug-in type architecture module and the machine learning algorithm, self-adaptive analysis of multiple heterogeneous protocols and variant protocols is achieved, the protocol analysis accuracy and generalization ability are improved, and the problem that a traditional static rule base is insufficient in adaptability to non-standard protocols is solved; according to the invention, the distributed edge computing architecture is adopted to construct the bidirectional communication link, so that the real-time performance and security of the communication link are improved, and the defects of high data delay and incomplete security mechanism in the traditional communication architecture are improved.

The invention belongs to the field of fault detection, and discloses a GIS partial discharge defect identification method and a related device, and the method comprises the steps: obtaining a GIS partial discharge signal through a terminal collection unit, and transmitting the GIS partial discharge signal to an edge calculation node; extracting features of the GIS partial discharge signal through the edge computing node to obtain a feature vector, and calling a partial discharge defect recognition model issued by the cloud computing center to obtain a defect recognition result; wherein the partial discharge defect identification model is obtained through the following steps: constructing a GIS digital twinborn body through a cloud computing center according to inherent attribute data and real-time operation data of a GIS, constructing a classifier model, and training based on the GIS digital twinborn body to obtain the partial discharge defect identification model. The problems that in an existing mode, the requirements for network bandwidth, transmission rate and data center processing capacity are high, time delay and stability of data are poor, and recognition timeliness and accuracy are low are solved, and the requirements for real-time performance, timeliness and accuracy of GIS partial discharge defect recognition are guaranteed.

The present invention relates to the technical field of crop growth monitoring, and specifically to a method and system for monitoring crop growth through images, comprising the following steps: deploying an unmanned aerial vehicle (UAV) to fly over the target paddy field, collecting image data, and transmitting the image data to the ground station in real time through data transmission to generate a preliminary image dataset; and cropping and correcting the preliminary image dataset. In the present invention, the use of a UAV for image collection avoids the problem of limited viewing angles of fixed ground cameras, and reduces data latency through real-time data transmission, enabling more timely monitoring. During the process of cropping and correcting the image data, angle deviation and background noise are eliminated, improving the accuracy of leaf area index calculation. The introduction of time series analysis enables dynamic monitoring of crop growth trends, making growth assessment no longer limited to a single time point, but forming a comparison of historical data, and improving the prediction ability of growth status.

A communication system incorporates a method and a computer program product that provide selecting and camping on primary band in idle mode in preparation for supporting an anticipated data connection for demanding application(s) to a network system. The communication system scans, using a radio frequency (RF) communication subsystem, available network node(s) to assess communication capacity. The communication system identifies a combination of a primary band and secondary band(s) of the available network node(s) that satisfies a communication demand requirement of data throughput, data latency, and / or data quality. The communication system selects and camps on the primary band in preparation for activation of the demanding application(s) and configuring the RF communication subsystem to use the secondary band(s) to operate in carrier aggregation and / or dual connection mode to satisfy the communication demand requirement in preparation for activation of the demanding application(s) and establishment of the data connection.

The invention relates to a flow management method and system of a multi-protocol industrial gateway. The method comprises the following steps: collecting time sequence characteristics of a plurality of time slices from a local buffer queue and a historical log of each protocol channel; loading an SDLSTM-ARIMA hybrid model and a fuzzy logic rule set, inputting each time sequence feature, outputting a flow prediction value of each channel in a next period, mapping the flow prediction value into an initial weight of each channel, setting a corresponding credit line through a DRR controller interface, and dynamically adjusting a minimum delay threshold and a congestion interval; the queue management unit updates parameters; the protocol transmit-receive units sequentially allocate bandwidths according to the dynamic credit line and issue messages from respective buffer queues; data packaging and reporting are carried out, and cloud publishing is carried out based on a preset transmission protocol; and downloading the model fine tuning parameters, updating the command and loading the command to a local industrial gateway system. According to the method, the problems of data delay and jitter in the scheduling process can be solved, and the scheduling efficiency is improved.

The invention discloses a data processing method based on hybrid modeling and a program product. The method comprises the following steps: constructing a new model by taking activation data of a bottom layer model as an input source; and customizing a data uploading process of the application model according to a business scene through a processing chain technology, and automatically scheduling a data uploading task. And according to the data uploading task, dynamically switching the new model to replace the underlying model for data uploading, and realizing loose coupling of data uploading and data extraction between the underlying model and the application model. According to the method, the effect that model data uploading and model data extraction do not interfere with each other is achieved in a hybrid modeling mode, so that the data delay time is shortened, and the data updating efficiency and the data updating stability of the data warehouse are remarkably improved by improving the system operation efficiency.

The invention discloses a communication method and device and a readable storage medium, relates to the technical field of communication, and aims to reduce data delay between terminals. The method comprises: selecting a first on-satellite UPF for a first terminal, the first on-satellite UPF being used for executing on-satellite direct communication between terminals; and configuring a data processing strategy for the first on-satellite UPF. According to the embodiment of the invention, the data delay between the terminals can be reduced.

The present application relates to a data synchronization method, apparatus, computer device, storage medium, and computer program product. The method includes: obtaining the current number of synchronization tasks in a first database; when the current number of synchronization tasks in the first database is greater than a first threshold, creating a second database based on the current number of synchronization tasks in the first database; synchronizing incremental data corresponding to the first number of synchronization tasks to the second database, and deleting the first number of synchronization tasks in the first database, wherein the difference between the current number and the first number is less than or equal to the first threshold; and synchronizing the incremental data corresponding to the synchronization tasks from the first database and the second database to a third database in parallel. This method can reduce data latency in synchronization tasks.

The invention discloses an electricity-carbon collaborative operation transaction platform of an electric power system, relates to the technical field of data management, and solves the technical problem of low data sharing efficiency caused by lack of a classification strategy and priority management based on an aging threshold in a hybrid data transmission sharing process. Data are divided into high timeliness and low timeliness, a transmission strategy is optimized in a targeted mode, key data transmission priorities such as a priority value is calculated in a weighted mode by combining fault influence duration, timeliness attenuation rate and broadband occupancy rate, real-time carbon price and the like are improved, fragment length is dynamically adjusted according to a network MTU, and carbon transaction data transmission delay is reduced through reverse-order offset and multi-channel transmission. Meanwhile, timestamps and serial numbers are added, outdated data packets are rejected, power and carbon market data coding rules are unified based on a cross-domain data dictionary, standard format specification storage is adopted, and the data fusion efficiency is improved.

The invention relates to the technical field of equipment detection, and discloses an equipment anomaly detection method, device, equipment, medium, program product and system, and the method comprises the steps: when an edge device monitors a local threat according to collected local data, and after the threat level exceeds a first preset threshold value, the local data is encrypted and then sent to a teacher model; the teacher model generates an encrypted soft label according to the encrypted local data, and sends the encrypted soft label to the student model; and the student model carries out model training based on the encrypted soft label and the local data, and carries out equipment anomaly detection after training is completed. By encrypting the local data, the teacher model and the student model can be trained based on the encrypted data, and the local data is always in an unexposed state, so that an edge cloud security protection mechanism is constructed, deep coupling of security domain detection is realized, data delay is reduced, and the accuracy and security of equipment anomaly detection are improved.

The application relates to the technical field of data accounting, in particular to an automatic data accounting method and system based on a rule engine, which comprises the following steps: obtaining a historical database based on a merchant, constructing a rule sample database for the rule engine through the historical database, and establishing rules and constructing a rule library according to the requirements of the merchant; evaluating the similarity of two rules in the rule library, and dividing the rule library into multiple rule sets; constructing an accounting database through the historical database and the rule sample database, obtaining a new rule through the accounting database, analyzing the new rule to determine a rule set, judging the data delay state of the new rule entering the rule engine and joining the rule library according to the rule set, and setting a data delay reaction window; evaluating the data delay performance degree based on the data delay reaction window, adjusting and iterating the rule set through the data delay performance degree until the data accounting is completed. The distributed accounting process of data is realized, and the automatic efficiency of the final data accounting is improved.

The utility model relates to an aluminum electrolysis cell two-level measurement mobile data acquisition vehicle based on a thermal infrared imager, which comprises a vehicle body, a data acquisition unit in communication connection with a background data center is arranged on the vehicle body, moving wheels are arranged at the bottom of the vehicle body, and an X-axis push rod is arranged at the top of the vehicle body; the action end of the X-axis push rod is connected with the fixed end of the Y-axis push rod, the action end of the Y-axis push rod is connected with the measuring drill rod, the thermal infrared imager and the shooting backboard are arranged on the side, close to the measuring drill rod fixing device, of the vehicle body, and the thermal infrared imager is in communication connection with the data collector; the X-axis push rod drives the Y-axis push rod and the measuring drill rod to move in the horizontal direction, and the Y-axis push rod drives the measuring drill rod to move in the vertical direction. The measuring drill rod is inserted into / pulled out of the electrolytic cell by simulating manual operation, and the thermal infrared imager is used for acquiring temperature distribution of the electrolyte and the molten aluminum solidified on the surface of the measuring drill rod, so that the liquid level heights of the electrolyte and the molten aluminum are determined, the accuracy and the real-time performance of data are improved, the delay of production process control caused by data delay is reduced, and the production efficiency is improved. The labor intensity is reduced.

The present invention relates to data processing technology and discloses a remote data synchronization method, comprising: extracting source data of a preset type from a first data center to obtain a target file; utilizing a pre-built traversal service to extract the file content and file structure in the target file; compressing the text content to obtain a compressed file, and encoding the text content using a message digest algorithm to obtain an encryption tag; utilizing an access token pre-generated by a second data center to transmit the encryption tag, the compressed file, and the text structure to the second data center. The present invention also proposes a remote data synchronization device, an electronic device, and a storage medium. The present invention can reduce data latency during remote information synchronization.

An instrumentation and measurement tool that provides a technological solution for precise data flow latency tracing within end-to-end data processing pipelines from ingestion of raw data through to consuming product systems. Cipher-coded date-time stamps for data field tagging replace numeric timestamps to eliminate data validation errors that can be triggered if numeric timestamps were used in data fields where character data is expected. The resulting latency metrics are systematically aggregated and presented through a dashboard, providing comprehensive insights into the performance of end-to-end data processing pipelines with adaptive monitoring and alerting capabilities.

The AI inference engine-based data time delay optimization control method of the application obtains historical service attribute labels, historical service processing data and to-be-inferred data flow of a target inference service, then constructs a semantic value evaluation model and a time delay budget allocation model to evaluate the semantic contribution degree of each to-be-inferred data, and allocates inference time delay budget and computing power channel access authority for each to-be-inferred data. The to-be-inferred data can be classified by combining the semantic contribution degree, the inference time delay budget and the computing power channel access authority, the priority of different to-be-inferred data is determined, and the corresponding execution channel is allocated based on the difference in priority, so as to avoid redundant service inference from occupying computing power resources, ensure that to-be-inferred data with high priority can obtain exclusive computing power resources for inference, ensure that the time delay meets the standard, and in addition, the semantic value evaluation model and the time delay budget allocation model can be updated in a closed loop based on the inference result and service feedback data, so as to ensure long-term adaptability and stability.

This invention specifically relates to a blockchain-based electricity trading method, encompassing the application of blockchain in the field of electricity trading technology, including: user identity and permission management; transaction matching and consolidation; smart contracts; and data transmission optimization. In this invention, a delay factor model is constructed based on spatial domain analysis, multi-dimensional risk quantification, and dynamic strategy adjustment to accurately address the data upload delay problem of smart meters. By focusing on physically adjacent meter groups through circular domains, and combining overlap and collision measurements to quantify congestion and failure risks, a neural network is used to predict delay evaluation coefficients, achieving precise optimization of upload time. This mechanism effectively disperses upload pressure during periods of high overlap, reduces data transmission failure rates, ensures timely on-chain uploading of electricity trading data, and avoids problems such as settlement delays and contract execution interruptions caused by data latency. This significantly improves the real-time performance and reliability of blockchain electricity trading, providing users with an efficient and stable trading experience.

This invention relates to the field of mobile communication technology, and in particular to a data transmission method and apparatus based on a special terminal. The method includes: pre-setting a unique tag for the special terminal through a Mobility Management Entity (MME); the special terminal initiating communication with the network side according to the unique tag and a new data transmission method; the network side recognizing the unique tag of the special terminal in the MAC header, reading the agreed-upon preset resources, reserving air interface resources for the special terminal in advance, and allocating a communication channel. The new data transmission method reduces the data transmission processing between the terminal side and the network side, thereby reducing data latency and signaling overhead during data transmission.

The application relates to the technical field of data management, and discloses a dynamic partitioning and priority scheduling method based on time series data, which comprises the following steps: collecting time series characteristics of an industrial data source through an edge gateway and structurally storing the time series characteristics in Redis, wherein the time series characteristics include a collection frequency, a historical peak period and a service priority; calculating a load index based on the time series characteristics, driving a distributed message system to perform dynamic partitioning adjustment of predictive expansion, accurate hotspot splitting and intelligent low-peak shrinkage; and realizing full-link data priority scheduling through production end routing isolation, Broker end resource tilting and consumption end thread pool isolation. The application realizes dynamic adaptation of distributed message system resources and industrial time series data load, guarantees the real-time performance of high-priority data, improves the integrity of data transmission and the system adaptability, and effectively solves the problems of poor load fluctuation adaptation, high-priority data delay and easy data loss in faults in the prior art.

The invention relates to the technical field of data accounting, in particular to an automatic data accounting method and system based on a rule engine, and the method comprises the steps: obtaining a historical database based on a commercial tenant, building a rule sample database as a rule engine through the historical database, building a rule according to the demand of the commercial tenant, and building a rule base; evaluating the similarity between every two rules in the rule base, and dividing the rule base into a plurality of rule sets; the method comprises the following steps: constructing an accounting database through a historical database and a rule sample database, obtaining a new rule through the accounting database, analyzing the new rule to determine an attribution rule set, judging a data delay state of the new rule entering a rule engine and adding into a rule base according to the attribution rule set, and setting a data delay response window; the data delay representation degree is evaluated based on the data delay reaction window, and the rule set is adjusted and iterated through the data delay representation degree until data accounting is completed. The distributed accounting process of data is realized, and the automation efficiency of final data accounting is improved.

The invention belongs to the technical field of report generation, and particularly relates to a financial data analysis report generation method, which comprises the following steps of: constructing a data access system with wide compatibility, acquiring data from a multivariate and heterogeneous data source of an enterprise by applying an automatic data interface technology, and generating a financial data analysis report. For various databases, whether a relational database or a non-relational database, adaptive data acquisition scripts are developed according to data structure characteristics of the databases, and the data acquisition efficiency is improved through common cooperation of multiple steps of multi-source data access, real-time data synchronization, standardized processing, data cleaning, analysis model construction and report generation. The problems of complicated data sources, non-uniform formats and data delay are solved, so that the difficulty of data integration is reduced, the latest financial condition of an enterprise is reflected through real-time enterprise data, and the timeliness of decision making is improved.

The present invention relates to a method for semi-synchronous caching data, belonging to the technical field of middleware, and includes the following steps: Write and run a distributed cache proxy layer service using a preset programming language, receive read and write command requests from application clients, parse the Key consistent hash value, and send it to the backend Redis shard nodes. The master instance parses the message packet, marks the write operation and records it in the AOF file. After the disk write is completed, the master instance sends an AOF file transfer command to the slave instance node, and the slave instance executes the receipt. After the master instance receives the receipt response, it updates the confirmation offset of the slave node and responds to the client. When the network latency is high, mark the data of the master and slave nodes as "out of sync" and automatically degrade to asynchronous replication. The present invention optimizes the implementation of master-slave semi-synchronization in Redis by self-developing the Redis kernel and using the asynchronous ack mechanism, improves the data reliability of single-point failures, and solves the problems of data latency and data consistency caused by the native Redis asynchronous replication mechanism.

The present invention provides a computing device for a streaming data processing method based on a many-core processor. The many-core processor includes multiple computing cores. The method includes: dividing the multiple computing cores into N computing core groups, wherein the N computing core groups execute different data processing methods; receiving data, such as images, videos, audio, or data transmitted by sensors; inputting the data into a corresponding computing core group in the N computing core groups to execute a data processing task; and outputting the processed data. The solution provided by the present invention can increase the data processing speed of the many-core processor while reducing the processor's energy consumption and data latency, thereby improving the overall computing efficiency of the many-core processor.

The invention provides an iOS mobile terminal-oriented data delay loading method and system based on a GraphQL protocol, and related equipment. The method comprises the following steps: receiving a stream segment load transmitted by a server based on a GraphQL protocol, and analyzing a causal fence identifier in the stream segment load; based on the causal fence identifier, establishing and maintaining a causal fence state for a key value corresponding to the stream segment in a standardized cache of a client; inputting the causal fence state into a user interface hydration engine of a client, and performing causal fence verification on fragments in a waiting queue in the user interface hydration engine; and when the causal fence verification meets a dependent closure, submitting a user interface update transaction of a corresponding segment by utilizing the user interface hydration engine.

An embodiment of the present application provides a resource processing method, apparatus, and medium, which are used to reduce data latency, improve channel resource utilization, and reduce channel resource waste. The method includes: a first device sends a beacon message on a beacon indication resource corresponding to a first resource, where the beacon message is used to indicate that the first resource is used by devices in a first user group, and all or part of the first resource cannot be used by other user groups; or, the first device does not send a beacon message on the beacon indication resource corresponding to the first resource, so that devices in other user groups determine that the first resource is not used by devices in the first user group, and all or part of the first resource can be temporarily used by devices in other user groups; where the first device belongs to the first user group, the first resource belongs to a first resource pool, and the first resource pool includes a plurality of periodic resources allocated for the first user group for sidelink SL communication, and each resource corresponds to a beacon indication resource.

The invention discloses a real-time data interaction method and device, electronic equipment and a storage medium, through the real-time data interaction method and device, efficient collection and sending of real-time operation data of related measuring points of a heat supply system are achieved in a broadcasting mode, and the stability of data receiving and the accuracy of decoding processing are guaranteed through physical connection of a line card; and then real-time uploading of the decoded data is realized through the wireless network module, so that intermediate links and delay factors in a data circulation process are reduced. The technical problems of long data acquisition period, low transmission efficiency, frequent manual operation and incapability of reflecting the running state of the heat supply system in time due to delayed data uploading in the data interaction of the existing DCS can be solved, and the purposes of improving the data real-time performance of the heat supply system and improving the real-time performance of the heat supply system are achieved. And the technical effects of dynamic regulation and control, fault early warning and energy efficiency optimization capability of the municipal administration department on the heat supply system are enhanced.

This application provides a data recovery method, system, and electronic device based on repeated reading, which can efficiently recover data using original read data, reduce read data latency, and improve service quality. The method includes: performing a regular read of the data to be recovered, and performing hardware decoding on the regular read result; if the regular read hardware decoding fails, repeatedly reading the data to be recovered, and performing hardware decoding on the repeated read result; if the repeated read hardware decoding fails, determining a corresponding soft information value for the data to be recovered based on the regular read result and the repeated read result; and performing software decoding on the data to be recovered based on the soft information value to obtain the recovered data. The system includes a regular read unit, a repeated read unit, and a repeated read software decoding module. The electronic device includes a memory, a processor, and a computer program stored in the memory for executing the data recovery method.

This invention relates to a combustible gas monitoring system based on 5G campus edge computing. The system includes: multiple gas collection terminals, multiple handheld inspection terminals, multiple location identification terminals, a 5G base station, a campus user plane gateway, and a campus edge computing server. The combustible gas monitoring system is deployed within a designated first campus and connected to the 5G core network. This invention improves the deployment flexibility of gas collection terminals, reduces data latency, and enables timely acquisition of real-time detection information from each monitoring point.

The present invention proposes a method for optimizing the loading of visual large-screen data based on a two-level cache mechanism, and particularly relates to a method for smooth data visualization in a multi-service concurrent request environment. The present invention is committed to solving the problem of how to load data and render charts on the interface fastest and improve the user experience of the data visualization large screen under the conditions of limited browser thread concurrency, multiple front-end display components, and high back-end data latency. By designing a mechanism of two-level data cache, default data display, and polling request cycle, when the component fails to request service data within a specified time period, it reads the "more" real default data and displays the service data requested with delay on the upper layer at a certain cycle.

This invention discloses a customer group operation method, apparatus, electronic device, and storage medium, relating to the field of internet data processing technology. The method includes: dynamically setting the number of shards and grouping user data into multiple independently executable micro-batch task units by assessing cluster size and resource status. A streaming engine with multiple execution nodes is used to adjust the micro-batch granularity in real time according to cluster load. Each execution node monitors resource status in real time, calculates a resource busyness coefficient based on the current number of micro-batch task units and estimated execution time, and dynamically allocates task volume accordingly. In the face of upstream tag data latency, the system automatically triggers a tiered degradation strategy, flexibly cutting non-core tasks, switching to offline tag snapshots, or implementing a fallback strategy based on the latency level and task priority, ensuring the continuity of core business. This invention effectively solves the problems of poor timeliness, low resource utilization, and lack of effective disaster recovery mechanisms in existing technologies.