112results about How to "Avoid performance bottlenecks" patented technology

The invention provides a big data platform scheduling task and data collaborative smooth migration method and system, and relates to the technical field of big data, and the method comprises the steps: constructing a digital twin environment of a target system, collecting task operation state data of a source system, extracting task features through a deep neural network, and carrying out the clustering and grouping. And deploying the task group to a digital twin environment, analyzing a task association relationship and a resource competition relationship based on a graph neural network, and generating a task stability score in combination with a task operation index. And constructing a migration risk prediction model to perform quantitative evaluation on the migration risk, and determining a migration priority and an execution sequence according to the quantitative evaluation. And making corresponding resource configuration, data synchronization and fault recovery plans for each task group, carrying out migration drilling in a digital twinning environment, and optimizing a migration scheme by utilizing a reinforcement learning algorithm. The migration risk can be effectively reduced, the smoothness and stability of the migration process are guaranteed, and the migration efficiency is improved.

The invention relates to the technical field of big data storage, in particular to a storage control method and device based on big data. The method comprises the following steps: acquiring an original data stream and application demand information; performing data dynamic correlation analysis on the original data flow according to the application demand information to obtain a dynamic update data correlation graph; performing feature vector generation on the dynamic update data association graph to obtain a data feature vector; performing intelligent quality evaluation on the data feature vector to obtain a data quality label; performing timeliness evaluation according to the data feature vector, and performing access popularity evaluation to obtain a timeliness score and an access popularity score; and acquiring system resource load condition information. The storage resource utilization rate, the data access performance and the overall efficiency of the system are improved by solving the limitation of a traditional method in the aspects of static data management and resource allocation.

The invention discloses a personalized recommendation system based on semantic analysis, and relates to the technical field of personalized recommendation systems.The personalized recommendation system comprises a data acquisition module, a dynamic situational semantic modeling module and a recommendation engine module, the data acquisition module transmits acquired user behavior data and situational data to the dynamic situational semantic modeling module, and the dynamic situational semantic modeling module transmits the acquired user behavior data and situational data to the recommendation engine module; the dynamic situational semantic modeling module extracts sequence features of user behavior data through a behavior context analyzer, generates context embedding through a situational semantic embedding network, completes cross-modal semantic alignment of multi-modal data through a multi-modal fusion layer, and generates multi-level semantic embedding features. According to the method, the dynamic situational semantic modeling module is designed, the semantic alignment function of the situation and the behavior is achieved, the problem that a traditional recommendation system is insufficient in situation data utilization is solved, the adaptability of the recommendation result to the dynamic situation is enhanced, and the method is suitable for dynamically changing user demand scenes.

The invention discloses a method and a system for realizing mine communication signal improvement based on edge computing, and relates to the technical field of mine communication signal improvement, and the method comprises the following steps: integrating a real-time monitoring system on each edge node, so as to continuously detect the fluctuation of communication flow and data request quantity, the real-time monitoring system identifies a potential communication peak period by collecting real-time data and generates an early warning signal to notify a network administrator or automatically trigger a load management program. According to the invention, through the real-time monitoring and early warning system on the edge node, active monitoring and peak prediction of mine communication are realized, the overload risk caused by traffic surge is reduced, and the stability of data transmission is ensured. And intelligent scheduling and dynamic resource allocation are combined, so that efficient execution of tasks under high load is ensured, and node overload is prevented. A self-adaptive load balancing and feedback mechanism enables the system to dynamically adjust distribution, quickly respond to a bottleneck and improve self-adaptability and stability.

The invention provides a log analysis adaptive optimization method and system based on swarm intelligence, and relates to the technical field of log analysis, and the method comprises the steps: obtaining a database log, and carrying out the feature extraction to generate a multi-dimensional feature matrix; constructing a hierarchical analysis network and deploying an agent analysis unit cluster with a self-learning capability; the agent analysis unit executes an analysis task through a feature recognition module, a parallel computing engine and a decision optimizer; constructing a multi-target evaluation model based on the performance evaluation indexes; and generating an optimization strategy set by adopting a self-adaptive evolution model and updating the optimization strategy set to the analysis network. According to the invention, the accuracy and efficiency of log analysis are improved, and the self-adaptive capability of the system is enhanced.

The invention provides a DETR-based 3D target detection and tracking method. The method comprises the steps of obtaining a point cloud data stream of continuous frames from an LIDER camera; original point cloud data of continuous frames are converted into regular voxel grids, and high-dimensional video features of the regular voxel grids are extracted; a group of 4D Tubelet Query is learned, and a time self-attention module and a space cross attention module are utilized to perform modeling on dynamic space-time characteristics of video clips so as to enhance the characterization capability of the dynamic space-time characteristics; and finally, performing bounding box prediction on each Tubelet Query by the model, and measuring the difference between a true value and a predicted value by using set-to-set loss to realize end-to-end learning of a multi-target tracking task. According to the method, the Tubelet is designed, the information in the space-time dimension is deeply mined and integrated, and a multi-target tracking task is simplified into a detection task, so that the unification of the detection task and the tracking task is realized, and the serious dependence of traditional multi-target tracking on a frame-level detector is reduced.

The invention discloses a quantum key encryption communication method and system based on a virtual private network, relates to the technical field of data encryption transmission, and solves the technical problems that the existing quantum key online distribution is covered by an OKD network, the key providing capability and the key generation rate are far lower than the data transmission speed of a modern network, and the performance bottleneck exists. According to the method, the data of the virtual private network is transmitted and encrypted by taking online distribution of the quantum key as a main part and pre-charging as an auxiliary part; the data is encrypted by the online distributed quantum key or the pre-charged quantum key, so that the data security can be improved, and the performance bottleneck of an online distribution mode can be avoided; according to the application, when the key supply gap is made up in the pre-charging mode, the quantum key surplus in the key demand gap before the time range corresponding to the key supply gap and closest to the key supply gap is preferentially selected, and when pre-charging is carried out through the selected quantum key, due to the fact that the time from generation to use is short, the leakage risk can be greatly reduced.

The invention discloses a micro-service-based enterprise software system construction method and device, and relates to the technical field of enterprise software system construction, and the method comprises the steps: carrying out the micro-service division of an initial software system according to enterprise demand information and micro-service boundary information, obtaining an independent micro-service system, and carrying out the evaluation of the independent micro-service system, determining communication architecture information between the independent micro-service systems according to the micro-service configuration information, evaluating the independent micro-service systems to obtain a micro-service configuration influence index, acquiring the micro-service configuration information, evaluating the independent micro-service systems to obtain the micro-service configuration influence index, and determining the communication architecture information between the independent micro-service systems according to the micro-service configuration information. The micro-service architecture is evaluated and optimized through the micro-service configuration influence index and the micro-service independence index, and through quantitative evaluation and the influence index, the micro-service architecture can be judged and adjusted in time, the system design is optimized, and potential performance bottleneck and system excessive dependence are avoided.

The invention discloses a character string data read optimization method based on a B + tree and a learning index. A learning index generated based on a machine learning (ML) model focuses on integer data of a fixed size, but is lack of consideration for character strings of variable lengths and is poor in performance in character string data. In order to solve the problem, the invention provides a character string slicing method which can convert a character string with a variable length into an integer with a fixed size for prediction and extract a common prefix from a character string key to reduce a model fitting error. According to the method, the characteristics of character string data are fully considered, complex multi-dimensional linear regression is simplified into one-dimensional linear regression, and the model calculation overhead is reduced. Besides, the invention provides a self-adaptive strategy to select a proper index to manage the calculation cost, the method for dynamically selecting the index nodes can utilize the advantages of the two index types to the maximum extent, and the calculation overhead is effectively reduced while the index efficiency is ensured.

The invention discloses an industrial equipment data intelligent management method based on a big data algorithm. The method comprises the following steps: acquiring operation data of industrial equipment from a plurality of data sources; the missing part in the operation data is filled based on a data filling algorithm; performing format conversion and standardization processing on the multi-source heterogeneous data; positive and negative samples are balanced by adopting a resampling technology in a model training process; and carrying out large-scale data processing by utilizing a distributed computing framework. The industrial equipment data management method based on the big data algorithm is high in accuracy, high in real-time performance, simpler in data processing and high in data processing upper limit.

The invention relates to a database operation instruction execution method and device, computer equipment, a computer readable storage medium and a computer program product. The method comprises the following steps: receiving a database operation instruction; the database operation instruction is used for executing data operation on a distributed database; the distributed database stores data in a distributed table through a plurality of fragments; splitting the database operation instruction to obtain a plurality of subtasks; and according to the dependency relationship between the sub-tasks and the task attributes corresponding to the sub-tasks, executing the sub-tasks on the fragments corresponding to the sub-tasks. By adopting the method, the operation and maintenance cost can be reduced.

The invention provides a server device control method and device and a medium. The server device control method comprises the steps that a sensor is used for collecting operation data, automatic modeling is carried out to determine a resource allocation scheme, and resource allocation is controlled. Collecting data after resource allocation, dividing a task queue, matching a server, and dividing sub-tasks; acquiring subtask execution information data; controlling the plurality of servers to execute tasks according to a preset speed, and acquiring environment information and data processing temperature; the processing speed is adjusted in real time by combining task execution information data, environment data and data processing temperature; and evaluating the completion degree after task processing is completed, and judging whether processing is continued or not. According to the method, the resource allocation and task processing speed can be optimized, the task processing quality and efficiency of the server are improved, and the running stability and reliability of the server are ensured.

The invention discloses a multi-bus decoupling distributed embedded hardware rendering architecture, system and method, and relates to the technical field of ultra-high-definition video hardware processing, and the key points of the technical scheme are that the architecture comprises a multi-bus decoupling module which comprises a plurality of hardware buses which are physically isolated from one another, each hardware bus is an exclusive hardware transmission link bearing a single-type manufacturing task; the modular processing unit is an independent hardware board card and is integrated with an external signal input port, an upstream bus signal input port and a downstream bus signal output port; the plurality of modular processing units are cascaded in sequence through a hardware bus in the multi-bus decoupling module to form a distributed assembly line rendering link; when the modular processing units are newly added, the signal processing capability and the rendering synthesis capability are linearly improved along with the increase of the number of the modular processing units. According to the invention, the problem of performance bottleneck of the traditional architecture in processing 4K / 8K ultra-high-definition and multichannel rendering is fundamentally solved.

The invention provides a method, a system, equipment and a medium for realizing online viewing of an original style of an Excel file, and belongs to the technical field of online file processing, the method comprises the following steps: a front-end Web page receives the Excel file uploaded by a user, stores the Excel file in a rear-end server and records stored file information; the Excel file is read, an xlsx.js library and an excel.js library are used for analysis, and analysis results are integrated; missing cell filling and style information conversion are carried out on the analyzed Excel file, cells with merging attributes in the Excel file are marked, and a format capable of being recognized by a data grid editor is obtained; and rendering a table consistent with the style of the original Excel file on a front-end Web page based on a format which can be identified by the data grid editor. The problem that a traditional online Excel viewing tool cannot completely reserve original file style information is solved, and the user experience is improved.

The invention discloses a QUIC protocol secure transmission method based on hierarchical encryption, and the method comprises the steps: collecting control message data, sensor data and video image data, and adding feature parameters to the data; introducing an XGBoost decision tree model, and training the XGBoost decision tree model by using the data added with the characteristic parameters to obtain a trained XGBoost decision tree model; dividing data input into the model into control message data, sensor data and video image data by using the trained XGBoost decision tree model; the control message data is classified as a high-level data layer, the sensor data and the video image data are classified as a secondary data layer, and the data sending end encrypts the high-level data layer and the secondary data layer respectively to obtain encrypted data streams; in combination with the QUIC protocol, the data sending end encapsulates and integrates the encrypted data streams into the QUIC encrypted data packets, and completes the secure transmission of the data, thereby achieving the improvement of the encryption efficiency and overall performance of the QUIC protocol.

The invention discloses a page rendering method and device, and relates to the technical field of front ends. A specific embodiment of the method comprises the following steps: in response to a page access request, dividing page contents of a to-be-accessed page into a plurality of floors, and grouping the plurality of floors to obtain at least one data group; in response to the view rendering request, acquiring a view number corresponding to a to-be-rendered view, and performing odd-even judgment on the view number; under the condition that the view number is an odd number, using the first card to obtain a data set of a sequence number corresponding to the view number, and performing view rendering based on a first page container corresponding to the first card; and under the condition that the view numbers are even numbers, acquiring a data set of a sequence number corresponding to the view numbers by using the second card, and performing view rendering based on a second page container corresponding to the second card. According to the embodiment, the memory consumed by page rendering is saved, the performance bottleneck of the APP is not triggered, and display abnormalities such as blank screen and lagging are avoided.

The invention provides an operator fusion mechanism distribution method and system for a vector quantization large language model, and the method comprises the following steps: obtaining layout data which comprises a dequantization data layout and a layout needed by a calculation kernel; calculating the number of data shuffling times based on the layout data, comparing the number of data shuffling times with a preset threshold value to dynamically respond to a decision mechanism, and when the number of data shuffling times is smaller than the preset threshold value, adopting a first decision mechanism which at least comprises a register level operator fusion mechanism; and when the number of data shuffling times is greater than or equal to a preset threshold value, adopting a second decision mechanism which at least comprises a shared memory level operator fusion mechanism. According to the operator fusion mechanism allocation method and system for the vector quantization large language model, the problems of bandwidth bottleneck and delay caused by frequent transmission of data between a shared memory and a register are solved, and therefore more efficient dequantization and calculation fusion are achieved.

The invention relates to the technical field of power acquisition terminal data storage, and discloses a data hybrid storage method and device and computer equipment, which are applied to a memory database, and the method comprises the following steps: when electric energy meter reading data is written into a main database of a power acquisition terminal, receiving a data change notification sent by the main database; recording the meter reading data into a data cache by adopting a key value mode based on the data change notification; and preferentially querying the corresponding meter reading data in the data cache based on a preset data retrieval requirement, and if the corresponding meter reading data is not queried, switching to the main database to continue data retrieval. According to the method, a large amount of data is prevented from simultaneously accessing the main database at the same moment, so that the load of the main database is reduced, load balancing is realized, the memory database is preferentially queried during data retrieval, and the main database is switched to retrieve when the memory database cannot be queried, so that the access frequency of the main database is greatly reduced, and the data retrieval efficiency is improved. And the performance bottleneck during batch data query of the relational database is solved.

The invention relates to a load balancing method and device in a heterogeneous computing power network, computer equipment and a readable storage medium. The method comprises the following steps: receiving a computing task submitted by a client; classifying the calculation tasks to obtain task categories; and according to the task category and the real-time resource information of each computing node in the heterogeneous computing power network, allocating the computing task to a target computing node in each computing node. According to the method, the resource condition of each computing node is monitored in real time, so that task allocation can be dynamically performed according to the actual resource condition of each computing node and the task demand of the computing task, efficient utilization of resources of each computing node can be ensured, idle or overload of the resources is avoided, the overall resource utilization rate is remarkably increased, and the resource utilization rate is increased. And the performance bottleneck caused by unbalanced resource utilization in the traditional method is solved.

The invention relates to the technical field of network communication management, and discloses a system and a method for establishing a VPN (Virtual Private Network) data flow acceleration model, and the method comprises the following steps: distributing an IP (Internet Protocol) address for access equipment through a DHCP (Dynamic Host Configuration Protocol), and obtaining the IP address of a message queue telemetry transport protocol (MQTT) server; and the access device registers identity information through the MQTT and stores the identity information. And performing batch management on the access equipment according to the subscription mechanism of the MQTT server, wherein the management content comprises equipment configuration, operation state, terminal access and batch upgrading. Meanwhile, VPN data features and historical data features of the access device are obtained and stored, a VPN data flow classification model is established based on the features, and the VPN features of the device are substituted into the model to obtain a classification result. And finally, obtaining real-time performance data of a network link, determining an effective link according to a demand relationship between the real-time data and a classification result, and selecting an optimal path transmission mechanism based on the effective link so as to optimize the transmission performance of the VPN data stream.

The invention relates to the technical field of big data, and discloses a rule matching method and device based on a graph theory, computer equipment and a storage medium. The method comprises the steps of obtaining a to-be-matched rule; constructing a directed acyclic graph according to the rule to be matched; traversing the directed acyclic graph, and matching according to a plurality of preset matching algorithms to obtain a matching result; and performing code response or returning specified content according to the matching result. By implementing the method provided by the invention, the dynamic management and optimization of the rule can be realized; the performance bottleneck of a traditional rule engine in processing large-scale data and complex rules is overcome.

The invention relates to the technical field of data processing, in particular to an order data processing method and system based on a block chain. The method comprises the following steps: acquiring a multi-source order data set; performing transaction address analysis on the multi-source order data set to generate order transaction address data; order processing server construction is carried out on the multi-source order data through the order transaction address data, and order processing distribution server data is generated; order processing access frequency analysis is carried out on the multi-source order data set through order processing distribution server data, and order processing access frequency data is generated; and performing order screening on the multi-source order data set based on the order processing access frequency data to generate high-frequency order access data and low-frequency order access data. According to the invention, through optimization of multi-source data integration, order access frequency analysis, transaction synchronization and channel optimization, the reliability and efficiency of order transaction are improved.

The invention provides an omnibearing power grid network equipment scanning system and method, and the system comprises a plurality of distributed scanning modules, each module communicates with scanned equipment through a network interface, and employs a scanning engine to automatically recognize and connect the network equipment, collect configuration information, operation states and safety parameters, and generate a safety evaluation report. And a scanning result is stored in the storage unit and is transmitted to the central control module through the communication unit. The central control module manages and coordinates the operation of the plurality of distributed scanning modules. And the data processing module is connected with the central control module, collects and analyzes the scanning data from the plurality of distributed scanning modules, detects potential security threats and network performance problems, and generates an overall security and performance evaluation report. The user interface module is connected with the central control module and the data processing module and provides an interface for a user to access scanning results and evaluation reports. According to the system, efficient network security monitoring and evaluation are realized through comprehensive management and analysis.

The invention discloses a hospital-oriented software and hardware collaborative medical data hierarchical processing method and device. According to the method, in a hospital intranet, statistics is carried out on the flow of medical data flow based on a source IP and a target IP two-tuple through a hardware side, a large flow and a small flow of the medical data flow are distinguished according to a dynamic threshold value, and an identifier is added to the large flow. The hardware flow table module carries out short-period quintuple statistics on the identified large-flow medical data message and reports a result with a timestamp; and the software flow table module performs long-period statistics on the small-flow medical data messages, synchronously fuses results of the two parties through timestamps, generates a full-amount medical network flow table, and further optimizes a dynamic threshold value and a processing strategy. According to the invention, through layered flow establishment and double-cycle cooperation, high performance of hardware processing and flexible large capacity of software processing are both considered, the utilization rate of hospital network resources and the consistency of flow data are effectively improved, and accurate support can be provided for hospital intranet monitoring, service awareness, safety protection and strategy automation.

The invention discloses a semi-supervised adaptive unstructured scene segmentation method, and relates to the technical field of computer vision. The method comprises the following steps: acquiring label-free image data of an unstructured scene; inputting the weakly enhanced image into a teacher model to generate a first prediction result; inputting the strong enhancement image into the student model to generate a second prediction result; calculating the JS divergence between the first prediction result and the second prediction result, and dynamically adjusting the attenuation coefficient of the index moving average according to the JS divergence; updating teacher model parameters according to the adjusted index moving average attenuation coefficient to obtain an unstructured scene segmentation model; and inputting a to-be-predicted unstructured scene image into the trained unstructured scene segmentation model, and outputting an unstructured scene segmentation result. According to the method, the teacher model weight updating rate is reduced in the model divergence significant stage such as the initial training stage or the difficult sample processing stage so as to suppress noise propagation, and the prediction precision of unstructured scene segmentation is effectively improved.

The embodiment of the invention provides a node graph rendering method and related equipment. The node graph rendering method comprises the following steps: monitoring the number of nodes contained in a node graph; if the number of the nodes does not exceed a preset node number threshold value, using a real-time rendering mode to render the node graph; and if the number of the nodes exceeds a preset node number threshold value, rendering the node graph by using a background rendering mode. According to the technical scheme, the number of the nodes in the node graph is monitored, real-time rendering is forbidden when the number of the nodes exceeds the preset node number threshold value, background rendering is used instead, the final layout of all the nodes is calculated through a background program, and after calculation is completed, the layouts of all the nodes are rendered into the page at a time, so that the layout of all the nodes is rendered into the page at a time. According to the method, frequent calculation and rendering are reduced, and the performance bottleneck of real-time rendering is avoided, so that the page loading speed and the user experience are remarkably improved.

A data storage encryption method, device and electronic device relate to the field of data processing. In the method, respond to the encryption request of the user, and obtain the data to be encrypted; use the preset public key to encrypt the data to be encrypted to obtain the basic encrypted data; determine the encryption node for responding to the encryption request among multiple spare nodes; obtain the node public key corresponding to each encryption node; use each node public key to perform secondary encryption on the basic encrypted data to obtain multiple target encrypted data; interleave and send the target encrypted data to each encryption node for storage, wherein the first encryption node does not receive the first encrypted data, the first encryption node receives the second encrypted data, the first encryption node is any one of the multiple encryption nodes, the first encrypted data is encrypted by the first node public key corresponding to the first encryption node, the second encrypted data is encrypted by the second node public key corresponding to the second encryption node, and the second encryption node is any one of the multiple encryption nodes except the first encryption node. Implementing the technical solution provided by the present application reduces the probability of data being leaked when the node is attacked when it is stored in the node.

The invention provides an energy efficiency optimization algorithm for a low-power wide area network (LPWAN), and aims to reduce the energy consumption of LPWAN equipment in a data transmission process and prolong the service life through adaptive data rate adjustment and a micro machine learning (TinyML) technology. The algorithm core comprises a self-adaptive data rate adjustment mechanism, and the transmission rate is dynamically adjusted according to the real-time link quality index and the signal strength. A TinyML model is integrated for local data processing and intelligent decision making, and the data uploading amount is reduced; according to the intelligent dormancy awakening strategy, energy consumption use of equipment is predicted and optimized according to an equipment use mode; and a multi-parameter optimization scheduling algorithm is adopted, and signal quality, equipment electric quantity and environmental factors are integrated for scheduling. In addition, the security of data transmission and user privacy protection are also considered, and a lightweight encryption technology is adopted. The practical application test in various LPWAN technologies verifies the effectiveness of the algorithm, realizes the obvious reduction of energy consumption and the prolonging of the service life of equipment, and has high expandability and adaptability.

The invention relates to an image processing method, a map generation method, electronic equipment and a storage medium. The image processing method comprises the following steps: extracting image features from an environment image to obtain a feature map of the environment image; segmenting the feature map through at least two different types of geometric element models to obtain different types of geometric element maps; fusing the geometric element diagrams of different categories to obtain a first fused diagram; and performing vectorization processing on geometric elements in the first fusion image to obtain a structured vector graph corresponding to the environment image.

The present invention provides a high-performance bare disk management method, including: dividing the disk space into a user data area and a metadata area, dividing the user data area into multiple slices, and the metadata information of the slices is located in the metadata area; the user module is responsible for maintaining the mapping relationship between data and data block management units and data block management units and slice IDs, and sending I / O requests to slice control modules; the slice control module is used to perform disk control, and the slice control module is a multi-layer structure, and each layer performs corresponding control operations; wherein the disk control includes disk space management, data consistency control, and I / O operations, and the data consistency control is performed through a clock mechanism. The present invention has the following beneficial effects: improving management efficiency, reducing metadata operations, reducing kernel interactions, improving software performance, and avoiding single-disk performance bottlenecks caused by CPU reasons.