141 results about "Distributed servers" patented technology

The invention relates to the technical field of server resource scheduling, in particular to a server resource scheduling system integrating AI and edge computing. The server resource scheduling system integrating the AI and the edge computing comprises a computing node module, a resource calling module, a task traversal module, a demand prediction module, a resource allocation module and a load scheduling module, the computing node module is used for monitoring the real-time running state of a server computing node and performing distributed node architecture fitting, and the load scheduling module is used for scheduling the load of the server computing node; constructing a distributed server node network; the resource calling module is used for acquiring a server running log; performing server resource calling behavior analysis on the server running log, performing resource calling time sequence characteristic evolution, and generating a server resource calling time sequence characteristic; and the task traversal module is used for carrying out unprocessed task traversal identification on the server running log and constructing an unprocessed task state mapping sequence. According to the invention, efficient and load-balanced server resource scheduling is realized.

The embodiment of the invention provides a distributed server cluster log processing method and device, and the method comprises the steps: constructing a distributed server cluster log collection network, and dynamically distributing collection tasks through a load balancing scheduling center. An incremental data acquisition channel is designed, efficient transmission is realized by using a websocket long connection pool, and the transmission efficiency is optimized in combination with real-time compression coding and a repeated data detection mechanism. An intelligent log analysis model is constructed, the intelligent log analysis model comprises an anomaly detection sub-model, a mode recognition sub-model and an event association analysis sub-model, anomaly score calculation, log classification labeling and multi-dimensional association analysis are achieved based on a deep learning method, and visual display and data export functions are provided. According to the method, the defects of the traditional technology in the aspects of distributed acquisition, data transmission, intelligent analysis and the like are effectively overcome, and the performance and practicability of a log processing system are remarkably improved.

The invention provides a distributed data path combination equivalence verification method and a distributed server, and the method comprises the steps: carrying out the rewriting of two to-be-verified data path circuits, and obtaining two circuit description files with similar circuit structures; constructing a Miter circuit according to the circuit description file; random logic simulation is carried out on the Miter circuit to obtain internal potential equivalent nodes, and the internal potential equivalent nodes are stored in an equivalent node queue; selecting potential equivalent node pairs from the equivalent node queue, extracting fan-in cones of the potential equivalent node pairs, and constructing a sub miter circuit according to two groups of fan-in cones; selecting a verification mode according to the density degree of the XOR block in the sub-miter circuit, and verifying the sub-miter circuit; if verification succeeds, the corresponding potential equivalent nodes and the corresponding fan-in cones are combined, otherwise, other potential equivalent node pairs continue to be verified until verification of all potential equivalent nodes is completed; and the SAT solver is used for executing final equivalence verification and returning a verification result, so that the equivalence verification of the data path combination is efficiently realized.

The invention relates to the technical field of virtual reality interaction, and discloses a virtual reality multi-person interaction method, which comprises the following steps: realizing environment synchronous initialization based on space anchor point calibration and dynamic object loading, and configuring value physical rules and interaction logic; executing a data synchronization mechanism by establishing connection and session management; performing real-time action synchronization and interaction logic processing according to user input processing and action capture; user data privacy and security are protected, and content security and user behaviors are supervised. According to the virtual reality multi-user interaction method and system, by adopting a distributed server architecture and dynamically distributing the nearest edge node according to the geographic position of the user, dynamic load balancing can be realized, QoS priority division is started, low-delay transmission is realized by adopting a UDP + RUDP protocol, communication data is encrypted by adopting an AES-256-GCM, and a key is dynamically updated by adopting a dual-ratchet protocol; and the biological characteristics are converted into irreversible hash values, so that the security of privacy data of the user can be effectively improved.

The invention discloses a distributed server load balancing system based on multi-modal data fusion. The distributed server load balancing system comprises a multi-modal sensing layer, a fusion analysis layer, an intelligent decision-making layer and an elastic execution layer, the multi-modal sensing layer collects multi-source heterogeneous data; the fusion analysis layer is used for mining an association relationship between data of different dimensions; meanwhile, converting multi-source data into a unified feature vector, and outputting a dynamic load balancing strategy; the intelligent decision-making layer generates an executable load balancing strategy according to the fusion analysis result; and the elastic execution layer converts the strategy generated by the intelligent decision-making layer into an actual action, and deals with load change through an elastic mechanism. According to the method, server performance, network topology and request semantic data are fused, a unified feature tensor is generated by using a cross-modal attention mechanism, and load association is accurately quantified; on the basis of cooperation of a global mixed integer programming model and a local lightweight DQN agent, load migration is completed in a very short time, and the response speed is increased.

The invention relates to a parameter adjustment strategy determination method and device, a server and a storage medium. The method comprises the following steps: storing a plurality of IO requests to corresponding target storage volumes according to storage volume identifiers carried by the received IO requests; determining a parameter adjustment strategy of the main server according to the target information of each target storage volume; wherein the target information of the target storage volume is determined according to the attribute information of the IO request stored in the target storage volume; and determining a target parameter adjustment strategy of the distributed server cluster according to the parameter adjustment strategy of the master server and the parameter adjustment strategies of the slave servers except the master server in the distributed server cluster. The adjustment strategy determined by the method cannot enable the performance of the distributed server cluster to be optimal.

The present invention is based on the objective of providing a control system, in particular for rail-bound transport, with which it is possible to configure non-functional requirements for the control system in a simple manner and to make them available for the control system.This problem is solved according to the invention by a control system for controlling an industrial process, in particular a control system for an industrial production plant or for controlling traffic, especially rail-bound traffic, comprising: a) a product instance for the software of the control system that controls the control requirements of the industrial process; b) a control system platform for executing an instance of the control system, wherein the control system platform has a runtime environment (Runtime Framework) comprising the following components: c) a core instance (RTF Core) that is capable of providing a runtime environment which enables application functions, such as train tracking, logging, etc., to be distributed across several monitored processes, i.e.each in a monitored thread; d) based on the core instance, a Workplace instance (RTF Workplace) is designed, which extends the core instance located on the lowest logical layer and supports the implementation of client applications; and e) based on the logical layer of the core instance, a further logical layer with an Ensemble instance (RTF Ensemble) is provided, which has helper functions that facilitate the implementation of server applications, preferably such helper functions that are relevant in the context of a distributed server system for the execution of the control system software.

The invention provides a building industry finance and tax compliance digital evidence chain integrated platform which is deployed based on a cloud computing architecture and comprises a distributed server cluster, a network communication module and a database storage system. By constructing the integrated digital platform, fundamental efficiency improvement and risk management and control reinforcement of finance and taxation management in the building industry are realized, the platform enables a data acquisition process to be highly automatic, manual repeated entry work is greatly eliminated, financial personnel are liberated from tedious account checking, and the financial personnel are greatly improved. The compliance check module based on a rule engine and artificial intelligence can perform real-time and comprehensive automatic analysis on all transaction data, significantly improves the identification accuracy and timeliness of potential compliance risks, realizes instant alarm, converts passive risk response into active risk response, and improves the risk handling efficiency. Compared with a traditional manual mode, the data processing speed is improved in order of magnitude, the monthly checkout and report generation time is greatly shortened, the enterprise decision cycle is remarkably accelerated, and the overall operation efficiency is improved.

The embodiment of the invention discloses a power failure fault warning method and device, electronic equipment and a computer readable medium. A specific embodiment of the method comprises the following steps: acquiring a real-time digital twinborn model; in response to the received equipment fault detection information, obtaining a target equipment identifier; obtaining a power equipment association relationship graph from a distributed server; according to the target equipment identifier, performing preliminary cutting on the electrical equipment association relationship graph to generate a first cut graph; determining first power failure influence range information according to the first clipped map; obtaining a distribution map from a distributed server; screening out at least one piece of first key facility object information from the distribution map; and displaying a first real-time region image corresponding to the first power supply sub-region in the real-time digital twin model. According to the implementation mode, the corresponding related power failure information can be quickly and efficiently generated for the fault equipment, subsequent power equipment maintenance can be carried out in time, and stable power supply is guaranteed.

The invention relates to the technical field of server data access control, and discloses a server data access control method, device and equipment and a storage medium. Distributed server deployment information is queried by estimating bidding document item service requirements of each sub-service area; solving a server data access control strategy by taking the overall processing delay condition of the server executing the corresponding service user bidding document item, the server hardware load and the server resource scheduling limitation as a constraint condition set and taking the server access experience of the service user in the target server access control time period as an optimization target; and resource scheduling and service user matching of the distributed server in each access control period are realized by using a control strategy, so that bidding document project service is executed. According to the method, the rationality of server data access control planning is improved by considering regional differences, time peak differences and strong regional relevance of bidding document application services in different industry categories and hardware resource limitations of distributed servers.

The invention provides an intelligent inspection system based on a robot and a camera, and relates to the field of intelligent manufacturing, the system adopts a four-layer architecture including a sensing layer, a transmission layer, a platform layer and an application layer, the sensing layer is composed of a fixed camera and an intelligent inspection robot; the transmission layer adopts optical fibers and 5G hybrid networking; the platform layer is integrated with a distributed server cluster, a data platform and an AI inference engine; the application layer provides a Web and mobile terminal management interface. The core of the system adopts a plurality of AI algorithms, including an instrument reading recognition algorithm based on Hough transform and CRNN, a leakage detection algorithm combined with background difference and an optical flow method, and a multi-device collaborative scheduling algorithm based on reinforcement learning, and constructs a digital twinborn inspection scene of virtual-real mapping. According to the invention, automatic and intelligent inspection and visual monitoring of power plant instruments, pipelines, power distribution rooms and other areas are realized, the inspection efficiency and accuracy are effectively improved, and the labor cost and the safety risk are reduced.

The invention discloses a student psychological health digital intelligence early warning method, which belongs to the technical field of big data, and comprises the steps of establishing a data acquisition layer, a data preprocessing layer, a data analysis and modeling layer and a psychological crisis early warning layer in a distributed server cluster. According to the invention, a more comprehensive psychological health assessment basis is provided, real-time updating and processing of data can be realized, timeliness and accuracy of data analysis are improved, psychological health states of students can be assessed more comprehensively, abnormal behaviors of the students can be accurately identified, and therefore, the students can have a better psychological health assessment effect. And according to the frequency and the grade of the abnormal behavior, adjusting the influence of the abnormal behavior on the psychological health score.

The invention provides a distributed service method and platform based on a service platform, and relates to the technical field of distributed computing power processing. The method comprises the steps of collecting historical computing power periodic supply data of different distributed servers, and performing performance analysis for stable available computing power to form distributed computing power supply data; obtaining a pre-estimated calculation power total amount of the training object set, and performing calculation power supply matching analysis in combination with the distribution calculation power supply data to form distribution calculation power matching data; and acquiring power supply price change data of the power grid, and performing computational power supplementary analysis in combination with the distributed computational power matching data and historical computational power period supply data of different distributed servers to form distributed computational power supplementary data. According to the method, reasonable computing power supply matching is carried out by extracting the distributed computing power based on historical computing power supply characteristics, and efficient and reasonable utilization of total computing power provided by a platform can be realized while a training object is ensured to obtain sufficient computing power.

Disclosed is a system for implementing a distributed encrypted database across database nodes of a distributed server network. The system comprises at least one server. The at least one server is configured to execute a database management system to configure at least one database node of the distributed encrypted database with a first software to provide automated failover and replication capabilities in the distributed encrypted database. Moreover, the database management system is executed to integrate a second software with the database management system and encrypt data at rest in a distributed encrypted database by employing the second software; and integrate a third software with a first platform that is capable of authenticating users of the distributed encrypted database for controlling access to the encrypted files. Disclosed also is a method for implementing a distributed encrypted database across database nodes of a distributed server network.

The invention discloses an intelligent traffic multi-angle night vision snapshot camera device and system, and belongs to the technical field of image processing, and the device comprises a multi-mode sensing layer which is connected to a traffic information collection end; the anti-interference physical layer comprises a lens anti-interference module arranged at the traffic information acquisition end; the edge computing layer comprises an embedded NPU (Network Processing Unit) chip, and the chip realizes multi-stage distributed processing through a multi-stage processing mechanism; and the cloud collaboration layer realizes real-time synchronization and storage of data through a distributed server cluster in combination with a network communication module, and supports access of multiple terminal devices at the same time. In the implementation process of the technical scheme of the invention, multi-dimensional data acquisition is performed on a traffic scene through the multi-modal sensing layer, and distributed processing is performed on the acquired image through the edge calculation layer after acquisition is completed, so that multi-dimensional analysis of the traffic image is realized.

A system is provided for process monitoring using a quantum artificial intelligence powered distributed server network. In particular, the system may continuously monitor processes being executed within the network environment. Upon detecting an issue with the process, the system may use a quantum AI oracle to identify the root cause of the issue. Once the root cause has been identified, the system may adjust a process reliability score associated with the faulty computing device or application. By generating process reliability scores for the various computing devices and applications within the network environment, the architecture of the network environment may be modified by selectively including components that function reliably.

Methods and systems for determining the type of a remote mobile device by combining multiple types of data sets. The system collects various types of data sets, such as data sets associated with identity information, traffic patterns, control signaling, and application data associated with a remote mobile device from a radio access network and a packet core. This data is processed using a machine learning model, or using other processing techniques, to generate an output data set, which is used to determine the device type. The determination is more accurate and consistent than using only one type of data set. The system can be implemented in various environments, including local servers, cloud-based servers, hybrid servers, and distributed servers. The service can be provided to clients as a cloud service, where clients provide a mobile number, and the service provider handles the data collection, processing, and device type determination.

The invention provides a digital certificate management method. The method can be applied to the technical fields of big data and financial science and technology. The method is applied to a server for distributing a digital certificate in a distributed server cluster, and comprises the following steps: acquiring a digital certificate application element, and generating a digital certificate request file and a private key based on the digital certificate application element. Wherein the private key is a private key of an environment system which cannot carry out data transmission and is bound with a server used for distributing the digital certificate. And sending the digital certificate request file to a digital certificate issuing mechanism for generating a digital certificate. Wherein the digital certificate comprises a public key corresponding to the private key, and the private key is used for verifying the digital certificate. And acquiring the digital certificate, and distributing the digital certificate to a server for authenticating the digital certificate in a distributed server cluster. The invention further provides a digital certificate management device and equipment, a storage medium and a program product.

The invention provides a service authorization method and device based on a single device fingerprint, equipment and a medium, and relates to the technical field of information security. The method comprises the following steps: acquiring single-device fingerprint information of a management server of a to-be-deployed big data platform; according to the single-device fingerprint information and multi-dimensional authorization information for the big data platform, a pre-generated private key is adopted for encryption, and an authorization file is generated; and sending an authorization file to a management server, decrypting the authorization file by using a public key corresponding to the private key by the management server, and performing authorization verification of the big data platform on the management server and a plurality of distributed servers of the management server according to the decrypted single-device fingerprint information and the decrypted multi-dimensional authorization information, and the plurality of distributed servers are used for deploying a plurality of service modules of the big data platform. According to the invention, refined authorization for the big data platform can be realized.

The invention belongs to the field of novel addictive chemical substance identification, and provides a new psychoactive substance identification and rapid comparison method and system based on big data in order to solve the problem that the current key steps of new psychoactive substances need to depend on artificial experience, and consequently sample analysis consumes too long time. Comprising an automatic data acquisition module, an HBase-based NPS data storage module, an NPS molecular structure analysis module, an NPS intelligent comparison module, an NPS result feedback and early warning module and an application terminal, the automatic data acquisition module, the HBase-based NPS data storage module, the NPS molecular structure analysis module, the NPS intelligent comparison module and the NPS result feedback and early warning module are all deployed on a distributed server in a micro-service architecture, and all the modules realize data interaction through an API (Application Program Interface). According to the method, potential novel addictive substances can be found and treated in time.

A routing process schedules and executes Java code excerpts across backend servers. A route table contains routes to be executed in JVM namespaces on servers and identifies for each route a Jar file containing applicable classes and methods to be executed at a CRON time. During execution, methods are retrieved from each applicable class and are executed to extract data from backend devices. The servers transform the extracted data into frontend data and load it onto frontend storage devices. Only the classes and methods in the Jar file for a route need be executed. Complete Java programs need not be run.

The invention discloses a distributed communication method and device, and the method at least comprises the steps: building a connection for warehousing equipment according to warehousing information, and carrying out the data call of the warehousing equipment according to a preset period; acquiring a device message of the storage device, and storing the device message in a target data queue of the management server according to the device control word; calculating resource processing time consumption of each distributed server according to the equipment control word, and allocating the target data queue to a target distributed server according to the resource processing time consumption; and performing analysis and service processing on the equipment message according to the target distributed server, and feeding back a processing result to the storage equipment. According to the invention, the target data queue is matched for the equipment message through the equipment control word, and the resource processing time consumption of each distributed server is calculated according to the equipment control word, so that the resource use condition of each distributed server is monitored, the target distributed server is allocated to process the equipment message, and the message processing efficiency is improved.

Nodal work assignments efficiently distribute server work items, such as storing redundant copies of electronic data. A cloud computing network establishes a policy that governs how and where the redundant copies are stored cloud computing nodes (such as by region, zone, and cluster targets). The cloud computing network repeatedly or continuously re-evaluates the work assignments based on replication assignment skews and / or leadership penalties. The nodal work assignments thus minimize hardware and software operations, network traffic, and electrical energy consumption.

Aspects of the disclosure relate to batch processing at distributed servers. A computing platform may receive a first web service request, which may be a request for batch servicing. The computing platform may initiate a batch queue thread manager to process the first web service request, which may initiate a plurality of process threads, each configured to process, at any one time, a single job of the batch servicing. The computing platform may process, using the batch queue thread manager, the first web service request, which may include, by each of the plurality of process threads: 1) processing a first job of the batch servicing, and 2) processing, after completion of the first job, at least a second job of the batch servicing. After completion of the processing of the first web service request, the computing platform may output a response to the first web service request.

A method for controlling an electronic device using blockchain can include transmitting, by a processor in the electronic device, a first transaction to a device account (DA) stored in a distributed server of a blockchain network and logically coupled with the electronic device, the DA including data uniquely identifying the electronic device, transmitting, by the DA, a second transaction to a smart contract, and transmitting, by the DA, device data for controlling an operation of the electronic device to the smart contract. Also, the method can further include receiving, by the DA, data corresponding to a first value according to a transaction rule defined in the smart contract, transmitting, by the DA, the first value to the electronic device, and executing, by the electronic device, a control command corresponding to the first value.

The application discloses a variable data risk index calculation method, device, equipment, storage medium and program product, relates to the technical field of data processing, and the variable data risk index calculation method comprises the following steps: the variable data risk index calculation task is distributed by the current load condition of the distributed server, the load balancing capability of the system is improved, and the task processing capability of the system is improved. Through the risk index calculation of the distributed storage file loaded into the memory of the target server, the flexibility of data processing is improved. Through uploading the updated distributed storage file to the distributed file storage system, business analysis personnel can more conveniently obtain data risk index execution results and intermediate values of risk index calculation, so that the accuracy and efficiency of data analysis are improved.

The distributed job service scheduling method, distributed server and service terminal provided by the present invention can be used in the field of big data technology. First, obtain the service scheduling information of each service terminal, and then arrange the service scheduling information into a message pipeline; finally, perform service scheduling on each service terminal according to the message pipeline. It can be seen that through the setting of the message pipeline, the present invention componentizes business functions with tasks as the carrier components, and completes the dependency relationship in the form of a pipeline, solving the problem of job execution with front-back dependency relationships in traditional projects. It reduces the coupling of data synchronization collection and function integration and disassembly between systems, and ensures data consistency. It provides scalability for changes in business rules and upgrades of business architectures in business systems. For the modification and addition of job scheduling, there is no need to modify the business-side application and redeploy it, and it can take effect online. For the extension and change of business rules on the business side, only the pipeline needs to be modified, and there is no need to redeploy the business-side application.

The present invention relates to IoT devices existing in a deployed ecosystem. The various computers in the deployed ecosystem are able to respond to requests from a device directly associated with it in a particular hierarchy, or it may seek a response to the request from a high order logic / data source (parent). The logic / data source parent may then repeat the understanding process to either provide the necessary response to the logic / data source child who then replies to the device or it will again ask a parent logic / data sources for the appropriate response. This architecture allows for a single device to make one request to a single known source and potentially get a response back from the entire ecosystem of distributed servers.

Systems, methods, and computer-readable media are described for facilitating network synchronization within a network comprising multiple distributed server clusters connected to various edge devices. The synchronization process involves maintaining multiple copies of a routing table, which are distributed across the locations of the server clusters and edge devices. When a connectivity change occurs and is detected by at least one server in the distributed server clusters, this change is represented as a delta in the routing table. The delta is then distributed across the server clusters and edge devices to update and synchronize all copies of the routing table, ensuring consistency across the network.

This invention discloses a multi-dimensional performance evaluation method and system for computing servers, relating to the field of server performance data analysis. By constructing existing computing server resources into single server systems, server cluster systems, and distributed server systems, this invention selects the most suitable server system for running the test task based on its characteristics during performance testing. It then evaluates the performance of existing computing servers by selecting the optimal value from four dimensions: deployment time, running time, upgrade time, and uninstallation time. This achieves comprehensive performance testing and full utilization of existing resources, ensuring that the final evaluation results reflect the best performance achievable under existing computing server resource conditions, thus improving the accuracy of performance testing.