33results about How to "Avoid service interruption" patented technology

The invention relates to the related technical field of integrated service management, in particular to a digital intelligent technology and software and hardware integrated service management method and platform and a storage medium, and the method comprises the steps: connecting an industrial internet, receiving integrated service requirements, deploying software and hardware based on specifications, fitting a service scene, setting a topological architecture conforming to the specifications, and collecting data to establish a performance model. According to the software and hardware matching topology architecture, a communication architecture is adopted, a monitoring mechanism is set, and abnormal response management is performed on each component and each service in the software and hardware matching topology architecture, so that the technical problems that a service scene is fixed and a static deployment mode is difficult to quickly respond to dynamically changing service requirements in a software and hardware integration process are solved; the technical effects that the industrial internet is connected, the integrated service demand information is received in real time, changes of service demands are flexibly coped with in the software and hardware configuration process, dynamic configuration and adjustment are carried out according to different service scenes and demands, service changes are rapidly responded, and the flexibility and adaptability of resource configuration are improved are achieved.

The invention relates to the field of allocation, and discloses a spare part allocation method for multiple warehouses, and the method comprises the steps: obtaining spare part inventory information and historical spare part delivery data of each warehouse in a plurality of warehouses; analyzing the stock quantity corresponding to each spare part model to obtain an out-of-stock spare part model of each warehouse, and determining the warehouse corresponding to the out-of-stock spare part model as a spare part receiving warehouse; according to the historical spare part ex-warehouse data and spare part inventory information of each warehouse, a spare part allocation list is determined; sending the spare part allocation list to a plurality of auditing terminal devices; after checking of the spare part allocation list is completed, allocation delivery information corresponding to the spare part allocation list is generated, and the allocation delivery information corresponding to the spare part allocation list is sent to a delivery terminal device corresponding to a target spare part delivery warehouse; and monitoring the allocation and transportation information, and if it is monitored that the allocation and transportation information is received, generating allocation and receiving information of the spare part allocation list. Therefore, multi-warehouse spare part allocation is realized.

The invention discloses a remote video monitoring data transmission method, and the method comprises the steps: collecting visual video information through a robot camera, and transmitting the visual video information to a remote power plant monitoring center through a HDMI interface, an encoder, a 5G-CPE, a decoder and other links. The 5G-CPE uses MEC, 5G slicing and SRT technologies to adjust resource allocation according to network conditions and requirements, and defines configuration slices and priorities. A network monitoring component is deployed to monitor slice loads in real time, a load threshold value is set for each slice, and a resource adjustment strategy is triggered when the loads exceed the threshold values. And resources are dynamically reallocated after analysis and evaluation, so that sufficient and optimized utilization of high-load slice resources is ensured. Performance is continuously monitored and feedback adjustment is performed, network adaptability and flexibility are improved, key video streams are ensured to be transmitted preferentially, and power plant inspection requirements are met.

The invention discloses a semantic perception intention-driven network guarantee method and a framework. S101, in the intention translation process, verification and conflict resolution are firstly carried out on the original intention of a user, and the processed intention is backed up in an intention library before and after a flow table is prepared to be issued; s102, periodically extracting a network intention from the network switch by adopting a bottom-up network intention extraction method; s103, comparing the backed-up original intention with the advanced intention, performing consistency comparison through consistency verification, screening out the intention which cannot be correspondingly matched with any user intention, and judging the intention as a failure intention; and S104, aiming at the failure intention marked in the S103, re-adopting intention translation from top to bottom, and carrying out installation on the failure intention. The method has the functions of automatically detecting and repairing network configuration errors, the problem that advanced intention is inconsistent with underlying configuration semantics due to network changes is relieved, the efficiency and accuracy of network operation and maintenance are improved, and meanwhile cost and time consumption are reduced.

The invention relates to an AI-based CDN resource intelligent scheduling cost optimization method and device. Obtaining the current resource use condition of each resource node in the distribution network and the cost strategy of each resource affiliation party to which each resource node belongs; adopting an AI cost strategy model to analyze an estimated resource demand required by a demand side in a prediction time period, a current resource use condition of each resource node and a cost strategy of each resource affiliation side to which each resource node belongs, and obtaining a target node selected by the AI cost model from each resource node; and providing corresponding resources for the demand side in the prediction time period by adopting the target node.

The invention provides a water meter reading system. The water meter reading system comprises mobile meter reading equipment, fixed meter reading equipment and a data center, wherein the mobile meter reading equipment and the fixed meter reading equipment are respectively in communication connection with the data center, and the mobile meter reading equipment and the fixed meter reading equipment are selectively in communication connection; the water meter reading system can support manual and automatic meter reading by integrating the mobile meter reading equipment and the fixed meter reading equipment, data can be mutually verified, the accuracy and tamper resistance of the data are improved, the data are uploaded to the data center to be analyzed and processed so as to find abnormity, and the safety of the water meter reading system is improved. The selectable communication connection between the mobile meter reading device and the fixed meter reading device provides additional flexibility and can be adjusted according to actual requirements, so that the resource use is optimized, the working efficiency is improved, and in addition, the position of a meter reading person can be determined through a positioning module to supervise the working efficiency of the meter reading person.

The invention relates to the field of Internet of Things cards, in particular to an artificial intelligence Internet of Things card traffic sharing method and system, and the method comprises the steps: receiving feature parameters, collected by Internet of Things cards, at the current moment, and calculating traffic consumption parameters of each Internet of Things card at the current moment according to the feature parameters at the current moment; predicting the traffic consumption parameter of each Internet of Things card at the next moment according to the traffic consumption parameters of all the Internet of Things cards at the current moment and the traffic consumption parameters of all the Internet of Things cards at other predetermined moments; according to the total traffic and the residual traffic in the shared traffic pool, the total duration and the residual duration of the charging period, the traffic consumption parameter of each Internet of Things card at the next moment and the traffic consumption parameters of other moments, performing traffic distribution for each Internet of Things card; and limiting the flow consumption of each Internet of Things card at the next moment according to the flow distributed for each Internet of Things card. The total flow of the shared flow pool can be prevented from being exhausted in advance, and network congestion is avoided.

The invention belongs to the technical field of shared charging, and particularly relates to a charging robot layout method based on environmental perception, which comprises the following steps of: acquiring crowd distribution information in a region by introducing an infrared sensing module, planning an advancing path of a robot in combination with information of a position module, and identifying an optimal staying position by using an image acquisition module; and the robot can intelligently avoid the crowded area and select the most suitable place to provide service. And meanwhile, the electric quantity state of the robot is continuously monitored, the recharging process is automatically started when the electric quantity is lower than a preset threshold value, and seamless switching between the robot about to run out of power and the standby robot is achieved in combination with dispatching of the central control system. The method not only improves service efficiency and user experience, but also effectively avoids service interruption caused by insufficient power of a single robot, and ensures continuity and stability of service.

This application provides an application context relocation method and apparatus. The method includes: For service continuity planning application context relocation ACR, if an edge enabler server determines that a terminal device moves to a target location, the edge enabler server sends an ACR complete message to the terminal device. According to the application context relocation method provided in this application, when it is determined that the terminal device moves to the target location, an application client can be switched to a target edge application server, to avoid service interruption of the application client that is caused by premature switching.

The invention provides a connection control method and device, equipment, a storage medium and a computer program product, and the method comprises the steps: sending the node information of an agent node in a target coverage area to second network equipment; receiving first access network information sent by the second network equipment; the first access network information comprises access network information of a candidate proxy node corresponding to the first terminal; determining a target proxy node corresponding to the first terminal from the candidate proxy nodes according to the first information; the first information comprises first access network information; sending second information to the target agent node; the second information comprises identity information of the first proxy node and first identification information of the first network connection; the first network connection refers to network connection between the first terminal and a source agent node. According to the scheme, the problem that a cloud network detour scheme in the prior art cannot ensure the service quality can be solved.

The invention provides a conference room water cup water replenishing strategy optimization method and system based on reinforcement learning, and relates to the technical field of intelligent services, and the method comprises the steps: obtaining the liquid remaining amount feature and the spatial position feature of a container in a target space, and constructing a state representation vector to represent the incidence relation between the two features; predicting the liquid consumption trend of each container in the target time window through the time sequence analysis model to obtain a demand prediction result; inputting the state representation vector and the demand prediction result into a reinforcement learning strategy network, and based on the multi-container liquid residual amount distribution state and the prediction consumption trend, generating a decision sequence containing a supplement priority and a supplement opportunity by optimizing a long-term accumulation reward function; and dynamically adjusting the supplementary execution sequence of each container according to the supplementary priority in combination with the available supplementary resource constraint, and generating and executing a supplementary execution scheme. According to the invention, intelligent optimization of the water replenishing strategy is realized through reinforcement learning, and the resource utilization efficiency and the service quality are improved.

The invention relates to a mirror image layer cleaning method and device, computer equipment and a readable storage medium. The method comprises the steps that multiple to-be-cleaned mirror image layers on a target user side are obtained, and the to-be-cleaned mirror image layers are unused mirror image layers in all mirror image layers stored on the target user side; obtaining target associated information and target weight information of each to-be-cleaned mirror image layer from a pre-constructed target user-level mirror image layer information base; and cleaning the to-be-cleaned mirror image layer according to the target associated information and the target weight information. The cleaning effect of the method is good.

The invention provides a main node election method of a multi-node network, the multi-node network and electronic equipment, and relates to the technical field of wireless communication. The method comprises the following steps: if a current main node judges that a preset election triggering condition is met, broadcasting an election instruction containing a score calculation rule to the whole network; scoring response data including node identifiers and energy consumption scoring values returned by the nodes are received, the energy consumption scoring values are scoring values calculated by the nodes according to energy consumption parameter sets of the nodes on the basis of scoring calculation rules, and the energy consumption parameter sets include the remaining battery capacity, the historical energy consumption rate and the data load; sorting all the nodes according to all the energy consumption score values so as to determine a new main node; and generating and broadcasting election result data containing the node identifier of the new master node so as to trigger the network to perform master-slave role switching and network synchronization according to the data. The scheme can solve the problems of unbalanced energy consumption and insufficient adaptability, so as to effectively prolong the service life of the network and improve the reliability of the network.

The invention discloses a load-balanced network service management method and device and a medium. The method comprises the following steps: acquiring an access request sent by a client; analyzing a domain name in the access request to obtain a target access address of the first target cloud server; determining a plurality of second cloud servers according to the target access address; and distributing the access traffic of the first target cloud server to a plurality of second cloud servers, controlling the plurality of second cloud servers to respond to the access request, and providing a cloud service for the client. According to the load-balanced network service management method and device and the medium, the second cloud server is determined by analyzing the domain name, so that load balancing can be realized, and overload of a single cloud server is avoided; through the flow distribution and response control mode, the flexibility and expandability of the system are improved, the requirements of service development are met, and the problems that reasonable flow distribution is difficult to achieve, and overload faults of the cloud server are avoided can be solved.

The present invention relates to the technical field of electric energy distribution, and discloses an electric energy distribution system and method based on dual-mode communication, including: according to a set of charging and swapping stations, adopting a data inference strategy to obtain the model type and quantity of batteries configured in each charging and swapping station; setting a threshold distance for dividing the area where the charging and swapping stations are located; according to the charging and swapping station set and the threshold distance, adopting a regional division strategy to obtain a replacement area set; according to a replacement vehicle set and a replacement area set, adopting an optimal replacement strategy to obtain the optimal charging and swapping station for replacing the battery of the replacement vehicle; obtaining the charging and swapping stations included in the replacement area to form an execution station set; according to the execution station set and the execution path, adopting an electric energy scheduling strategy to coordinate the batteries of the charging and swapping stations with replacement vehicles. Through the scheduling of replacement vehicles, the battery resources of full power stations and qualified power stations are coordinated, the battery resource utilization rate is improved, and the service level and user satisfaction of the charging and swapping stations are improved.

A method and an apparatus for upgrading client software are provided, to provide a technical solution of online upgrade, and avoid service interruption caused by upgrade of a client deployed on a computing node in a storage system. Alternatively, compared with a manner in which a service processed by client software is scheduled by using a scheduler during upgrade, this application does not increase scheduling time costs, thereby improving upgrade efficiency. The method includes: The computing node in the storage system receives an upgrade instruction for client software deployed on the computing node, where the client software is used to access one or more storage nodes in the storage system based on a received input / output I / O instruction; performs I / O suspension on the received I / O instruction in response to the upgrade instruction; and upgrades the client software based on the upgrade instruction.

The invention relates to the technical field of communication equipment configuration management, and discloses a communication equipment configuration management system based on a distributed backup mechanism, which comprises a power supply and distribution system, the distributed backup mechanism, an air conditioning system, a lightning protection and grounding system, an automatic data acquisition and transmission technology, a fire extinguishing system, a monitoring system and a computerized maintenance management system, the power supply and distribution system is in communication connection with the distributed backup mechanism, the distributed backup mechanism is in communication connection with the air conditioning system, the air conditioning system is in communication connection with the lightning protection and grounding system, and the lightning protection and grounding system is in communication connection with the automatic data acquisition and transmission technology. The communication equipment configuration management system has the beneficial effects that by adopting an automatic data acquisition and transmission technology, the defects of the communication equipment configuration management system can be effectively reduced, the development efficiency and the system stability are improved, manual intervention is reduced through automatic generation and an intelligent algorithm, and the development efficiency and accuracy are improved; defects of a communication equipment configuration management system can be effectively reduced.

The present invention provides a resource scheduling method, device and platform equipment, wherein the resource scheduling method includes: using the capability resource scheduler of the first platform equipment to receive the resource occupancy information respectively sent by the capability schedulers included in at least two second platform equipments; transmitting the resource occupancy information to the capability orchestrator of the first platform equipment through the capability resource scheduler; using the capability orchestrator to determine the resource scheduling information for the at least two second platform equipments according to the resource occupancy information; transmitting the resource scheduling information to the capability resource scheduler through the capability orchestrator; using the capability resource scheduler to perform resource scheduling for the at least two second platform equipments according to the resource scheduling information. This solution solves the problem in the prior art that the resource scheduling solution may lead to poor service calling capability, service interruption and resource waste due to insufficient resources.

The invention discloses a national standard service module based on a railway video monitoring system. The national standard service module comprises a national standard signaling module and an international access module, a national standard signaling module is arranged in each video area node or video access node, the national standard signaling module interacts with a terminal user or a superior platform and is only used for forwarding a signaling request, and the signaling request comprises a video signaling request; one or more international access modules are arranged in each video area node or video access node, and the international access modules are used for receiving the video signaling requests forwarded by the national standard signaling modules and processing and responding to the video streams of the front-end equipment. Therefore, the national standard service of a traditional structure is split into the national standard signaling module and the national standard access module, and the signaling stream and the media stream are separated, so that the processing capability of signaling and video streams can be independently expanded according to actual business requirements, and the situation that the single national standard management service is interrupted or paralyzed due to overhigh load under high-concurrency request pressure is avoided; the system flexibility is improved.

The invention provides a communication management machine upgrading method and system, and belongs to the technical field of data processing, and the method comprises the steps: obtaining an available upgrading file from an upgrading file server, and downloading the upgrading file to a local storage; acquiring historical flow data; according to the historical traffic data, predicting the traffic data by using a jump gating cycle unit; analyzing a communication load according to the predicted flow data, and determining a low-load period; checking by using a Z-Score threshold value, and judging whether the low-load time period is a real low-load time period or not; if yes, entering the next step to execute the upgrading plan; otherwise, delaying the upgrading plan; the upgrading file is decompressed and installed in a standby system partition, and a standby system is subjected to pre-start check and test; when the standby system runs stably, the system is guided to the standby system partition through a hardware switching mechanism, and system upgrading is carried out. A hardware switching mechanism is adopted, the upgrading process almost has no influence on a user, and the system can be seamlessly switched.

The invention discloses a quantum key distribution method and a quantum key distribution system. The quantum key distribution method comprises the following steps: in response to a received service demand sent by a first service terminal, determining a quantum key distribution target scheduling path according to a first network state and the service demand; and issuing a quantum key scheduling instruction to the target ground quantum key distribution network and / or the target non-ground quantum key distribution network based on the target scheduling path. Thus, through overall planning and scheduling of global resources, unified management and optimal configuration of global quantum key distribution resources are realized, the transmission distance bottleneck that a single ground quantum key distribution network is limited by optical fiber loss is effectively broken through, and the inherent shortages that the coverage range is fixed are effectively broken through; the service requirement that a cross-regional ground quantum key distribution network is difficult to touch is met, and the overall utilization rate of key resources and the satisfaction rate of user requests are improved.

The invention belongs to the technical field of data center management, and particularly relates to a data center operation and maintenance management system based on big data, which comprises a data acquisition module used for acquiring data from data sources of various devices of a data center in real time or at regular intervals; and the data processing module is used for receiving the data transmitted by the data acquisition module. The data center operation and maintenance management system based on big data can intelligently allocate the storage space according to the actual demand of the system and the resource use condition, and avoids resource waste and storage bottleneck. Through the technologies of data compression, duplicate removal and the like, the utilization rate of the storage space is further improved, the storage cost is reduced, meanwhile, a data storage strategy is optimized, a data backup and recovery mechanism is implemented, and it is ensured that system data can be recovered in time when faced with risks such as hardware faults, software errors or manual misoperation. And system instability and service interruption caused by data loss are avoided.

The invention provides a storage system volume mistaken deletion prevention method and device, electronic equipment and a storage medium, and relates to the technical field of data processing.The method comprises the steps that under the condition that a target operation of a user on a target storage volume in a storage system is received, the latest access time of each storage volume is obtained; wherein the target operation comprises at least one of the following operations: a target storage volume de-mapping operation, a target storage volume deletion operation, an operation of removing a target storage volume from a target storage volume group containing the target storage volume, a host group de-mapping operation corresponding to the target storage volume group, and a deletion operation of a host corresponding to the target storage volume. The target storage volume corresponds to a port deletion operation of the host, and the host unit removes the operation of the host corresponding to the target storage volume; and obtaining a time difference value between the latest access time of the target storage volume and the current timestamp, and controlling the processing of the target operation based on the size relationship between the time difference value and the preset interval protection time.

The invention discloses a multi-frequency time-sharing communication system and method. The system comprises a controller and a plurality of wireless function modules, after the high-frequency signal of the matching object is received, a corresponding control instruction is generated according to the high-frequency signal of the matching object and sent to other function modules of the vehicle; when the controller replaces the matching object, the controller sends a corresponding low-frequency signal to the replaced corresponding wireless function module; after the replaced corresponding wireless function module receives the corresponding low-frequency signal, a high-frequency signal is sent to the controller; and after receiving the high-frequency signal of the replaced matching object, the controller generates a corresponding control instruction according to the high-frequency signal of the replaced matching object and sends the control instruction to other functional modules of the vehicle. According to the invention, the number of receivers needing a plurality of wireless function modules originally is reduced to one, so that the cost of the receivers is greatly saved, and no extra hardware circuit is introduced.

This application provides an environment deployment method, apparatus, device, storage medium, and program product, which can be applied to the field of big data technology. The method includes: in response to an environment deployment instruction, performing a rolling deployment operation on N preset containers for the same service, where N is a positive integer greater than 1; wherein the rolling deployment operation includes: for any of the preset containers, determining a target container among the N preset containers, wherein the target container is used for service shutdown, and the other preset containers among the N preset containers (excluding the target container) are used to provide the service; performing version deployment on the target container to obtain a deployed target container; performing verification on the deployed target container; and, if the deployed target container passes verification, bringing the deployed target container online.

The application discloses a high-availability and anti-split-brain industrial data acquisition system, comprising: a basic server cluster, which comprises a business server cluster and a history server cluster, the business server cluster comprises a plurality of business instances, the business instances are used for undertaking business logic processing tasks, the business instances are separately deployed from a database master node, and at least one special master node is included in the plurality of business instances; and an acquisition server cluster, which is used for acquiring real-time data from field devices or IoT terminals; wherein the business server cluster is based on an election mechanism of a Redis cluster, and when network partitioning occurs, an external coordinator is used for judging and forcibly closing the write permission of a non-master node. Compared with the prior art, the business service and the database master node are separately deployed, and a three-node anti-split-brain mechanism is introduced, so that the stability and data consistency of the system in a complex network environment are remarkably improved.

The invention discloses a prediction content cache scheduling system based on machine learning. The prediction content cache scheduling system comprises a content feature perception module, a user demand prediction module, a dynamic cache decision module, a cache synchronization optimization module, a tracing audit module and an emergency guarantee module. According to the method, the content feature sensing module collects three types of core features of cloud game attributes, operation dependency and user interaction through multi-dimensional feature support, Min-Max normalization and one-hot coding standardization processing are carried out, a high-quality data set with a unified structure and a clear hot degree and delay sensitivity scoring rule are output, game priority quantification is controllable, and the game quality is improved. Decision subjectivity is avoided, a fusion model is constructed through a time sequence diagram neural network and a gradient boosting decision tree, association of regions and time accessed by players is captured, a nonlinear demand rule is mined, the prediction precision is remarkably improved after weighted fusion, a high-frequency iteration mechanism can quickly respond to sudden demands, and the problem of resource supply and demand mismatching is solved.

The invention relates to the technical field of container management, and provides a cluster node scheduling method, a cluster node scheduling device, a cluster system, a computer readable storage medium and electronic equipment.The cluster node scheduling method is applied to the cluster system, and the cluster system comprises a plurality of working nodes. The cluster system further comprises a created network resource management model, the network resource management model is used for maintaining the network resource use condition on each working node, and the cluster node scheduling method comprises the following steps: reading the network resource use condition on each working node from the network resource management model; and when the network resource use condition corresponding to the target working node exceeds a resource use threshold value, setting the target working node to be in a scheduling forbidding state. According to the invention, the problem that the new container cannot be scheduled due to insufficient network resources on the node can be avoided.

The embodiment of the invention provides an information security processing method and device, electronic equipment and a storage medium. The information security processing method comprises the following steps: acquiring running behavior characteristics of a to-be-detected program and running behavior characteristics of multiple types of pre-stored malicious programs; for each type of malicious program, calculating the similarity between the operation behavior characteristics of the to-be-detected program and the operation behavior characteristics of the type of malicious program, and taking the similarity as the similarity corresponding to the type of malicious program; based on the similarities corresponding to the multiple types of malicious programs, similarity influence factors corresponding to the multiple types of malicious programs are calculated; calculating a malicious index of the to-be-detected program based on the similarities corresponding to the multiple types of malicious programs and the similarity influence factors corresponding to the multiple types of malicious programs; and executing information security processing operation corresponding to the malicious index on the to-be-detected program. In the embodiment of the invention, the accuracy of executing the information security processing operation according to the malicious index is higher.

The invention provides a terminal scheduling method, device and equipment and a readable storage medium, and the method comprises the steps: collecting the operation information of a terminal under the statistical dimensions of state, business, queue occupation and the like, and determining a comprehensive abnormal score of the terminal based on the matching condition of the operation information and a preset abnormal condition; according to the method, abnormal occupation of a terminal on shared communication resources can be accurately identified without depending on independent queue hardware of each STA with high cost, scheduling intervention is implemented on an abnormal terminal, and the scheduling efficiency is improved on the premise of not increasing hardware queue resources. The situation that a single abnormal terminal occupies too many packet sending queue resources, and consequently forwarding of the whole machine is blocked or stuck is effectively avoided, and the system robustness, the resource utilization efficiency and the multi-user fairness are improved. The method can be applied to various IP network environments and various network topology structures, including optical fiber access scenes, such as fiber to the room (FTTR) networking scenes.