81 results about "Inter-server" patented technology

A resource set which includes multiple servers with a respective plurality of training computing devices is identified for training a machine learning model. The resource set is subdivided into partition groups, such that each partition group can store a respective replica of state information of the model. The model is trained using the partition groups. The training comprises a multi-stage gathering of a portion of the state information at training computing devices of a particular partition group. Different types of communication channels between training computing devices are used in respective stages of the gathering, including inter-server communication channels in one stage and an intra-server communication channel during another stage. A trained version of the model is stored.

The invention discloses a cluster job planning method and system based on a dual time window mechanism. The method comprises the steps that jobs are divided into a multi-level structure with an execution sequence, and a directed acyclic graph is constructed to form a task topological structure; constructing a dual time window mechanism; designing a multi-objective optimization function; modeling cluster job scheduling into a multi-agent Markov decision process, setting a hierarchical action space, and designing a reward function reflecting scheduling balance; the method comprises the following steps: constructing a hybrid neural network architecture, extracting a time sequence correlation feature of a task, encoding a heterogeneous feature between the task and a server by using a heterogeneous graph neural network, and generating an intelligent matching score between the task and the server; a multi-agent near-end strategy optimization algorithm is applied, and agent collaborative optimization is achieved through a collaborative mechanism updated by a centralized value function and a distributed strategy. According to the method, fine modeling and state dynamic perception of complex operation topology are realized, and scientificity and controllability of scheduling decision are improved.

The invention provides a physical guidance multi-level federated learning energy storage unit degradation estimation method for heterogeneous terminal equipment, and mainly relates to the field of artificial intelligence and energy storage health estimation. The method mainly comprises the following steps: taking power battery data of various devices such as an electric vehicle, an unmanned aerial vehicle and a robot as local data of a client, and performing data preprocessing; establishing a lightweight model for each client, and embedding a battery aging physical mechanism into a neural network model; a multi-layer federated learning framework is established, the first layer is a client formed by all devices, the second layer is local servers of multiple types of devices (electric vehicles, unmanned aerial vehicles and robots), and the third layer is a central server; designing a model screening strategy and an error perception weighted aggregation strategy between the client and the local server, and designing a model compression strategy between the local server and the central server; and obtaining a global model through multiple rounds of training, and estimating the health state of the power battery of the target equipment. In order to solve the problem that generalization of power battery health estimation in multiple heterogeneous devices is weak, a multi-level federated learning framework is designed, meanwhile, physical mechanisms and data modeling are combined, the limitation that the accuracy of battery health state estimation is insufficient is overcome, model estimation errors are remarkably reduced, and therefore the safety of an energy storage system is improved.

The invention belongs to the field of server clusters, and particularly relates to a dynamic resource scheduling-based server cluster energy efficiency optimization method, which comprises the following steps of: obtaining a resource load capacity of a server in a historical time period and a total resource load capacity of a server cluster, and training a load prediction model based on data; predicting the total resource load amount in the future time period through the load prediction model, and generating a load curve of the corresponding time; dynamically making a plurality of resource scheduling decisions according to the load curve, wherein the decisions comprise task migration, dormancy awakening and dynamic frequency modulation among the servers; and simulating and executing an energy consumption curve of each resource scheduling decision, wherein the decision with a low fluctuation index of the energy consumption curve is a target resource scheduling decision. The total resource load amount of the server cluster is predicted, a plurality of energy consumption curves conforming to the predicted load curve are generated and compared, the energy consumption curve with a low fluctuation index is selected as a target resource scheduling decision, and the influence of fluctuation on server hardware is solved while energy efficiency optimization is performed.

The present application provides a software development resource scheduling method and system based on big data. Among them, the method includes: mapping the heterogeneous configuration feature graph to the hyperbolic embedding space, combining the curvature adaptive algorithm, measuring the environmental configuration similarity value between the client server and the existing business servers in the pre-built resource pool, and the resource pool is constructed based on historical big data; according to the resource type required for the software development task provided by the client server, screening the existing business servers with configuration similarity values ​​greater than the preset similarity threshold and matching resource types from the resource pool; sorting the called business servers in descending order according to the similarity value, and elastically scheduling the software development resources in the called business servers based on the sorting results. The present application utilizes a mechanism for dynamically evaluating the environmental configuration similarity value, and combines it with a priority scheduling strategy to achieve zero-dependency conflict, high-precision, and highly effective resource scheduling, as well as the elastic reuse capability of resources.

Methods and apparatus are described for enhanced node communication within a wireless node network having nodes and a server. The method begins with a first node associating with a second node, and the first node capturing relevant node information. The first node transmits the relevant node information to the server via the second node operating as an intermediary for indirect communication with the server. A third node captures relevant node information and transmits the relevant node information to the server without using the second node as an intermediary or bridge to the server. Each of the first node, the second node, and the third node may be wireless transceiver-based nodes and respectively implemented as integrated circuits.

The invention discloses a heterogeneous cellular network task unloading method oriented to location privacy protection, and belongs to the technical field of communication. The invention provides a heterogeneous cellular network task unloading method oriented to location privacy protection, aiming at solving the problem that location privacy leakage is possibly caused when a mobile user unloads a task to a micro base station edge server to which the mobile user belongs in heterogeneous cellular network edge calculation. According to the method, the privacy leakage risk of task unloading is evaluated according to user position distribution, the number of unit tasks to be unloaded and the resource state of each edge server, the position correlation between users and target servers is weakened by using a relay forwarding mechanism of a macro base station, and a deep reinforcement learning method is adopted, so that the task unloading efficiency is improved. And the position privacy risk and the task unloading strategy of the user are dynamically learned and optimized, so that the position privacy protection of the user is effectively realized and the average unit task energy consumption is minimized under the constraint of average unit task tolerance time delay.

The invention provides a satellite communication method and device, computer equipment and a storage medium, the method is applied to a satellite communication system, the satellite communication system comprises user equipment, a first modem, a second modem and a target server, and the method comprises the following steps: responding to a communication connection request of the user equipment to the target server; creating a satellite communication link between the user equipment and the target server through the first modem and the second modem; and performing data transmission control on the satellite communication link based on a dynamic bandwidth delay product window model and a BBRv2 congestion control algorithm. Based on the scheme of the invention, the transmission performance in a high-delay and high-error-code environment is remarkably improved while the transparent proxy of a satellite link is realized.

The invention discloses a complex application-oriented extensible server energy efficiency modeling method and device, and the method comprises the steps: carrying out the energy efficiency modeling of a baseline server, and carrying out the extensible modeling of a target server: 1), carrying out the energy efficiency modeling of the baseline server: carrying out the independent energy efficiency modeling of hardware and software, the comprehensive performance and power consumption of the hardware are obtained based on software and hardware collaborative analysis, and finally the multi-hardware weight is dynamically adjusted to obtain the system-level energy efficiency of the server; and 2) extensible modeling of the target server: updating the trained energy efficiency model to migrate the business energy efficiency assessment from the baseline server to the target server to be tested by combining the operation energy efficiency of the unknown application to be tested under the baseline server and the hardware architecture difference between the target server. By means of the hardware decoupling method, the energy efficiency of the application load on the non-running target server can be predicted, complexity of real machine energy efficiency evaluation is avoided, extensible server energy efficiency modeling is achieved, and the generalization problem of an energy efficiency model in a complex software and hardware combination environment is solved.

The application provides a CPU load balancing-based inter-server communication scheduling method and system, and relates to the technical field of CPU load balancing, wherein the method comprises: performing quality evaluation on network state data to generate strategy data, and meanwhile converting electromagnetic intensity signals and temperature distribution signals in a computer room into corresponding digital signals to form an environment data set; fusing the strategy data and the environment state data set through a dynamic weight adjustment algorithm to generate a frequency modulation scheme and a channel switching instruction; screening a set of available CPU cores according to load data; and finally distributing data packets to target CPU cores for processing and transmission according to the frequency modulation scheme and the channel switching instruction, establishing multiple concurrent connection channels, and thereby realizing load balancing and high stability transmission between servers. The application improves the communication efficiency and transmission reliability of a server cluster.

The invention discloses a DNS cache snooping attack protection method and device based on an onion network. The method comprises the following steps: receiving a DNS query request sent by a client; a DNS pseudo resource record type is packaged in the DNS query request, and the DNS pseudo resource record type comprises an onion field; extracting an onion field in the DNS pseudo resource record type, and searching a DNS record corresponding to the request domain name, the request type and the onion field in a cache of the DNS pseudo resource record; if the corresponding DNS record is found in the own cache, a refusal response result is returned to the client; and if the corresponding DNS record is not found in the cache, triggering recursive query. According to the DNS cache snooping attack protection method based on the onion network provided by the invention, cache snooping protection is provided for DNS query by utilizing the idea of onion routing, and meanwhile, the decreasing effect of ttl is considered, so that the problem of influencing the performance or the consistency between data and an authoritative server is avoided.

The embodiment of the invention provides a federal large model learning method based on confrontation feature aggregation and a multi-party computing system, and relates to the field of artificial intelligence. The method is applied to a multi-party computing system, the multi-party computing system comprises a plurality of participants and a central service party, and the participants are in communication connection with the central service party. The method comprises the following steps: for any one of a plurality of participants, the participants perform adversarial feature generation processing on local data based on a noise generator to obtain adversarial features, and the noise generator is used for generating noise data; uploading the confrontation features to the central service party; and the central service party performs model training on a specific task through an adversarial feature cluster to obtain a target model, and the adversarial feature cluster is obtained by aggregating the adversarial features issued by the plurality of participants. According to the method provided by the invention, the communication overhead between each participant and the server is reduced, and the privacy protection of local data is improved.

The application provides a book management system data real-time synchronization processing method for dynamic updating of a book inventory, relates to the technical field of book management, and comprises the following steps: real-time monitoring of book inventory data change events of each book management terminal and a background server end, if a change is monitored, a change trigger signal carrying a change end identifier and a timestamp is generated; based on the change trigger signal, incremental change data is captured to analyze a book identifier, change content and an operation type, and a plurality of key frame identifier nodes corresponding to a transmission protocol encapsulation layer of the incremental data are extracted as dynamic anchor points to form an anchor point coordinate set; the anchor point coordinate set is bound with the incremental data packet and is synchronized to all other terminals and servers, so that each receiver simultaneously obtains the incremental data to be processed and the corresponding anchor point coordinate set. The application can realize real-time and strongly consistent synchronization of book inventory data between multiple terminals and a background server, and avoids inventory data errors caused by concurrent operations.

Server to server direct integration is provided. A system constructs an array of power values from time series data collected by a power sensor coupled with a television. The system inputs the array of power values into a model trained with machine learning based on log files of data collected from a plurality of power sensors coupled with a plurality of televisions. The system determines, based on output from the model generated with the array of power values, the television is active. The system executes, responsive to the determination that the television is active, an action to evaluate a performance of content rendered by the television.

This invention relates to an inter-domain data transmission device for industrial field instruments and a DCS monitoring system. The device includes: a device management IO data processor, a device management IO data encoder, a memory, and a device management IO data decoder. The device management IO data processor acquires data from industrial field instruments transmitted by all DCS controllers within a specified range and encodes all the data into character sequences. When data from different character sequences are aggregated, the data is processed according to the information encoding hierarchy, and the data is classified and merged to obtain information items for categorized storage in the memory. The device management IO data encoder, based on the domain to which the stored information item belongs, sends the information item to the DCS monitoring server of the corresponding domain according to the output data stream format. This invention solves the problems of slow data transmission speed and cumbersome configuration of structured data of field instrument devices between different servers.

The present disclosure provides an SCADA system that can equalize the time to which alarm information is given between two redundant SCADA servers. A SCADA system is provided with a first SCADA server and a second SCADA server configured so as to be able to receive a signal relating to an alarm from a PLC. When each of the first SCADA server and the second SCADA server receives a signal related to an alarm from the PLC, the first SCADA server and the second SCADA server generates alarm data in which the signal related to the alarm is endowed with the current time, and transmits the generated local alarm data to the SCADA server of the opposite side. In addition, remote alarm data is received from the counterpart SCADA server. In addition, when at least one of the local alarm data and the remote alarm data is acquired, any one of the local alarm data and the remote alarm data is selected according to a predetermined rule.

The embodiment of the present application provides a method and device for sending a penetration handshake packet, comprising: receiving a target connection request from a platform server by a device end, wherein the target connection request carries a first smooth round trip time between a client and a first network address translation device, and a second smooth round trip time between the client and the platform server; receiving a time delay acquisition response from the platform server by the device end, wherein the time delay acquisition response carries a third smooth round trip time between the platform server and a second network address translation device; determining a target time for sending the penetration handshake packet to the client according to the first smooth round trip time and the second smooth round trip time, and the third smooth round trip time by the device end, and sending the penetration handshake packet to the client at the target time. Through the present application, the problem of NAT penetration failure caused by the time sequence difference of the connectivity detection message reaching the exit NAT of the opposite end in the related art is solved.

The invention discloses a time delay optimization method based on cloud computing, and the method comprises the following steps: S1, collecting a historical access data record of a user in a current edge server, and inputting the request data of the user into a system; s2, when a user side receives a user request, a system sends out an electric signal to start a node optimization module, the data volume, the priority evaluation grade and the node load rate of to-be-processed data of a node start to be analyzed, and the load of the node is adjusted according to an analysis result; s3, when the edge server and the central server synchronize data, a data management module is started, a transmission path is started to be adjusted, and the efficiency of data synchronization between the servers is adjusted; and S4, responding to the access request of the user according to the access request analysis result of the user. The method has the characteristics of reducing time delay and improving efficiency.

The application discloses a kind of based on reinforcement learning's internet of things terminal remote upgrading method and device, it is related to internet of things technical field, the method includes by gateway sends upgrade request to internet of things terminal, to notify internet of things terminal to carry out remote upgrading, the upgrade request includes the address of update server, the latest deadline of remote upgrading;The flash area of internet of things terminal is divided, and flash is divided into application software program area and upgrade boot program area;Internet of things terminal receives upgrade request and switches interrupt vector table from application software program to upgrade boot program, carries out distributed autonomous upgrading decision based on reinforcement learning algorithm;Based on FTP protocol, communication between internet of things terminal and update server, to download the file required for updating, and carry out the update of Q table, and carry out the update of application software firmware.The application can guarantee the reliability of remote update upgrading.

The utility model discloses a server indirect liquid cooling radiator based on a heat pipe, which comprises a base, a supporting boss is formed on the upper surface of the base, the upper surface of the supporting boss is fixedly connected with a liquid cooling part, the heat pipe is arranged in the liquid cooling part, and the heat pipe is attached to a heating surface of a server. The liquid cooling part comprises a mounting body, mounting grooves are formed in the upper part and the lower part of the mounting body, liquid cooling pipes are fixedly connected to the inner parts of the mounting grooves in a manner of being attached to the bottom walls, a plurality of disturbers are arranged in the liquid cooling pipes, and the disturbers can promote cooling liquid to move in the radial direction of the liquid cooling pipes. According to the utility model, through the arrangement of the disturber, the cooling liquid can move along the radial direction of the liquid cooling pipe, so that the cooling liquid flow layer with higher temperature close to the condensation section of the heat pipe is effectively mixed with the flow layer with lower temperature, the heat is quickly and uniformly diffused in the whole cooling liquid, and the heat dissipation effect is improved; therefore, the server indirect liquid cooling radiator based on the heat pipe has an ideal heat dissipation effect.

The invention relates to a DNS encrypted transmission and flow dynamic allocation method and system based on TLS, and the method comprises the steps: executing a TLS protocol handshake to generate an encrypted transmission channel through building a TCP connection, and limiting an 853 port to only receive a TLS handshake message; the encrypted DNS query is sent and processed through the encrypted transmission channel, and the transmission efficiency is optimized by using pipeline scheduling and a disordered response mechanism; by monitoring a network state and a server load, an encrypted transmission mode or an unencrypted transmission mode is dynamically switched based on a preset threshold value. By decoupling the DoT module and the recursion function, flexible configuration and dynamic loading are supported, full-process encryption communication between the recursion server and the authoritative server is achieved, and the problem that in the prior art, a safety link is incomplete is solved. A dynamic allocation mechanism is introduced, encrypted and unencrypted paths are intelligently switched according to the network state and the load, and the safety and the availability are balanced.

The application provides a multi-connection and diversity liquid distributor for a data center cabinet, which comprises a distributor and a liquid collector, the distributor and the liquid collector are installed on a side plate of the cabinet, the extension direction of the distributor is parallel to the extension direction of the liquid collector, the distributor is provided with a distribution outlet, the liquid collector is provided with a liquid inlet, the distribution outlet is connected with a cooling inlet of a server in the cabinet, and the liquid inlet is connected with a cooling outlet of the server in the cabinet. The multi-connection and diversity liquid distributor for the data center cabinet can be flexibly adjusted according to the layout and the number of the servers, the cooling system does not need to be reconfigured, the production cost is reduced, the distributor and the liquid collector are arranged at intervals from the servers, and the overall safety is improved.

The invention discloses a zero-trust service access method and device, equipment and a storage medium, and relates to the technical field of network security, and the method comprises the steps: collecting user authentication information through employing a target webview assembly, and transmitting the user authentication information to a zero-trust authentication platform, thereby carrying out the identity authentication of an SDP client, and generating dynamic authorization information; receiving the dynamic authorization information, and sending an SPA request to the zero-trust authentication platform by using the target webview component so as to open a target firewall port; and establishing an encryption tunnel between the local and the target server based on the target webview component, and performing service access on the target server based on the encryption tunnel and the dynamic authorization information. An encryption tunnel with the target server is established through the webview component, service access is carried out, the range of zero-trust network control is limited in the application of the integrated component, and the problem that the influence range of a zero-trust mechanism is too large is avoided.

The data processing method and apparatus provided by the present invention can be applied to an intermediate proxy device. In a session established by the intermediate proxy device for a client and a server, the method determines a session to be decrypted; detects a session to be decrypted including an encrypted connection request session and uses it as a target session; obtains message key information of the target session, where the message key information is obtained by the intermediate proxy device during the encrypted connection proxy process between the client and the server; and decrypts the transmission message of the target session based on the message key information. The present invention can detect the target session through data detection, thereby effectively detecting and decrypting the transmission message between the client and the server that needs to be decrypted. While effectively decrypting the message, the method avoids decrypting the transmission message between the client and the server that does not need to be decrypted, effectively avoiding unnecessary consumption of decryption resources and ensuring the utilization rate of decryption resources.

The invention provides an RDMA network performance abnormity diagnosis method under set communication. In a collective communication process, firstly, a monitor located at a server side executes algorithm disassembly in advance, monitors related performance information of a collective communication flow in real time according to steps, and reports the related performance information to an analysis server; the monitors inform the servers of waiting relations by sending Notification packets among the monitors, adaptively execute an appropriate anomaly detection triggering process when performance anomaly occurs, send a polling query data packet to the switches through the servers, trigger telemetry information collection on all the switches related to the anomaly, and report the telemetry information collection to an analysis server in sequence; and finally, the analysis server constructs a waiting relation graph and a network traceability graph, and comprehensively analyzes the waiting relation graph and the network traceability graph to give a diagnosis result. The problems that in a set communication scene, existing analysis modes such as a network traceability graph cannot give the overall performance bottleneck of set communication and cannot give contribution evaluation of flow to overall set communication performance abnormity and the like are solved.

The present invention discloses a cloud computing-based latency optimization method, which is applied to a cloud computing-based latency optimization system. The method includes a data collection module, a loading management module, and a server management module. The method is characterized in that: the data collection module is used to collect user historical access data and user operating habits, and enter the data to be processed into the system; the loading management module is used to analyze the characteristics of user access data, and select corresponding data to be pre-loaded in the edge server based on the data characteristics; the server management module is used to optimize the load of the server processing node and the data synchronization between servers; the data collection module, the loading management module, and the server management module are communicatively connected to each other; the data collection module includes a data collection module and a data entry module; the data collection module is used to collect user historical access data. The present invention has the characteristics of reducing latency and improving efficiency.

The utility model discloses a helium cooling system suitable for a high-density air-cooled cabinet, and the system comprises a sealing box which is internally provided with a sealing cavity, the interior of the sealing cavity is suitable for the arrangement of a server, and the interior of the sealing cavity is filled with helium; the driving part and the server are arranged in a spaced mode so as to drive the helium to flow in the sealing cavity in the direction from the driving part to the server; and the heat exchanger is arranged between the driving part and the server so as to exchange heat with the helium. According to the helium cooling system disclosed by the utility model, the helium is adopted as a heat exchange medium, and the nitrogen flows to the server after passing through the heat exchanger to cool the server, so that the overall heat exchange capability of the cooling system is improved, the heat dissipation requirement of the server is met, static electricity is not easy to generate, and equipment damage caused by the static electricity can be reduced; while the heat dissipation requirement of the server is met, original cooling parts are reserved as much as possible, the system modification cost is reduced, and the economical efficiency is improved.

The application discloses a constraint-aware heterogeneous cluster fair scheduling method and system based on space-time sharing. The method comprises the following steps: obtaining a task execution request of a user, and constructing a task constraint matrix; generating a task execution list based on space sharing and maximum minimum fairness; performing constraint-aware fair scheduling among servers, and allocating a target server for a highest priority task; performing round-based time sharing dynamic adjustment until the end of the current round of time; and continuously performing round scheduling until the task execution list is empty. The constraint-aware heterogeneous cluster fair scheduling method based on space-time sharing comprehensively considers task constraints and heterogeneous resource fairness, thereby coordinating and managing distributed computing tasks, ensuring fairness among users, and improving computing efficiency.

This invention belongs to the field of edge computing technology, specifically disclosing a method and system for edge computing deduplication. The method treats all servers in the edge computing network as agents, with each agent transmitting information to all neighboring agents. An objective function is established using data deletion loss, deduplication benefit, and load balancing benefit. The data deletion loss represents the impact of a deletion scheme between two neighboring servers on the service quality of users within their coverage area. The deduplication benefit measures the retention of local duplicate data after a server deletes locally cached data. The load balancing benefit represents the cache occupancy between two neighboring servers at the network edge after implementing a deletion allocation scheme. Under hard constraints, the objective function is solved to obtain the deduplication scheme. This technical solution interacts with neighboring information, makes decisions based on local and regional information, solves the problem, and protects privacy.