23 results about "Resource virtualization" patented technology

The invention discloses a coordinated regulation and control method for a comprehensive energy system to participate in multiple frequency modulation services of a power grid, and the method comprises the steps: collecting the operation state data of four resources, carrying out the preprocessing of the operation state data, obtaining the original data of the resources, constructing four resource virtualization energy storage models, and bringing the original data of the resources into the four models. The method comprises the following steps: respectively obtaining adjustable energy and power boundaries, constructing a virtual energy storage model, uniformly mapping four resources into a virtual energy storage data set through the virtual energy storage model, substituting the virtual energy storage data set into a multi-frequency modulation collaborative optimization model, obtaining an optimal scheduling result, and realizing model flexibility. And the coordination control between each subsystem in the IES and the power grid is realized, and the coordination operation mechanism of multiple auxiliary service markets is perfected.

The invention discloses a switching communication device, a switching communication method and a server, relates to the technical field of computers, and realizes equipment-level decoupling and resource pooling basis by actively managing a GPU (Graphics Processing Unit) through a second interface configured to be in a root complex mode. The on-chip management system and the switching logic module form a control core, a data switching strategy is dynamically executed, and conversion from passive forwarding to autonomous management is achieved. And the virtual port module performs software definition and dynamic allocation on network resources, so that the flexibility of resource utilization is improved. Meanwhile, MAC ports in two modes of direct connection and exchange are supported, so that the device can flexibly construct a high-performance direct connection network or a large-scale exchange network, and the limitation of fixed topology is broken through. And the data processing module ensures high efficiency of data conversion between different interface protocols. According to the device, the communication efficiency and schedulability between the GPUs are improved by integrating high-speed exchange, intelligent management, resource virtualization and flexible networking capabilities.

The application discloses a kind of switching communication device and method, server, it is related to computer technical field, by being configured as the second interface of root complex mode actively manages GPU, equipment level decoupling and resource poolization foundation are realized.The on-chip management system and switching logic module constitute control core, dynamically execute data exchange strategy, realize from passive forwarding to the change of autonomous management.Virtual port module carries out software definition and dynamic allocation to network resource, improve the flexibility of resource utilization.Meanwhile, support the MAC port of two modes of direct connection and switching, so that device can flexibly build high-performance direct connection network or large-scale switching network, break the limit of fixed topology.Data processing module then ensures the efficiency of data conversion between different interface protocols.The device improves the communication efficiency and schedulability between GPUs by integrating high-speed switching, intelligent management, resource virtualization and flexible networking capabilities.

The invention provides a power line communication resource virtualization collaborative networking method and system, and the method comprises the steps: carrying out the data collection and feature extraction of each node in a power line communication network, generating a communication feature vector, constructing a communication state sensing network based on the communication feature vector, constructing a virtual resource transaction market based on the communication state sensing network, and carrying out the resource virtualization collaborative networking. Performing pre-training by adopting multi-agent reinforcement learning, acquiring communication service demand data, generating a communication service resource demand list, inputting the communication service resource demand list into a virtual resource transaction market for resource transaction, generating an initial resource transaction contract, and performing resource transaction on the initial resource transaction contract; and processing the initial resource transaction contract based on a transaction contract generation mechanism, generating a resource transaction contract, executing the resource transaction contract, monitoring and obtaining a communication networking effect in real time, and performing feedback optimization according to the communication networking effect, thereby realizing efficient and reliable distribution of communication and computing resources.

The application relates to the technical field of distributed computing resource scheduling, and discloses a Xinchuang cloud resource scheduling method and system based on a multi-core architecture. The method comprises the following steps: collecting load data and chip integration information to generate real-time monitoring results; performing node grouping by using a load balancing algorithm according to the monitoring results to determine resource allocation requirements; when the node load exceeds a preset threshold, triggering a resource virtualization technology to perform resource remapping to obtain node resource configuration; constructing a cluster structure based on the new configuration and determining a resource reconstruction scheme; performing data migration according to the reconstruction scheme, generating a migration path by using a compatibility interface algorithm and verifying state synchronization integrity; when the synchronization is complete, activating a dynamic management strategy to optimize a resource allocation model. The application can improve the resource utilization rate and parallel processing capacity of the multi-core cluster, solves the problems of low efficiency and stability caused by uneven resource distribution and load surge in the Xinchuang cloud environment, and realizes efficient and self-controllable utilization of resources.

The invention relates to the technical field of unmanned collaboration and resource virtualization, and provides a task collaboration-oriented unmanned system virtual resource representation and organization method and device and a storage medium. The method comprises the following steps: firstly, determining physical resource virtualization granularity (platform level, equipment level and function unit level) according to unmanned collaboration styles (task level, resource level and element level); secondly, establishing a resource tree model comprising a resource base class, an attribute resource, a data table resource and a resource sub-tree based on granularity; resource storage is carried out by utilizing an organization structure constructed by a hash table, a list and a set; and finally, forming a resource pool through standardized packaging, providing management interfaces (resource registration, cancellation and state maintenance) and scheduling interfaces (demand response, resource allocation and release), and realizing resource addressing by adopting URI coding. According to the method, the problems of low task execution efficiency, insufficient resource utilization rate and complex management caused by poor coordination task and resource adaptability, non-uniform heterogeneous resource description and non-standard packaging are solved.

The invention provides a distributed edge machine room computing power integration method and system based on a DPU, and relates to the field of processors, and the method comprises the steps: transmitting parameter copy management data and consistency control function data to a DPU layer corresponding to a DPU card deployed in an edge machine room, and obtaining a target DPU layer; constructing a hardware hierarchical communication topology combining aggregation in the machine room and cross-machine room controlled transmission in the target DPU layer to obtain a target DPU, and executing bandwidth sensing, QoS scheduling, cross-machine room parameter coordination and traffic shaping control through the target DPU; the gradient processing and parameter synchronous control logic data corresponding to the edge machine room are transmitted to a target DPU, and hardware-level unloading and cross-machine-room intelligent scheduling are carried out through the target DPU; gPU resource virtualization and network virtualization control are carried out through the target DPU, so that the multiple edge machine rooms form a unified training resource pool logically, and a distributed edge machine room computing power integration result is obtained.

This invention relates to an open multi-core controller for agricultural machinery and its resource virtualization mapping method. It includes a core board module with a main control processing unit and an expansion board module consisting of input / output circuit units and a cascaded structure including at least two sub-control units. In the method, the main control processing unit generates control commands, and the sub-control units parse the control commands and control the state of electronic components in each topology multiplexing circuit according to the parsing results, thereby changing the electrical characteristics of each physical port and realizing dynamic switching of the same physical port between different operating modes. Compared with the prior art, this invention has advantages such as improved controller interface versatility, expansion flexibility, and ease of software and hardware upgrades and maintenance.

The invention, which relates to the technical field of the data communication network, discloses a multi-service-bearer-oriented production control dedicated data network layered architecture system comprising a physical resource layer, a virtualization service layer, a service arrangement layer and a strategy management layer. The virtualization service layer provides a logically isolated resource pool through a resource virtualization and slicing technology; the service arrangement layer realizes optimal dynamic mapping from service flow to resources based on deep service awareness and a multi-objective optimization algorithm; the strategy management layer integrates security situation awareness and automatic operation and maintenance, and provides global strategy management and control. The invention aims to solve the problems of difficult service quality guarantee, low resource utilization rate and high security risk during multi-service bearing, realizes fine isolation, efficient scheduling and endogenous security of resources through cooperation of the layers, and ensures the service quality and network security of production control services.

The invention relates to the technical field of industrial automation and control, and discloses a sensing and calculation control fusion control method, an industrial control system and electronic equipment. The method comprises the following steps: acquiring multi-source heterogeneous industrial sensor data, generating an environment information model with unified semantics according to the industrial sensor data, and abstracting physical hardware resources into a virtual resource pool through a virtualization technology; automatically identifying a semantic analysis result of the to-be-executed task, and dynamically allocating computing resources from the virtual resource pool according to the semantic analysis result based on a preset dynamic scheduling algorithm; and after the scheduled computing resources are obtained, according to the environment information model, multi-source information is fused to generate an intelligent control instruction, and the intelligent control instruction is issued. The architecture idea of hierarchical decoupling and unified scheduling is adopted, a control method with resource virtualization as a basis, intelligent scheduling as a hub and hybrid drive as a core is constructed, multi-modal sensing processing, intelligent calculation and a high-reliability real-time control kernel are fused in the controller, and physical barriers and communication bottlenecks are eliminated.

This invention provides a method and system for integrating distributed edge data center computing power based on DPU, relating to the processor field. The method involves: transmitting parameter replica management data and consistency control function data to the DPU layer corresponding to the DPU card deployed within the edge data center, obtaining the target DPU layer; constructing a hardware-layered communication topology combining intra-data center aggregation and cross-data center controlled transmission within the target DPU layer, obtaining the target DPU, which performs bandwidth awareness, QoS scheduling, cross-data center parameter coordination, and traffic shaping control; transmitting gradient processing and parameter synchronization control logic data corresponding to the edge data center to the target DPU, and performing hardware-level offloading and cross-data center intelligent scheduling through the target DPU; and controlling GPU resource virtualization and network virtualization through the target DPU, so that multiple edge data centers logically form a unified training resource pool, resulting in the distributed edge data center computing power integration.

This invention provides a perceptual deep learning resource virtualization energy efficiency optimization system, relating to the field of energy efficiency optimization technology. It includes a centralized control platform responsible for overall reactive power coordination and control optimization, and issuing reactive power control commands to subordinate substations; a field automatic controller for receiving SVG signals and commands from the centralized control center in three operating modes; a field device layer including an FC automatic switching electrical cabinet that receives commands from the field automatic controller and controls the on / off switching of internal contactors, thereby achieving automatic capacitor switching; the centralized control platform also includes a dot matrix mapping module; the dot matrix model automatically generates the topology, requiring only the addition of corresponding feature nodes when adding / modifying distribution network equipment, shortening the graphic update time; maintenance personnel can quickly grasp the distribution network status without viewing backend data; the dot matrix graphic links historical data with real-time control strategies, assisting maintenance personnel in accurately judging FC switching needs, avoiding blind operation, and reducing the number of voltage fluctuations caused by improper control.

The invention discloses a nuclear power plant DCS field layer CAN communication simulation system and a nuclear power plant DCS field layer CAN communication simulation method, which adopt a simulation system with a semi-physical architecture, dynamically convert a standard frame / extension frame of physical CAN equipment into a DCS recognizable signal through a bidirectional information mapping engine built in a protocol conversion gateway, and completely simulate CAN non-destructive arbitration logic. The core characteristics of the bus are completely restored; a data link layer fault is dynamically injected through a fault simulation unit integrated by the protocol conversion gateway, and node state machine conversion is realized through a TEC / REC counter; iD conflicts are eliminated through a built-in resource virtualization interface of the protocol conversion gateway in combination with a hierarchical arbitration strategy, meanwhile, communication delay is compressed to be smaller than or equal to 1 ms through a clock offset compensation algorithm, and the time sequence precision is improved by 10 times.

The invention provides a computing power resource virtualization and pooling method and device of an intelligent computing center, and relates to the technical field of intelligent computing centers, intelligent computing centers and computing power infrastructures. The method comprises the following steps: virtualizing a first GPU into N vGPUs, wherein the sum of the computing power of the N vGPUs is consistent with the computing power of the first GPU; and concentrating the N vGPUs into the same resource pool to obtain a target resource pool. Through the method, virtualization and pooling of the computing power resources of the intelligent computing center are achieved, all the vGPUs are independent of one another, operation of the other vGPUs is not affected under the condition that a certain vGPU executes a task, and the condition that the whole first GPU is used for executing a single task is avoided, that is, after virtualization and pooling of the computing power resources are conducted, operation of the other vGPUs is not affected. Different vGPUs can execute different tasks at the same time, so that the waste of computing power resources can be greatly reduced, and the utilization rate of the computing power resources is greatly improved.

The invention relates to the technical field of distributed computing resource scheduling, and discloses a credential cloud resource scheduling method and system based on a multi-core architecture. The method comprises the following steps: acquiring load data and chip integration information, and generating a real-time monitoring result; performing node grouping by adopting a load balancing algorithm according to a monitoring result, and determining a resource allocation demand; when the node load exceeds a preset threshold value, a resource virtualization technology is triggered to execute resource remapping, and node resource configuration is obtained; constructing a cluster structure based on the new configuration, and determining a resource reconstruction scheme; executing data migration according to the reconstruction scheme, generating a migration path by adopting a compatible interface algorithm, and verifying state synchronization integrity; and when the synchronization is complete, activating the dynamic management strategy to optimize the resource allocation model. According to the method, the resource utilization rate and the parallel processing capability of the multi-core cluster can be improved, the problems of low efficiency and stability caused by non-uniform resources and sharp load increase in a credential cloud environment are solved, and efficient and autonomous controllable utilization of the resources is realized.

This application provides a root cause alarm determination method, electronic device, and apparatus, relating to the field of data processing technology. The method includes: acquiring an alarm to be analyzed; determining the target network resource that generated the alarm; for the alarm to be analyzed, determining associated alarms generated by network resources belonging to the same combined topology as the target network resource within a preset time period, the preset time period including the time when the alarm to be analyzed was generated, each combined topology including at least one of the following network resources ordered from low to high hierarchy: network layer resources, server layer resources, virtualization layer resources, system layer resources, middleware layer resources, and application layer resources, with association relationships between network resources of the same or adjacent levels; and determining the lowest-level associated alarm of the targeted network resource as the root cause alarm that caused the alarm to be analyzed. The solution provided by this application can determine root cause alarms.

This invention relates to the field of information technology and provides a resource virtualization and resource scheduling architecture for a general resource management platform. This application aims to solve the problems of difficult deployment and reuse of application services developed on a general resource management platform. The main solution includes a management agent, a device resource virtualization combination service, an application resource virtualization combination service, and a device / application resource scheduling combination service. The management agent is responsible for dynamically generating the above services and manipulating the resource tree to form a complete service resource virtualization framework process. During the initialization of the general resource management platform, it is responsible for loading the service virtualization configuration file and constructing the device resource tree and application resource tree on the platform according to the resource tree structure. Next, according to the service combination configuration, the source code and compilation scripts of each service module are recursively concatenated according to the service slot matching relationship to generate a single complete executable module, which is dynamically loaded into the general resource management platform for execution.

The invention provides a perception type deep learning resource virtualization energy efficiency optimization system, and relates to the technical field of energy efficiency optimization, and the system comprises a centralized control platform which is responsible for global reactive power coordination control optimization and sends a reactive power control instruction to a subordinate transformer substation; the on-site automatic controller is used for receiving three operation modes of SVG signals and centralized regulation and control center instructions; the field equipment layer comprises an FC automatic switching electrical cabinet and is used for receiving an instruction transmitted by the field automatic controller and controlling the on-off of an internal contactor so as to realize the automatic switching of the capacitor; the centralized control platform further comprises a dot matrix mapping module; the dot matrix model automatically generates topology, only corresponding feature nodes need to be added when distribution network equipment is newly added / transformed, and the graph updating time is shortened; operation and maintenance personnel can quickly master the distribution network condition without checking background data; the dot-matrix graph is linked with historical data and a real-time control strategy, operation and maintenance personnel are assisted in accurately judging FC switching requirements, blind operation is avoided, and the voltage fluctuation frequency caused by improper control is reduced.

The invention relates to the technical field of broadcast television and virtual-real fusion, and particularly discloses a studio virtual-real picture synchronous tracking and fusion system which comprises a multi-sensor fusion tracking module, a full-IP synchronous control module, a virtual-real fusion rendering module and a multi-program sharing scheduling platform. The multi-sensor fusion tracking module fuses various sensor data and outputs high-precision six-degree-of-freedom pose information; the full-IP synchronous control module controls a synchronous error within 10ms based on PTP (Precision Time Protocol) synchronization and dynamic delay compensation; the virtual-real fusion rendering module combines AR / MR rendering, digital twinning and artificial intelligence to realize seamless fusion of virtual and real pictures; the multi-program sharing scheduling platform realizes resource virtualization and flexible reuse. The method solves the tracking defect of a single sensor, improves the virtual-real synchronization precision and visual expressive force, reduces the operation and maintenance cost, improves the intelligent level of news production, and is suitable for studio live broadcast and other scenes.

The embodiment of the invention provides a high-computing-power scene-oriented container elastic computing power conveying method, device and equipment and a medium. The method comprises the following steps of: acquiring a computing power task sent by a client; determining a target container matched with the computing power task in a container cluster; the container cluster comprises a plurality of containers; the container is obtained by virtualization according to computing power resources in the computing power platform; processing the computing power task through the target container to obtain a processing result; sending a processing result to the client; through a mode of acquiring the computing power task sent by the client and accurately matching the target container, computing power resources can be quickly matched with specific task requirements, and mismatching and waste of the computing power resources are avoided; as the container is generated based on the computing power resource virtualization of the computing power platform, the flexible characteristic of the container can fully adapt to the requirements of complex model and large data volume in a large computing power scene, and the utilization efficiency of the computing power resource is improved.

The invention relates to the technical field of computer servers, in particular to a server and a server design method.The server comprises a basic framework unit, a heterogeneous computing module, an intelligent storage module, a configurable network module, an intelligent management control unit and a system firmware layer which are interconnected through standardized interfaces; the management control unit drives calculation, storage and network resources to perform collaborative dynamic reconstruction through real-time monitoring and AI prediction; the design method comprises six systematic stages of demand analysis, modular design, resource virtualization, dynamic reconstruction mechanism design, energy efficiency optimization and reliability design. According to the method, the problems of low utilization rate, poor expansibility and low energy efficiency caused by static configuration of traditional server resources are solved, on-demand accurate supply of the resources is realized, the resource utilization rate, the energy efficiency ratio and the cross-scene adaptive capacity are remarkably improved, and the method can be widely applied to the fields of cloud computing, high-performance computing, edge computing and the like.

The invention discloses a universal electrical equipment control system, method and device based on hardware resource virtualization and software defined logic. The system comprises a central controller, a system bus and at least one programmable controlled terminal. The core innovation is as follows: the terminal is universal hardware which is internally arranged or can access a control logic function library and can be remotely defined by a logic mode code issued by the central controller, and the lifelong software reconfiguration of a hardware logic function is realized by calling a preset function or loading a configuration module to dynamically instantiate and solidify. The terminal is integrated with a state monitoring circuit, real-time feedback of the load state is achieved, and the central controller conducts trend analysis on data based on self-adaptive baseline modeling so as to achieve predictive maintenance. The system adopts a daisy chain bus to realize extremely simple deployment, and supports local direct connection control such as radio frequency remote control to realize common interaction. According to the invention, an evolvable, highly reliable, green and energy-saving open type general control platform with intelligent operation and maintenance capability is constructed.

The invention discloses a serial port multiplexing method and device, equipment, a medium and a product. The method comprises the following steps: acquiring a first communication instruction corresponding to a physical serial port; determining a first resource scheduling strategy under the first working scene according to an instruction mode corresponding to the first communication instruction; based on a first resource scheduling strategy, determining a first target communication task in communication tasks corresponding to a plurality of virtual serial ports corresponding to the physical serial port; and mapping the read-write request of the first target communication task to the physical serial port. The current working scene of the serial port is automatically identified through an instruction mode, the number limitation of physical serial ports is broken through based on the resource virtualization of virtual serial ports according to the service quality requirements of different working scenes, the resources of the serial ports are dynamically and differentially distributed, the serial port communication strategy is adjusted, physical serial port hardware does not need to be added, and the communication efficiency is improved. Therefore, the multi-task parallel communication requirement can be supported, so that the optimization of the overall communication efficiency is realized under the condition that the resources are limited.