1881 results about "Virtualization" patented technology

The present invention relates to adaptive multi-state encoding and processing in virtualized computing environments. The system includes a virtualized state selection module that dynamically transitions between binary, ternary, quaternary, and higher-order encoding states based on workload, bandwidth, security posture, and compliance requirements. A virtual encoding engine utilizes hardware-accelerated components, such as vFPGAs, vGPUs, and cTPUs, to enhance encoding throughput. A compliance-driven feedback controller continuously monitors encoding efficiency, threat levels, and adherence to mandates such as GDPR, HIPAA, and FIPS 140-3. Additional features include AI-based anomaly detection, federated model refinement, distributed ledger-backed audit trails, and quantum-resistant encoding techniques. By integrating intelligent encoding decisions with scalable compliance enforcement, the system enables high-performance, secure, and regulation-ready data processing across distributed cloud and edge environments, delivering measurable improvements in system responsiveness, data integrity, and operational trust.

The invention discloses a compatible operation method for an Android camera HAL in a container based on memory access virtualization, and the method comprises the steps: taking a DMA-Buf memory heap of a Linux kernel host system as a target memory heap, taking an ION memory heap of an Android container system as a source memory heap, building a process exclusive memory management context, an FD cache table and a synchronous fence pool, and carrying out the execution of the process exclusive memory management context, the FD cache table and the synchronous fence pool; kernel registration and node binding of virtual ION equipment, pre-allocation of a first memory pool and access hook registration of kernel layer equipment are completed, and when an ION file descriptor is obtained in an HAL process, legality of a container process is verified, and context binding is initialized to the file descriptor; intercepting a memory allocation request of the HAL process, analyzing and adapting parameters, and preferentially multiplexing first memory pool resources to obtain an ION handle; when a data sharing request is processed, matching an FD cache or generating a new FD through an ION handle; when the HAL process releases the memory, resources are recycled according to a memory source, and when the HAL process exits, the context is cached or destroyed, so that cross-system memory operation compatibility is realized.

The invention relates to a server cluster monitoring system based on multi-node collaboration and an implementation method thereof, a dynamic topology network module is configured to reconstruct a connection topology among monitoring nodes in real time according to node performance and link quality, support mixed configuration of a star type, a ring type and a net structure, and realize multi-node collaboration. Multi-dimensional data capture from a physical layer to an application layer is realized through a cross-level index acquisition module based on an integrated hardware sensor interface and a virtualization layer probe, and each node is enabled to perform collaborative reasoning through parameter encryption sharing through a decision model based on federated learning. A monitoring task fragmentation strategy is dynamically adjusted through an adaptive elastic fragmentation unit according to network delay and load fluctuation, and an abnormal event association rule base is updated in real time through an incremental knowledge graph construction unit. High availability and elastic expansion are realized through a multi-node collaborative architecture, the monitoring efficiency is improved in combination with dynamic load balancing and hybrid detection, and an intelligent multi-level response mechanism is constructed to guarantee the service continuity.

The invention relates to the technical field of virtualization management, in particular to a virtual machine operation management system based on RISC-V. The system comprises an instruction set mapping module, a resource scheduling optimization module, a virtual machine monitoring integration module, an operation tuning update module and an operation configuration distribution module. According to the method, by analyzing the operation instruction of the virtual machine and combining the RISC-V underlying characteristics, accurate instruction mapping is achieved, the processing efficiency and accuracy are remarkably improved, the performance loss and conversion delay caused by too high abstraction level of a traditional virtual machine on the instruction level are overcome, the optimal allocation scheme is screened, the resource utilization rate and the system response speed are effectively improved, and the system performance is improved. The operation state and performance indexes of the virtual machine are integrated, anomaly detection and resource recovery are embedded, system stability and effective resource reutilization are ensured, basic configuration is continuously and incrementally updated, operation configuration refinement and automatic management and updating are achieved, the overall operation efficiency and management flexibility are improved, and the manual intervention cost is reduced.

The invention relates to a GPU resource space-time slicing and dynamic reconstruction virtualization method and system based on AI training, and the method comprises the steps: receiving an AI training task, obtaining the task feature data of the AI training task, and transmitting the task feature data to a task prediction model; the task prediction model outputs a training demand portrait of the current AI training task based on the task feature data, and the training demand portrait comprises an estimated computing power demand, a peak video memory demand, an expected running time length and a task priority; based on the training demand portrait, a preset AI scheduler generates a vGPU slicing strategy corresponding to the AI training task according to the current GPU resource distribution condition; operation information of each vGPU is obtained in real time and updated to the GPU resource pool, and the computing power or the video memory size of the vGPU in operation is adjusted in real time according to the training demand portrait. The method has the advantages that the dynamic allocation capacity of the GPU load resources is improved, and therefore the task training efficiency of the GPU is improved.

The invention provides a rail transit power supply digital twin system and a construction method, and relates to the technical field of data processing, and the method comprises the steps: constructing an urban rail transit power supply system digital twin model, achieving the digital virtualization associated with a physical entity, completing the model rendering, and displaying the state of the entity through a virtual model; according to the entity state, operating parameters of a substation and key equipment of a contact network are collected through a sensor and a hardware device; the operation parameters are cached by the station-level monitoring device body through the double-ring network architecture and then scheduled to a cloud platform communication ring network node, a data transmission path is optimized based on a load balancing strategy, and the data are uploaded to a cloud platform in real time. The management level can be improved, the operation and maintenance cost can be reduced, and a foundation is laid for intelligent operation and maintenance of a rail transit power supply system.

The invention discloses a distributed training scheduling and communication optimization method and system of a multi-modal large model on a domestic computing power platform. The method comprises the following steps: virtualizing a heterogeneous computing unit of a preset platform into a virtual device pool, and fusing first-order gradient of a multi-modal sample and Hessian matrix information based on quantitative perception training to generate a sample sensitivity grading atlas; virtual device pool attributes and the sensitivity grading atlas are used as input, an optimal hybrid parallel configuration scheme is automatically generated through a configuration search algorithm, and a parallel combination mode, resource mapping and a high-sensitivity sample scheduling strategy are defined; a distributed training code of an integrated communication optimization strategy is automatically generated according to a configuration scheme, pipeline parallel communication and data parallel gradient synchronization constraint are executed in a topology adjacent equipment subset, and a hierarchical aggregation mechanism is adopted; and dynamically screening a core training set and scheduling a calculation task to complete distributed training. According to the method, efficient cooperative training of the multi-modal large model on the domestic computing power platform is realized.

The invention relates to the technical field of computer hardware and network communication, in particular to a high-speed I / O (input / output) virtualization server based on an FPGA (field programmable gate array) and a remote forwarding method.The high-speed I / O virtualization server comprises an FPGA chip, a network processing unit, an I / O protocol processing unit, a protocol conversion and scheduling unit, a time sequence and transaction management unit and a data buffering and flow control unit are integrated in the FPGA chip; the optical fiber Ethernet interface module comprises a physical layer interface and an MAC layer processing and network configuration interface; the local I / O interface module comprises a USB interface circuit, a serial port interface circuit, a PCIe interface circuit and an interface expansion connector; the power supply and monitoring module comprises a multi-path power supply management system, a state monitoring and diagnosis system and an LED indication system; according to the self-adaptive Baud rate detection circuit, the Baud rate can be accurately locked under the condition that data with less than two characters is received, the number of data bits, the type of a check bit and the length of a stop bit are automatically identified, and compared with a traditional microcontroller scheme, the self-adaptive Baud rate detection circuit has higher precision and higher detection speed.

The embodiment of the invention provides an AI large model training resource dynamic scheduling method and device based on a VGPU, and effective planning of resources is realized through innovatively designing a resource prediction system and through index analysis and demand prediction. A multi-target scheduling mechanism is constructed, and a reliable scheduling strategy is established in combination with competition analysis and scheme screening. Virtualized isolation is introduced, and the training stability is ensured through VGPU and resource control. According to the method, the defects of the traditional technology in the aspects of resource prediction, scheduling optimization, virtualization isolation and the like are effectively overcome, and technical support is provided for large model training.

The invention relates to an enterprise data operation multi-source data virtualization access and index automatic management and control method and system, belongs to the technical field of computers, and aims to solve the problems of index definition fragmentation, frequent logic conflicts, dependency static management and verification rule rigid coupling in the prior art. Comprising the following steps: constructing a unified virtualized data access layer to integrate heterogeneous data sources; the indexes are disassembled into semantic atoms capable of being managed in a versioning mode and registered to an atom knowledge base; dynamically constructing an index dependency relation directed acyclic graph based on semantic atom combination; dynamically binding the data quality rules with semantic atoms; and analyzing an index request through a virtualized query engine, reversely traversing atlas aggregation dependency and rules, generating and executing local query, and automatically checking result data quality at the same time. According to the method, unified index definition, dependence on automatic conduction, quality embedded verification and multi-source transparent access are realized, and the data consistency, the treatment efficiency and the system flexibility are remarkably improved.

The invention discloses a Linux container-based Android and open source gap dual-system collaborative operation method, relates to the technical field of operation system collaboration, and aims to reduce resource occupation and improve collaboration and switching coherence, and the method comprises the following steps: step 1, by taking an Android as a host, creating a container isolation running domain, starting a namespace and managing resources by a control group; the method comprises the following steps: presetting a binder virtualization and three-state template; 2, deploying an open source gap in a container, mounting a shared directory in a directory binding manner, configuring bridging or address translation, and establishing copy-on-write and snapshot identifiers; and step 3, establishing a cross-system binder channel, and setting a service registration agent in a service manager and completing mapping of a handle and an authority domain by combining a shared memory and a local socket. And step 4, executing system switching without restarting, enabling one foreground and the other background through a foreground interface and continuous quota assignment, freezing a background session, limiting the speed of background heartbeat, and returning according to a snapshot when an exception occurs.

The invention discloses a trusted execution environment construction method, system, equipment and medium for electric power intelligent equipment, and relates to the technical field of electric power intelligent equipment monitoring, and the method comprises the following steps: carrying out Hash measurement on a to-be-detected area in an operating system kernel, carrying out comparison based on a preset reference value, and monitoring the consistency of kernel static data and codes; performing list management and integrity verification on the system kernel module, and identifying illegal loading, unloading or tampering behaviors; monitoring a kernel module event, sensing the change of the life cycle of the module and dynamically triggering a verification mechanism; performing Hash verification on an execution file of the specified user space process, and identifying process-level illegal replacement or injection behaviors; and updating the trusted measurement database based on a detection result, and executing log recording, alarming and blocking strategy response. The method does not depend on a chip, a virtualization platform or hardware extension, realizes security monitoring only through a software means, and is suitable for an embedded terminal with limited resources.

The invention belongs to the technical field of computer server management, and particularly discloses a laboratory collaborative environment-oriented user and data full-life-cycle server management system, which comprises a container virtualization layer, a server management layer and a server management layer, dynamic resource allocation is supported through a state saving-resource reallocation-environment recovery mechanism; the heterogeneous transaction coordination layer adopts a Saga transaction mode to coordinate a heterogeneous system so as to realize cross-system transaction consistency; the data collaboration ecological layer establishes typed management of a personal data volume, a shared software environment volume and a public data set volume, and supports software environment encapsulation sharing and versioning management; and the metadata management layer realizes real-time update and high-performance query of metadata based on a Redis hot update architecture. According to the method, the problems of inflexible resource allocation, incomplete environment isolation, dilemma in authority management and difficulty in data collaboration and recovery in the prior art are solved.

A system for analyzing a computing system for potential breach points, the system comprising a memory device having executable instructions stored therein, and a processing device, in response to the executable instructions, configured to parse a breach scenario file, the breach scenario file comprising a graph including action component nodes connected by edges, determine a root node from the action component nodes, execute the root node with breach point data, generate a root node return value based on the execution of the root node, the root node return value including a modified copy of the breach point data, determine children nodes from the action component nodes connected to the root node, execute the children nodes wherein each execution of the children nodes produces children node return values for a subsequent one of the children nodes, and return a final return value from the execution of the children nodes.

The invention discloses a virtual machine memory processing method and device, a product, a virtualization server and a medium, and relates to the field of server virtualization. In the method, through a virtual input and output rear-end module arranged on a virtual machine monitor in a host and a virtual input and output front-end module on a virtual machine, it is ensured that the virtual input and output rear-end module can obtain information of a memory allocation event of direct memory access; secondly, after acquiring the information of the memory allocation event of the direct memory access, the virtual input / output rear-end module locks the address related to the memory allocation event, namely, the locked address meets the direct memory access requirement, and the memory of the virtual machine is dynamically locked, so that the memory utilization rate is improved, and the waste of resources is reduced; and only part of the memory of the virtual machine is locked, and only the locked memory part is migrated after the host is replaced, so that the amount of data to be migrated after the host is replaced is reduced.

The invention relates to a heterogeneous AI computing virtualization architecture and slice enhancement method and system, and the method comprises the steps: evaluating the demands of an AI task for GPU resources through an analytic hierarchy process, and dividing the GPU resources into ultrafine-grained slice units according to an optimization model; predicting a resource demand through an ARIMA model, allocating slice resources through a minimum error sum of squares algorithm, and generating a resource allocation scheme; the method comprises the following steps: dividing a GPU into a plurality of independent hardware isolation units based on a resource allocation scheme and GPU hardware topology, and generating a hardware unit configuration table; establishing an isolation mechanism based on the identity information and the ACL, and establishing a software isolation environment; the method comprises the following steps: dividing network partitions, configuring a firewall rule to control network access authority, monitoring network traffic in real time, processing abnormal traffic, and generating a network partition mapping table; gPU resources are abstracted into a logic resource pool, a resource scheduling platform based on an intelligent scheduling algorithm is constructed, and resource scheduling of heterogeneous slices is carried out.

The invention discloses a virtual simulation and security evaluation method and system based on a network security target range, and the method comprises the steps: constructing a network asset knowledge graph for describing a virtualized target range environment through information collection; secondly, based on an attack strategy grammar rule base, adopting a Monte Carlo Tree Search (MCTS) algorithm to carry out intelligent attack simulation on the knowledge graph so as to discover a nonlinear and multi-stage attack path; thirdly, constructing a Bayesian attack graph (BAG) based on the knowledge graph, and performing probabilistic and systematic quantitative evaluation on the security risk of each asset node in the network through Bayesian reasoning; and finally, integrating the attack path and the quantitative risk value, and generating a comprehensive assessment report containing a visual path, a risk sequence and a reinforcement suggestion. According to the target range simulation method and device, the problems that existing target range simulation is insufficient in confrontation authenticity, one-sided in safety evaluation and lack of predictability are solved by combining the strategy simulation of the MCTS and the global quantitative analysis of the BAG.

The invention discloses a tracking connection number control method and device of a virtual machine, equipment and a medium, and relates to the technical field of virtualization, the method comprises the following steps: determining a demand tracking connection number of a host machine according to historical tracking connection number information of the host machine; determining a virtual machine distributable tracking connection number of the host machine according to the total tracking connection number upper limit value and the demand tracking connection number of the host machine; adjusting the tracking connection number upper limit value of each virtual machine according to the virtual machine distributable tracking connection number and the tracking connection number of each virtual machine on the host machine; according to the method, the total tracking connection number of the host machine is divided into the tracking connection number of the host machine and the tracking connection number of the virtual machine, and the tracking connection number required by the follow-up host machine can be predicted by utilizing the historical tracking connection number information of the host machine, so that the tracking connection number of the host machine can be predicted under the condition of ensuring normal communication of the host machine. The tracking connection number of the virtual machine is conveniently and effectively controlled, and the resource utilization rate and safety of the host machine are improved.

The invention relates to the field of digital security assessment, and discloses a data security compliance risk assessment system, which comprises the steps of automatically retrieving data related to a target industry based on a preset network model, extracting a structured risk factor and an aging identifier of the data, and judging whether an index difference exists or not; performing semantic alignment and difference comparison on the output knowledge fragment and a local risk index, and judging whether the credible score of the risk adjustment suggestion exceeds a set threshold value or not; according to the generated updating suggestion, judging whether the updating result identifies a high-risk item or not; in a virtualized security event simulation environment, based on a multi-dimensional logic deduction algorithm, constructing an attack path corresponding to a high-risk item, simulating a multi-scene risk propagation process, calculating a comprehensive risk index and outputting a deduction result; and based on a deduction result, recording a risk propagation path, forming a verified risk knowledge fragment and feeding back the fragment to a safety compliance evaluation database. The method has the advantage of improving the accuracy of the evaluation result.

The invention discloses an agent-free honeypot mapping method and device, and relates to the technical field of network security. The method comprises the following steps: analyzing metadata of core switching equipment, and establishing a domain-address mapping matrix; periodically detecting an address space, constructing an IP asset dynamic portrait and generating an asset state map; deploying a cross-domain traffic forwarding protocol stack and a virtual domain identifier mapping rule; deploying a software-defined virtual switching unit and accessing the virtual honeypot probe cluster; allocating idle addresses for the probes and establishing a binding relationship; and periodically detecting and triggering a self-healing process when an address conflict occurs. The device comprises a core exchange and domain management unit, an IP asset detection unit, a network protocol configuration unit, a probe virtualization management unit, an address resource scheduling unit and a system cooperative control unit. According to the method, agency-free and automatic deployment of the honeypot is realized, and the problems that a traditional scheme depends on agency software, deployment is complex and IP conflict processing lags are solved.

The invention discloses a private key management method and apparatus, and a computer device. The private key management method comprises the steps of obtaining instance binding information sent by a virtualization platform; verifying the instance binding information according to a preset key strategy, and generating a token when the verification is passed; splitting the logic private key based on the birth token to generate a first private key share and a derived parameter used for deriving a second private key share, and performing encryption packaging on the derived parameter by taking the instance binding information as additional authentication data to form a key capsule containing the instance binding information; returning the key capsule to the corresponding instance, so that the instance unpacks the key capsule in the own operating environment and derives a second private key share; and when a signature request sent by the instance based on the second private key share is received, cooperatively generating a signature result based on the first private key share and the second private key share. The security and controllability of private key management can be effectively improved on the premise of not depending on a special hardware module.

The invention discloses a network threat evidence fixation technology for solving source tracing evidence chain deficiency, and belongs to the field of network security. Aiming at the problems of distributed log time sequence chaos, easy tampering of virtual environment metadata, difficult association of cross-platform attack traces and the like existing in the traditional evidence obtaining technology, the invention constructs a technical system of dynamic data capture and space-time fusion modeling, evidence chain reconstruction and distributed verification, anti-quantum storage and security solidification. A self-adaptive sensor network is constructed through an improved BFGS algorithm, a space-time fusion evidence model is provided, and an improved MPT structure and a lattice-based cryptographic algorithm are designed in combination with a time sequence Petr i network and a Byzantine fault-tolerant protocol. Tests show that the attack feature capture rate reaches 91%, the cross-platform attack association accuracy rate reaches 93%, the quantum signature resistance speed is 1200 times per second, and the problem of source tracing evidence chain deficiency is effectively solved.

The invention discloses a full-link analysis display method and device based on routing configuration, a medium and equipment. The method comprises the following steps: collecting and extracting equipment routing data; confirming the type of equipment routing data, and executing data cleaning processing according to the type of the equipment routing data; path acquisition is carried out based on the routing configuration information of the target assets, and three groups of network incoming link diagrams are respectively obtained; and sequentially splicing the Internet network inbound link diagram, the internal network inbound link diagram and the cluster network inbound link diagram to generate a hierarchical whole network link topological diagram, and performing front-end link display on the whole network link topological diagram. Visualization of various assets and internet access links in a virtualized network is realized, and in an actual application scene, problems can be quickly found based on the topological graph of the whole network links according to association of the collected equipment routing data and the security events, the influence range is positioned, and the security response efficiency is improved.

The application provides a data security method, related device and system, the method relates to the field of virtualization, the method is applied to a heterogeneous device, part or all of hardware resources in the heterogeneous device are divided into a trusted execution environment (TEE) side, the TEE side of the heterogeneous device is preset with confidential data, and the method comprises the following steps: a processor of the heterogeneous device verifies whether a virtual machine running on the TEE side of a host can obtain the confidential data in the heterogeneous device on the TEE side; in the case that the virtual machine running on the TEE side of the host cannot obtain the confidential data, the TEE side of the heterogeneous device receives an access request of the virtual machine running on the TEE side of the host to the TEE side of the heterogeneous device. By implementing the embodiment of the application, the confidential data can be protected from being leaked and stolen.

The invention discloses an anti-countercurrent system based on V2G equipment and a control method, and the system comprises at least two charging and discharging modules which are connected to one side of a power line, and the other side of the power line is connected to a power grid; the charging and discharging module comprises a first bidirectional electric meter and a V2G charging pile. One end of the V2G charging pile is connected with the power line through the first bidirectional ammeter, and the other end is connected with the charging terminal. The bidirectional main electricity meter is connected between the power line and the power grid; the contactor is connected between the bidirectional main ammeter and the power line. The anti-countercurrent control module is in communication connection with the bidirectional main electric meter, the contactor, the first bidirectional electric meter and the V2G charging pile; according to the invention, a virtualized anti-countercurrent control architecture is adopted, any V2G charging pile or cloud server is used as an anti-countercurrent control module, a traditional hardware controller is replaced by existing equipment computing power, global power regulation and control are realized based on data provided by the bidirectional main ammeter and the first bidirectional ammeter, and the system deployment cost and complexity are significantly reduced.

The invention discloses an embedded system resource allocation method and system based on hardware virtualization. The method comprises the following steps: deploying a Type-1 virtual machine monitor system on a multi-core processor hardware platform supporting virtualization extension; the Type-1 virtual machine monitor carries out virtualization, resource partitioning and security isolation on hardware resources, and creates operation system execution environment'domain 'partitions zoneG and zoneR. A universal operating system is deployed in a zoneG domain partition to take charge of a high-computing-power computing task, and a real-time operating system is deployed in a zoneR to take charge of a real-time computing task. Low-delay inter-core communication between a real-time operating system and a general operating system is realized based on an OpenAMP protocol, and data is transmitted through a shared memory and an interrupt mechanism; according to the requirements of real-time tasks and non-real-time tasks, a Type-1 virtual machine monitor dynamically adjusts a resource allocation strategy, and the priority and deadline of the real-time tasks are ensured.

The invention discloses an AI dynamic game virtualization resource scheduling system and method for a 5G low-delay service, and aims to solve the problems of insufficient QoS guarantee and low resource utilization rate caused by insufficient static rule adaptability, lack of service differentiation scheduling and low fusion degree of a game model and AI. A service feature extraction module is used for distinguishing a low-delay service (T = 0) and a common service (T = 1), constructing an AI dynamic game model taking the two types of services as participants, defining a payment function comprising a QoS satisfaction function and a resource consumption cost function, solving Nash equilibrium by adopting a deep reinforcement learning algorithm, outputting an optimal resource demand strategy, and realizing the optimal resource demand strategy. And the bandwidth and CPU allocation are dynamically adjusted through the virtualized resource management module. According to the invention, the delay compliance rate of the low-delay service can be improved by 20%-30%, the resource utilization rate of the common service can be improved by 15%-25%, the strategy iteration period is shortened to millisecond level, and differential fine scheduling and dynamic optimization in a 5G mixed service scene are realized.

The invention provides a multi-speech synthesis model bearing method and device based on a virtual GPU, and relates to the technical field of graphics processing units, and the method comprises the steps: carrying out the virtualization processing of a physical graphics processing unit, dividing the physical graphics processing unit into a plurality of virtual processing units with independent video memories and calculation quotas, and combining a resource scheduling mechanism, and deploying the speech synthesis language model instances in a plurality of service containers, and constructing a plurality of speech synthesis model bearing units. After a voice synthesis request is accessed, the scheduling module carries out load balancing according to the request connection number of each bearing unit, the request is distributed to a target bearing unit with the minimum connection number, and a voice generation task is completed by a virtual processing unit bound with the target bearing unit. According to the invention, resource division can be carried out on the physical graphic processing unit, and efficient operation of the multi-speech synthesis model is realized.

The invention relates to the technical field of industrial control system security testing, and provides a construction method and device for a dynamic attack and defense testing environment of an industrial control system. The method comprises the following steps: realizing virtualization operation and behavior modeling of industrial control firmware through a hardware system simulation technology based on logic self-learning; constructing a meta-aggregation data resource pool to realize intelligent scheduling and automatic deployment of industrial control component resources; when it is detected that the behavior of the industrial equipment is abnormal, deviation behavior data are complemented based on a causal relationship reasoning mechanism, and a simulation model is driven to be adjusted; constructing a digital-analog fusion model supporting space-time driving and data synchronization, and realizing data consistency and linkage between a virtual environment and a real environment; an AI agent mechanism is introduced, an attack path is automatically deduced, a defense strategy is optimized, and intelligent evaluation of a drilling process is completed; attack protection scene configuration and control are carried out through an interactive user interface, and simulation and verification operations in a complex dynamic attack and defense environment are realized.

According to the PCIe Switch system and the PCIe switch, a PCIe hardware IP is used as a bottom layer, and a basic PCIe interface function for physical layer and link layer management is provided; and identifying and configuring all connected devices to construct a device address routing mapping table through a Soft Switch IP mounted on the PCIe hardware IP, and determining a specific target of data transmission based on the constructed mapping table so as to route the data to a specific position of the corresponding device. According to the invention, flexible equipment enumeration can be carried out by selecting a pure hardware mode or a software and hardware combined mode according to actual requirements, so that the data can be correctly and efficiently transmitted to the target endpoint from the source equipment, and the complex problems of address resolution and routing management are solved. Compared with the prior art, the method can replace the existing PCIe Switch IP of a manufacturer, provides higher flexibility and expansibility, obtains better balance in the aspect of cost control, and is suitable for various applications needing large-scale PCIe equipment connection, virtualization and high-speed data exchange.