125results about How to "Avoid overhead" patented technology

The invention belongs to the technical field of front-end development, and particularly relates to a React framework-based tree component optimization method fusing virtualization rendering and increment rendering. Comprising the steps of S1, data preprocessing; S2, dynamic virtualization rendering: dynamically calculating a node index range in a visible area according to a real-time scrolling position of a user viewport, only rendering nodes in the range, and realizing seamless lazy loading of data through scrolling event monitoring; s3, intelligent incremental updating: identifying changed nodes through a state change comparison algorithm, and executing local re-rendering only for the changed nodes based on a component life cycle control mechanism of a React framework; and S4, lazy loading cooperative control. The method aims at solving the problems in the aspects of performance, memory management, user experience and the like when a tree component in a React ecological system processes large-scale data, and is widely applied to various Web application program development scenes needing to display and operate a large-scale tree data structure.

The invention relates to the technical field of satellite communication, in particular to a time synchronization method, device and equipment for satellite communication, a medium and a program product. A terminal receives a synchronization signal block broadcasted by a satellite base station to perform preliminary synchronization, and decodes a main information block broadcasted by the satellite base station to obtain a cell-level public timing advance parameter and a time-frequency resource; selecting a lead code and a time-frequency resource in combination with a cell-level public timing advance parameter, initiating a random access request, and sending a first message to a satellite base station; receiving a second message from the satellite base station, wherein the second message comprises a timing advance instruction fed back according to the detection result of the lead code; and adjusting uplink timing synchronization according to the timing advance instruction, and sending a third message to the satellite base station through the physical uplink shared channel. According to the invention, on the premise that an existing preamble format and a timing advance indication range do not need to be changed, a terminal without GNSS capability can also realize initial random access and maintain uplink time synchronization.

The invention provides a dynamic spreading factor anti-interference method based on annealing Q learning. The method comprises the following steps: determining an information transmission rate according to a spreading factor; determining system throughput and an optimization target according to the signal-to-noise ratio of the receiving end; determining a state space, an action space, a state transition probability matrix and rewards in the decision process; calculating a reward obtained by the selection action according to a broadband spectrum sensing result; the interference condition at the current moment is obtained through broadband spectrum sensing; deciding a spreading factor of the next time slot according to the Q value table; the user selects the action of the next time slot according to the decision information and updates the state; the award obtained by selecting the corresponding action is calculated according to the broadband spectrum sensing result; selecting the spreading factor of the next time slot according to the Q value table, and updating the Q value of the selection action in the state; and the user makes the most anti-interference strategy in a dynamic interference environment. According to the method, the system throughput is maximized, and time delay and overhead caused by channel switching are avoided.

The invention provides an intelligent cartoon line manuscript generation system capable of keeping human face features. The system comprises: 1, a backbone network, which is used for receiving cue word embedding representation input, controlling network embedding representation input, and generating a first draft of a cartoon line draft; the control network is used for receiving the human face, the human face key point embedded representation and the content image embedded representation, and generating a control network embedded representation; 3, four encoders of prompt words, human faces, human face key points and content images respectively generate corresponding embedded representations; and 4, a later-stage line draft adjustment module which performs local and overall style adjustment on the cartoon line draft generated by the backbone network by using a multi-layer generative adversarial network architecture to generate a final cartoon line draft finished product. According to the invention, the cartoon line manuscript with the specified face features can be efficiently generated, and the production efficiency of cartoon products is improved.

The invention provides a shared memory-based data interaction method for an embedded virtualization platform, which comprises the following steps of: dividing a shared memory area, including a management information area and a shared data area, initializing the management information area, including setting a magic number, configuring a mutual exclusion access flag and recording use information of the shared data area; acquiring a physical initial address of the shared memory, verifying the availability of the management information area, and ensuring that the management information area is correctly initialized; a proper data transmission mode is selected according to the data size, small data volume can be directly transmitted through an inter-core communication register, and large data volume is transmitted through a shared memory; the Szymanski algorithm is used to realize mutual exclusion access control, and the consistency of data is ensured; after data interaction is finished, if shared memory resources which do not need to be used any more need to be released, use information in the management information area is updated; and other related operation areas or virtual machines are notified according to needs, and state changes of data interaction are notified to the operation areas or the virtual machines.

The invention discloses a parasitic parameter extraction method based on supervised learning decision, which predicts a method which meets the precision requirement and has the shortest parasitic parameter extraction time from a plurality of parasitic parameter extraction technologies. The method comprises the following steps: reading a layout file; scanning and dividing the layout file into modules; extracting a density voltage matrix by all modules, flattening the density voltage matrix to serve as an input vector, and transmitting the input vector to a multi-layer sensor (MLP); predicting a parasitic parameter extraction technology which accords with precision and is shortest in time through MLP; each module executes the predicted parasitic parameter extraction technology; and generating an extraction netlist. According to the method, the advantages of the existing parasitic parameter extraction technology are fully exerted, and the respective defects are avoided.

The invention discloses a key value storage system indexing method oriented to an NVM-NVMe SSD (Non-Volatile Memory-Non-Volatile Memory Express Solid State Disk) hybrid architecture, which comprises the following steps of: constructing a heterogeneous storage architecture taking cold and hot data perception as a core driving mechanism, coordinating and managing two types of storage media, namely a non-volatile memory NVM and a solid state disk NVMe SSD, and realizing efficient identification, layered writing and dynamic migration of cold and hot data. According to the method, the characteristics of low delay, durability and byte addressing of the NVM are utilized, the frequency and I / O overhead of Flush and Compaction operations are reduced in a data write-in path, meanwhile, the problem of mixed storage of cold and hot data is avoided, and therefore the overall performance and storage efficiency of a system are remarkably improved. In addition, by introducing an asynchronous migration module, the method can dynamically adapt to the change of data popularity along with time evolution, and effectively support high performance and high availability of the key value system in long-term operation.

The invention discloses a data transmission optimization method and device in an Internet of Vehicles environment, terminal equipment and a storage medium, a minimum data packet size is calculated according to a network protocol and throughput corresponding to a network bandwidth, and a maximum value between the minimum data packet size and a data packet size threshold value is used as a first data packet size; the size of the first data packet can simultaneously meet the requirements of network transmission and the minimum size limit of the data packet processed by the vehicle system, so that the obtained size of the first data packet is ensured not to enable the data packet to be too small; and taking the minimum value between the first data packet size and the maximum data packet size corresponding to the network bandwidth as the second data packet size, thereby ensuring that the obtained second data packet size does not enable the data packet to be too large. Compared with the prior art, a reasonable data packet size can be adjusted in real time according to the change of network conditions, the transmission efficiency and reliability of the data packet can be ensured, and the transmission efficiency and stability of vehicle data are guaranteed.

The invention discloses a data processing method and device, equipment and a storage medium. When the method provided by the embodiment of the invention is executed, firstly, each time domain signal to be stored is acquired one by one according to a signal input sequence, a time domain sequence number is set for each signal, then a plurality of splitting sequence numbers are set for each signal, a storage position is determined according to a calculation formula, and the signals and the corresponding time domain sequence numbers are stored in a multi-path parallel SRAM in an associated manner. And finally, performing in-situ storage on a butterfly operation result to an SRAM (Static Random Access Memory) according to the serial number of the associative storage. According to the method, the storage position is accurately calculated, and the result is stored in situ, so that an additional cache SRAM (Static Random Access Memory) is prevented from being used, and the occupation of hardware resources is reduced. And meanwhile, an in-situ storage strategy is adopted, so that the carrying of data from one SRAM to another SRAM is reduced, the requirements of data movement and copying are further reduced, the storage efficiency is improved, and the extra data transmission overhead is avoided.

The invention relates to the technical field of computers, and discloses an inference system and method based on a multi-stage model, a readable medium and electronic equipment. The system comprises an intermediate cache module and a model reasoning module, wherein the model reasoning module comprises a feature construction sub-module and a result reasoning sub-module. When a reasoning request is received, an intermediate result can be queried in an intermediate cache module based on a cache identifier in the reasoning request, and a result reasoning module can directly perform reasoning based on the intermediate result under the condition of successful query to obtain a reasoning result corresponding to the reasoning request; and under the condition that the query fails, the feature construction sub-module constructs an intermediate result based on the original features in the reasoning request, and the intermediate cache module caches the intermediate result based on the cache identifier. The system provides a unified deployment platform of feature processing and model calculation, additional overhead can be avoided in different stages of the whole process, and most reasoning requests can multiplex cached intermediate results, so that the overhead of the system is further reduced.

The invention discloses a virtual machine pause processing method of a micro kernel Hypervisor based on an ARM VHE (Advanced RISC Machines VHE), which is characterized in that the micro kernel Hypervisor based on the ARM VHE is deployed and comprises a Hypervisor micro kernel module, a Host OS (Operating System) service thread and a virtual machine user mode management thread, wherein a CPU (Central Processing Unit) virtualization module in a kernel virtualization extension module in the Hypervisor microkernel module comprises a vCPU running thread running in an EL0 / EL1 mode and a vCPU processing thread running in the EL0 mode, and when the Hypervisor monitors that the vCPU running thread is suspended, the kernel virtualization extension module in the kernel virtualization extension module in the Hypervisor microkernel module is started; corresponding processing operation is adopted according to the pause trigger reason: if the current pause reason belongs to interrupt trigger or abnormal trigger processed under a Hypervisor microkernel, the kernel virtualization extension module directly performs corresponding virtual machine pause processing operation on EL2, and if the current pause reason belongs to other conditions, the kernel virtualization extension module directly performs corresponding virtual machine pause processing operation on the EL2; if yes, scheduling a vCPU processing thread to perform virtual machine pause processing operation at EL0; and after the operation is completed, the vCPU running thread recovers running. According to the method, the interrupt and exception processing of the Hypervisor on the virtual machine is optimized, and the pause processing performance of the virtual machine is improved.

The invention discloses an encryption method based on an RSA algorithm, and relates to the technical field of data encryption, and the method comprises the steps: collecting to-be-encrypted data; generating a session key of the to-be-encrypted data by adopting a symmetric block encryption algorithm RC5; encrypting the generated session key by adopting an RSA public key; encrypting the to-be-encrypted data by adopting a symmetric block encryption algorithm RC5 and the encrypted session key to generate encrypted data, dividing the to-be-encrypted data into N1 groups, and encrypting the grouped to-be-encrypted data by calling the RC5 algorithm in parallel through multiple threads; and performing confusion processing of sequentially and circularly exchanging adjacent data positions on the encrypted data to obtain the encrypted data. Aiming at the low encryption security based on an RSA algorithm in the prior art, the method comprises the following steps: collecting to-be-encrypted data, and generating a session key based on data content by using an RC5 algorithm; encrypting the session key by adopting an RSA algorithm; an RC5 algorithm is called in parallel for encryption; and block position confusion processing is carried out on the encrypted data, so that the encryption security of the RSA algorithm is improved.

The invention discloses an instruction-driven coprocessor architecture design method for an in-memory computing platform of a high-performance magnetic memory. The instruction-driven coprocessor architecture design method comprises the following steps of: switching a magnetic memory into a normal mode or an in-memory computing mode by writing a corresponding operation code into a state register OP; the normal mode is used for the read-write function of a normal memory, and the in-memory calculation mode provides the function that the magnetic memory serves as a calculation unit; when the magnetic memory is used as a computing unit, the operation of in-memory computing consists of two memory access instructions, namely, an in-memory computing activation instruction and an in-memory computing address transmission instruction; the in-memory calculation activation instruction is used for activating an in-memory mode of the memory, and the in-memory calculation address transmission instruction is used for providing necessary control signals for in-memory calculation. On the premise that a memory protocol and an instruction set architecture are not changed, memory access and calculation instructions can be distinguished through the memory circuit with the changeable state, and the high-reliability, low-power-consumption and high-parallelism in-memory calculation architecture based on the magnetic memory is achieved.

The embodiment of the invention discloses a business data desensitization method and device, a storage medium and computer equipment, and relates to the field of data processing. The method comprises the following steps: acquiring a data set; the data set comprises multiple pieces of business data of the enterprise; identifying a frequent sequence of which the support degree is greater than a support degree threshold value in the data set, and marking a frequent sequence in each piece of business data; selecting a mapping table; the mapping table is used for storing a mapping relation between the identifier and the frequent sequence; and according to the mapping table, replacing the frequent sequence included in each piece of service data with an identifier to obtain a desensitized data set. Through a series of efficient and accurate steps, efficient desensitization processing of enterprise business data is realized. The data desensitization efficiency is improved, the processing cost is reduced, the accuracy of the desensitization result is ensured, and sensitive information of enterprises is protected.

The invention provides a channel prediction method and system based on a multi-cycle feature convolutional network. According to the method, context sensing weighted input and a dynamic multi-model pool mechanism are introduced. A terminal device obtains environmental context features in real time, dynamically calculates the weight of each time step in a historical channel state information sequence based on the features, and generates a weighted optimized input sequence. Meanwhile, the network equipment pre-trains and maintains a plurality of multi-period feature convolutional network models specific to different environments, and the network can effectively capture the complex time-varying rules in the period and during the weeks in the channel, so that the accuracy of channel state information prediction is improved. And the terminal equipment immediately selects and activates the optimal sub-model in the model pool for prediction according to the real-time context features, and locally performs increment fine adjustment. According to the invention, through management of the data input end and rapid and adaptive switching of the prediction model end, the precision of channel prediction and the adaptive capacity to environmental sudden change are effectively improved.

This invention proposes a management method for the radio resource control layer in a 5G mobile communication network, relating to the technical field of 5G wireless communication. First, network data analysis elements collect and preprocess terminal session state data and network energy efficiency data. Based on the preprocessed terminal session state data and network energy efficiency data, a deep Q-network model is used to select the optimal adjustment action for the timing threshold of the RRC inactive timer, and analysis information containing this adjustment action is generated. This information is then converted into RRC auxiliary information and sent to the radio access network via access and mobility management elements, dynamically adjusting the timing threshold of the RRC inactive timer and managing the RRC connection state. This scheme improves the energy efficiency of the access network under different network load conditions while avoiding air interface signaling overhead and service latency caused by frequent terminal reconnections, enhancing the flexibility and accuracy of terminal state migration management.

This invention discloses a method for visualizing the surface quality of machined parts based on GPU and mesh search algorithms, belonging to the field of machining technology. The method includes acquiring tool point cloud data and discretizing it to construct a three-dimensional mesh structure surrounding the point cloud; linearizing the three-dimensional mesh data into a one-dimensional array and packaging it; creating four types of structured GPU computing buffers to achieve batch data transmission; utilizing GPU shader programs to achieve parallel data access and fast local neighborhood queries; completing high-precision real-time reconstruction of fragment surface normal vectors through neighborhood search and signed projection distance calculation; and outputting realistic rendering results based on an optimized Phong lighting model. This invention leverages the advantages of GPU parallel computing to accurately reproduce complex textures, microstructures, and special curved surfaces, making it suitable for surface quality inspection, wear assessment, and process optimization of milled parts and tools.

The invention discloses a traffic dynamic shortest path distribution method and system based on a triangular fuzzy number weight, and relates to the technical field of intelligent traffic systems.Fuzzy information in a path evaluation attribute is represented through a triangular fuzzy number, a comprehensive weight is analyzed and calculated in combination with deviation maximization and a moisture value, and the decision reliability is effectively improved; a K-Means algorithm is adopted to perform dynamic path search, and through a representative vertex subset pre-calculation and increment updating strategy, the path retrieval efficiency is remarkably improved; a travel time prediction model related to departure time and real-time flow is established, and accurate response to accidental congestion is realized; and finally, outputting an optimal path scheme through a multi-objective decision-making method. Compared with a traditional algorithm, the speed is improved on a real road network data set, the path distribution accuracy is improved, meanwhile, the path safety, comfort and efficiency are effectively balanced, real-time path planning under a large-scale road network is supported, and an efficient solution is provided for intelligent traffic management.

The invention relates to an image super-resolution method, system and equipment based on low-resolution increment, and the method comprises the steps: carrying out the initial down-sampling and multi-round increment reconstruction, obtaining information increment through the additional down-sampling of each round of increment reconstruction, and carrying out the up-sampling and super-resolution processing based on the information increment until a reconstructed image meeting the requirements is obtained. Through multi-round on-demand additional down-sampling and focusing on an interested area (which can be a whole image or one or more local image blocks) of a user, incremental optimization is realized, transmission of redundant data is effectively reduced, unnecessary resolution overhead is avoided, dependence on low-resolution image size is reduced, data transmission and processing are enabled to be more simplified, and user experience is improved. The system efficiency is improved, and the bandwidth is saved.

The application discloses a composite data transmission method and related device, and relates to the technical field of computers, and the method comprises the following steps: if it is judged that the data transmission from a device end to a host end is one-way transmission, the device end collects original audio and video data, carries out algorithm processing and classification; the original audio and video data is encapsulated and transmitted to the host end, the first composite data is received, and the first composite data is analyzed; the first analysis data is written into a target virtual drive, the first analysis data is integrated, a target instruction is generated, and the target instruction is transmitted to the device end; if it is judged that the data transmission is not one-way transmission, the host end packs the original audio and video data, transmits the second composite data to a computing box; the second composite data is analyzed, the second analysis data is processed by calling an algorithm library, the second analysis data is packed, and the second analysis data is returned to the host end; the packed data is analyzed, and the packed data is transmitted to a target application. The application provides high-quality original audio and video data transmission.

The invention relates to the technical field of distributed computing and micro-service architecture, in particular to a micro-service leader election method and system based on distributed coordination, and the method comprises the steps: deploying a plurality of micro-service copies in a container environment, and carrying out the routing request through a load balancing server, all micro-service copies share a distributed coordination storage instance as a coordination center, and on this basis, the micro-service leader election method comprises the following steps: S1, all micro-service copies attempt to acquire a distributed lock through a distributed lock acquisition command of the coordination center at the same time; s2, successfully obtaining a micro-service copy of the distributed lock as a Leader copy, and taking other micro-service copies as Follower copies; and S3, the Leader copy renews the lock every fixed interval, and the free count is updated. According to the method, distributed coordination storage is used as a coordination mechanism, and it is ensured that only one micro-service copy provides service for the outside in a specific scene.

The invention relates to the field of industrial internet-of-things data transmission, in particular to an industrial internet-of-things data secure transmission method, system, device and medium, and the method comprises the steps: pre-registering client information at a server, and generating a client unique identifier; the client generates a client key according to the public key obtained from the server and the unique identifier of the client, and registers the key to the server; the client uses the registered key to initiate security authentication to the server, and after the authentication is passed, the server generates or negotiates with the client to generate a session key for data encryption transmission, and distributes the session key to the client; the client and the server encrypt or decrypt interaction data by using the session key; according to the method, the data transmission security of the industrial Internet of Things can be ensured, the real-time performance, the reliability and the usability are considered, and the method is particularly suitable for industrial control, monitoring and cooperative processing scenes with relatively high requirements on the security and the real-time performance, and has relatively high practical value and popularization prospect.

The application discloses a humanoid robot whole-body control reinforcement learning method and system based on parallel computing, and the method comprises the following steps: constructing a CasADi expression of a computing joint connecting rod space inertia tensor; constructing a CasADi symbolic expression of a center of mass position and a center of mass momentum; converting the expression and the symbolic expression into a CUDA kernel and compiling into an executable file; when a training environment is initialized, importing the CUDA kernel of the CasADi expression and the symbolic expression and opening up a GPU memory space; after the mass and the center of mass domain of the connecting rod are randomized, calling the CasADi expression to perform parallel computation on the joint space inertia tensor of each environment; after each simulation step, calling the CasADi symbolic expression to perform parallel computation on the center of mass position and the center of mass momentum of each environment; combining the center of mass position and the center of mass momentum to calculate a reward function; introducing the reward function into reinforcement learning training to obtain a robot whole-body control strategy, and the application improves the utilization rate of the GPU.

This invention provides a method and system for updating a synchronous forwarding table in a 5G private network device based on UDP, belonging to the field of communication technology. The method includes: a central processing module generating synchronous forwarding table update information and encapsulating it into UDP packets, which are then sent to a message processing module. This information includes a slice identifier, a forwarding table identifier (SEID), PDR rule content, QER rule content, FAR rule content, and a QER rule quantity field. Upon receiving the data, the message processing module determines the valid QER rule content based on the QER rule quantity field, updates the forwarding table according to the synchronous forwarding table update information, stores the updated forwarding table in a hardware forwarding table storage area bound to the slice identifier, and performs packet forwarding processing according to the FAR rule content. This invention achieves efficient, reliable, and multi-slice isolation-compliant synchronous forwarding table updates between the central processing module and the message processing module.

The application discloses a kind of image recognition method and system under complex illumination environment, the method includes: obtaining the image to be identified needing to carry out image recognition, the illumination influence area is obtained by analyzing the image to be identified, and the illumination influence area is divided into a plurality of grid units according to pre-set rule by grid division;Respectively, randomly select pixel points from illumination influence area and non-illumination influence area, and obtain corresponding pixel block based on pre-set window size;The similarity weight between the pixel block of illumination influence area and non-illumination influence area is calculated respectively, to denoise the image to be identified, and the denoising identification image is input into pre-set image recognition model to obtain corresponding image recognition result.The application solves the problem of low image recognition efficiency in the prior art under complex illumination environment.

The present invention provides a BD3 high-precision timing method, system, computer equipment and medium, the method comprising: constructing a transmission and distribution park timing model; constructing a cumulative clock deviation model according to the transmission and distribution park timing model, and determining the transmission and distribution park timing optimization problem according to the cumulative clock deviation model; converting the transmission and distribution park timing optimization problem into a corresponding MAB problem, and using an adaptive UCB algorithm to solve the MAB problem, and obtaining the adaptive optimal timing interval corresponding to each transmission and distribution communication terminal being timed; according to each adaptive optimal timing interval, the timing gateway device performs adaptive timing management on the corresponding transmission and distribution communication terminal being timed. The present invention realizes the effective balance of timing error and timing overhead by adaptively selecting the timing interval according to business needs, provides a safer and more reliable high-precision power grid timing, and effectively reduces the timing cost of the power system, ensuring the safe and stable operation of the power system.

The application discloses a configuration warehousing method and device for knowledge collection, equipment and a storage medium. The method comprises the following steps: acquiring source knowledge data sent by an external system; reading a pre-configured mapping rule, wherein the mapping rule comprises a field mapping operation type configured for a standard field in a knowledge management platform, and the field mapping operation type comprises a selection type, a text type and a label type; performing a field mapping operation on the source knowledge data according to the mapping rule, obtaining target knowledge data and storing the target knowledge data into a standardized knowledge base. The pre-configured mapping rule is used to replace customized code development, when a new external system is accessed or a field definition is changed, only the mapping rule configuration needs to be modified, and code rewriting and deployment are not needed, so that the period of accessing heterogeneous knowledge into the standardized knowledge base is shortened.

The invention provides a non-parked vehicle OTA upgrading method, device and equipment and a storage medium, task cycle polling in the prior art is changed into event notification, that is, when a cloud end has a new upgrading task, firstly, an OTA vehicle end program is started through a resident program deployed at a vehicle end in a network wake-up mode, and then the OTA vehicle end program is started through the resident program deployed at the vehicle end; at the moment, communication is established between the OTA vehicle end program and the cloud end, query and synchronization of an upgrading task are completed, if the ECU versions of the vehicle are all latest versions, the OTA vehicle end program automatically quits and releases resources, and when version updating needs to be executed indeed, the follow-up process is started to be executed until upgrading succeeds / fails, the OTA vehicle end program quits, and the OTA vehicle end program returns to the cloud end. Therefore, the network load and the system overhead caused by frequent version query and report are avoided fundamentally, the real-time performance of the OTA task is improved, and the system overhead and the flow consumption when no task exists are reduced to the maximum extent.

The embodiment of the invention provides a data transmission method and device based on a container network, and the method comprises the steps: receiving a data packet transmitted by a transmitting end container node, the data packet being configured to carry a target container node network address and first mapping information of an expected receiving end container identifier; the data packet is analyzed to obtain first mapping information of a target container node network address and an expected receiving end container identifier, second mapping information corresponding to the target container node network address is inquired from a locally maintained mapping relation table, and the second mapping information is used for representing a mapping relation between the target container node network address and the current container identifier; if the first mapping information is inconsistent with the second mapping information, discarding the data packet; and if the first mapping information is consistent with the second mapping information, allowing to process the data packet. The method can improve the security of data transmission and reduce resource overhead.

The invention discloses a distributed lease management method and system, a storage medium and electronic equipment, relates to the technical field of storage management, is used for a client layer, and comprises the steps that under the condition that a file operation request is received, a lease request is sent to a node layer, and the lease request is used for indicating a target lease of a target file corresponding to the file operation request; after a target lease sent by a node layer is received, the target file is accessed in a storage system according to the target lease, the node layer corresponds to at least one client layer, and under the condition that the target lease conflicts with a reference node layer, the node layer accesses a cluster layer, and under the condition that the node layer receives an authorization instruction sent by the cluster layer, the target file is accessed in the storage system according to the authorization instruction. And the node layer sends the target lease. The technical problem that a distributed file system in the related technology is low in resource utilization rate is solved, and the technical effect of improving the resource utilization rate of the file system is achieved.