161 results about "Distributed management" patented technology

The invention relates to the technical field of cloud computing, and discloses a distributed management system and method for a cloud container cluster, and the system comprises a data collection module which is used for collecting the resource remaining amount of each node in the cloud container cluster and the resource demand of a tenant, and providing real-time data updating support; the state modeling module is used for establishing a state variable model for describing the dynamic change of tenant resources based on the resource data acquired by the data acquisition module, and state variables comprise the resource occupation amount, the resource application amount and the resource release rate of the tenants; the scheduling optimization module is used for generating a resource allocation strategy based on the tenant resource dynamic change characteristics and the multi-tenant competition relationship; according to the invention, through system architectures of data acquisition, state modeling, scheduling optimization and the like which are modularly designed, dynamic acquisition frequency and resource dynamic change modeling are introduced, the data acquisition real-time performance and the resource allocation accuracy are improved, and the problems of low resource utilization rate and slow scheduling response in the prior art are solved.

The invention discloses a large model data distributed management method and device, equipment and a storage medium, and relates to the technical field of data processing, and the method comprises the steps: segmenting large model training data to obtain a plurality of data blocks, and determining a predicted access frequency based on a long short-term memory network model and the historical access frequency of the data blocks; caching the large model training data corresponding to the data block to a corresponding data cache layer by utilizing the predicted access frequency; constructing a resource portrait by using the static attribute and the dynamic index of the GPU node, and allocating the large model training task to a target GPU node by using a preset hybrid strategy and the resource portrait based on the predicted access frequency and the storage position corresponding to the data block in the data cache layer; when it is monitored that the large model training task on the target GPU node is executed, periodic snapshot is conducted on the large model training task through a distributed snapshot algorithm, and the obtained complete data state is stored in a distributed storage center. And the resource vacancy rate is reduced.

The invention relates to the technical field of liquid cooling, in particular to a distributed full liquid cooling device which comprises a liquid cooling distribution module, a liquid supply main pipe, a liquid return main pipe and a plurality of liquid cooling modules, and the liquid cooling distribution module adjusts the flow speed of low-temperature cooling liquid in the liquid supply main pipe according to the total heating value, so that the overall heat dissipation balance of a system is guaranteed; the cooling liquid inlet flow of each liquid cooling unit is accurately regulated and controlled based on the inlet and outlet liquid temperature difference and the real-time liquid supply mass flow of the liquid cooling units in the liquid cooling module and the real-time reference power of the electronic equipment, so that the heat dissipation requirement of the single liquid cooling module can be met; meanwhile, the liquid cooling distribution module can control the opening state of the jet flow unit according to the surface temperature of the heating element in the electronic equipment, and local enhanced cooling can be conducted on the heating element. According to the distributed full liquid cooling device, accurate control from a global system to a local system is realized through distributed management, and heat dissipation requirements of different levels can be met.

The invention discloses an unmanned aerial vehicle group distributed management method based on a mobile active secret sharing technology, which supports off-line of a trusted institution and comprises the following steps: the trusted institution TA generates public parameters; a mobile base station MS and an unmanned aerial vehicle UAV participating in communication respectively register with a trusted mechanism in a registration stage, and acquire information such as a secret key and a certificate; the UAV joins the MS and is administered by the MS, and after mutual identity authentication, the MS distributes secret shares to the UAV; performing identity authentication on the unmanned aerial vehicle group; the unmanned aerial vehicles of the two groups share the share, group fusion is achieved, and after a new share is obtained, each unmanned aerial vehicle updates the certificate of the unmanned aerial vehicle. According to the method, the sub-secrets of the unmanned aerial vehicles are autonomously updated through a mobile active secret sharing technology, and fusion of completely decentralized unmanned aerial vehicle groups is realized. Secondly, an efficient certificate self-updating method is designed. The unmanned aerial vehicle can update the certificate only by calculating a threshold signature. Detailed safety certification and comprehensive experiments show that dynamic autonomous management of the distributed unmanned aerial vehicle group can be realized, and the method has good safety characteristics and relatively low calculation overhead.

The present invention provides a software design method for intelligent vehicle-mounted terminal based on a microservice architecture, and belongs to the technical field of intelligent networked vehicles. Software system development is realized based on the framework of distributed microservices. In terms of software architecture, the single application integrated by the original intelligent vehicle-mounted terminal is divided into a group of small services, and the services are coordinated and cooperated with each other to provide ultimate value for the application layer and the terminal. Each service runs in its own independent process, and services communicate with each other using a lightweight communication mechanism. Each service is built around a specific business and can be independently deployed to a production environment, a production-like environment, etc. The distributed scenario development method based on the microservice architecture enables different service modules to be freely combined to form application scenarios, which is convenient for independent deployment, distributed management and code decoupling, and the applications can be updated and expanded independently, reducing the coupling of hardware platforms and improving software portability.

A computer-implemented method of distributed management of locks includes: receiving, by a plurality of servers, a plurality of concurrent requests; performing lock preemption on the distributed lock using a synchronization mechanism; only one server uses a synchronization mechanism to obtain the distributed lock; updating the lock value of the distributed lock by only one server; and executing the business logic. Lock preemption is performed on the distributed lock by the respective server, including comparing a current memory value of the distributed lock to an expected value. The method further comprises the steps that if the current memory value is matched with the expected value, only one server modifies the current memory value into an updated value; writing the updated value into a memory of the distributed lock; and if the execution of the service logic fails, recovering the memory value of the distributed lock to the current memory value.

The invention relates to the field of software development application data processing, and discloses a software development application data processing method based on an AI large model, which comprises the following steps: deploying an anomaly detection model in a data access layer, and carrying out dynamic anomaly detection and real-time cleaning on software development application data, based on historical security event feedback, optimizing the scoring model and grading the software development application data; anti-association desensitization training is carried out on the software development application data, homomorphic encryption is carried out, association attack simulation testing is carried out regularly, and parameters are adjusted; carrying out distributed management on the key, and carrying out audit tracking based on a block chain; accessing a regulation database based on a dynamic compliance engine, analyzing a regulation to generate a rule base, deploying check points in a data key link for real-time detection and blocking, and performing secure erasure verification; dynamic scheduling resources are predicted in combination with a large model, and the cost is monitored in real time through a monitoring system; nodes are deployed on multiple platforms, an aggregation parameter updating model is encrypted, and vulnerabilities are scanned regularly.

The invention discloses a multi-time-scale coordination control method and system for a virtual power plant with new energy access, and aims to solve the challenge of the fluctuation of new energy on the stability of a power grid. The method comprises the following steps: in a day-ahead scheduling stage, constructing a baseline scheduling plan based on natural conditions and historical loads, and allocating energy storage node demands through a block chain; in the intra-day rolling optimization stage, the plan is dynamically adjusted through short-term prediction, and energy storage requirements are redistributed; in the construction stage, a digital twinborn technology is adopted to simulate dynamic interaction between new energy and bus nodes and energy storage nodes; in the real-time control stage, energy storage demand sharing is realized in combination with model prediction control and a block chain. The system comprises a baseline scheduling module, an intraday optimization module, a virtual power plant construction module and a real-time control module. According to the method, through multi-time scale cooperation, block chain distributed management and total element simulation, the power balance capability is remarkably improved, the adaptability to the uncertainty of natural conditions is enhanced, and the operation efficiency and transparency are improved.

The invention discloses a computer self-check cycle optimization method based on the Internet of Things in the technical field of server maintenance, and relates to the technical field of server maintenance. Server node operation state data is collected in real time, a dynamic load evaluation model is constructed, and a comprehensive load index is calculated; and dynamically dividing performance states based on the threshold values L1 and L2, and adjusting a self-checking period and a module priority. Calculating a single-node risk index Ri by adopting a fault risk model, generating a fault generalization risk factor R1 through a probability graph model in combination with network topology, and triggering a linkage mechanism; dividing and dynamically adjusting a self-checking period according to the early warning level; during advanced early warning, redundant resources are distributed to preferentially process key faults, edge calculation is combined to carry out data cleaning and standardization, distributed management is realized through a consistent Hash algorithm, and finally, a visual interface is used for displaying an optimized scheduling result, so that a closed-loop optimization system of data acquisition, risk prediction and resource scheduling is formed.

The invention relates to the technical field of data processing, in particular to a carbon asset information security synchronization method depending on an internet cloud platform, and the method comprises the steps: constructing each carbon asset change sequence of each user based on the similar condition of the carbon asset information of each user during two adjacent carbon asset information updating, in combination with the data updating frequency of various kinds of carbon asset information, analyzing the type information influence degree corresponding to each user; constructing the trend matching confidence of each kind of carbon asset information of each user based on the similarity between the carbon asset change sequences of each user and other users; and determining the synchronization priority of the carbon asset information of each user based on the type information influence degree and the trend matching confidence so as to ensure the security and high efficiency of the transmission process, and realizing real-time and high-efficiency information transmission for the security synchronization method of the carbon asset information depending on the Internet cloud platform. The problems of data delay and inconsistency in carbon asset distributed management are solved.

The present invention relates to the field of software development application data processing, and discloses a software development application data processing method based on an AI large model, including: deploying an anomaly detection model at the data access layer to perform dynamic anomaly detection and real-time cleaning on software development application data, optimizing the scoring model based on historical security event feedback and classifying the software development application data; performing anti-correlation desensitization training on the software development application data, performing homomorphic encryption, regularly conducting association attack simulation tests and adjusting parameters; managing keys in a distributed manner and performing audit tracking based on the blockchain; accessing a regulation database based on a dynamic compliance engine, parsing regulations to generate a rule library, deploying checkpoints at key data links for real-time detection and blocking, and performing secure erasure verification; dynamically scheduling resources in combination with large model prediction, and monitoring costs in real time through a monitoring system; deploying nodes on multiple platforms, encrypting and aggregating parameter update models, and regularly scanning for vulnerabilities.

The invention discloses a customer service work order management system based on network employer service, which relates to the technical field of work order management and comprises a multifunctional service module, a distributed management module, an elastic module, an operation and maintenance monitoring module and a real-time notification module. The multifunctional service module comprises a user service unit, a work order service unit, a communication service unit, a knowledge base service unit and a data analysis unit, and is used for serving a network employer; the distributed management module is used for verifying user validity, determining user legality and creating a work order based on a legal user; and the elastic module is used when the customer service work order service response is overtime. According to the invention, omnibearing real-time monitoring and deep analysis are carried out on the system, discovered problems and work order state change conditions are pushed to related personnel in time, timely transmission of information is ensured, failure retry is carried out based on an exponential backoff algorithm, the reliability of notification is ensured, and notification loss caused by network fluctuation is avoided.

The invention discloses a source-load-storage coordinated active power distribution network cooperative operation optimization method, and belongs to the technical field of active power distribution network optimization. Comprising the following steps: partitioning the power distribution network by using an electrical coupling degree and a power matching degree to obtain an optimal power distribution network partitioning result; taking the minimum comprehensive operation cost of the active power distribution network as a target function, introducing a demand response constraint, and constructing an active power distribution network partition collaborative optimization model; and constructing a regional agent for each regional partition based on the optimal power distribution network partition result, modeling an objective function into a distributed partial observable Markov decision process, and performing iterative optimization on the active power distribution network partition collaborative optimization model through the regional agent to obtain the real-time electricity price in each region. Distributed management of flexible resources of each region can be realized, and the problem that the operation regulation and control difficulty is increased due to multivariate uncertainty factors and ever-increasing structure complexity in the existing ADN is solved.

The invention relates to the field of energy storage battery communication management, and particularly discloses a large-scale multi-node high-throughput data communication system of an energy storage battery, which comprises an equipment layer, a communication layer and a management scheduling layer, the management of the equipment layer on the battery comprises an IP mode and grouping management based on a battery state; a broadband industrial bus of the communication layer is used for data transmission among a BMU, a BCU and a BAU in the BMS and data interaction between the BMS and an EMS; the distributed domain bus is used for dividing the BMS into different domains, and cluster communication between BMS nodes is achieved in each domain. Cluster management is realized by using a distributed domain bus, the problems of complex wiring and difficult maintenance of traditional networking are solved, unified scheduling of energy storage devices of different manufacturers is realized through a self-defined domain address strategy, and addressing efficiency and distributed management and control capability of large-scale nodes are optimized.

Methods and systems for managing the operation of data processing systems are disclosed. A data processing system may include a computing device that may provide computer implemented services. To provide the computer implemented services, hardware components of the data processing system may need to operate in predetermined manners. To manage the operation of the hardware components, the data processing system may heat them when their temperatures fall outside of thermal operating ranges. The data processing system may implement a distributed management framework for managing the operation of a thermal management subsystem tasked with maintaining the temperatures of the hardware components through heating.

The embodiment of the invention discloses a user interaction record distributed management method, system and device and a storage medium. According to the technical scheme provided by the embodiment of the invention, the interaction request for consistent hash forwarding based on the first identifier of the interaction object is received, and the interaction request is initiated through the target terminal corresponding to the interaction object; according to the interaction request, an interaction record of an interaction object in the current storage node is updated, the interaction record is synchronized to the associated storage node, and the interaction record comprises interaction content of an interaction type corresponding to the interaction request, an interaction sorting value and / or a total interaction number; and performing consistent hash forwarding of the interaction request to the associated interaction record service node based on the second identifier of the user corresponding to the target terminal, so as to update the associated interaction record based on the interaction request. By adopting the technical means, complex and high-frequency interactive record query requirements can be supported, the query efficiency and flexibility of the user interactive record are improved, and the interactive record query experience of the user is further improved.

The invention relates to the technical field of image processing and data management, and discloses an infrared image data classification filing method and platform, and the method comprises the following steps: 1, collecting infrared image data from a plurality of different types of infrared sensors, the sensors including an infrared thermal imaging camera, a visible light camera and a radar; 2, the collected infrared image data are preprocessed, noise removal, temperature correction and image enhancement are included, and wavelet transform and a deep convolutional neural network are adopted for noise removal; through intelligent classification and management, the infrared image data processing efficiency is improved, manual intervention is reduced, the error rate is reduced, the data storage and retrieval speed is optimized by adopting multi-level storage and distributed management, the storage cost is reduced, the data safety and reliability are guaranteed through redundant backup and data de-duplication, and the data storage and retrieval efficiency is improved. And long-time reliable storage and efficient recovery of the data are ensured.

The invention discloses a water conservancy informatization management system based on a digital twinborn model, and relates to the technical field of water conservancy management, and the system comprises a block management module which is based on the equipment, terrain and hydrological information data of water conservancy facilities, management blocks are divided according to the equipment, terrain and hydrological information data characteristics of the water conservancy facilities, computing equipment is locally deployed in each management block, and the local computing equipment of the management blocks is utilized to distribute management computing tasks according to the load capacity. Management blocks of equipment, terrains and hydrological environments of water conservancy facilities are divided into a plurality of gridding node units through the block management module, data storage and calculation tasks are independently undertaken through independent monitoring management of each management block, the data load pressure of a single central server is reduced, and the management efficiency of the water conservancy facilities is improved. Response delay and fault risks caused by overload of the central server are avoided, and stable operation of the water conservancy informatization management system is guaranteed.

The invention provides a heterogeneous GPU resource pooling method and system combining Ray and Volcano, and relates to the technical field of GPU resource scheduling. According to the method and the system, firstly, a Ray + Volcano framework is constructed on a Kubernetes cluster; then deep learning model training is carried out based on a Ray + Volcano framework, distributed management is carried out on deep learning training tasks through a task scheduling framework of a Ray cluster, and task load balance is ensured; and a resource management mechanism of Volcano job scheduling is utilized to realize control and optimal distribution of GPU resources. According to the method and the system, rapid execution of large-scale tasks and efficient utilization of resources are realized through the efficient distributed computing capability of Ray and the dynamic resource scheduling and isolation mechanism of Volcano.

The invention discloses a cloud platform design method based on a Docker container technology, and relates to the field of cloud computers. The method comprises the following steps: deploying a plurality of containerized target application services in a distributed management cluster, and respectively determining the number of container instances required by the plurality of target application services; for each target application service, distributing a plurality of container instances to different working nodes for operation according to a scheduling strategy and the number of the container instances; configuring a multi-level network isolation strategy for the plurality of target application services; constructing a label-based dynamic container instance scheduling strategy, and performing real-time scheduling on the container instances of the plurality of target application services through the dynamic container instance scheduling strategy; and copying the cluster management state among the plurality of management nodes in real time, and carrying out synchronization and regular backup on the application state of the running container instance, so that the running states of all nodes in the distributed management cluster are consistent. The method can improve the reliability of cloud platform design.

The disclosed system provides distributed management and control of satellite constellations. Such distributed management and control that involves a plurality of satellites, a plurality of ground stations, a mission control station, and a data center that hosts a portion of an Internet cloud. The system resolves issues that have plagued legacy attempts. Specifically the disclosed system includes optimized communication with satellites that leads to more efficient transfer of data and payloads to or from or by or between satellites and ground control systems. This is achieved through use of micro-batching of communications. In this manner, data may be processed and more effectively transmitted to and from more than one satellite and back to one or more ground stations, including coordinated transmissions of portions of a micro-batch between two or more ground stations.

The invention relates to the technical field of equipment connection, and discloses a multi-camera equipment connection management method and system based on portable WiFi, and the method comprises the steps: calculating a resource limitation coefficient in a portable WiFi environment; generating a distributed management configuration table of a multi-camera management task in the portable WiFi based on the resource-constrained coefficient, and executing active scanning and passive monitoring alternate acquisition to obtain a camera access priority table; carrying out resource allocation on camera equipment in the camera access priority table to obtain a multi-camera resource allocation strategy, and carrying out three-layer transmission channel division and allocation based on the multi-camera resource allocation strategy to obtain a multi-path data transmission control table; according to the multi-channel data transmission control table, a multi-level resource feedback mechanism in a carry-on WiFi environment is established, and the bandwidth allocation proportion between the camera devices is dynamically calculated to obtain a cooperative transmission optimization scheme, so that the utilization efficiency of limited bandwidth resources is improved, and efficient cooperative work of the multiple camera devices is realized.

The invention discloses a rule engine and low-code dual-drive power grid digital graph fusion treatment platform and method. The platform comprises an infrastructure layer, a data layer, an algorithm engine layer and a business application layer. And the data layer is used for accessing and managing multi-source power grid data. And the algorithm engine layer comprises a rule engine module for configuring and executing data verification, digital graph association and exception handling rules, a data quality diagnosis algorithm module for performing data quality diagnosis to identify exceptions, and a digital graph fusion driving engine module for realizing bidirectional linkage between data and graphs. And the business application layer comprises a low-code arrangement platform for customizing a governance scene page and a work order process, a digital graph integrated display module for displaying multi-source power grid data on the same screen, and a closed-loop work order management module for automatically generating and distributing governance work orders. The method constructs a depth digital graph fusion system, improves the anomaly positioning and treatment efficiency, achieves automatic management and control and whole-course tracing, does not need a large amount of code development, and shortens the response period of a new business scene.

The invention relates to the technical field of block chain application, in particular to a privacy protection autonomous identity management system and method based on a block chain in an Internet of Things scene, each identity issuer and an identity verification party form an alliance chain, the identity issuer generates system parameters and registers, uploads and revokes an equipment identity, and the identity verification party verifies the equipment identity. The verification party retrieves equipment identity verification and revocation information uploaded to the block chain by the issuer, and constructs a distributed management framework of the Internet of Things equipment identity based on the block chain; an identity issuer generates a plurality of unassociated anonymous identities for equipment based on a one-way hash chain, privacy protection certificateless signature is realized, and one-time anonymous identities are added into leaf nodes based on a Merkle Tree structure to generate verifiable declarations so as to protect association among a plurality of verifiable declarations of the equipment and realize attribute selective disclosure; and the on-chain node realizes management of device identity registration, authentication, tracking and revocation and updating of a full life cycle by using an intelligent contract. According to the invention, the privacy requirement of the Internet of Things equipment can be met.

The invention provides an intelligent streaming media inside rear-view mirror system and a working method, the intelligent streaming media inside rear-view mirror system comprises an out-cabin rear-view camera, an in-cabin camera and a streaming media inside rear-view mirror, and a streaming media inside rear-view mirror ECU is integrated in the streaming media inside rear-view mirror; the in-cabin camera is arranged at the lower jaw of the streaming media inside rear-view mirror, communicates with the ECU of the streaming media inside rear-view mirror through an MIPI (Mobile Industry Processor Interface), and is used for acquiring an image signal in a vehicle and transmitting the signal to the ECU carrying a DMS / OMS (Distributed Management System / Optical Management System) algorithm to realize a driver / passenger monitoring function; the outboard rearview camera collects image signals behind the vehicle and transmits the signals to the ECU. And after receiving the image signal, the ECU performs ISP processing and related algorithm analysis, and transmits the processed signal to a streaming media inside rear-view mirror display screen. According to the integrated design, the influence of the camera on the interior trim is reduced, the project cost and the whole vehicle weight are reduced, meanwhile, the DMS / OMS function can be modularized, and the convenience of configuration and loading is improved.

The invention discloses a cloud edge efficient synchronization mechanism and distributed management scheduling system based on crop water shortage data, and relates to the technical field of intelligent agriculture. The system comprises an edge end, an edge computing node module, a cloud edge communication module and a cloud storage and management module, wherein the edge end is used for collecting multi-source original data related to crop water shortage; the edge computing node module is used for preprocessing the multi-source original data and extracting a feature vector comprehensively reflecting a crop water shortage state; the cloud side communication module is used for constructing a two-way communication link and adjusting the data transmission rate according to an adaptive window adjustment strategy; and the cloud storage and management module is used for carrying out encrypted storage on the data by adopting a distributed hash table technology and carrying out dynamic scheduling and distribution on the stored data by utilizing a distributed management scheduling algorithm. According to the invention, efficient collection, accurate transmission, intelligent scheduling and safe storage of crop water shortage data can be realized, and agricultural data management precision and decision-making efficiency are improved.

The invention discloses a distributed remote multi-available-area computing power scheduling method, and relates to the technical field of distributed management, and the method comprises the following steps: a management node collects available area state information and reports the available area state information to a main service node, so as to construct a dynamic global resource view; after receiving the calculation task, the main service node analyzes and splits the calculation task into sub-tasks; calculating the cost of scheduling to different available regions for each sub-task by constructing an adaptive cost function, and selecting the sub-task with the lowest cost as a target available region; distributing the sub-tasks to management nodes of the target available area, and distributing the sub-tasks to computing nodes for execution by the management nodes; the result is aggregated and returned to the main service node; meanwhile, the state of the available area is monitored, and tasks in the fault available area are rescheduled. Through combination of centralized coordination and distributed execution, computing power scheduling with low delay, high availability and high resource utilization rate is realized.

This application relates to the field of device connectivity technology and discloses a method and system for managing the connection of multiple cameras based on portable WiFi. The method includes: calculating the resource constraint coefficient in the portable WiFi environment; generating a distributed management configuration table for the management tasks of multiple cameras in the portable WiFi based on the resource constraint coefficient, and performing alternating active scanning and passive listening to obtain a camera access priority table; allocating resources to the camera devices in the camera access priority table to obtain a multi-camera resource allocation strategy, and dividing and allocating three-layer transmission channels based on the multi-camera resource allocation strategy to obtain a multi-channel data transmission control table; establishing a multi-level resource feedback mechanism in the portable WiFi environment based on the multi-channel data transmission control table, and dynamically calculating the bandwidth allocation ratio between camera devices to obtain a collaborative transmission optimization scheme, thereby improving the utilization efficiency of limited bandwidth resources and realizing the efficient collaborative work of multiple camera devices.

An integrated circuit (IC) device includes a functional circuit and a distributed management circuit that includes a plurality of configuration interface manager (CIM) circuits that receive respective programming partitions as configuration packets over a first communication channel (e.g., a network-on-chip or NoC), the configuration packets being configured to communicate with the functional circuit. And performing management operations on the respective regions of the functional circuit in parallel with each other based on the respective configuration packets, the management operations including providing configuration parameters to the respective regions of the functional circuit. The configuration packets may be streamed from the central manager to the CIM circuitry and / or read by a direct memory access (DMA) engine of the CIM circuitry. The central manager may configure the CIM circuitry and the NoC over a second communication channel (e.g., a global communication ring interconnect) during the initialization phase. The CIM circuitry may include respective packet processors, random access memories, authentication circuitry, error detection circuitry, and interconnect circuitry having a standardized bus width.

The application discloses a kind of distributed data encryption sharing methods based on block chain, and using block chain realizes the traceable management of search and authorization process.The scheme is first by multi-authorization center to carry out distributed management to attribute domain, and generates attribute key associated with identity for user;In access verification link, construct parameter masking mechanism based on bilinear pairing, so that user attribute private key is not directly exposed in block chain verification and query process.Secondly, data owner carries out layered encryption to shared data and session key, and constructs the improved multi-key search structure, index and ciphertext positioning information are recorded to block chain, to support fast positioning target ciphertext.In addition, the application uses linear secret sharing to set access structure, and designs subset determination mechanism of general attribute name set, binds the download permission of ciphertext with the attribute condition that user can satisfy, to prevent overreach download behavior.Finally, with the help of cloud, outsourcing decryption is executed to generate intermediate result, and terminal only needs to complete light recovery and decryption.The application can give consideration to fine-grained control, high-performance search access and terminal side low load, and is suitable for secure data encryption sharing in resource-limited scene.