69 results about "Resource description" patented technology

The invention discloses a resource allocation and configuration method and device and electronic equipment. The method comprises the following steps: converting network resources in a private network into programmable objects, and constructing a resource label model according to attribute information of the programmable objects and the network resources; receiving service demand information, extracting a service intention in the service demand information, and converting the service intention into a standardized intermediate instruction; generating a resource allocation scheme according to the standardized intermediate instruction and the network resource use state information, and evaluating the resource allocation scheme in a digital twin environment of the private network; and under the condition that the evaluation result of the resource allocation scheme in the digital twin environment meets a preset requirement, converting the resource allocation scheme into a control instruction, and sending the control instruction to the network resource. The technical problems of low network resource allocation efficiency and slow service response speed caused by non-uniform resource description and high service demand analysis difficulty in a multi-manufacturer heterogeneous network environment are solved.

The invention discloses a data storage method and device, electronic equipment and a storage medium, and relates to the technical field of computers, and the method comprises the following steps: obtaining load description information and resource description information corresponding to virtual storage units matched with a target terminal; determining respective priority coefficients of the at least one virtual storage unit according to the load description information and the resource description information; under the condition that a first virtual storage unit is determined from the at least one virtual storage unit, at least one second virtual storage unit in routing connection with the first virtual storage unit and the at least one first virtual storage unit are added to a storage unit group; and determining a target storage unit from all the storage unit groups. According to the technical scheme, the priority is comprehensively obtained through the load description information and the resource description information, and then the target storage unit is obtained based on the priority, so that the accuracy of selecting the virtual storage unit is improved, and the problem that the accuracy of selecting the virtual storage unit is low in the related technology is solved.

The invention discloses a computing power resource intelligent transaction optimization method and system, and relates to the technical field of cloud computing. Comprising the following steps: acquiring multi-source heterogeneous computing power resource data, performing normalization processing and vectorization modeling, and generating a standardized resource feature vector; historical and real-time data are collected to construct a demand side service portrait and a supply side dynamic resource map, and a space-time perception supply and demand situation model is formed; a multi-objective optimization model comprehensively considering resource utilization rate, carbon emission intensity, policy preferential income and transaction cost is established based on the model, and a non-dominated solution set is generated by adopting a Pareto optimization algorithm; and constructing an intelligent matching decision engine based on a reinforcement learning framework, carrying out real-time sensing, dynamic adjustment and execution on the transaction strategy scheme, and outputting a final executable transaction scheme. The technical problems of low computing power transaction efficiency and low resource utilization rate caused by non-uniform computing power resource description, supply and demand situation perception lag, single optimization target and stiffness of a matching mechanism are solved.

This application discloses a data storage method, apparatus, electronic device, and storage medium, relating to the field of computer technology. The method includes: acquiring load description information and resource description information corresponding to each virtual storage unit matched with a target terminal; determining a priority coefficient for each of at least one virtual storage unit based on the load description information and resource description information; if a first virtual storage unit is determined from the at least one virtual storage unit, adding at least one second virtual storage unit with a routing connection to the first virtual storage unit, as well as at least one first virtual storage unit, to a storage unit group; and determining a target storage unit from the entire storage unit group. By comprehensively obtaining priority information from both load description information and resource description information, and then selecting the target storage unit based on that priority, the accuracy of virtual storage unit selection is improved, thereby solving the problem of low accuracy in virtual storage unit selection in related technologies.

The invention relates to the technical field of computers, in particular to a training method of a voice recognition model, a voice recognition method and a related device, which are used for efficiently and automatically constructing a training sample of audio and video resources so as to quickly improve the voice recognition precision of the voice recognition model. The method comprises the following steps: performing lexical element splitting on resource description information of a to-be-processed resource to obtain a plurality of candidate lexical elements; selecting at least one candidate lexical element meeting a first screening condition as a keyword element based on the structure evaluation values corresponding to the plurality of candidate lexical elements and the occurrence times of the candidate lexical elements in the resource description information; for each candidate sentence, constructing a training sample based on the candidate sentence, and performing audio conversion on the training sample to obtain an audio tag of the training sample; and training the speech recognition model based on the plurality of training samples and the respective audio tags.

Provided in the present disclosure are an information transmission method, an apparatus, a device, a storage medium and a computer program product. The method comprises: a first network element receives first information, wherein the first information represents a resource descriptor related to a field programmable gate array (FPGA) hardware resource required by an application to be deployed, and the first information is used for generating configuration information of a target FPGA device deploying said application.

Embodiments of the present application provide a resource processing method, a cloud service instance processing method and device, comprising: receiving a resource application request sent by a target user equipment; the target user equipment belongs to a user equipment in a resource platform; in response to the resource application request, finding a quota corresponding to target resource description information corresponding to the target user equipment from preset quota data to obtain a target quota; the target resource is resource description information applied by the target user equipment this time, and the preset quota data includes quotas corresponding to different resource description information predicted for the user equipment in the resource platform; and according to the target quota, allocating a target resource in the resource platform to the target user equipment, the target resource including a resource described by the target resource description information. In this way, the accuracy of the preset quota data can be improved to some extent, and the resource allocation effect can be improved.

The invention provides a resource sharing method, device and equipment and a storage medium, and relates to the field of resource management. The resource sharing method comprises the following steps: acquiring resource retrieval information input by a user; according to the resource retrieval information, performing resource retrieval from uniform resource description information; displaying the retrieved resources, scheduling information of the retrieved resources and a reservation function control; and performing approval processing on a resource reservation request submitted by the user through the reservation function control. Therefore, resource sharing is realized, and the resource utilization rate is improved.

The application discloses a resource allocation method and device for offshore emergency rescue, and the method comprises the following steps: acquiring a set of offshore emergency rescue demand information, a set of rescue resource description information and a set of rescue resource technical state parameter time series; the rescue resource description information comprises a rescue capability index value; each rescue demand index is one-to-one corresponding to the rescue capability index; pre-processing the set of offshore emergency rescue demand information, the set of rescue resource description information and the set of rescue resource technical state parameter time series to obtain a set of pre-processed information; performing resource allocation processing on the set of pre-processed information to obtain a set of resource allocation information; the set of resource allocation information comprises resource allocation information; the resource allocation information is used for describing the allocation information of resources for tasks.

The invention discloses a code generation method and device, equipment, a storage medium and a program product. The method comprises the steps that a data file of a target system is obtained, and the data file comprises a command statement; extracting a plurality of command elements from a command statement of the data file; based on the semantic mapping relationship, mapping the plurality of command elements into structured resource description information; generating an open interface metadata file based on the open interface protocol and the structured resource description information, the open interface metadata file being used for providing interface generation metadata and interface generation specification information for generating an executable interface code; and generating a target executable interface code based on the interface generation template and the open interface metadata file. According to the code generation method provided by the embodiment of the invention, the efficiency and accuracy of generating the target executable interface code can be improved.

The invention discloses a resource transaction monitoring method and device, equipment and a medium, and relates to the technical field of financial science and technology. The method comprises the following steps: acquiring resource quotation data provided by an intermediate party and historical transaction data provided by a transaction platform party; wherein the resource quotation data comprises target resource description data, initial quotation data and asset voucher data of an intermediate party; verifying the qualification of the intermediate party according to asset voucher data in the resource quotation data, performing abnormal fluctuation verification on the initial quotation data and the historical transaction data according to the target resource description data, and determining target quotation data according to a qualification verification result and an abnormal fluctuation verification result; and forming a resource transaction request based on the target quotation data, and reporting the resource transaction request to a block chain layer, so that the block chain layer performs transaction processing according to the resource transaction request. Through the technical scheme of the invention, nearly real-time pricing update can be realized, and the efficiency and accuracy of the pricing process are improved.

The application discloses a kind of general task scheduling framework systems and methods supporting dynamic arrangement, belong to computer software system architecture technical field, including framework engine core, field adaptation layer and functional plug-in;The framework engine core is the general scheduling execution engine irrelevant to specific business field, including resource abstract module, task abstract module, dynamic arrangement and execution engine and plug-in warehouse and manager;The resource abstract module defines uniform resource description interface, and converts original resource data into resource image.The application can dynamically retrieve, load plug-in and assemble into exclusive plug-in workflow according to the unique needs of individual task from plug-in warehouse during scheduling operation by dynamic arrangement mechanism, realize the "thousand people thousand faces" and "one task one strategy" of scheduling strategy, so that scheduling strategy can dynamically adapt to task demand, completely solve the defect that static strategy cannot match individualized needs of task.

Methods, apparatus, and systems are disclosed for container attestation in client-based workloads. An example apparatus includes at least one memory, machine readable instructions, and processor circuitry to at least one of instantiate or execute the machine readable instructions to access a container attestation and an owner policy, the container attestation including a first signature and the owner policy including a second signature, determine that the first signature and the second signature are valid, iterate through configuration sets of the owner policy to identify a match between a claim of the container attestation and a configuration set, identify a resource constraint associated with the configuration set, and generate a resource description based on the resource constraint, the resource description to determine execution of a container workload on a client-based platform.

The invention discloses a resource allocation method and device for maritime emergency rescue. The method comprises the following steps: acquiring a maritime emergency rescue demand information set, a rescue resource description information set and a rescue resource technical state parameter time sequence set; the rescue resource description information comprises a rescue capability index value; each rescue demand index is in one-to-one correspondence with the rescue capability index; preprocessing the maritime emergency rescue demand information set, the rescue resource description information set and the rescue resource technical state parameter time sequence set to obtain a preprocessed information set; performing resource allocation processing on the preprocessed information set to obtain a resource allocation information set; the resource allocation information set comprises resource allocation information; the resource allocation information is used for describing allocation information of resources for tasks.

The invention, which relates to the technical field of the computing power Internet, discloses a computing power identification method for the computing power Internet, comprising the following steps: S1, collecting computing power resource information; s2, computing power identification coding; s3, registering and reporting the computing power identifier; s4, computing power identification analysis and statistics are carried out; and S5, scheduling based on computing power identification. According to the computing power identification method oriented to the computing power internet, the computing power resources are identified in a unified mode through clear steps and coding principles, the problem that in the prior art, description and positioning of the computing power resources are lack of unified standards and specifications is solved, description, positioning and addressing of the computing power resources can be achieved, and the computing power resources can be identified in a unified mode. And the deep development requirement of the computing power internet is met. And through registration, reporting, analysis and statistics of the computing power identifiers, unified resource description is provided for links such as access, perception, scheduling and transaction settlement of the computing power resources, so that efficient management and scheduling of the computing power resources are realized, and the utilization efficiency of the computing power resources is improved.

The invention discloses a real-time house resource matching system and method based on LBS and dynamic weight, and relates to the technical field of house resource information processing, and the method comprises the steps: constructing a dynamic semantic network fusing a house resource description text and geographic space information; establishing a dynamic weight calibration strategy of spatio-temporal situation perception, and generating a dynamic house resource weight representing the current spatio-temporal situation and the potential demand of the user; based on the dynamic semantic network and the dynamic house resource weight, performing multi-source evidence cross validation in combination with user query semantics, house resource geographic space attributes, historical user evaluation emotion tendencies and house resource surrounding real-time environment data to generate a house resource matching evaluation result; collecting and analyzing a user interaction behavior track, and identifying dynamic transformation information of a user behavior mode; and according to the housing resource matching evaluation result and the dynamic transformation information, generating and executing differential matching strategies for different users.

The invention discloses a knowledge graph construction method and device, equipment, a storage medium and a program product. The method comprises the following steps: acquiring resource description information of a target domain; the method comprises the following steps: extracting a large model through target information, and extracting entities, association relationships between the entities and attribute information of the entities from resource description information to obtain an entity-relationship-entity triple and an entity-attribute-attribute value triple; the target information extraction large model is obtained by performing fine tuning on a first information extraction large model based on a fine tuning data set, the first information extraction large model is obtained by pre-training an initial information extraction large model based on first resource description sample information, and the fine tuning data set comprises second resource description sample information and a corresponding triple tag; and based on the entity-relation-entity triple and the entity-attribute-attribute value triple, constructing a knowledge graph of the target domain. According to the embodiment of the invention, the construction efficiency of the knowledge graph can be improved.

The embodiment of the invention discloses an instruction scheduling method and device, computer equipment and a storage medium, and belongs to the technical field of computers. The method comprises the steps that hardware resource description information is obtained, the hardware resource description information comprises description information of multiple instructions, and the description information comprises first hardware resources needed to be used by the instructions; the hardware resource description information is updated, so that the description information of the at least one instruction comprises at least one of a first virtual hardware resource and a second virtual hardware resource and a first hardware resource, and the first virtual hardware resource represents a space to which a transmitting slot required to be used by the instruction belongs in an instruction packet; the second virtual hardware resource represents a pipeline stage to which the instruction belongs; and in the instruction scheduling process, conflict detection is carried out based on the updated hardware resource description information. According to the method and the device, the conflict detection accuracy is improved, the instruction scheduling accuracy is further improved, the operation is simplified, and the operation efficiency is improved.

The embodiment of the invention provides a resource information processing method and device, a storage medium and a program product. After a terminal request is received, a first target object triggered by a preset behavior and a second target object of which the historical interest is higher than a threshold value are included in a conversion range, and a target resource mapping matrix is constructed in real time in combination with resource information updated by a platform in real time and a use rule; converting the matrix into a target resource allocation matrix capable of representing an optimal allocation relationship between resource information and objects by taking maximization of the quantity of resources allocated to all target objects as a target, and completing global assignment at one time; and generating resource description information according to the target resource allocation matrix and displaying the information back to the terminal to guide the user to complete the target operation. According to the scheme, normal form upgrading from static superposition to dynamic matrix global optimal allocation is realized, continuous, accurate and maximized resource saving experience is provided for a user in a scene that multiple target objects, resource information and use rule information thereof change in real time, and the platform object conversion rate is remarkably improved.

The invention relates to a virtualized security resource pool construction method, system and device and a medium. The method comprises the following steps: carrying out attribute normalization on state data and credible baseline measurement to obtain a security resource description set and a baseline measurement abstract; converting the business demand information into a business security intention graph by adopting intention modeling; generating a candidate service chain, a candidate instance set and a verifiable service chain pass according to the security resource description set, the service security intention graph and the baseline measurement abstract; performing remote certification on the candidate instance set to collect runtime measurement reports, and performing credible instance screening according to the matching condition with the baseline measurement abstract to obtain a credible security instance pool; and performing mapping binding on each function node of the candidate service chain and the instance in the trusted security instance pool, and adding a corresponding verifiable service chain pass to a mapping binding relationship to obtain a security resource pool. By adopting the method, the virtualized security resource pool deployed by the trusted service chain can be generated.

A computing device, a method of operation thereof, and a machine-readable storage medium are provided. The computing device includes execution unit (EU) circuitry and instruction scheduler (IS) circuitry. The IS circuitry can issue instructions to the EU circuitry for execution. The IS circuitry includes a descriptor address register (DAR). The DAR is used to store address information of a resource descriptor. In a case where a current instruction being processed by the IS circuitry uses the resource descriptor, the IS circuitry accesses the address information stored in the DAR local to the IS circuitry without triggering the EU circuitry to read the address information of the resource descriptor from a scalar register file external to the IS circuitry to the IS circuitry. After obtaining the address information of the resource descriptor, the IS circuitry issues the current instruction using the resource descriptor to the EU circuitry for execution based on the address information.

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

A manufacturing system design verification apparatus capable of expanding design information that can be verified is provided. The manufacturing system design verification apparatus has a design information model, a design information input section, a verification logic storage section, and a design information verification section. The design information model is a framework that collectively represents design information. Design information is input to the design information input section. The design information input section converts the design information into an expression described by a resource description language with reference to the design information model. The verification logic storage section stores verification logic including a group of queries described by a query language corresponding to the resource description language and an expected result. The design information verification section has a query execution engine that executes a query on the expression and returns an execution result, and a comparison engine that compares the execution result with the expected result and returns a verification result.

The invention provides a service deployment system, method and device, electronic equipment, a storage medium and a product, and belongs to the field of cloud computing. The method comprises the steps that a second deployment request, sent by a client, of a target service facing a second virtual private cloud is received, the second deployment request comprises a deployment file, and the deployment file comprises resource description information of resources needed when the target service corresponding to the second virtual private cloud runs and an automatic script; on the basis of the deployment file, configuring resources required for operation for a target service corresponding to the second virtual private cloud in the first virtual private cloud; and after the resource configuration is completed, loading the target mirror image file in the object storage service of the first virtual private cloud into the configured computing resource so as to complete the deployment of the target service oriented to the second virtual private cloud. According to the method and the device, the resources required for operation of the target service can be automatically configured, and the mirror image file of the target service can be automatically loaded, so that automatic deployment of the target service is realized, and the complexity of a deployment process is simplified.

This invention discloses a method and system for pooling description and scheduling adaptation of heterogeneous hardware resources on the device side for embodied tasks. The method includes: identifying heterogeneous hardware resources on the device side; performing pooling modeling on the resources and collecting capability parameters, real-time status, and interface protocol types; generating standardized resource description files and uploading them to the cloud; and matching and adapting resources according to the requirements of the embodied task and issuing scheduling instructions from the cloud. This invention achieves a unified expression of device-side resource capabilities, improving resource utilization and scheduling efficiency.

The invention provides a cross-cluster scheduling method and system for heterogeneous computing power resources, and the method comprises the steps: carrying out the unified modeling of different types of hardware resources in a plurality of heterogeneous computing power clusters according to a preset resource description specification, and generating a global unified virtual resource pool model; collecting dynamic state information of internal resources of the heterogeneous computing power clusters from the heterogeneous computing power clusters in real time, and performing mapping and updating according to the virtual resource pool model; receiving a user job, analyzing a resource demand specification of the user job, and retrieving an available resource set meeting the resource demand specification among a plurality of clusters based on the updated virtual resource pool model; and selecting a target resource from the available resource set according to a preset scheduling strategy, converting the user job into a job instruction which can be identified by a target cluster, and distributing the job instruction to a corresponding cluster for execution. According to the invention, the overall utilization rate and scheduling efficiency of computing power resources can be improved.

The application discloses a data transmission system resource scheduling method based on a declarative API and a storage medium, belongs to the technical field of resource scheduling under a Kubernetes environment, and aims to solve the technical problem of how to utilize Kubernetes resource arrangement capability to realize convenient and quick scheduling of data transmission system resources.The technical scheme is as follows: the method is as follows: custom API resource type CRD: defining the resource type CRD of the collection end resource, the warehousing end resource and the message middleware resource of the data transmission system respectively; wherein, the group of the resource type CRD is dts; the resource description file corresponding to the resource type CRD is used to schedule the collection end resource, the warehousing end resource and the message middleware resource, and the corresponding resource scheduling work is realized through the resource file of the application captured by the custom controller; the definition of the resource file is used to complete the abstraction of the underlying physical resource and the business logic resource, and the scheduling of the business resource is realized through the custom controller.

The invention provides an SDN network structure and a communication method thereof, and belongs to the technical field of network architectures, and the network structure comprises a controller, a distributed fault detection node, a cross-domain resource interaction module and an elastic forwarding plane module. The distributed fault detection nodes collect fault information and transmit the collected fault information to the data intercommunication layer; the cross-domain resource interaction module generates a resource availability matrix, and transmits the resource availability matrix to the data intercommunication layer through a cross-domain resource description protocol; the elastic forwarding plane module collects a load-energy efficiency mapping relation and transmits the load-energy efficiency mapping relation to the data intercommunication layer; and the data intercommunication layer receives the fault information, the resource availability matrix and the load-energy efficiency mapping relation, sends the fault information and the resource availability matrix to the reinforcement learning safety-flow cooperative scheduling module, and sends the load-energy efficiency mapping relation to the fault self-healing path reconstruction module. On-demand collaboration is realized, and industrial control service time delay is reduced.

The invention discloses a network target range resource pool dynamic construction method based on multi-architecture virtualization fusion, comprising: abstracting heterogeneous computing resources from a multi-architecture virtualization environment into a resource abstract description unit according to a uniform resource description model, the multi-architecture virtualization environment comprising at least two different types of virtualization architectures; generating a dynamic construction request containing resource function attributes and architecture constraint conditions based on target range experiment requirements; and according to architecture constraint conditions in the dynamic construction request, packaging the matched resource abstract description units into virtualized resource instances meeting target range experiment requirements as required through a dynamic packaging adapter, and obtaining a network target range resource pool. Cross-architecture abstraction is carried out on electric power heterogeneous equipment through a uniform resource description model, and the problem that multiple types of industrial control nodes cannot be fused in a traditional target range is solved; and based on the architecture constraint condition of the dynamic construction request, driving resource packaging, and realizing the real-time reconstruction of the topology in the attack and defense experiment process.

This application relates to the field of unmanned aerial vehicle (UAV) technology and discloses a method for generating a modeling language for UAV swarm application scenarios. The method includes: constructing a task model to determine the three-level hierarchical relationship between the UAV swarm's scenario tasks, tasks, and sub-tasks, the collaborative relationships between tasks, and the collaborative relationships between sub-tasks; constructing a resource model to analyze the resources required by the task model and provide a unified resource description; constructing a constraint model to analyze the constraints of each UAV regarding resources, motion, environment, and time, and determining the constraints of the UAV swarm based on the constraints corresponding to each UAV; determining the BNF paradigm of the task model, resource model, and constraint model, and constructing syntax rules; constructing XML conforming to the BNF paradigm based on the syntax rules, and combining the results to generate a modeling language for UAV swarm application scenarios applicable to different application scenarios, providing a good underlying foundation for multi-UAV collaborative task planning.