WO2021056201A1 - Procédé et dispositif pour évaluer un système à déployer et support de stockage lisible par ordinateur - Google Patents

Procédé et dispositif pour évaluer un système à déployer et support de stockage lisible par ordinateur Download PDF

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Publication number
WO2021056201A1
WO2021056201A1 PCT/CN2019/107582 CN2019107582W WO2021056201A1 WO 2021056201 A1 WO2021056201 A1 WO 2021056201A1 CN 2019107582 W CN2019107582 W CN 2019107582W WO 2021056201 A1 WO2021056201 A1 WO 2021056201A1
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Prior art keywords
deployed
elements
configuration
performance
user
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PCT/CN2019/107582
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English (en)
Chinese (zh)
Inventor
于禾
王琪
周文晶
孙维
张海涛
王力
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西门子股份公司
西门子（中国）有限公司
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Priority to PCT/CN2019/107582 priority Critical patent/WO2021056201A1/fr
Publication of WO2021056201A1 publication Critical patent/WO2021056201A1/fr

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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06G—ANALOGUE COMPUTERS
    • G06G7/00—Devices in which the computing operation is performed by varying electric or magnetic quantities
    • G06G7/48—Analogue computers for specific processes, systems or devices, e.g. simulators
    • G06G7/62—Analogue computers for specific processes, systems or devices, e.g. simulators for electric systems or apparatus

Definitions

  • the embodiments of the present disclosure relate to the computer field, and more specifically, to methods, devices, and computer-readable storage media for evaluating a system to be deployed.
  • IoT Internet of Things
  • IT information technology
  • cloud services provide a good choice, which enables users to quickly expand service resources and/or capacity, such as bandwidth, central processing unit (CPU), random access memory (RAM), and so on.
  • service resources and/or capacity such as bandwidth, central processing unit (CPU), random access memory (RAM), and so on.
  • a set of IoT services can be built in the cloud.
  • each sub-service is usually allocated a container, such as one (Kubernetes, K8S).
  • K8S Kernetes
  • this blind expansion method increases the cost of building IoT services.
  • the inventor of this application realizes that in IoT or IoT-based closed-loop services, some problems need to be faced.
  • the first question is how to set the connection or communication mode of the various elements involved in the loT/closed-loop service; the second question is how to ensure normal service communication and avoid bottlenecks; the third question is how to choose the best deployment plan and maintain continuous Optimization and integration.
  • embodiments of the present disclosure provide methods, devices, and media for evaluating a system to be deployed.
  • the operation of the system to be deployed can be simulated based on the system configuration of the system to be deployed and the functional configuration (for example, scripts) of multiple elements constituting the system to be deployed, so as to predict and evaluate the system to be deployed before actual deployment , And make adjustments if necessary.
  • an efficient and cost-effective system such as an IoT service system.
  • a method for evaluating a system to be deployed includes: obtaining the system configuration of the system to be deployed, the system configuration including the individual configuration of the multiple elements constituting the system to be deployed and the association between the multiple elements; based on the system configuration and the functional configuration corresponding to the multiple elements, Simulate the operation of the system to be deployed, the functional configuration is used to define at least one or more operations associated with the corresponding element; and through simulation, obtain the evaluation result of the system to be deployed, the evaluation result at least indicates whether the system to be deployed achieves expected performance.
  • the performance of the system to be deployed can be evaluated from the level of the entire system (not necessarily the level of part of the application or part of the device) before the actual deployment, and determine whether the configuration of the desired system meets the requirements.
  • the finally deployed system (such as a system for IoT services) can be operated in an efficient and cost-saving manner.
  • the multiple elements include at least two of the following: device, application, operating environment, communication protocol, message protocol, and database.
  • the system to be evaluated can be customized according to the specific system desired to be constructed, and elements such as the system can be integrated.
  • obtaining the evaluation result includes: determining the performance of the simulated system to be deployed through simulation; determining whether the performance of the system to be deployed is lower than the expected performance; and if it is determined that the performance of the system to be deployed is lower than the expected performance, then Identify multiple elements that cause performance below the expected performance. In this way, it is possible to determine the bottleneck that causes the performance not to meet the performance requirements, that is, to determine the potential defects of the system to be deployed. As a result, adjustments can be made to the identified defects, thereby improving the system to be deployed.
  • the method further includes: selecting another element to replace the identified element from candidate elements of the same type as the identified element; and providing the user with an indication of the other element so that the user can Adjust the system to be deployed based on the instructions. In this way, alternatives to defects can be provided so that users can more easily improve the system to be deployed. In addition, in this way, the knowledge threshold required to construct a service system can be reduced.
  • obtaining the system configuration includes: providing a user with a representation of candidate elements and configurable parameters of the candidate elements that constitute the system to be deployed; and receiving a user's selection of multiple elements among the candidate elements, The arrangement of elements and configuration parameters for multiple elements.
  • users can easily configure the system to be deployed and avoid blind construction.
  • users' requirements for professional knowledge of building a service system can be reduced, so that the needs of more users can be met.
  • simulating the operation of the system to be deployed includes: for one element among multiple elements, parameterizing the functional configuration corresponding to the element based on the individual configuration of the element; and running the parameter based on the association of the multiple elements Functional configuration.
  • the method further includes: generating a script for simulating the operation of the system to be deployed based on the parameterized function configuration; and providing the script to the user for the user to use when deploying the system to be deployed.
  • the user can reuse the test script to further help the user build a system with excellent performance.
  • the system to be deployed is intended to be deployed into an IoT system.
  • the services in the IoT system usually involve elements such as, and these elements have complex associations.
  • the IoT service system to be built can be comprehensively evaluated before actual deployment, which helps to provide high-quality IoT services without causing system redundancy and cost increase.
  • the functional configuration includes scripts or functions.
  • the functional configuration for simulating the operation associated with the element is implemented in a common form, so that the simulation of the system to be deployed can be conveniently performed.
  • a device for evaluating a system to be deployed includes a processor and a memory coupled with the processor.
  • the memory has instructions stored therein, and the instructions cause the electronic device to perform actions when executed by the processor.
  • Actions include: obtaining the system configuration of the system to be deployed.
  • the system configuration includes the individual configuration of multiple elements constituting the system to be deployed and the association between multiple elements; simulation based on the system configuration and the functional configuration corresponding to the multiple elements
  • the operation and functional configuration of the system to be deployed are used to at least define one or more operations associated with the corresponding element; and through simulation, the evaluation result of the system to be deployed is obtained, and the evaluation result at least indicates whether the system to be deployed achieves the expected performance.
  • a computer-readable storage medium having computer-executable instructions stored thereon, and the computer-executable instructions, when executed, cause at least one processor to execute each of the methods according to the first aspect. Examples.
  • Fig. 1 shows a schematic diagram of an environment in which an embodiment of the present disclosure can be implemented
  • Fig. 2 shows a schematic diagram illustrating an example of a knowledge model according to an embodiment of the present disclosure
  • FIG. 3 shows a flowchart of a process for evaluating a system to be deployed according to an embodiment of the present disclosure
  • FIG. 4 shows a schematic diagram illustrating selection of elements of a system to be deployed according to an embodiment of the present disclosure
  • FIG. 5 shows a schematic diagram illustrating parameters of configuring elements of a system to be deployed according to an embodiment of the present disclosure
  • FIG. 6 shows a schematic diagram illustrating the integration of system configuration according to an embodiment of the present disclosure
  • FIG. 7 shows a schematic diagram of an example process for obtaining evaluation results according to an embodiment of the present disclosure
  • FIG. 8 shows a schematic diagram illustrating the provision of evaluation results according to an embodiment of the present disclosure.
  • Figure 9 shows a block diagram of an example device that can be used to implement embodiments of the present disclosure.
  • resources can be dynamically expanded based on the cloud, but this expansion is usually blind and does not consider how to prove and save costs.
  • the inventor of the present application realizes that in order to enable IoT services or other types of services involving computing resources, storage resources, communication resources, etc., to operate efficiently without system redundancy, a comprehensive verification and evaluation is carried out before deploying the service system would be advantageous. Through verification and evaluation, the deployment plan of the service system can be adjusted in a targeted manner, so that the deployed system can meet the performance requirements without causing unnecessary waste of resources and costs.
  • a solution for evaluating a system to be deployed is provided.
  • the operation of the system to be deployed can be simulated based on the system configuration of the system to be deployed and the functional configuration (for example, scripts) of multiple elements constituting the system to be deployed, so as to predict and evaluate the system to be deployed before actual deployment, and Make adjustments if necessary.
  • the functional configuration for example, scripts
  • FIG. 1 shows a schematic diagram of an environment 100 in which an embodiment of the present disclosure can be implemented.
  • the environment 100 includes a user 102 and a computing device 101, where example embodiments according to the present disclosure may be implemented on the computing device 101, for example, may be implemented as a service building tool. Therefore, the computing device 101 may also be referred to as a service construction device 101 herein.
  • the environment 100 shown in FIG. 1 is only exemplary, and multiple computing devices may also be used for system evaluation and verification.
  • the computing device 101 may be a stationary computing device or a portable computing device, such as a mobile phone, a tablet computer, and the like.
  • the computing device 101 may be a separate computing device or a distributed computing device.
  • the user 102 or other users desire to build a computing system including multiple elements, such as an IoT-based service system.
  • a system may be referred to as a system to be deployed.
  • the system to be deployed can be a system that is completely rebuilt or conceived, or it can be a system that has been changed, added, or deleted on top of the built system.
  • the embodiments according to the present disclosure are not limited in this respect. The embodiments of the present disclosure can be used to evaluate such systems to be deployed.
  • the computing device 101 may include a knowledge module 110, a layout module 120, and a verification module 130.
  • the knowledge module 110 integrates information of various elements that may be used when constructing a system for IoT services or closed-loop services. For the purpose of discussion only, this collection of information is referred to as a knowledge model in this article.
  • the various elements involved in the knowledge module 110 for constructing a computing system may include, but are not limited to, equipment, applications, operating environments, deployment methods, communication protocols, message protocols, databases, and so on.
  • the knowledge module 110 may include the knowledge model 111 of the device, the knowledge model 112 of the application, the knowledge model 113 of the operating environment, the knowledge model 114 of the deployment mode, the knowledge model 115 of the communication protocol, the knowledge model 116 of the message protocol, and the knowledge model 116 of the database. Knowledge model 117 and so on.
  • the equipment involved in the knowledge model 111 of the equipment may include both physical equipment and virtual equipment.
  • Physical equipment may include, but is not limited to, computing equipment, data collection equipment, data storage equipment, monitoring equipment, and so on. Such physical devices can be fixed, portable, or embedded in other machines.
  • the knowledge model 111 of the device may include the knowledge model of a controller, a data logger, a programmable logic controller (PLC), and a Raspberry Pi.
  • Virtual devices may include, but are not limited to, virtual machines, containers, and so on.
  • the knowledge model about virtual machines and containers may also be included in the knowledge model 114 of the deployment mode.
  • the application knowledge model 112 may involve applications that are intended to be deployed on various physical devices and virtual devices.
  • the knowledge model 113 of the operating environment may involve various software operating systems, such as a Windows operating system, a Linux operating system, and an Android system.
  • the knowledge model 114 of the deployment mode may involve a direct deployment mode, a virtualized deployment mode, such as a virtual machine or container deployment.
  • the knowledge model 115 of the communication protocol may involve the protocols used for communication between various devices, devices, and machines, such as Hypertext Transfer Security Protocol (HTTPS), Transmission Control Protocol/Internet Protocol (TCP/IP), and industrial The protocol used, such as the OPC data acquisition protocol.
  • HTTPS Hypertext Transfer Security Protocol
  • TCP/IP Transmission Control Protocol/Internet Protocol
  • industrial The protocol used such as the OPC data acquisition protocol.
  • the knowledge model 116 of the message protocol may involve various protocols for transmitting the message queue, which, for example, specifies the organization structure, content format, and hierarchy of the message queue.
  • message protocols may include, for example, the Message Queuing Telemetry Transmission (MQTT) protocol, the Advanced Message Queuing Protocol AMQP, and the like.
  • the knowledge model 117 of the database may involve databases of various sizes, such as SQL server, Oracle database, and so on. It should be understood that the classification of the various elements used to construct the computing system as described above is only exemplary, and the knowledge model of these elements can be created in other ways or classifications. As shown in FIG. 1, the knowledge model and elements included in the knowledge module 110 are extensible, for example, it can be extended by the user 102 or professionals.
  • FIG. 2 shows a schematic diagram 200 illustrating an example of the knowledge model 210 according to an embodiment of the present disclosure.
  • the knowledge model 210 may refer to any one of the knowledge models 111-117 shown in FIG. 1.
  • the knowledge model 210 may include four parts, which are attribute definition 211, function configuration 212, performance restriction 213, and association 214, respectively.
  • the attribute definition 211 can define one or more basic attributes of the element involved in the knowledge model 210, and these basic attributes can be used to describe the element.
  • the attribute values of some of the defined attributes can be set as default values by the knowledge module 110, and the attribute values of other attributes can be set or selected by the user 102 when constructing the system to be deployed.
  • the defined attributes may include the hardware configuration of the device, including the capacity of computing resources, communication resources, and storage resources. Wait.
  • the attribute definition 211 may include CPU, RAM, hard disk, pointer length running per second, and so on.
  • the attribute definition 211 may include the data collection rate and the like.
  • the defined attributes may include the development tools, framework, dependencies, and application programming interface (API) types, parameters, etc. of the application.
  • the function configuration 212 may be used to define one or more operations associated with the corresponding element, for example, calculation or simulation of data source, communication, and resource consumption.
  • the function configuration 212 may be implemented in a script, a function block, a function, or a combination thereof.
  • the functional configuration 212 may be a script used to define the resource consumption of the device, such as calculating or otherwise determining the computing resources consumed by an application with a specific attribute when running on the device. , Storage resources, communication resources, etc.
  • the functional configuration 212 may be a script for data simulation, search, and the like.
  • the performance limit 213 may support setting performance requirements related to the system to be deployed. Such performance requirements may include performance requirements for the entire system as well as performance requirements for individual elements (such as devices, applications, communication protocols, etc.) included in the system.
  • the knowledge module 110 can provide performance requirements that can be set by the user, and the user 102 can set specific values for each performance requirement when constructing the system to be deployed.
  • the knowledge model 210 relates to an application (for example, the knowledge model 112 of the application shown in FIG. 1)
  • the performance limit 213 may include the total number of users expected to be supported, the number of concurrency, balance, and the like.
  • the performance limitation 213 may include a limitation requirement on CPU usage, a ratio of RAM usage, and so on.
  • the association 214 may include the relationship between the elements involved in the knowledge model 111-117 included in the knowledge module 110. For example, such a relationship may indicate that the application is deployed on the device, the device is loaded with an operating system, and the devices transfer information according to the communication protocol and the message protocol.
  • the association 214 can indicate the relationship between elements in various ways. In some embodiments, the association 214 may be realized by the knowledge graph 224 shown in FIG. 2. The nodes in the knowledge graph 224 may represent elements or components of elements.
  • Each of the knowledge models 111-117 shown in FIG. 1 may include one or more of the attribute definition 211, the function configuration 212, the performance restriction 213, and the association 214 described with respect to FIG. 2. It should be understood that the construction and mechanism of the knowledge model 210 shown in FIG. 2 are only exemplary, and the information used to construct the elements of the system to be deployed may be organized in other ways.
  • the layout module 120 can be used to instantiate the system to be deployed.
  • the layout module 120 may include a model instantiation unit 121, an association determination unit 122 and a performance setting unit 123.
  • the layout module 120 may provide the user 102 with a visual user interaction interface, and provide the user 102 with the representation of the elements included in the knowledge module 110 through the interaction interface. In this way, the user 102 can conveniently construct the system to be deployed based on the interactive drag-and-drop operation.
  • the user 102 can also set the configuration parameters and performance requirements of the selected element through an interactive interface. Such an embodiment will be described in detail below in conjunction with FIGS. 4 and 5.
  • the verification module 130 may be used to simulate the operation of the system to be deployed and provide an evaluation result 103 of the system to be deployed. For example, the verification module 130 may simulate the operation of the system to be deployed based on the instance of the system to be deployed obtained by the layout module 120 and the related knowledge model in the knowledge module 110. If the system to be deployed does not meet the expected performance (for example, the performance requirements set by the user 102), the verification module 130 may also determine the corresponding bottleneck. In the example environment 100 of FIG. 1, the verification module 130 may include a simulation execution unit 131, an element identification unit 132 and a result generation unit 133.
  • the evaluation result 103 may include one or more of the following: the system configuration of the evaluated system, the expected performance that has not been reached, the elements that refer to the performance bottleneck, possible alternatives, computing resources, storage resources , The use of communication resources, possible expansion, etc.
  • the verification module 130 may also provide a test file for simulating the operation of the system to be deployed, such as a collection of test scripts 104.
  • modules shown in FIG. 1 and the units included in the modules are only exemplary, and are not intended to be any limitation.
  • the embodiments of the present disclosure can be divided into any suitable modules and/or units.
  • FIG. 3 shows a flowchart of a process 300 for evaluating a system to be deployed according to an embodiment of the present disclosure. It should be understood that the process 300 may be performed by the information processing device 101 described above with reference to FIG. 1. To facilitate discussion, the process 300 will be described with reference to FIG. 1.
  • the system configuration of the system to be deployed is obtained, where the system configuration includes respective individual configurations of multiple elements constituting the system to be deployed and associations between the multiple elements.
  • the system configuration of the system to be deployed can be obtained through the layout module 120 in FIG. 1, and the system to be deployed with the system configuration can also be regarded as an instantiated system to be deployed.
  • the instantiated system to be deployed may include multiple elements, such as one or more devices, one or more applications, one or more operating environments, one or more communication protocols, one or more message protocols, one One or more deployment methods, one or more databases, etc.
  • the system configuration may include individual configurations of these elements, for example, may include attribute values for each attribute defined in the attribute definition described in FIG. 1.
  • the individual configuration can include the specific capacity of the CPU, RAM, and hard disk.
  • the system configuration also includes the association between these elements, for example, the application is deployed on the device, and the devices communicate according to the communication protocol.
  • the system configuration of the system to be deployed can be obtained through the layout module 120.
  • the layout module 120 may directly receive (for example, from the user 102) a file including the system configuration.
  • the layout module 120 may obtain the system configuration of the system to be deployed from the user 102.
  • the layout module 120 may provide the user 102 with a representation of candidate elements and configurable parameters of the candidate elements for constituting the system to be deployed.
  • the layout module 120 may receive the user 102's selection of multiple elements among the candidate elements, the arrangement of the multiple elements, and the configuration parameters for the multiple elements.
  • the user 102 may be provided with candidate elements and related configurable parameters based on the knowledge model in the knowledge module 110. These candidate elements may be elements involved in the knowledge model 111-117, and may provide the user 102 with configurable parameters based on, for example, the attribute definition 211.
  • the layout module 120 may also obtain one or more prefetch properties related to the system to be deployed.
  • the expected performance may include the overall performance of the system to be deployed and the expected performance of one or more of its elements.
  • the layout module 120 may provide the user 102 with performance requirements that can be configured by the user based on the performance constraints 213 of the knowledge model, and receive the corresponding specific performance requirements from the user 102 as the expected performance.
  • one or more expected performance may also be a default value, such as an average value for a specific performance of the element.
  • FIG. 4 shows a schematic diagram 400 illustrating selection of elements of a system to be deployed according to an embodiment of the present disclosure.
  • the interactive interface mainly includes a display area 401 and a display area 402, where the display area 401 may present a representation of candidate elements for constructing the system to be deployed, in other words, it may indicate candidate elements for constructing the system to be deployed.
  • the sub-area 411 may indicate one or more candidate devices, such as Raspberry Pi, data logger, PLC, and so on.
  • the sub-region 412 may indicate one or more candidate applications, such as a data collection application, a spare parts management application, a material procurement application, and so on.
  • the sub-region 413 may indicate one or more candidate operating environments, such as a Windows system or a Linux system.
  • the sub-area 414 may indicate one or more deployment methods, such as direct deployment, virtualization, and so on.
  • the sub-area 415 may indicate one or more communication protocols, such as HTTPS, TCP/IP, and so on.
  • the sub-region 416 may indicate one or more message protocols, such as MQTT, AMQP, and so on. Each of these sub-regions 411-416 can be expanded or collapsed.
  • the user 102 can also add elements not included in the knowledge module 110 through the display area 401, or add a new knowledge model through the display area 401.
  • the display area 402 may present the layout of an example system to be deployed constructed by the user 102.
  • the application 422 is deployed on the field device 421.
  • the field device 421 may be a data acquisition device, such as a Raspberry Pi, and the application 422 may be a data acquisition application.
  • the cloud platforms 424 and 434 may be platforms based on the same or different mechanisms.
  • the field device 421 communicates with the cloud platform 434 according to MQTT 426, and communicates with the cloud platform 424 according to HTTPS 425.
  • the cloud platform 424 may include a space 429 where an application 432 is deployed and a space 439 where an application 442 is deployed.
  • the space 429 and the space 439 may be allocated the same amount or different amounts of virtualized resources.
  • the space 429 and the space 439 (and the application 432 and the application 442 deployed thereon) can exchange data through a database 427 such as PostgreSQL.
  • the cloud platform 434 may include nodes 428, 438, and 448 managed by the server 431.
  • An application 452 is deployed on the node 428, and applications 462 and 472 are deployed on the node 438.
  • the node 428 and the application 452 deployed thereon communicate with the application 472 deployed on the node 438 according to AMQP 436.
  • the node 448 may be implemented with another small cloud platform 444 in which an application 482 is deployed in the space 449.
  • the application 482 communicates with the application 462 according to HTTPS 446.
  • the arrangement of the system to be deployed shown in FIG. 4 is only exemplary and not intended to be limiting.
  • the embodiments according to the present disclosure can be applied to a system to be deployed with any suitable configuration and layout.
  • the constructed system may only involve elements arranged in the cloud; in other embodiments, the constructed system may only involve elements arranged in a field (for example, a factory).
  • FIG. 5 shows a schematic diagram 500 illustrating parameters of configuring elements of a system to be deployed according to an embodiment of the present disclosure.
  • the display area 501 may be presented above the display area 401 and the display area 402.
  • the sub-area 511 can be used to set the attributes of the selected element, such as the attributes defined by the knowledge model in the knowledge module 110 (for example, the attribute definition 211 shown in FIG. 2).
  • the application name, application development tools, framework, dependencies, API, uniform resource locator (URL), parameters, etc. can be configured in the subarea 511.
  • the sub-area 512 can be used to configure the prefetch performance, for example, to set the value of the performance limit defined by the knowledge model in the knowledge module 110.
  • a limit on the total number of users, a limit on the number of concurrent users, etc. of the application can be configured in the subarea 512.
  • a function configuration such as the function configuration 212 described with respect to FIG. 2
  • the automatically selected function configuration may also be presented to the user 102 in the sub-area 513.
  • the user 102 can select the recommended script.
  • the interactive interface shown in FIG. 5 is only exemplary and not intended to be limiting.
  • the embodiments according to the present disclosure may enable the user to set the individual configuration and expected performance of the selected element in any suitable manner.
  • the sub-region 511 and the sub-region 512 may be merged and presented to the user in a manner of pull-down and expansion.
  • block 320 based on the system configuration and the function configuration corresponding to the multiple elements, simulate the operation of the system to be deployed, where the function configuration is at least used to define one or more operations associated with the corresponding element.
  • the function configuration mentioned here may be the function configuration in the knowledge model involved in the knowledge module 110 (for example, refer to the function configuration 212 described in FIG. 2), such as scripts, functions, and function blocks.
  • the action of block 320 may be performed by, for example, the verification module 130 shown in FIG. 1.
  • FIG. 6 shows a schematic 600 illustrating the integration of the system configuration according to an embodiment of the present disclosure.
  • the verification module 130 can integrate or synthesize the acquired system configuration, for example, extract the instantiated system configuration of the system to be deployed to obtain the system schema 610 of the system to be deployed, when the system to be deployed is used for IoT services It can also be called a service mode.
  • the system mode 610 can be divided into an element 611, a data stream 612, and an expected performance 613.
  • the element 611 may be used to describe various elements (for example, devices, nodes, etc.) constituting the system to be deployed, including the configuration of the elements.
  • the data flow 612 may be used to describe the flow of data between elements (for example, various nodes and devices).
  • the expected performance 613 may be used to describe the performance requirements of at least some of the elements constituting the system to be deployed.
  • the verification module 130 can simulate the operation of the system to be deployed based on the system mode 610. For example, a script for the selected element may be organized based on the combination of the system pattern 610 and the knowledge module 110 to perform simulation. In the simulation process, the performance obtained through the simulation can be compared with the expected performance to determine whether the conceived system can meet the expected performance.
  • the verification module 130 may parameterize the functional configuration corresponding to the element based on the individual configuration of the element for one element of the multiple elements constituting the system to be deployed, and based on the multiple element configuration. Associate, run the parameterized function configuration. For example, for the element "device", the verification module 130 may select a suitable one or more scripts from the knowledge model of the device based on the association of the device with other elements in the system to be deployed. Then, the selected script is parameterized using the individual configuration of the device (for example, the configuration parameters selected by the user 102 via the layout module 120).
  • the verification module 130 may further organize the parameterized script based on the association of these elements (for example, deployment relationship, connection relationship, containment relationship, etc.). As just an example, script A and script B can be run in parallel, while script A and script C can be run in series, for example, the output of script A is used as the input of script C. At this time, the verification module 130 can simulate the operation of the entire to-be-deployed system, such as simulating the conceived service solution.
  • an evaluation result 103 of the system to be deployed is obtained.
  • the evaluation result at least indicates whether the system to be deployed achieves the expected performance.
  • the evaluation result 103 may indicate which of the expected performances set by the user 102 are satisfied and which are not satisfied.
  • the verification module 130 may further identify factors that cause the expected performance to be not achieved, such as one or more elements.
  • the verification module 130 may determine the performance of the simulated system to be deployed through simulation and determine whether the performance is lower than the expected performance. If it is determined that the performance is lower than the corresponding expected performance, the verification module 130 may identify an element among the plurality of elements that causes the performance to be lower than the expected performance.
  • FIG. 7 shows a schematic diagram of an example process 700 for obtaining evaluation results according to an embodiment of the present disclosure.
  • the actions of the example process 700 of FIG. 7 are described with respect to the simulation execution unit 131, the element identification unit 132, and the result generation unit 133, this is only illustrative and not intended to be limiting.
  • the embodiment of the present disclosure may divide the unit in other ways, or not do such division.
  • the simulation execution unit 131 sets 705 a data stream based on the system configuration and the knowledge model in the knowledge module 110, and generates 710 a virtual service, such as running a parameterized script. At the same time, the simulation execution unit 131 can monitor the execution of the simulation and determine one or more performances of the system to be deployed. The simulation execution unit 131 may compare the determined performance of the system to be deployed with the corresponding expected performance. If the determined performance does not meet the corresponding expected performance, the simulation execution unit 131 may send 720 to the element identification unit 132 an indication that one or some expected performances are not achieved. For example, the CPU occupancy rate of the field collection device obtained through simulation is 80%, and the expected value of the CPU occupancy rate for the field collection device is 50%. In this case, the simulation execution unit 131 may determine that the expected performance is not achieved.
  • the element identification unit 132 may identify 720 an element (also referred to as a risk element) that causes the determined performance to be lower than the expected performance among the elements constituting the system to be deployed, and may send an indication of the element identified by 725 to the result generation unit 133.
  • the result generating unit 133 may present the element identified by 730 to indicate to the user 102 or other parties that the identified element has a problem or risk.
  • the element identification unit 132 may further determine another element to replace the risk element. For example, the element identification unit 132 may select 735 another element to replace the risk element from candidate elements of the same type as the identified risk element. For example, if a certain communication protocol constituting the system to be deployed is identified as a risk element, the element identification unit 132 may also select another communication protocol based on the knowledge model 115 of the communication protocol included in the knowledge module 110. The element identification unit 132 may send 740 an indication of another element selected as the recommended element to the result generation unit 133. The result generation module 133 may provide 745 the instruction, for example, so that the user 102 or other related parties can adjust the system to be deployed based on the instruction. For example, the risk element originally configured in the system to be deployed can be replaced with a recommended element, or the configuration parameters of the risk element can be modified.
  • FIG. 8 shows a schematic diagram 800 illustrating the provision of evaluation results according to an embodiment of the present disclosure.
  • FIG. 8 schematically shows the evaluation of the system to be deployed constructed in FIG. 4.
  • warning signs 801, 802, 803 are used to present the identified risk elements.
  • the warning sign 801 indicates that MQTT 426 is a risk element
  • the warning sign 802 indicates that the cloud platform 424 is a risk element
  • the warning sign 803 indicates that the application 472 is a risk. element.
  • the verification model 130 provides a corresponding alternative, that is, a recommended element.
  • HTTPS 826 can be used instead of MQTT 426.
  • the user 102 or other related parties can adjust the system to be deployed based on the recommended element.
  • the verification module may also provide corresponding recommendation elements.
  • the user 102 or other related parties may also adjust the configuration parameters of the risk element based on the prompt of the warning sign.
  • the verification module 130 may also generate a script for simulating the operation of the system to be deployed based on the parameterized functional configuration, for example, as a test script; and provide the script to the user for subsequent use by the user, for example Used when deploying the system to be deployed.
  • Figure 9 shows a schematic block diagram of an example device 900 that can be used to implement embodiments of the present disclosure.
  • the device 900 may be used to implement the process 300 of FIG. 3 and/or the process 700 of FIG. 7.
  • the device 900 may be implemented as the device 101 described above.
  • the device 900 includes a central processing unit (CPU) 901, which can be loaded according to computer program instructions stored in a read-only memory (ROM) 902 or loaded from a storage unit 908 to a random access memory (RAM) 903. Program instructions to perform various appropriate actions and processing. In the RAM 903, various programs and data required for the operation of the device 900 can also be stored.
  • the CPU 901, the ROM 902, and the RAM 903 are connected to each other through a bus 904.
  • An input/output (I/O) interface 905 is also connected to the bus 904.
  • the I/O interface 905 includes: an input unit 906, such as a keyboard, a mouse, etc.; an output unit 907, such as various types of displays, speakers, etc.; and a storage unit 908, such as a magnetic disk, an optical disk, etc. ; And the communication unit 909, such as a network card, a modem, a wireless communication transceiver, etc.
  • the communication unit 909 allows the device 900 to exchange information/data with other devices through a computer network such as the Internet and/or various telecommunication networks.
  • the processing unit 901 executes the various methods and processes described above, for example, the processes 300 and/or 700.
  • the process 300 and/or 700 may be implemented as a computer software program or computer program product, which is tangibly contained in a computer-readable medium, such as a non-transitory computer-readable medium (such as a storage unit). 908).
  • part or all of the computer program may be loaded and/or installed on the device 900 via the ROM 902 and/or the communication unit 909.
  • the CPU 901 may be configured to execute the processes 300 and/or 700 in any other suitable manner (for example, by means of firmware).

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  • Computer Hardware Design (AREA)
  • Physics & Mathematics (AREA)
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  • General Physics & Mathematics (AREA)
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  • Stored Programmes (AREA)

Abstract

La présente invention concerne un procédé et un dispositif pour évaluer un système à déployer et un support de stockage lisible par ordinateur. Le procédé d'évaluation d'un système à déployer consiste à obtenir une configuration de système d'un système à déployer, la configuration de système comprenant une configuration individuelle de chacun des multiples éléments constituant le système à déployer et une association entre les multiples éléments (310). Le procédé consiste également à simuler des fonctionnements du système à déployer sur la base de la configuration du système et des configurations fonctionnelles correspondant aux multiples éléments, la configuration fonctionnelle étant utilisée pour au moins définir un ou plusieurs fonctionnements associés à l'élément correspondant (320). Le procédé consiste en outre à obtenir un résultat d'évaluation pour le système à déployer au moyen d'une simulation, le résultat d'évaluation indiquant au moins si le système à déployer atteint des performances attendues (330). En évaluant un système avant le déploiement réel, le système déployé final peut fonctionner de manière efficace et peu coûteuse.
PCT/CN2019/107582 2019-09-24 2019-09-24 Procédé et dispositif pour évaluer un système à déployer et support de stockage lisible par ordinateur WO2021056201A1 (fr)

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Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20100082314A1 (en) * 2008-09-30 2010-04-01 Rockwell Automation Technologies, Inc. Simulation of tuning effects for a servo driven mechatronic system
CN106054822A (zh) * 2015-04-08 2016-10-26 西门子公司 规划和工程设计方法，软件工具和模拟工具
CN106534270A (zh) * 2016-10-21 2017-03-22 上海庆科信息技术有限公司 一种物联网模拟系统
WO2018158181A1 (fr) * 2017-02-28 2018-09-07 Siemens Aktiengesellschaft Système d'entraînement et évaluation associée

Patent Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20100082314A1 (en) * 2008-09-30 2010-04-01 Rockwell Automation Technologies, Inc. Simulation of tuning effects for a servo driven mechatronic system
CN106054822A (zh) * 2015-04-08 2016-10-26 西门子公司 规划和工程设计方法，软件工具和模拟工具
CN106534270A (zh) * 2016-10-21 2017-03-22 上海庆科信息技术有限公司 一种物联网模拟系统
WO2018158181A1 (fr) * 2017-02-28 2018-09-07 Siemens Aktiengesellschaft Système d'entraînement et évaluation associée

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