TWI722643B - Method of deploying cloud services quickly - Google Patents

Abstract

A method of deploying cloud services quickly is provided. The method is to make a local apparatus be connected to a cloud virtual machine of a cloud server, establish a cloud agent module in the cloud virtual machine, continuously synchronize local data from the local apparatus to the cloud virtual machine and converse the local data into cloud structured data, upload local data flow task from the local apparatus to the cloud virtual machine for configuring cloud task program. A cloud execution result based on the cloud task program and the cloud structured data corresponds to a local execution result based on the local data and the local data flow task.

Description

A method to quickly deploy cloud services

The present invention is related to cloud services, and particularly relates to methods for deploying cloud services.

Existing IoT systems usually consist of management equipment, gateways, and multiple local devices. The local device is connected to the gateway and used to obtain data streams (such as sensing data). The management device can be connected to the gateway through an internal network (such as a local area network or a corporate private network).

When the administrator wants to monitor the local equipment, it is to operate the management equipment to connect to the gateway via the aforementioned internal network, and to view the operating status and data flow of the local equipment through the gateway to monitor and manage the local equipment

The existing Internet of Things system does not have a remote monitoring function because it is set up based on the internal network, which makes it very inconvenient for the administrator to go to the place where the Internet of Things system is installed to perform monitoring and management.

The present invention provides a method for rapidly deploying cloud services, which allows users to quickly deploy services of near-end devices to a cloud server without requiring complicated operation settings.

In one embodiment, a method for quickly deploying cloud services is used to deploy services of a near-end device to a cloud server. The method for quickly deploying cloud services includes the following steps: connecting the near-end device to the cloud server according to cloud virtual machine connection information Cloud virtual machine of the device; in the cloud virtual machine Build a cloud proxy module for the local device; establish a cloud synchronization connection between the near-end device and the cloud server, and continuously synchronize the local data of the near-end device to the cloud virtual machine through the cloud synchronization connection; use the cloud proxy module on the cloud virtual machine Convert local data to cloud structured data; upload the local data flow job of the near-end device to the cloud virtual machine; and set the cloud working program on the cloud virtual machine according to the local data flow job through the cloud proxy module, which is based on the cloud working program and The cloud execution result generated by the cloud structured data corresponds to the local execution result generated based on the local data and the local data process work.

The invention can quickly and effectively deploy the service of the near-end device to the cloud server, and is applicable to different cloud service providers.

10: Connected equipment

101: The first local deployment module

102: The second local deployment module

103: Third Local Deployment Module

104: Local data flow work

105: local data

11: The first cloud server

110: Cloud device

114: Cloud data flow work

115: Cloud data

12: The second cloud server

13: The third cloud server

14: local device

20: Near-end equipment

201: Local data flow work

202: local data

203: Local deployment module

21: Cloud server

210: Cloud Virtual Machine

211: Cloud Work Program

212: Cloud structured data

213: Cloud Proxy Module

22: consumer electronic equipment

23: Manage equipment

24: Set up the device

30: The first near-end device

301: Local data flow work

302: local data

303: Local deployment module

31: The second near-end device

311: Local data flow work

312: local data

313: Local deployment module

32: Cloud server

320: cloud virtual machine

321: The first cloud working program

322: The first cloud structured data

323: Second Cloud Work Program

324: Second cloud structured data

325: Cloud Proxy Module

40: Near-end equipment

401: Local data flow work

402: local data

403: Local deployment module

41: The first cloud server

410: Cloud Virtual Machine

411: Cloud Work Program

412: Cloud structured data

413: Cloud Proxy Module

42: The second cloud server

420: cloud virtual machine

421: Cloud Work Program

422: Cloud structured data

423: Cloud Proxy Module

50: Connected equipment

500: Local deployment module

501: Local data flow work

502: local data

503: Cloud virtual machine connection information

504: Edge server connection information

505: Edge Agent Module

51, 52: local device

510, 520: local data

53: Edge Server

530: Edge Data Process Work

531: Edge Data

532: Edge Agent Module

533: local data

54: Cloud server

540: Cloud Virtual Machine

541: Cloud Work Program

542: Cloud structured data

543: Cloud Proxy Module

55: Connected equipment

56: local device

57: Management equipment

58: Set up the device

6: Gateway

60: processing device

61: storage device

62: The first network device

63: second network device

S10-S15: first deployment step

S20-S24: Use steps

S30-S32: build steps

S40-S48: Synchronization steps

S500-S511: Second deployment step

FIG. 1 is an architecture diagram of an IoT system with cloud service capability according to an embodiment of the present invention.

Fig. 2 is an architecture diagram of an Internet of Things system with cloud service capabilities according to the first embodiment of the present invention.

Fig. 3 is an architecture diagram of an Internet of Things system with cloud service capabilities in a second embodiment of the present invention.

Fig. 4 is an architecture diagram of an Internet of Things system with cloud service capabilities according to the third embodiment of the present invention.

Fig. 5 is an architecture diagram of an Internet of Things system with cloud service capabilities in a fourth embodiment of the present invention.

Fig. 6 is a structural diagram of a networking device according to a fifth embodiment of the present invention.

FIG. 7 is a flowchart of a method for rapidly deploying cloud services according to the first embodiment of the present invention.

FIG. 8 is a flowchart of using cloud services according to the second embodiment of the present invention.

FIG. 9 is a flowchart of building a cloud virtual machine according to the third embodiment of the present invention.

Fig. 10 is a flowchart of synchronization processing in the fourth embodiment of the present invention.

FIG. 11 is a flowchart of a method for rapidly deploying cloud services according to a fifth embodiment of the present invention.

With regard to a preferred embodiment of the present invention, in conjunction with the drawings, the detailed description is as follows.

Please refer to FIG. 1, which is an architecture diagram of an IoT system with cloud service capabilities according to an embodiment of the present invention. The present invention provides an Internet of Things system with cloud service capabilities, which can automatically deploy local services of the connected device 10 to a cloud server (such as the first cloud server 11, the second cloud server 12, or the third cloud server 13 ) So that the administrator can monitor and manage the near-end devices through the cloud server.

The first cloud server 11, the second cloud server 12, and the third cloud server 13 may be servers of different cloud service providers (such as Microsoft Azure, Amazon Web Service, or Google Cloud Platform). The first local deployment module 101, the second local deployment module 102, and the third local deployment module 103 are respectively used to communicate with the first cloud server 11, the second cloud server 12, and the second cloud server of different cloud service providers. The three cloud servers 13 communicate.

The networked device 10 stores a plurality of local data flow tasks 104, and can obtain a plurality of local data 105 from different local devices 14 via the internal network. Each local data flow job 104 is used to implement different data services. Specifically, each local data flow task 104 is used to process the specified one or more local data 105 to generate the execution result for the data service.

In the IoT system of FIG. 1, when the user wants to cloudize the aforementioned local service, he must build a local deployment module (such as the first local deployment module 101, the second local deployment module 102 on the connected device 10). And the third local deployment module 103).

Taking the deployment of the service to the first cloud server 11 through the first local deployment module 101 as an example, the networked device 10 can build multiple models in the first cloud server 11 through the first local deployment module 101 to simulate The cloud device 110 of the local device 14 maintains synchronization between the cloud device 110 and the corresponding local device 14 (that is, the cloud data 115 stored by the cloud device 110 is the same as the local data 105 provided by the local device 14). In addition, the networked device 10 can also use the first local deployment module 101 to build a plurality of cloud data flow tasks 114 that are the same as the plurality of local data flow tasks 104 in the first cloud server 11.

In this way, the user can directly connect to the first cloud server 11 through the Internet to execute the aforementioned data service without connecting to the network device 10 through the internal network. Moreover, since the cloud data 115 of the cloud device 110 is synchronized with the local data 105, the cloud execution result obtained by the user on the first cloud server 11 will be the same as the local execution result.

However, because different cloud service providers use different transmission protocols, the aforementioned local deployment module is developed for the transmission protocol of the selected cloud service provider (such as Microsoft Azure), and is only applicable to this cloud service provider . Once the user changes to a new cloud service provider (such as Amazon Web Service), a new local deployment module must be developed for the new transmission protocol of the new cloud service provider, which increases the cost of research and development and causes time for the cloud service to be launched. put off.

In addition, the cloud server converts the received data into the unique structure of the cloud service provider to which it belongs, which makes it only use the development tools (such as API) provided by the cloud service provider to develop cloud programs (if used) The program to simulate the cloud device 110) can perform data processing (such as generating cloud execution results) in the execution environment provided by the cloud service provider. However, because different cloud service providers adopt different unique structures, users must change to a new cloud service provider once they change to a new cloud service provider. It is necessary to re-develop cloud programs for new cloud service providers, which increases research and development costs and delays the launch of cloud services.

Please refer to FIG. 2 at the same time. FIG. 2 is an architecture diagram of an IoT system with cloud service capability according to the first embodiment of the present invention. FIG. 7 is a flowchart of a method for rapidly deploying cloud services according to the first embodiment of the present invention.

In order to solve the above problems, the present invention additionally proposes an Internet of Things system with cloud service capabilities (hereinafter referred to as the Cloud Internet of Things system) and a method for rapidly deploying cloud services. The cloud IoT system mainly includes a near-end device 20 and a cloud server 21. The near-end device 20 is connected to the cloud server 21 via a public network (such as the Internet).

The present invention mainly enables the near-end device 20 to directly communicate with the cloud virtual machine (virtual machine) 210 in the cloud server 21. Since the execution environment provided by the cloud service provider is not directly used, the cloud service provider designation is not required This makes it unnecessary to re-develop the near-end deployment module 203 even if the cloud service provider is changed in the present invention.

In addition, the present invention also provides an execution environment through the cloud virtual machine 210. Since the specifications of the cloud virtual machine 210 are set by the user, the user can create the cloud virtual machine 210 of the same specification in the cloud servers of different cloud service providers. This enables the present invention to change the execution environment even if the cloud service provider is changed, and the cloud program does not need to be re-developed.

Specifically, in the present invention, the cloud server 21 can provide the deployed cloud service via the Internet after the cloud service deployment is completed.

A near-end deployment module 203 is built in the near-end device 20, and multiple local data process tasks 201 and multiple local data 202 can be obtained (for example, read from a built-in memory or received from an external device).

Before deploying cloud services, users need to operate user electronic devices 22 (such as smart phones, tablets, laptops or personal computers, etc.) to connect to the cloud server 21 via the public network, and build in the cloud server 21 Set a cloud virtual machine 210, this cloud virtual machine 210 is used to execute Cloud services completed by the deployment. The foregoing creation of the cloud virtual machine 210 in the cloud server 21 is a prior art in the technical field of the present invention, and the details of its operation will not be repeated here.

Then, the near-end device 20 and the cloud server 21 can perform the following steps to quickly deploy cloud services.

Step S10: The near-end device 20 connects to the cloud virtual machine 210 of the cloud server 21 via a public network (such as the Internet).

Specifically, after creating the cloud virtual machine 210, the user can obtain a set of cloud virtual machine connection information. The aforementioned cloud virtual machine connection information may include the network address and port number of the cloud virtual machine 210, or the identification information (such as name) and key (such as the SSH public key) of the cloud virtual machine 210, without limitation.

Then, the user can operate the near-end device 20 and input the obtained cloud virtual machine connection information so that the near-end device 20 establishes a network connection with the cloud virtual machine 210 of the cloud server 21 through the public network according to the cloud virtual machine connection information. .

In one embodiment, the user can operate the setting device 24 (such as a smart phone, a tablet computer, a notebook computer or a personal computer, etc.) to connect to the near-end device 20 through an internal network (such as a local area network) to operate the near-end device 20.

Step S11: The near-end device 20 builds a cloud proxy module 213 in the cloud virtual machine 210.

In one embodiment, the cloud proxy module 213 is a software module, and the near-end device 20 uploads the installation program of the cloud proxy module 213 to the cloud virtual machine 210, and installs the cloud proxy module 213 in the cloud virtual machine 210. The cloud proxy module 213 is initialized, but it is not limited thereto.

In one embodiment, the user can pre-install the cloud virtual machine 210 when creating the cloud virtual machine 210. At this stage, only the cloud proxy module 213 needs to be initialized, so as to greatly shorten the construction time.

In one embodiment, the cloud proxy module 213 is a studio software module. When the cloud proxy module 213 is executed, an execution environment can be provided for users to deploy programs.

Step S12: The near-end device 20 establishes a cloud synchronization connection with the cloud virtual machine 210 of the cloud server 21, and continuously synchronizes the local data 202 of the near-end device 20 to the cloud virtual machine 210 via the established cloud synchronization connection.

In one embodiment, the near-end device 20 sends the latest local data 202 (or only the changed content) to the cloud virtual machine 210 through the cloud synchronization connection when the synchronization condition is met. The aforementioned synchronization conditions can be specified time (e.g. every 5 minutes), specified state (e.g. each time the local data 202 is changed) or manual trigger (e.g. received synchronization instruction), without limitation. In this way, the cloud virtual machine 210 can obtain the latest local data 202 after each synchronization

In one embodiment, the near-end device 20 can obtain multiple local data 202 from different sources or different types, select part of the local data 202 according to the user's operation or settings, and upload only the selected local data 202 to the cloud virtual machine 210 to synchronize.

In one embodiment, the near-end device 20 includes a networked device and a local device. The aforementioned networked equipment and local equipment can be integrated in the same housing, or separately installed and connected to each other via an internal network. In addition, the aforementioned local data flow job 201 is stored in the networked device, and the local data 202 is stored in the local device.

In one embodiment, the cloud proxy module 213 provides a web service to perform data transmission with the near-end device 20, such as transmitting data based on HTTP and URI technologies. In this way, the present invention can realize data transmission between different programs or different execution environments.

In one embodiment, the cloud proxy module 213 provides the aforementioned web service via a RESTful API, that is, the aforementioned web service can be implemented by a RESTful API (application programming interface of the presentation layer state transition style).

Step S13: The cloud virtual machine 210 converts the received local data 202 into the cloud structured data 212 through the cloud proxy module 213.

It is worth mentioning that in the embodiment shown in FIG. 1, a virtual cloud device 110 is created in the first cloud server 11 to store cloud data 115 to simulate the behavior of the local device 14 to store local data 105, which requires a lot of cost. Computing resources.

In this embodiment, structured processing is performed on each of the received local data 202 to obtain the corresponding cloud structured data 212. The aforementioned cloud structured data 212 may represent hardware information related to the local data 202 (such as the name, address, or type of the near-end device 20 (or local device) that provides the local data 202). In this way, the present embodiment can convert the aforementioned analog behavior into simple data access through structured processing, and can greatly save computing resources.

Step S14: the near-end device 20 uploads the local data flow job 201 to the cloud virtual machine 210.

In one embodiment, the near-end device 20 can select part of the local data flow job 201 according to the user's operation or setting, and only upload the selected local data flow job 201 to the cloud virtual machine 210 for setting.

Step S15: The cloud virtual machine 210 uses the cloud proxy module 213 to respectively set the corresponding cloud work program 211 according to the received local data flow work 201.

Specifically, the cloud proxy module 213 programmatically processes each local data flow job 201 to generate a corresponding cloud job program 211.

It is worth mentioning that each local data flow job 201 is used to achieve a specific function and records application rules on how to process the specified one or more local data 202. The aforementioned programming process is to generate a cloud work program 211 for implementing the aforementioned application rules.

In other words, after the cloud working program 211 is executed in the cloud virtual machine 210, the same processing can be performed on the cloud structured data 212 corresponding to the aforementioned local data 202. In this way, the cloud execution result generated based on the cloud work program and cloud structured data and the local execution result generated based on the local data and the local data process work will correspond (such as the same or similar).

The invention can quickly and effectively deploy the service of the near-end device to the cloud server, and is applicable to different cloud service providers.

Please also refer to FIG. 8, which is a flowchart of using cloud services according to the second embodiment of the present invention. Compared with the method for quickly deploying cloud services shown in FIG. 7, the method for quickly deploying cloud services in this embodiment further includes the following steps for providing cloud services after cloud service deployment is completed.

Step S20: The management device 23 establishes a connection with the cloud virtual machine 210 according to a user operation.

In one embodiment, the user can input cloud virtual machine connection information into the management device 23 to make the management device 23 connect to the cloud virtual machine 210 of the cloud server 21 according to the cloud virtual machine connection information.

In one embodiment, the user connects to the cloud virtual machine 210 through the WEB service, such as directly inputting the cloud virtual machine connection information in the browser.

Step S21: The management device 23 sends a dashboard command to the cloud virtual machine 210.

In one embodiment, the management device 23 can display an operating interface (such as displaying a GUI through a browser), and the user can select the local data to be viewed or the local data flow task to be executed through the displayed operating interface. Then, the management device 23 generates a corresponding dashboard command according to the user's selection operation, and sends the dashboard command to the cloud virtual machine 210.

In one embodiment, the management device 23 automatically generates a dashboard command after connecting to the cloud virtual machine 210, and sends the dashboard command to the cloud virtual machine 210.

In one embodiment, the aforementioned dashboard commands are used to instruct the user to implement the functions (such as viewing temperature statistics, access control data for a specified time period, etc.), and each of the aforementioned functions can be performed by one or more local data flow tasks 201 ( Or the corresponding cloud work program 211) can be implemented separately or together.

Step S22: After the cloud virtual machine 210 receives the dashboard command from the management device 23, selects all or part of the multiple cloud work programs 211 according to the dashboard command.

Step S23: The cloud virtual machine 210 reads the one or more cloud structured data 212 respectively associated with each selected cloud work program 211, and executes the selected multiple cloud work programs to perform processing on the cloud structured data 212 Analyze and process to generate each cloud execution result. The aforementioned cloud execution results are used to express the functions specified by the dashboard commands.

Then, the cloud virtual machine 210 can generate dashboard data based on the generated one or more cloud execution results (for example, the cloud execution results are aggregated or typeset to generate graphical description data), and return this instrument via the public network Board data to the management device 23.

For example, if three cloud working programs 211 are used to realize the average temperature function (the first cloud working program), the off-duty access control function (the second cloud working program), and the environmental comfort function (the third cloud working program). , The cloud virtual machine 210 can obtain the cloud structured data 212 associated with the first cloud working program (for example, multiple pieces of temperature sensing data, the corresponding local data 202 can be generated by a temperature sensor (local device)), Obtain the cloud structured data 212 associated with the second cloud work program (if multiple personnel access data are obtained, the corresponding local data 202 can be generated by the access control device (local device)), and obtain the association with the third cloud work program The cloud structured data 212 (such as multiple temperature sensing data and multiple humidity sensing data, the corresponding local data 202 can be generated by a temperature sensor and a humidity sensor (local device)).

Then, the cloud virtual machine 210 can execute the first cloud working program to analyze and process the multiple pieces of temperature sensing data (such as averaging) to obtain the average temperature as the result of the first cloud execution, and execute the second cloud working program to compare the multiple temperatures. Analyze and process the personnel entry and exit data (for example, perform filtering processing to obtain personnel entry and exit data between 7 pm and 7 am the next day) to obtain the personnel entry and exit data during the off-duty period and use the second cloud execution result as the second cloud execution result, and execute the third cloud The work program analyzes and processes multiple temperature sensing data and multiple humidity sensing data (such as comfort calculation) to obtain a comfort index and use it as a third cloud execution result.

Finally, the cloud virtual machine 210 can convert the generated first cloud computing result, second cloud computing result, and third cloud computing result into text and graphic data (such as drawing into a dashboard) and use it as dashboard data.

It is worth mentioning that the aforementioned cloud work programs 211 and cloud structured 212 store corresponding local data flow work 201 and local data 202 in the near-end device 20.

The near-end device 20 executes the local data flow job 201 to perform analysis and processing on the associated local data 202. The local execution result obtained is the same or similar to the aforementioned cloud execution result (such as the same average temperature, personnel access data, and comfort index) .

Step S24: The management device 23 draws the dashboard interface according to the received dashboard data, and displays the drawn dashboard interface on the display device. The aforementioned dashboard interface is used to present the aforementioned cloud execution results.

In this way, after the cloud service deployment is completed, users can conveniently use the management device to use the same service in the cloud without having to be close to the location of the end device.

Please also refer to FIG. 9, which is a flowchart of building a cloud virtual machine according to the third embodiment of the present invention. Compared with the method for quickly deploying cloud services shown in FIG. 7, the method for quickly deploying cloud services in this embodiment further includes the following steps for creating cloud virtual machines before starting to deploy cloud services.

Step S30: The user can operate the user electronic device 22 to connect to the cloud server 21 via the public network, and input user identification information (such as an account and password) to log in to the cloud service to enter the management interface of the cloud service.

Step S31: The user can create a cloud virtual machine 210 associated with the user identification information in the cloud server 21 via the management interface.

Step S32: The user can initialize the cloud virtual machine 210 through the management interface and obtain the aforementioned cloud virtual machine connection information.

In one embodiment, the aforementioned initialization settings may include setting the execution environment of the cloud virtual machine 210 (such as operating system version, random access memory capacity, non-volatile storage space capacity, etc.).

It is worth mentioning that since the execution environment of the cloud virtual machine 210 can be set by the user, the user can create the cloud virtual machine 210 with the same execution environment on the cloud servers of different cloud service providers.

Therefore, when a user changes a cloud service provider, since the execution environment has not changed, the existing cloud proxy module 213 and the local deployment module 203 (if only the cloud virtual machine connection information needs to be changed) can directly use the new cloud service provider Business’s cloud server 21 without the need to re-develop.

Please also refer to FIG. 10, which is a flowchart of synchronization processing according to the fourth embodiment of the present invention. Compared with the method for quickly deploying cloud services shown in FIG. 7, the method for quickly deploying cloud services in this embodiment further includes the following steps S40-S48 for providing synchronization services after cloud service deployment is completed.

The method for quickly deploying cloud services in this embodiment can at least realize the local data flow synchronization function, the local data synchronization function, and the near-end device synchronization function (it can be divided into the synchronization of the newly added near-end device function and the synchronization of the synchronization deactivation of the near-end device function) .

Specifically, the local data flow synchronization function is implemented by the following steps.

Step S40: The near-end device 20 detects whether the local data flow job 201 has changed.

If the local data flow job 201 is changed, the near-end device 20 uploads the changed local data flow job 201 to the cloud virtual machine 210 via the public network, and executes step S41.

In one embodiment, the cloud work program 211 and the cloud structured data 212 corresponding to the near-end device 20 are associated with the near-end device identification information of the near-end device 20. The near-end device 20 can further upload the near-end device identification information (such as MAC address, device name, or network address, etc.) of the near-end device 20 to the cloud virtual machine 210 for identification.

If the local data flow job 201 does not change, the near-end device 20 performs other detections (such as step S43).

Step S41: The cloud virtual machine 210 can identify the corresponding cloud working program 211 according to the received near-end device identification information through the cloud proxy module 213, and update the corresponding cloud working program 211 according to the changed local data flow job 201.

In one embodiment, the cloud virtual machine 210 can set a new cloud task program 211 according to the changed local data flow task 201, and directly replace the original cloud task program 211 with the new cloud task program 211.

For example, if the user modifies the content of any local data flow job 201 on the near-end device 20, the cloud virtual machine 210 can simultaneously modify the corresponding cloud job program 211. If the user adds a new local data flow job 201 to the near-end device 20, the cloud virtual machine 210 can simultaneously add a corresponding cloud job program 211. If the user deletes the existing local data flow job 201 in the near-end device 20, the cloud virtual machine 210 can delete or disable the corresponding cloud job program 211 simultaneously.

Step S42: The near-end device 20 and the cloud virtual machine 210 determine whether to stop synchronization, such as whether the user turns off the synchronization function, or whether the synchronization connection between the near-end device 20 and the cloud virtual machine 21 is interrupted.

If it is judged to stop the synchronization, the processing is ended. Otherwise, the near-end device 20 and the cloud virtual machine 210 perform a synchronization function again (for example, perform step S40 again).

The local data synchronization function is realized by the following steps.

Step S43: The near-end device 20 detects whether the local data 202 has changed.

If the local data 202 changes, the near-end device 20 uploads the changed local data 202 to the cloud virtual machine 210 via the previously established cloud synchronization connection, and executes step S44.

In one embodiment, the near-end device 20 further uploads the near-end device identification information of the near-end device 20 to the cloud virtual machine 210.

If the local data 202 has not changed, other detections are performed (for example, step S45).

Step S44: The cloud virtual machine 210 can identify the cloud structured data 212 associated with the near-end device identification information through the cloud proxy module 213 according to the received near-end device identification information, and update the identified data according to the changed local data 202 Structured data in the cloud 212. Then, the cloud virtual machine 210 and the near-end device 20 may perform step S42.

In one embodiment, the cloud virtual machine 210 can convert the changed local data 202 into the new cloud structured data 212, and directly replace the original cloud structured data 212 with the new cloud structured data 212.

For example, if the user modifies the content of any local data 202 on the near-end device 20, the cloud virtual machine 210 can modify the corresponding cloud structured data 212 simultaneously. If the user adds new local data 202 to the near-end device 20, the cloud virtual machine 210 can simultaneously add corresponding cloud structured data 212. If the user deletes the existing local data 202 on the near-end device 20, the cloud virtual machine 210 can delete or disable the corresponding cloud structured data 212 simultaneously.

The function of synchronously adding a near-end device is realized by the following steps.

Step S45: The cloud virtual machine 210 can detect whether a new near-end device 20 is connected (hereinafter referred to as a new near-end device).

If the cloud virtual machine 210 is connected to the newly added near-end device, step S46 is executed. Otherwise, the cloud virtual machine 210 performs other detections (such as step S47).

Step S46: the cloud virtual machine 210 and the newly added near-end device perform deployment processing to deploy the service of the newly added near-end device to the cloud virtual machine 210. Then, the cloud virtual machine 210 and the near-end device 20 may perform step S42.

The aforementioned deployment processing may be, for example, executing steps S10-S15 in FIG. 7. For example, the newly added near-end device can connect to the cloud virtual machine 210, and the cloud proxy module 213 (such as registering information about the newly added near-end device) can be set up to establish a synchronization connection with the cloud virtual machine 210 (hereinafter referred to as “new synchronization”). Connection), and continuously synchronize the local data of the newly added near-end device (hereinafter referred to as the newly added synchronization connection) to the cloud virtual machine 210 through the newly added synchronization connection. Then, the cloud virtual machine 210 can convert the received newly added local data into cloud structured data (hereinafter referred to as newly added cloud structured data) through the cloud proxy module 213.

In addition, the newly added near-end device can also upload a local data flow job (hereinafter referred to as a new local data flow job) to the cloud virtual machine 210. The cloud virtual machine 210 can set the corresponding cloud work program (add cloud work program) one by one according to the received new local data flow job via the cloud proxy module 213. The aforementioned new cloud execution result generated based on the newly added cloud work program and the added cloud structured data corresponds to the new local execution result generated based on the new local data and the new local data process work. And each newly added cloud structured data and each newly added cloud work program is related to the newly added near-end device identification information of the newly added near-end device.

In this way, the present invention can deploy the service of the newly added near-end device to the cloud.

The function of synchronously deactivating the near-end device is realized by the following steps.

Step S47: The cloud virtual machine 210 detects whether any connected near-end device 20 is disconnected.

If any connected near-end device 20 is disconnected, the cloud virtual machine 210 executes step S48. Otherwise, the cloud virtual machine 210 executes step S42.

Step S48: The cloud virtual machine 210 identifies the associated cloud structured data 212 and the cloud work program 211 according to the near-end device identification information of the disconnected near-end device 20, interrupts the established cloud synchronization connection and disables the near-end device All cloud structured data 212 and cloud work programs 211 corresponding to 20.

Then, the cloud virtual machine 210 and the near-end device 20 may perform step S42.

Thereby, the present invention can effectively realize the synchronization function.

Please also refer to FIG. 3, which is an architecture diagram of the Internet of Things system with cloud service capabilities in the second embodiment of the present invention. Next, it will be explained how the cloud virtual machine 320 of the cloud server 32 of the present invention can simultaneously provide multiple near-end devices when connecting to multiple near-end devices at the same time (FIG. 3 takes the first near-end device 30 and the second near-end device 31 as an example). Cloud services for end devices without errors.

Specifically, the first near-end device 30 can perform cloud deployment processing through the near-end deployment module 303 and the cloud proxy module 325 of the cloud virtual machine 320 to deploy its local data flow work 301 and local data 302 to the cloud virtual machine. The machine 320 serves as the first cloud working program 321 and the first cloud structured data 322. The aforementioned first cloud working program 321 and the first cloud structured data 322 are associated with the near-end device identification information of the first near-end device 30.

In addition, the second near-end device 31 can perform cloud deployment processing through the near-end deployment module 313 and the cloud proxy module 325 of the cloud virtual machine 320 to deploy its local data flow work 311 and local data 312 to the cloud virtual machine 320 As the second cloud working program 323 and the second cloud structured data 324. The aforementioned second cloud working program 323 and the second cloud structured data 324 are associated with the near-end device identification information of the second near-end device 31.

In this way, when the cloud virtual machine 320 can connect to multiple near-end devices at the same time, it can identify the ownership of the stored cloud work program and the cloud structured data according to the near-end device identification information.

Please also refer to FIG. 4, which is an architecture diagram of an IoT system with cloud service capability according to the third embodiment of the present invention. Next, it will be explained how the Internet of Things system of the present invention can quickly change cloud service providers.

When the user wants to change the cloud service from the first cloud server 41 of the first cloud service provider to the second cloud server 42 of the second cloud service provider, it is before the second cloud server 42 A cloud virtual machine 420 with the same or similar settings as the cloud virtual machine 410 of the first cloud server 41 is created to establish the same or similar execution environment on the second cloud server 42.

Then, the user can execute the local deployment module 403 to configure the cloud proxy module 423, and execute deployment to deploy the local data flow job 401 and local data 402 of the local device 40 to the cloud of the second cloud server 42 The virtual machine 420 generates a cloud working program 421 and cloud structured data 422.

Finally, the user can configure the near-end deployment module 403 of the near-end device 40 to connect to the cloud virtual machine 420 to complete the deployment operation.

In this way, only a simple setting and re-deployment are required, and the near-end device 40 can synchronize the local data flow 401 and the local data 402 with the new cloud virtual machine 420.

Please refer to FIGS. 5 and 11 together. FIG. 5 is an architecture diagram of an IoT system with cloud service capabilities in a fourth embodiment of the present invention. FIG. 11 is a method for rapidly deploying cloud services according to a fifth embodiment of the present invention. Flow chart.

In the present invention, the aforementioned near-end devices may include networked devices and local devices. For example, the local devices 51 and 52 can be connected to the networked device 50 via an internal network, or the local device 56 can be connected to the networked device 55 via an internal network.

In this case, the networked device 50 (such as a gateway or other Internet of Things relay device) may include a near-end deployment module 500 and a local data flow work 501, and local devices 51, 52 (such as cameras, sensors, I/O devices or other IoT node devices) are used to generate their respective local data 510, 520 (such as frequency, sensor data, input signal, output signal, etc.), and transmit the generated local data 510, 520 To the networked device 50.

In the present invention, the networked device 55 directly deploys local services to the cloud virtual machine 540 of the cloud server 54. In this situation, the networked device 55 can forward the local data of the connected local device 56 to the cloud virtual machine. 54.

In addition, one or more connected devices 50 deploy local services to an edge server 53 (such as a gateway or other relay server) as an edge service, and then the edge server 53 deploys the edge service to a cloud virtual machine 540. The deployment of the aforementioned edge service is similar to the deployment of the cloud service described in FIG. 7.

Specifically, the edge server 53 includes an edge proxy module 532 (which may be a studio software module). The edge server 53 and the networking device 50 execute the following steps to complete the deployment of edge services.

Step S500: The networked device 50 (ie the near-end device) connects to the edge server via the public network or the internal network according to the edge server connection information (such as network address and port number, or identification information and key, etc.)器53.

Step S501: The networked device 50 builds an edge proxy module 532 on the edge server 53.

In one embodiment, the edge proxy module 532 is a software module and is installed on the edge server 53 (the installation can be completed at the factory, or the user can manually upload the installation program to the edge server 53 for installation).

In one embodiment, the edge agent module 532 is a studio software module. When the edge agent module 532 is executed, it can provide a development environment and a variety of software tools for users to design, develop, and deploy programs.

Step S502: The networked device 50 establishes an edge synchronization connection with the edge server 53, and continuously synchronizes multiple local data 510 and 520 (of the local devices 51 and 52) to the edge server 53 through the edge synchronization connection, so that the edge The server 53 stores a plurality of local data 533.

Step S503: The edge server 53 selects all or part of the multiple local data 533 as the multiple edge data 531 through the edge proxy module 532.

Step S504: The edge server 53 sets a plurality of edge data flow tasks 530 according to the local data flow tasks 501 associated with the selected plurality of local data 533, wherein the edge data flow tasks 530 and each edge data set in step S504 are set Each edge execution result generated by 533 (for the specified edge data service) will correspond to each local execution result (for the specified local data service) generated based on the corresponding and local data process work 501 and the local data 510, 520 The local service is the same as the edge service in step S504).

Step S505: The edge server 53 accepts an edge data process job setting operation (for example, accepts the operation via the management device 57), and sets a plurality of edge data process jobs 530 according to the operation. The edge data flow task 530 set in step S505 is used to process the specified edge data 531 to generate the execution result for the specified data service (edge service).

It is worth mentioning that step S504 and step S505 can be executed alternatively, or both of them can be executed, which is not limited thereto.

In this way, the present invention can complete the deployment of edge services. The user can choose to operate the setting device 58 at the near end to use the local service, or operate the management device 57 to use the edge service at the far end.

Then, the edge server 53 and the cloud virtual machine 540 can execute the following steps to deploy cloud services.

Step S506: The edge server 53 connects to the cloud virtual machine 540 according to the cloud virtual machine connection information.

Step S507: The edge server 53 builds a cloud proxy module 543 in the cloud virtual machine 540.

Step S508: The edge server 53 sets the synchronization range. Specifically, the user can input the synchronization range setting operation (via the management device 57 or the setting device 58) to control the edge server 53 to select the edge data and multiple edge data processes to be deployed to the cloud (such as part of multiple edge data processes). Data flow task 530 and associated multiple edge data 531).

It is worth mentioning that step S508 is not a necessary step of the present invention. If the user wants to deploy all edge services in the cloud, step S508 can also be omitted.

Step S509: The edge server 53 establishes a cloud synchronization connection with the cloud virtual machine 540, and continuously synchronizes the edge data 531 of the edge server 53 to the cloud virtual machine 540 via the cloud synchronization connection.

In one embodiment, if the synchronization range is set, the edge server 53 will only synchronize the selected multiple edge data 531 or the edge data 531 associated with the selected edge data process task 530.

Step S510: the edge data process work 531 of the edge server 53 to the cloud virtual machine 540.

In one embodiment, if the synchronization range is set, the edge server 53 will only upload the selected edge data process task 530.

Step S511: The cloud virtual machine 540 sets the cloud work program 541 through the cloud proxy module 543 according to the received edge data process work. The cloud execution result generated based on each cloud task program 541 and the related cloud structured data 542 corresponds to the edge execution result generated based on each edge data process task 530 and the associated edge data 531.

In this way, the present invention can deploy all or part of the edge services to the cloud according to user requirements.

Please also refer to FIG. 6, which is a structural diagram of a networked device according to the fifth embodiment of the present invention. The edge server 53, the networking equipment 50, 55, or the aforementioned near-end equipment may be the gateway 6. The gateway 6 may include a first network device 62, a second network device 63, a storage device 61, and a processing device 60 electrically connected to the above devices and used to control the gateway 6.

The first network device 62 and the second network device 63 can be heterogeneous network modules, for example, the first network device 62 can be a Wi-Fi module, an Ethernet module, a mobile network module, etc. , The second network device 63 can be a Bluetooth module, a ZigBee module, an infrared module, etc.

In one embodiment, the first network device 62 is used to connect to a public network (such as the Internet) to connect to a cloud server. The second network device 63 is used to connect to local devices to obtain local data of each local device.

In one embodiment, when the networked device 50, 55 or the aforementioned near-end device is the gateway 6, the storage device 61 can store the local data flow job 501, the local data 502, the local deployment module 500, and the cloud virtual machine connection Information 503 is connected to information 504 with the edge server.

In one embodiment, when the edge server 53 is the gateway 6, the storage device 61 can store the cloud virtual machine connection information 503 and the edge proxy module 505.

In this way, the present invention can provide more uses for the gateway 6. Moreover, through the installation of the edge server 53, users can deploy services more conveniently and improve information security.

The above are only preferred specific examples of the present invention, and are not limited to the scope of the patent of the present invention. Therefore, all equivalent changes made by using the content of the present invention are included in the scope of the present invention in the same way, and they are all included in the present invention. Bright.

S10-S15: first deployment step

Claims (14)

A method for rapidly deploying cloud services for deploying local services of a near-end device to a cloud server. The method for rapidly deploying cloud services includes the following steps: a) According to a cloud virtual machine connection information on the near-end device A cloud virtual machine connected to the cloud server; b) a cloud proxy module is built on the cloud virtual machine; c) a cloud synchronization connection is established between the near-end device and the cloud virtual machine, and synchronized through the cloud The connection continuously synchronizes a local data of the near-end device to the cloud virtual machine; d) the cloud virtual machine converts the local data into a cloud structured data through the cloud proxy module; e) uploads the local data of the near-end device A local data flow is working to the cloud virtual machine; and f) a cloud working program is set on the cloud virtual machine according to the local data flow job through the cloud proxy module, which is based on the cloud working program and the cloud structured data office A generated cloud execution result corresponds to a local execution result generated based on the local data and the local data flow job, wherein each of the cloud structured data and each of the cloud work programs is a near-end device associated with the near-end device Identification information; wherein, the method for rapidly deploying cloud services further includes the following steps: g1) when the cloud virtual machine is connected to a newly added near-end device, the newly-added near-end device is synchronized with the cloud virtual machine Connect, and continuously synchronize a piece of newly added local data of the newly added near-end device to the cloud virtual machine through the newly added synchronization connection; g2) convert the newly added local data on the cloud virtual machine through the cloud proxy module For a new cloud structured data; g3) Upload a new local data flow job of the newly added local device to the cloud virtual machine; and g4) Set a new cloud in the cloud virtual machine according to the new local data flow job setting via the cloud proxy module Work program, where a new cloud execution result generated based on the new cloud work program and the new cloud structured data corresponds to a new local data generated based on the new local data and the new local data process job As a result of the execution, each of the newly added cloud structured data and each of the newly added cloud work programs is a piece of newly-added near-end device identification information associated with the newly-added near-end device. The method for rapidly deploying cloud services according to claim 1, which further includes the following steps: h1) establishing a connection between the cloud virtual machine and a management device; h2) after receiving a dashboard command from the management device, according to the The dashboard command selects the multiple cloud work programs, wherein the multiple cloud work programs are respectively associated with the multiple cloud structured data; h3) execute the selected multiple cloud work programs to perform the associated multiple cloud structured data The data generates the plurality of cloud execution results; and h4) generates a dashboard data according to the plurality of cloud execution results, and transmits the dashboard data to the management device to display a dashboard interface. The method for rapidly deploying cloud services as described in claim 1, wherein before step a), it further includes the following steps: i1) log in to the cloud server in a user electronic device according to a user identification information; i2) in the cloud server The device creates the cloud virtual machine with the user identification information; and i3) performs an initialization setting on the cloud virtual machine and obtains the cloud virtual machine connection information. The method for rapidly deploying cloud services as described in claim 1, which further includes the following steps: j1) Upon detecting that the local data of the near-end device has changed, upload the changed local data and the near-end device identification information of the near-end device to the cloud virtual machine via the cloud synchronization connection; j2 ) Identify the corresponding cloud structured data according to the identification information of the near-end device in the cloud virtual machine through the cloud proxy module; and j3) update the identified cloud structured data according to the changed local data. The method for rapidly deploying cloud services as described in claim 1, which further includes the following steps: k1) when any change in the local data flow of the near-end device is detected, upload the changed local data flow Work and the near-end device identification information of the near-end device to the cloud virtual machine; k2) the cloud virtual machine uses the cloud proxy module to identify the corresponding cloud work program according to the near-end device identification information; and k3) Update the identified cloud work program according to the changed local data flow work. The method for rapidly deploying cloud services according to claim 1, which further includes a step 1) when the cloud virtual machine detects that the connected near-end device is disconnected, the cloud synchronization connection is interrupted and the association is disabled All the cloud structured data of the near-end device and the cloud work program. The method for rapidly deploying cloud services according to claim 1, wherein the cloud proxy module provides a web service to perform data transmission with the near-end device. The method for rapidly deploying a cloud service according to claim 7, wherein the cloud proxy module provides the web service via a RESTful API. The method for rapidly deploying cloud services as described in claim 1, further comprising the following steps: m1) connecting an edge server on the near-end device according to an edge server connection information; m2) establishing an edge on the edge server Agent module m3) Make the near-end device establish an edge synchronization connection with the edge server, and continuously synchronize a plurality of the local data of the near-end device to the edge server via the edge synchronization connection; m4) at the edge server The device selects part of the multiple local data as multiple edge data through the edge agent module; and m5) according to the multiple local data flow jobs of the near-end equipment associated with the selected multiple local data or a The edge data flow job setting operation sets multiple edge data flow jobs. The method for rapidly deploying cloud services according to claim 9, wherein the method for rapidly deploying cloud services further includes the following steps after the step m5): m6) connecting to the cloud at the edge server according to the cloud virtual machine connection information Virtual machine; m7) build the cloud proxy module on the cloud virtual machine; m8) make the edge server and the cloud virtual machine establish the cloud synchronization connection, and continuously synchronize the edge server through the cloud synchronization connection M9) upload the plurality of edge data processes of the edge server to the cloud virtual machine; and m10) on the cloud virtual machine through the cloud proxy module according to the cloud virtual machine; An edge data process task sets the multiple cloud work programs, wherein each cloud execution result generated based on each cloud work program and each cloud structured data corresponds to each edge data and each edge data process job generated The execution result of each edge. The method for rapidly deploying cloud services according to claim 10, wherein before the step m8), it further includes a step m11) selecting part of the plurality of edge data or part of the plurality of edge data processes according to a synchronization range setting operation The step m8) is to continuously synchronize the selected multiple edge data or the multiple edge data associated with the selected multiple edge data process work via the cloud synchronization connection; the step m9) is to upload all The selected multiple edge data processes work. The method for rapidly deploying cloud services according to claim 9, wherein the edge server or the near-end device is a gateway. The method for rapidly deploying cloud services according to claim 9, wherein the edge proxy module or the near-end proxy module is a studio software module. The method for rapidly deploying cloud services according to claim 1, wherein the near-end device includes a networked device and at least one local device; the local data flow work is stored in the networked device, and the local data is stored in the at least one local Device, the networked device is used to connect the at least one local device and the cloud virtual machine; the step c) is to transfer the local data from the at least one local device to the cloud virtual machine via the networked device; the step e ) Is the process of uploading the local data of the networked device to the cloud virtual machine.

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