CN112764884A - Service-oriented perception cloud system, method, medium and equipment - Google Patents
Service-oriented perception cloud system, method, medium and equipment Download PDFInfo
- Publication number
- CN112764884A CN112764884A CN202110095323.3A CN202110095323A CN112764884A CN 112764884 A CN112764884 A CN 112764884A CN 202110095323 A CN202110095323 A CN 202110095323A CN 112764884 A CN112764884 A CN 112764884A
- Authority
- CN
- China
- Prior art keywords
- sensing
- service
- description model
- resource
- perception
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 230000008447 perception Effects 0.000 title claims abstract description 78
- 238000000034 method Methods 0.000 title claims abstract description 31
- 238000001514 detection method Methods 0.000 claims abstract description 53
- 238000005538 encapsulation Methods 0.000 claims abstract description 15
- 238000013507 mapping Methods 0.000 claims abstract description 7
- 230000008569 process Effects 0.000 claims description 9
- 230000004931 aggregating effect Effects 0.000 claims description 6
- MHKKFFHWMKEBDW-UHFFFAOYSA-N dimethyl 2,5-dioxocyclohexane-1,4-dicarboxylate Chemical compound COC(=O)C1CC(=O)C(C(=O)OC)CC1=O MHKKFFHWMKEBDW-UHFFFAOYSA-N 0.000 claims description 6
- ACTRVOBWPAIOHC-XIXRPRMCSA-N succimer Chemical compound OC(=O)[C@@H](S)[C@@H](S)C(O)=O ACTRVOBWPAIOHC-XIXRPRMCSA-N 0.000 claims description 6
- 238000004590 computer program Methods 0.000 claims description 4
- 230000009286 beneficial effect Effects 0.000 description 5
- 230000006855 networking Effects 0.000 description 3
- 238000010586 diagram Methods 0.000 description 2
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000012544 monitoring process Methods 0.000 description 1
- 230000003287 optical effect Effects 0.000 description 1
- 238000012545 processing Methods 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F9/00—Arrangements for program control, e.g. control units
- G06F9/06—Arrangements for program control, e.g. control units using stored programs, i.e. using an internal store of processing equipment to receive or retain programs
- G06F9/44—Arrangements for executing specific programs
- G06F9/455—Emulation; Interpretation; Software simulation, e.g. virtualisation or emulation of application or operating system execution engines
- G06F9/45533—Hypervisors; Virtual machine monitors
- G06F9/45558—Hypervisor-specific management and integration aspects
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F9/00—Arrangements for program control, e.g. control units
- G06F9/06—Arrangements for program control, e.g. control units using stored programs, i.e. using an internal store of processing equipment to receive or retain programs
- G06F9/46—Multiprogramming arrangements
- G06F9/50—Allocation of resources, e.g. of the central processing unit [CPU]
- G06F9/5061—Partitioning or combining of resources
- G06F9/5077—Logical partitioning of resources; Management or configuration of virtualized resources
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F2209/00—Indexing scheme relating to G06F9/00
- G06F2209/50—Indexing scheme relating to G06F9/50
- G06F2209/5011—Pool
Abstract
The invention relates to a service-oriented perception cloud system, a method, a medium and a device, wherein the system comprises: the sensing cloud resource module is used for mapping the sensor resources into virtual sensing resources; the perception cloud service module is used for performing service encapsulation on the virtual perception resources and establishing a perception service description model base; the perception cloud application module is used for establishing a perception application description model library; the sensing cloud management module is used for matching a corresponding sensing application description model in the sensing application description model base according to the task type of the detection sensing task in the user request, matching a corresponding sensing service description model in the sensing service description model base according to the service requirement in the sensing application description model, and calling corresponding sensor resources according to the sensing service description model, so that various detection sensing application services are dynamically provided for the user according to the requirement, and the detection sensing capability under the complex environment can be effectively improved.
Description
Technical Field
The invention relates to the technical field of perception cloud, in particular to a service-oriented perception cloud system, method, medium and device.
Background
Detection perception faces increasing challenges, on the one hand: the detection sensing task is more diversified, the detection sensing object is more diversified and difficult to detect, and the detection sensing environment is more complex; on the other hand, due to the limitation of conditions such as performance and resources, a single sensor is difficult to complete a detection sensing task in a complex environment. The cooperative detection sensing system has become an effective way for improving the detection sensing capability in a complex environment.
However, the traditional networking coordination detection sensing mode is to perform networking on a specific task corresponding to a specific scene, that is, the traditional networking coordination detection sensing mode can only complete the specific sensing task in the specific scene, but cannot complete the dynamic sensing task in a complex environment.
Disclosure of Invention
The technical problem to be solved by the invention is to provide a service-oriented perceptual cloud system, a service-oriented perceptual cloud method, a service-oriented perceptual cloud medium and a service-oriented perceptual cloud device.
To solve the above technical problem, an embodiment of the present invention provides a service-oriented perceptual cloud system, including:
the sensing cloud resource module is used for mapping the sensor resources into virtual sensing resources, establishing a sensing resource description model and aggregating to form a virtual sensing resource pool;
the sensing cloud service module is used for carrying out service encapsulation on the virtual sensing resources and establishing a sensing service description model library, wherein a sensing service description model in the sensing service description model library comprises a service type and sensing resources corresponding to the service type;
the perception cloud application module is used for establishing a perception application description model library, and a perception application description model in the perception application description model library comprises a task type and a service requirement corresponding to the task type;
and the perception cloud management module is used for matching a corresponding perception application description model in a perception application description model base according to the task type of a detection perception task in a user request, matching a corresponding perception service description model in a perception service description model base according to the service requirement in the perception application description model, and calling a corresponding sensor resource according to the perception service description model.
The invention has the beneficial effects that: sensor resources are virtualized, and virtual sensing resources are subjected to service encapsulation to obtain a plurality of sensing service description models, so that a sensing service system is constructed; constructing various perception application description models according to the task type and the service requirement of the detection perception task, and constructing a perception application system; the service requirement of the sensing application description model is matched with the service type of the sensing service description model; when a user request is received, matching the corresponding sensing application description model according to the task type of the detection sensing task in the user request, matching the corresponding sensing service description model according to the service requirement of the sensing application description model, and calling the corresponding sensor resource according to the sensing service description model, so that various detection sensing application services are dynamically provided for the user according to the requirement, and the detection sensing capability under the complex environment can be effectively improved.
On the basis of the technical scheme, the invention can be further improved as follows:
further, the sensing cloud resource module is specifically configured to map various sensor resources that are dispersedly deployed into virtual sensing resources by using a resource virtualization technology, and establish a sensing resource description model, where the sensing resource description model is as follows:
DMSR＝(ID，State，Location，Capability)
wherein, ID refers to the sensing resource identification, State refers to the current State of the sensing resource, Location refers to the geographical position of the sensing resource entity, and Capability refers to the sensing Capability of the sensing resource.
The beneficial effect of adopting the further scheme is that: sensor resources are virtualized into virtual sensing resources comprising content items such as ID, State, Location, Capability and the like, various sensor resources which are dispersedly deployed are combined into a unified and efficient task system, a sensing cloud system is constructed, and the various sensor resources cooperatively work under time synchronization and space synchronization according to an optimal application strategy through unified scheduling, so that the interoperability, self-organization, adaptability and the like of the system are enhanced, and conditions are provided for constructing intelligent detection sensing.
Further, the sensing cloud service module is specifically configured to perform service encapsulation on the virtual sensing resources in the virtual sensing resource pool, and establish a sensing service description model library, where a sensing service description model in the sensing service description model library is as follows:
DMSS＝(Type，Resource)
the Type refers to a service Type, the Resource refers to sensor resources required in a detection sensing process, and the sensor resources are formed by sensing resources corresponding to a sensing Resource description model DMSR.
The beneficial effect of adopting the further scheme is that: the virtual sensing resources in the virtual sensing resource pool are subjected to service encapsulation, the internal attributes of the resources are hidden, and the external public only through a uniform interface meets the requirement that a user dynamically calls various sensor resources as required through a service form.
Further, the perception cloud application module is specifically configured to establish a perception application description model library, where a perception application description model in the perception application description model library is as follows:
DMSA＝(Task，Requirement)
the Task refers to a detection sensing Task, the Requirement refers to the service Requirement of the detection sensing Task, and the service Requirement in the sensing application description model corresponds to the service Type in the sensing service description model.
The beneficial effect of adopting the further scheme is that: constructing a plurality of perception application description models according to the task type and the service requirement of the detection perception task; the service requirement of the sensing application description model is matched with the service type of the sensing service description model; when a user request is received, the required sensor resources can be rapidly acquired, various detection sensing application services can be dynamically provided for the user according to the requirement, and the detection sensing capability under the complex environment can be effectively improved.
In order to solve the above technical problem, an embodiment of the present invention further provides a service-oriented perceptual cloud method, including:
matching a corresponding perception application description model in a perception application description model library according to the task type of the detection perception task in the user request;
matching a corresponding sensing service description model in a sensing service description model library according to the service requirement in the sensing application description model, and calling a corresponding sensor resource according to the sensing service description model;
mapping sensor resources into virtual sensing resources in advance, establishing a sensing resource description model, and aggregating to form a virtual sensing resource pool; performing service encapsulation on the virtual sensing resources, and establishing a sensing service description model library, wherein a sensing service description model in the sensing service description model library comprises service types and sensing resources corresponding to the service types; and establishing a perception application description model library, wherein a perception application description model in the perception application description model library comprises a task type and a service requirement corresponding to the task type.
The invention has the beneficial effects that: sensor resources are virtualized, and virtual sensing resources are subjected to service encapsulation to obtain a plurality of sensing service description models, so that a sensing service system is constructed; constructing various perception application description models according to the task type and the service requirement of the detection perception task, and constructing a perception application system; the service requirement of the sensing application description model is matched with the service type of the sensing service description model; when a user request is received, matching the corresponding sensing application description model according to the task type of the detection sensing task in the user request, matching the corresponding sensing service description model according to the service requirement of the sensing application description model, and calling the corresponding sensor resource according to the sensing service description model, so that various detection sensing application services are dynamically provided for the user according to the requirement, and the detection sensing capability under the complex environment can be effectively improved.
On the basis of the technical scheme, the invention can be further improved as follows:
further, the perceptual resource description model is as follows:
DMSR＝(ID，State，Location，Capability)
wherein, ID refers to the sensing resource identification, State refers to the current State of the sensing resource, Location refers to the geographical position of the sensing resource entity, and Capability refers to the sensing Capability of the sensing resource.
Further, the perceptual service description model in the perceptual service description model library is as follows:
DMSS＝(Type，Resource)
the Type refers to a service Type, the Resource refers to sensor resources required in a detection sensing process, and the sensor resources are formed by sensing resources corresponding to a sensing Resource description model DMSR.
Further, the perceptual application description model in the perceptual application description model library is as follows:
DMSA＝(Task，Requirement)
the Task refers to a detection sensing Task, the Requirement refers to the service Requirement of the detection sensing Task, and the service Requirement in the sensing application description model corresponds to the service Type in the sensing service description model.
In order to solve the foregoing technical problem, an embodiment of the present invention further provides a computer-readable storage medium, which includes instructions, and when the instructions are run on a computer, the instructions cause the computer to execute the service-oriented perceptual cloud method according to the foregoing technical solution.
In order to solve the foregoing technical problem, an embodiment of the present invention further provides a computer device, including a memory, a processor, and a computer program stored in the memory and capable of running on the processor, where when the processor executes the computer program, the service-oriented perceptual cloud method according to the foregoing technical solution is implemented.
Additional aspects of the invention and its advantages will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention.
Drawings
Fig. 1 is a block diagram of a service-oriented perceptual cloud system according to an embodiment of the present invention;
fig. 2 is a flowchart of a service-oriented perceptual cloud method according to an embodiment of the present invention.
Detailed Description
The principles and features of this invention are described below in conjunction with the following drawings, which are set forth by way of illustration only and are not intended to limit the scope of the invention.
Fig. 1 is a block diagram of a service-oriented perceptual cloud system according to an embodiment of the present invention. As shown in fig. 1, the system includes: a perceptual cloud resource module 101, a perceptual cloud service module 102, a perceptual cloud application module 103, and a perceptual cloud management module 104.
The sensing cloud resource module 101 is used for mapping the sensor resources into virtual sensing resources, establishing a sensing resource description model, and aggregating to form a virtual sensing resource pool;
the perception cloud service module 102 is configured to perform service encapsulation on the virtual perception resources and establish a perception service description model library, where a perception service description model in the perception service description model library includes a service type and perception resources corresponding to the service type;
the perception cloud application module 103 is used for establishing a perception application description model library, and a perception application description model in the perception application description model library comprises a task type and a service requirement corresponding to the task type;
the sensing cloud management module 104 is configured to match a corresponding sensing application description model in a sensing application description model library according to a task type of a sensing task detected in a user request, match a corresponding sensing service description model in a sensing service description model library according to a service requirement in the sensing application description model, and call a corresponding sensor resource according to the sensing service description model.
In the embodiment, sensor resources are virtualized, and virtual sensing resources are subjected to service encapsulation to obtain a plurality of sensing service description models, so that a sensing service system is constructed; constructing various perception application description models according to the task type and the service requirement of the detection perception task, and constructing a perception application system; the service requirement of the sensing application description model is matched with the service type of the sensing service description model; when a user request is received, matching the corresponding sensing application description model according to the task type of the detection sensing task in the user request, matching the corresponding sensing service description model according to the service requirement of the sensing application description model, and calling the corresponding sensor resource according to the sensing service description model, so that various detection sensing application services are dynamically provided for the user according to the requirement, and the detection sensing capability under the complex environment can be effectively improved.
Optionally, the sensing cloud resource module is specifically configured to map various sensor resources that are dispersedly deployed into virtual sensing resources by using a resource virtualization technology, and establish a sensing resource description model, where the sensing resource description model is as follows:
DMSR＝(ID，State，Location，Capability)
wherein, ID refers to the sensing resource identification, State refers to the current State of the sensing resource, Location refers to the geographical position of the sensing resource entity, and Capability refers to the sensing Capability of the sensing resource.
For example, the sensor resources include sensors S1, S2, … …, Sn, and the mapped virtual sensing resources include virtual sensors VS1, VS2, … …, VSn, where n represents the number of sensors.
In the above embodiment, the sensor resources are virtualized into virtual sensing resources including content items such as ID, State, Location, Capability, and the like, various sensor resources that are deployed in a dispersed manner are synthesized into a unified and efficient task system, a sensing cloud system is constructed, and the various sensor resources cooperatively work according to an optimal application strategy under time synchronization and space synchronization through unified scheduling, so that interoperability, self-organization, adaptivity, and the like of the system are enhanced, and conditions are provided for constructing intelligent detection sensing.
Optionally, the sensing cloud service module is specifically configured to perform service encapsulation on the virtual sensing resources in the virtual sensing resource pool, and establish a sensing service description model library, where a sensing service description model in the sensing service description model library is as follows:
DMSS＝(Type，Resource)
wherein, Type refers to service Type, such as scouting, monitoring, tracking and positioning; resource refers to sensor resources required in the detection sensing process, and the sensor resources are formed by sensing resources corresponding to a sensing Resource description model DMSR.
In the embodiment, the virtual sensing resources in the virtual sensing resource pool are subjected to service encapsulation, the internal attributes of the resources are hidden, and the external public only through a uniform interface meets the requirement that a user dynamically calls various sensor resources as required through a service form.
Optionally, the perceptual cloud application module is specifically configured to establish a perceptual application description model library, where perceptual application description models in the perceptual application description model library are as follows:
DMSA＝(Task，Requirement)
the Task refers to a detection sensing Task, the Requirement refers to the service Requirement of the detection sensing Task, and the service Requirement in the sensing application description model corresponds to the service Type in the sensing service description model.
In the actual detection process, the sensing cloud system receives an application request from an external user, matches a corresponding sensing application description model according to the content of the application request, finds a corresponding sensing service description model according to Requirement in the sensing application description model, aggregates corresponding sensor resources according to a sensing Resource description model associated with Resource in the sensing service description model, and finally completes the application request provided by the user together by the aggregated sensor resources.
The service-oriented aware cloud system provided by the embodiment of the invention is described in detail above with reference to fig. 1. The service-oriented perceptual cloud method provided by the embodiment of the invention is described in detail below with reference to fig. 2.
As shown in fig. 2, a service-oriented perceptual cloud method includes:
s201, matching a corresponding perception application description model in a perception application description model library according to the task type of a detection perception task in a user request;
s202, matching a corresponding sensing service description model in a sensing service description model library according to the service requirement in the sensing application description model, and calling a corresponding sensor resource according to the sensing service description model;
mapping sensor resources into virtual sensing resources in advance, establishing a sensing resource description model, and aggregating to form a virtual sensing resource pool; performing service encapsulation on the virtual sensing resources, and establishing a sensing service description model library, wherein a sensing service description model in the sensing service description model library comprises service types and sensing resources corresponding to the service types; and establishing a perception application description model library, wherein a perception application description model in the perception application description model library comprises a task type and a service requirement corresponding to the task type.
Optionally, the perceptual resource description model is as follows:
DMSR＝(ID，State，Location，Capability)
wherein, ID refers to the sensing resource identification, State refers to the current State of the sensing resource, Location refers to the geographical position of the sensing resource entity, and Capability refers to the sensing Capability of the sensing resource.
Optionally, the perceptual service description model in the perceptual service description model library is as follows:
DMSS＝(Type，Resource)
the Type refers to a service Type, the Resource refers to sensor resources required in a detection sensing process, and the sensor resources are formed by sensing resources corresponding to a sensing Resource description model DMSR.
Optionally, the perceptual application description model in the perceptual application description model library is as follows:
DMSA＝(Task，Requirement)
the Task refers to a detection sensing Task, the Requirement refers to the service Requirement of the detection sensing Task, and the service Requirement in the sensing application description model corresponds to the service Type in the sensing service description model.
The embodiment of the invention also provides a computer-readable storage medium, which comprises instructions, and when the instructions are run on a computer, the computer is enabled to execute the service-oriented perceptual cloud method in the technical scheme.
The embodiment of the invention also provides computer equipment which comprises a memory, a processor and a computer program which is stored on the memory and can be run on the processor, wherein the processor realizes the service-oriented perceptual cloud method in the technical scheme when executing the program.
It is clear to those skilled in the art that, for convenience and brevity of description, the specific working processes of the above-described apparatuses and units may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.
In the several embodiments provided in the present application, it should be understood that the disclosed apparatus and method may be implemented in other ways. For example, the above-described apparatus embodiments are merely illustrative, and for example, a division of a unit is merely a logical division, and an actual implementation may have another division, for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed.
Units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment of the present invention.
In addition, functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit.
The integrated unit, if implemented in the form of a software functional unit and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present invention essentially or partially contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product stored in a storage medium and including instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents, improvements and the like that fall within the spirit and principle of the present invention are intended to be included therein.
Claims (10)
1. A service-oriented, aware cloud system, comprising:
the sensing cloud resource module is used for mapping the sensor resources into virtual sensing resources, establishing a sensing resource description model and aggregating to form a virtual sensing resource pool;
the sensing cloud service module is used for carrying out service encapsulation on the virtual sensing resources and establishing a sensing service description model library, wherein a sensing service description model in the sensing service description model library comprises a service type and sensing resources corresponding to the service type;
the perception cloud application module is used for establishing a perception application description model library, and a perception application description model in the perception application description model library comprises a task type and a service requirement corresponding to the task type;
and the perception cloud management module is used for matching a corresponding perception application description model in a perception application description model base according to the task type of a detection perception task in a user request, matching a corresponding perception service description model in a perception service description model base according to the service requirement in the perception application description model, and calling a corresponding sensor resource according to the perception service description model.
2. The system according to claim 1, wherein the sensing cloud resource module is specifically configured to map various sensor resources that are deployed in a decentralized manner to virtual sensing resources by using a resource virtualization technology, and establish a sensing resource description model, where the sensing resource description model is as follows:
DMSR＝(ID，State，Location，Capability)
wherein, ID refers to the sensing resource identification, State refers to the current State of the sensing resource, Location refers to the geographical position of the sensing resource entity, and Capability refers to the sensing Capability of the sensing resource.
3. The system according to claim 2, wherein the sensing cloud service module is specifically configured to perform service encapsulation on the virtual sensing resources in the virtual sensing resource pool, and establish a sensing service description model library, where a sensing service description model in the sensing service description model library is as follows:
DMSS＝(Type，Resource)
the Type refers to a service Type, the Resource refers to sensor resources required in a detection sensing process, and the sensor resources are formed by sensing resources corresponding to a sensing Resource description model DMSR.
4. The system according to claim 3, wherein the perceptual cloud application module is specifically configured to build a perceptual application description model library, and perceptual application description models in the perceptual application description model library are as follows:
DMSA＝(Task，Requirement)
the Task refers to a detection sensing Task, the Requirement refers to the service Requirement of the detection sensing Task, and the service Requirement in the sensing application description model corresponds to the service Type in the sensing service description model.
5. A service-oriented perceptual cloud method, comprising:
matching a corresponding perception application description model in a perception application description model library according to the task type of the detection perception task in the user request;
matching a corresponding sensing service description model in a sensing service description model library according to the service requirement in the sensing application description model, and calling a corresponding sensor resource according to the sensing service description model;
mapping sensor resources into virtual sensing resources in advance, establishing a sensing resource description model, and aggregating to form a virtual sensing resource pool; performing service encapsulation on the virtual sensing resources, and establishing a sensing service description model library, wherein a sensing service description model in the sensing service description model library comprises service types and sensing resources corresponding to the service types; and establishing a perception application description model library, wherein a perception application description model in the perception application description model library comprises a task type and a service requirement corresponding to the task type.
6. The method of claim 5, wherein the perceptual resource description model is as follows:
DMSR＝(ID，State，Location，Capability)
wherein, ID refers to the sensing resource identification, State refers to the current State of the sensing resource, Location refers to the geographical position of the sensing resource entity, and Capability refers to the sensing Capability of the sensing resource.
7. The method of claim 6, wherein the perceptual service description models in the perceptual service description model library are as follows:
DMSS＝(Type，Resource)
the Type refers to a service Type, the Resource refers to sensor resources required in a detection sensing process, and the sensor resources are formed by sensing resources corresponding to a sensing Resource description model DMSR.
8. The method of claim 7, wherein the perceptual application description model in the perceptual application description model library is as follows:
DMSA＝(Task，Requirement)
the Task refers to a detection sensing Task, the Requirement refers to the service Requirement of the detection sensing Task, and the service Requirement in the sensing application description model corresponds to the service Type in the sensing service description model.
9. A computer-readable storage medium comprising instructions that, when executed on a computer, cause the computer to perform the service-oriented perceptual cloud method of any one of claims 5 to 8.
10. A computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor implements the service-oriented perceptual cloud method of any one of claims 5 to 8 when executing the program.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110095323.3A CN112764884A (en) | 2021-01-25 | 2021-01-25 | Service-oriented perception cloud system, method, medium and equipment |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110095323.3A CN112764884A (en) | 2021-01-25 | 2021-01-25 | Service-oriented perception cloud system, method, medium and equipment |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN112764884A true CN112764884A (en) | 2021-05-07 |
Family
ID=75707035
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202110095323.3A Pending CN112764884A (en) | 2021-01-25 | 2021-01-25 | Service-oriented perception cloud system, method, medium and equipment |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN112764884A (en) |
Citations (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20110058202A1 (en) * | 2009-09-10 | 2011-03-10 | Xerox Corporation. | Method and system for matching distributed users with distributed multi-function devices |
| CN102176723A (en) * | 2011-03-25 | 2011-09-07 | 北京航空航天大学 | Manufacturing cloud system for supporting on-demand use and dynamic collaboration of manufacturing resources and manufacturing capacities |
| CN102523278A (en) * | 2011-12-09 | 2012-06-27 | 中国联合网络通信集团有限公司 | Cloud-computing based service providing method and network operator server |
| US20130080579A1 (en) * | 2011-09-26 | 2013-03-28 | Unicorn Media, Inc. | Dynamically-executed syndication services |
| US20160044035A1 (en) * | 2012-04-05 | 2016-02-11 | Arizona Board Of Regents On Behalf Of Arizona State University | Systems and Apparatuses for a Secure Mobile Cloud Framework for Mobile Computing and Communication |
| CN105357199A (en) * | 2015-11-09 | 2016-02-24 | 南京邮电大学 | Cloud computing cognitive resource management system and method |
| CN109151042A (en) * | 2018-09-06 | 2019-01-04 | 广州知弘科技有限公司 | Internet of Things perception data Intelligent planning method |
| CN111160658A (en) * | 2019-12-31 | 2020-05-15 | 同济大学 | Collaborative manufacturing resource optimization method, system and platform |
| CN111563018A (en) * | 2020-04-28 | 2020-08-21 | 北京航空航天大学 | Resource management and monitoring method of man-machine-object fusion cloud computing platform |
-
2021
- 2021-01-25 CN CN202110095323.3A patent/CN112764884A/en active Pending
Patent Citations (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20110058202A1 (en) * | 2009-09-10 | 2011-03-10 | Xerox Corporation. | Method and system for matching distributed users with distributed multi-function devices |
| CN102176723A (en) * | 2011-03-25 | 2011-09-07 | 北京航空航天大学 | Manufacturing cloud system for supporting on-demand use and dynamic collaboration of manufacturing resources and manufacturing capacities |
| US20130080579A1 (en) * | 2011-09-26 | 2013-03-28 | Unicorn Media, Inc. | Dynamically-executed syndication services |
| CN102523278A (en) * | 2011-12-09 | 2012-06-27 | 中国联合网络通信集团有限公司 | Cloud-computing based service providing method and network operator server |
| US20160044035A1 (en) * | 2012-04-05 | 2016-02-11 | Arizona Board Of Regents On Behalf Of Arizona State University | Systems and Apparatuses for a Secure Mobile Cloud Framework for Mobile Computing and Communication |
| CN105357199A (en) * | 2015-11-09 | 2016-02-24 | 南京邮电大学 | Cloud computing cognitive resource management system and method |
| CN109151042A (en) * | 2018-09-06 | 2019-01-04 | 广州知弘科技有限公司 | Internet of Things perception data Intelligent planning method |
| CN111160658A (en) * | 2019-12-31 | 2020-05-15 | 同济大学 | Collaborative manufacturing resource optimization method, system and platform |
| CN111563018A (en) * | 2020-04-28 | 2020-08-21 | 北京航空航天大学 | Resource management and monitoring method of man-machine-object fusion cloud computing platform |
Non-Patent Citations (5)
| Title |
|---|
| 孟飙;吴兴杰;陈俊辉;: "云制造资源服务化封装与服务发现研究", 航空制造技术, no. 04 * |
| 张朱玲;: "中小企业云制造服务平台的资源虚拟化实现", 电子元器件与信息技术, no. 07, 20 July 2018 (2018-07-20) * |
| 张霖;罗永亮;陶飞;任磊;郭华;: "制造云构建关键技术研究", 计算机集成制造系统, no. 11 * |
| 李从东;谢天;汤勇力;李浩民;: "面向云制造服务的语义X列表知识表达与推理体系", 计算机集成制造系统, no. 07 * |
| 李长仪;刘婷婷;张军;付军;: "基于资源云端化的服务调度本体描述模型", 制造技术与机床, no. 02, 2 February 2015 (2015-02-02) * |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| US10459764B2 (en) | Stateless instance backed mobile devices | |
| CN112583883A (en) | Method and apparatus for aggregating telemetry data in a marginal environment | |
| EP3571586B1 (en) | Dynamic and application-specific virtualized graphics processing | |
| CN107092544B (en) | Monitoring method and device | |
| JP2018503275A (en) | Method, apparatus, and system for exploring application topology relationships | |
| CN105868389A (en) | Method and system for implementing data sandbox based on mongoDB | |
| US10002075B1 (en) | Managing memory resources in a network environment in order to handle querying of logical data structures | |
| WO2023005771A1 (en) | Track querying method and device, storage medium, and computer program product | |
| CN109327540A (en) | Electronic device, server load balancing method and storage medium | |
| CN111506434B (en) | Task processing method and device and computer readable storage medium | |
| CN110933136A (en) | Service node selection method, device, equipment and readable storage medium | |
| CN103399791A (en) | Method and device for migrating virtual machines on basis of cloud computing | |
| CN114095567A (en) | Data access request processing method and device, computer equipment and medium | |
| CN114036031B (en) | Scheduling system and method for resource service application in enterprise digital middleboxes | |
| US11899823B2 (en) | Privacy safe anonymized identity matching | |
| CN112764884A (en) | Service-oriented perception cloud system, method, medium and equipment | |
| CN109388770B (en) | Web page generation method and device | |
| CN107368351B (en) | Automatic upgrading and capacity expanding method and device for virtual machine configuration | |
| CN113467823B (en) | Configuration information acquisition method, device, system and storage medium | |
| CN115098272A (en) | GPU resource scheduling method, scheduler, electronic device and storage medium | |
| Silva et al. | Mobile cloud face recognition based on smart cloud ranking | |
| CN115309520A (en) | Task migration method and device, electronic equipment and storage medium | |
| US11631052B2 (en) | Ad hoc supply chain community node | |
| CN110990471A (en) | Data processing method and device for vehicle dealership | |
| CN107608765B (en) | Virtual machine migration method and device |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |