CN110545307B - Edge computing platform, calling method and computer readable storage medium - Google Patents
Edge computing platform, calling method and computer readable storage medium Download PDFInfo
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Abstract
The embodiment of the invention relates to the technical field of communication, and discloses an edge computing platform, a calling method and a computer readable storage medium. In the present invention, an edge computing platform comprises: the distribution unit is used for identifying information called by an application program deployed on the edge computing platform to obtain the information type of the information; sending the information to an execution unit according to the information type; an execution unit to execute a processing operation according to the information. The embodiment of the invention also provides a calling method and a computer readable storage medium; the efficiency of processing information can be further improved.
Description
Technical Field
The embodiment of the invention relates to the technical field of communication, in particular to an edge computing platform, a calling method and a computer readable storage medium.
Background
The Multi-access Edge Computing (MEC) is a technology proposed by the European Telecommunications Standardization Institute (ETSI) based on a 5G evolution architecture, which deeply integrates a base station and internet services, and the MEC is a key technology for the evolution of a 4G/5G network architecture, and can meet various requirements of a system on throughput, delay, network scalability, intellectualization and the like.
However, the inventors found that at least the following problems exist in the related art: the position advantage of the edge computing platform is not fully exerted, and the information processing efficiency is low.
Disclosure of Invention
An object of embodiments of the present invention is to provide an edge computing platform, a calling method, and a computer-readable storage medium, so that a position advantage of the edge computing platform can be fully utilized, and processing efficiency of information is further improved.
To solve the above technical problem, an embodiment of the present invention provides an edge computing platform, including: the distribution unit is used for identifying information called by an application program deployed on the edge computing platform to obtain the information type of the information; sending the information to an execution unit according to the information type; an execution unit to execute a processing operation according to the information.
The embodiment of the invention also provides a calling method, which comprises the following steps: identifying information called by an application program deployed on an edge computing platform to obtain the information type of the information; sending the information to an execution unit according to the information type; processing operations are performed based on the information.
The embodiment of the invention also provides a computer readable storage medium, which stores a computer program, and the computer program realizes the calling method when being executed by a processor.
Compared with the prior art, the embodiment of the invention provides an edge computing platform, which comprises: the distribution unit is used for identifying information called by an application program deployed on the edge computing platform to obtain the information type of the information; sending the information to an execution unit according to the information type; an execution unit to execute a processing operation according to the information. The type division is carried out according to the information called by the application program deployed on the edge computing platform, and the information is sent to the execution unit according to the information type, so that the edge computing platform with a better data acquisition and data processing mode is provided, and the information processing efficiency can be further improved.
In addition, the execution unit specifically includes any one of the following or any combination thereof: the system comprises a capability acquisition module, a capability calling module, a capability combination module and a local processing module; the capability acquisition module is used for performing at least one of the following processing according to the information: authenticating request equipment sending a request to an application program, performing protocol conversion, acquiring parameters of a physical channel and acquiring network throughput; the capability calling module is used for executing forwarding operation on the information according to the capability open platform; the capability combination module is used for combining the data of the remote end to process the information; and the local processing module is used for processing the local data according to the information. In this embodiment, different modules can process different information types, so that the information processing efficiency can be further improved.
In addition, the capacity combination module is specifically used for performing data analysis and/or report generation according to the strategy information issued by the big data center platform when the remote end is specifically the big data center platform; and the capability combination module is specifically used for carrying out data reasoning according to the training result of the far end to obtain a reasoning result when the third information type is the information type related to the artificial intelligence. In the embodiment, the strategy information can be issued by the big data center platform, and the edge computing platform performs data analysis and/or report generation, so that the load pressure of the big data center platform can be reduced; since the training required for artificial intelligence is done at the far end, reasoning is done at the edge computing platform, which can reduce the load pressure at the far end.
In addition, the capability combination module is also used for judging the accuracy of the training result of the remote end according to the reasoning result; and when the accuracy is smaller than a preset threshold value, triggering an error correction function. In this embodiment, the accuracy of the training result at the remote end is determined according to the inference result, and when the accuracy is smaller than the preset threshold, the error correction function is triggered, so that the accuracy of the training result can be improved.
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One or more embodiments are illustrated by way of example in the accompanying drawings, which correspond to the figures in which like reference numerals refer to similar elements and which are not to scale unless otherwise specified.
FIG. 1 is a schematic structural diagram of an edge computing platform according to a first embodiment of the present invention;
FIG. 2 is a schematic structural diagram of another edge computing platform provided in accordance with a first embodiment of the present invention;
fig. 3 is a flowchart of a calling method according to a fifth embodiment of the present invention.
Detailed Description
To make the objects, technical solutions and advantages of the embodiments of the present invention more apparent, embodiments of the present invention will be described in detail below with reference to the accompanying drawings. However, it will be appreciated by those of ordinary skill in the art that numerous technical details are set forth in order to provide a better understanding of the present application in various embodiments of the present invention. However, the technical solution claimed in the present application can be implemented without these technical details and various changes and modifications based on the following embodiments.
A first embodiment of the invention is directed to an edge computing platform, as shown in FIG. 1, comprising: the distribution unit 11 is configured to identify information called by an application deployed on the edge computing platform, and obtain an information type of the information; sending the information to the execution unit 12 according to the information type; an execution unit 12 for executing processing operations according to the information.
In this embodiment, by performing type division according to information called by an application deployed on the edge computing platform and sending the information to the execution unit 12 according to the information type, the edge computing platform with a better data acquisition and data processing mode is provided, and the processing efficiency of the information can be further improved.
The following describes implementation details of an edge computing platform of the present embodiment, and the following is provided only for the sake of understanding and is not necessary for implementing the present embodiment.
In one example, the execution unit 12 may include any one or any combination of the following: a capability acquiring module 121, a capability calling module 122, a capability combining module 123, and a local processing module 124, as shown in fig. 2. Wherein, the capability obtaining module 121 is configured to, according to the information, perform at least one of the following processes: authenticating request equipment sending a request to an application program, performing protocol conversion, acquiring parameters of a physical channel and acquiring network throughput; the capability calling module 122 is used for executing forwarding operation on the information according to the capability open platform; the capability combination module 123 is used for processing information by combining data of a far end; and the local processing module 124 is used for processing the local data according to the information. In this embodiment, different modules can process different information types, so that the information processing efficiency can be further improved.
In an example, the distribution unit 11 may perform decapsulation processing on an Application Programming Interface (API) with encapsulation, identify information called by an Application program (i.e., MEC APP) deployed on the edge computing platform, obtain an information type of the information, and forward the information to any one of the capability obtaining module 121, the capability calling module 122, the capability combining module 123, and the local processing module 124 or any combination thereof according to the information type. And may also receive information fed back by any one of or any combination of the capability obtaining module 121, the capability calling module 122, the capability combining module 123, and the local processing module 124, and forward the fed-back information to the corresponding application program.
For example, the MEC APP calls the API to obtain the current capacity of a restaurant with a mobile phone number of 138 xxx at a location within 300 meters around the current location, the distribution unit 11 may send the request information to the capability obtaining module 121, obtain the current location of the user through the capability obtaining module 121, and feed back the obtained current location of the user to the distribution unit 11, the distribution unit 11 may send the request information and the current location of the user to the capability calling module 122, obtain a pre-stored market map through the capability calling module 122, read market list information around the user within 300 meters, and feed back the obtained result to the distribution unit 11, the distribution unit 11 may send the request information and the obtained result to the capability combining module 123, perform real-time streaming processing through the capability combining module 123, perform a full seat condition on the market condition in the market list information, and perform a full seat condition on the market list information, And analyzing queuing conditions and the like to obtain an analysis result, feeding back the analysis result to the distribution unit 11, and sending the analysis result to the MEC APP by the distribution unit 11 through the API, so that the MEC APP can obtain the current capacity condition of the restaurant within 300 meters around the current position of the user.
As will be appreciated by those skilled in the art, ETSI defines MEC as the ability to provide IT and cloud computing to the edge of a mobile network by deploying a generic server on the wireless access, emphasizing close proximity to the user. The MEC enables the traditional wireless access network to have the conditions of service localization and close-range deployment, thereby providing the transmission capability with high bandwidth and low time delay, simultaneously, the service plane is sunk to form the localized deployment, and the requirement on the network return bandwidth and the network load can be effectively reduced. However, in the related art, there is no clear framework of the edge computing platform, and the advantages of the edge computing platform are not fully exerted, resulting in low efficiency of processing information.
In this embodiment, based on the advantage that the edge computing platform is located at the boundary between the access network and the core network, that is, the edge is sunken, various capabilities that the core network can open are fully utilized.
It is easy to find that, the edge computing platform provided in this embodiment performs type division according to the information called by the application deployed in the edge computing platform, and sends the information to the execution unit 12 according to the information type, so as to provide an edge computing platform with a better data acquisition and data processing manner, which can further improve the processing efficiency of the information.
A second embodiment of the invention is directed to an edge computing platform. The second embodiment is substantially the same as the first embodiment, and mainly differs therefrom in that: in this embodiment, the distributing unit 11 is specifically configured to send the information to the capability acquiring module 121 when the information type is the first information type; the first information type is: the type of information that needs to be obtained and/or executed by the access network element. In this embodiment, when the information type is the first information type, the information is sent to the capability obtaining module 121, and the capability obtaining module 121 processes the information, so that the processing efficiency of the information can be further improved.
In this embodiment, the distributing unit 11 is specifically configured to send the information to the capability obtaining module 121 when the information type is a first information type that needs to be obtained and/or executed by an access network element; a capability obtaining module 121, configured to perform at least one of the following processes according to the information: the method comprises the steps of authenticating a request device sending a request to an application program, carrying out protocol conversion, obtaining parameters of a physical channel and obtaining network throughput.
The access network elements referred to herein may include, but are not limited to: a Radio Network Controller (RNC), NodeB, eNodeB, and a Control Unit (CU).
Specifically, the capability obtaining module 121 in this embodiment is mainly used to obtain and process information related to an access network element. The parameters of the physical channel may include, but are not limited to: a Channel Quality Indicator (CQI), a Block Error rate (BLER), and the like, where the network throughput may be real-time network throughput and network throughput statistical information, and the capability obtaining module 121 may be further configured to process positioning information of a mobile user, and the like.
In one example, the capability acquisition module 121 may be configured with standard interfaces and protocol flows. Such as: a related protocol defined by the third Generation Partnership Project (3rd Generation Partnership Project, abbreviated "3 GPP"), an industry standard defined by industry standards association, an enterprise standard defined by china mobile, and the like. In this way, the capability obtaining module 121 may convert the message received from the north direction into a south direction related protocol message, send the south direction related protocol message to the access network element, obtain the capability according to the access network element, and then send the obtained information to the MEC APP through the distributing unit 11.
That is, by configuring the standard interface and protocol flow for the capability obtaining module 121, the capability obtaining module 121 can be made to have at least one of the following functions: authentication function, access function, and message conversion function. For example, the authentication function may be understood as performing bidirectional authentication according to MEC APP, the access function may be understood as acquiring scheduling information of a base station or channel information of a user under the base station, and the message conversion function may be understood as: the conversion of messages is done from the API to the API or signaling that interfaces with the remote network element. Of course, this is only an example, and in practical applications, this should not be taken as a limitation.
In other examples, the distribution unit 11 may be further configured to send the information to the local processing module 124 when the information type is the fourth information type; the fourth information type is: only the information type of the local application of the edge computing platform needs to be called; and the local processing module 124 is used for processing the local data according to the information.
Here, the processing of local data may be, for example: and calling functions such as rendering or transcoding and the like through the capability of resources after the edge computing platform is compiled and related capability (such as memory application, CPU (central processing unit) adjustment and the like) executed by the MEC APP on the host machine. These processing operations may be performed only locally at the edge computing platform and therefore require no interaction with the outside.
It is easy to find that, in the edge computing platform provided in this embodiment, when the information type is the first information type, the information is sent to the capability obtaining module 121, and the capability obtaining module 121 processes the information, so that the processing efficiency of the information can be further improved.
A third embodiment of the present invention relates to an edge computing platform, and is substantially the same as the first embodiment, and is mainly different in that: in this embodiment, the distributing unit 11 is specifically configured to send the information to the capability calling module 122 when the information type is the second information type; the second information type is: the type of information that needs to interact with the capability openness platform. In this embodiment, when the information type is the second information type, the information is sent to the capability obtaining module 121, and the capability obtaining module 121 processes the information, so that the processing efficiency of the information can be further improved.
In this embodiment, the distributing unit 11 is specifically configured to send the information to the capability invoking module 122 when the information type is a second information type that needs to interact with the capability opening platform; and the capability calling module 122 is configured to perform forwarding operation on the information according to the capability open platform.
Specifically, the capability calling module 122 in this embodiment may interface a capability open platform, such as a Quality of Service (QoS) capability open platform, a voice and short message capability open platform, and the like. By doing so, except that the consistency of the interface can be ensured, the MEC APP can run compatibly on the edge computing platform; in addition, for example, when the short message needs to be sent, the message is directly sent to the capability opening platform, and the capability opening platform executes the operation of sending the short message, so that the waste of resources can be avoided, and the use threshold of the MEC APP in the edge computing platform is reduced.
In one example, the capability calling module 122 may quickly and reliably send information to the capability openness platform according to the address information of the capability openness platform, so that the capability openness platform performs an operation corresponding to the information. That is to say, the capability calling module 122 basically does not perform relevant processing operation on the information, or simply replaces the sending and receiving relevant fields according to the address information, the port information and the like carried by the information, so as to relay the message.
Of course, in other examples, the capability calling module 122 may interact only with the capability openness platform. And may also interact with other modules in the edge computing platform or the MEC APP, which is not specifically limited herein.
It is easy to find that, in the edge computing platform provided in this embodiment, when the information type is the second information type, the information is sent to the capability obtaining module 121, and the capability obtaining module 121 processes the information, so that the processing efficiency of the information can be further improved.
A fourth embodiment of the invention is directed to an edge computing platform. The fourth embodiment is substantially the same as the first embodiment, and mainly differs therefrom in that: in this embodiment, the distributing unit 11 is specifically configured to send the information to the capability combination module 123 when the information type is the third information type; the third information type is: the type of information requiring co-processing both remotely and locally. In this embodiment, when the information type is the third information type, the information is sent to the capability combination module 123, and the capability combination module 123 processes the information, so that the processing efficiency of the information can be further improved.
In this embodiment, the distributing unit 11 is specifically configured to send the information to the capability combination module 123 when the information type is a third information type that requires remote and local cooperative processing; and the capability combination module 123 is used for combining data of the remote end to process information.
In one example, the distal end may be: a big data center platform; the capability combination module 123 is specifically configured to perform data analysis and/or report generation according to measurement information issued by the big data center platform. The strategy information can be issued by the big data center platform, and the edge computing platform performs data analysis and/or report generation, so that the load pressure of the big data center platform can be reduced.
In one example, the third information type may be: the type of information about artificial intelligence; the capability combination module 123 is specifically configured to perform data reasoning according to the training result of the remote end to obtain a reasoning result.
Specifically, in the capability combination module 123 of the present embodiment, an inference action may be performed, and in a remote end in cooperation therewith, data may be preprocessed and a training action may be performed. After training the data at the remote end to obtain a training result, the capability combination module 123 may obtain the training result synchronously, and perform data inference according to the training result, for example, the capability combination module 123 may call a relevant API, and perform relevant data inference through streaming processing (generally, processing for real-time video streaming and the like) or offline processing (generally, processing for statistical processing of data or offline video streaming and the like).
Wherein, the said far end can be but not limited to: servers, computer clusters.
Those skilled in the art will appreciate that in the related art, both the reasoning actions and the training actions are done remotely. For example, 10 ten thousand cameras are installed in the hang state city, and the far end needs to acquire data of the 10 ten thousand cameras, execute inference actions and training actions, and consume huge traffic. In the embodiment, the training action is performed at the far end, and the reasoning action is performed on the edge computing platform, so that the load pressure at the far end can be reduced.
In an example, the capability combination module 123 may further be configured to determine the accuracy of the training result according to the inference result; and when the accuracy is smaller than a preset threshold value, triggering an error correction function. The accuracy of the training result at the far end is judged according to the reasoning result, and when the accuracy is smaller than a preset threshold value, an error correction function is triggered, so that the accuracy of the training result can be improved.
For example, if the inference result is a face image, when the edge computing platform applies the inference result to perform inference matching on the received face image, if the inference result is matched 100 times in total, and only 2 times of matching succeeds, it may be indicated that the inference result is inaccurate to some extent, so that an error correction function is triggered for the remote end to perform training again to obtain a new training result.
It is easy to find that, in the edge computing platform provided by this embodiment, when the information type is the third information type, the information is sent to the capability combination module 123, and the capability combination module 123 processes the information, so that the processing efficiency of the information can be further improved.
It should be noted that each module referred to in this embodiment is a logical module, and in practical applications, one logical unit may be one physical unit, may be a part of one physical unit, and may be implemented by a combination of multiple physical units. In addition, in order to highlight the innovative part of the present invention, elements that are not so closely related to solving the technical problems proposed by the present invention are not introduced in the present embodiment, but this does not indicate that other elements are not present in the present embodiment.
A fifth embodiment of the present invention relates to a calling method. The method comprises the following steps: identifying information called by an application program deployed on an edge computing platform to obtain the information type of the information; sending the information to an execution unit according to the information type; processing operations are performed based on the information.
A flowchart of a calling method in this embodiment is shown in fig. 3, and includes:
And 102, sending the information to an execution unit according to the information type.
And step 103, executing processing operation according to the information.
In one example, at least one of the following processes may be performed according to the information: authenticating request equipment sending a request to an application program, performing protocol conversion, acquiring parameters of a physical channel and acquiring network throughput; the platform can be opened according to the ability, and the forwarding operation can be executed on the information; the information can be processed by combining the data of the remote end; the processing of the local data may be performed based on the information.
In one example, when the information type is the first information type, at least one of the following processes may be performed according to the information: authenticating request equipment sending a request to an application program, performing protocol conversion, acquiring parameters of a physical channel and acquiring network throughput; the first information type is: the type of information that needs to be obtained and/or executed by the access network element.
In one example, when the information type is the second information type, the platform is opened according to the capability, and the forwarding operation is executed on the information; the second information type is: the type of information that needs to interact with the capability openness platform.
In one example, when the information type is the third information type, the information can be processed by combining the data of the far end; the third information type is: the type of information that requires co-processing both remotely and locally.
In one example, when the remote end is a big data center platform, data analysis and/or report generation are performed according to policy information issued by the big data center platform; and when the third information type is the information type related to the artificial intelligence, performing data reasoning according to the training result of the far end to obtain a reasoning result.
In one example, the accuracy of the training result at the far end can be judged according to the reasoning result; and when the accuracy is smaller than a preset threshold value, triggering an error correction function.
In one example, when the information type is the fourth information type, the local data may be processed according to the information; the fourth information type is: only the information type of the native application of the edge computing platform needs to be invoked.
It should be understood that this embodiment is a method example corresponding to the first embodiment, and may be implemented in cooperation with the first embodiment. The related technical details mentioned in the first embodiment are still valid in this embodiment, and are not described herein again in order to reduce repetition. Accordingly, the related-art details mentioned in the present embodiment can also be applied to the first embodiment.
A sixth embodiment of the present invention relates to a computer-readable storage medium storing a computer program. The computer program realizes the above-described method embodiments when executed by a processor.
That is, as can be understood by those skilled in the art, all or part of the steps in the method for implementing the embodiments described above may be implemented by a program instructing related hardware, where the program is stored in a storage medium and includes several instructions to enable a device (which may be a single chip, a chip, or the like) or a processor (processor) to execute all or part of the steps of the method described in the embodiments of the present application. 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 various media capable of storing program codes.
It will be understood by those of ordinary skill in the art that the foregoing embodiments are specific examples for carrying out the invention, and that various changes in form and details may be made therein without departing from the spirit and scope of the invention in practice.
Claims (9)
1. An edge computing platform, comprising:
the distribution unit is used for identifying information called by an application program deployed on the edge computing platform and obtaining the information type of the information; sending the information to an execution unit according to the information type;
the execution unit is used for executing processing operation according to the information;
the execution unit specifically includes any combination of the following:
the system comprises a capability acquisition module, a capability calling module, a capability combination module and a local processing module; wherein,
the capability obtaining module is configured to perform at least one of the following processes according to the information: authenticating the request equipment sending the request to the application program, performing protocol conversion, acquiring parameters of a physical channel and acquiring network throughput;
the capability calling module is used for executing forwarding operation on the information according to the capability open platform;
the capability combination module is used for combining the data of the remote end and processing the information;
the local processing module is used for processing local data according to the information;
the distribution unit is also used for receiving the information fed back by the execution unit in any combination and forwarding the fed back information to the application program.
2. The edge computing platform of claim 1,
the distribution unit is specifically configured to send the information to the capability acquisition module when the information type is a first information type; the first information type is as follows: the type of information that needs to be obtained and/or executed by the access network element.
3. The edge computing platform of claim 1,
the distribution unit is specifically configured to send the information to the capability calling module when the information type is a second information type; the second information type is: the type of information needed to interact with the capability openness platform.
4. The edge computing platform of claim 1,
the distribution unit is specifically configured to send the information to the capability combination module when the information type is a third information type; the third information type is: the information types requiring the remote and local cooperative processing.
5. The edge computing platform of claim 4,
the capacity combination module is specifically used for performing data analysis and/or report generation according to policy information issued by the big data center platform when the remote end is specifically a big data center platform;
and the capability combination module is specifically used for performing data reasoning according to the training result of the far end to obtain a reasoning result when the third information type is an information type related to artificial intelligence.
6. The edge computing platform of claim 5,
the capability combination module is also used for judging the accuracy of the training result of the remote end according to the reasoning result; and when the accuracy is smaller than a preset threshold value, triggering an error correction function.
7. The edge computing platform of claim 1,
the distribution unit is specifically configured to send the information to the local processing module when the information type is a fourth information type; the fourth information type is: only the information type of the local application of the edge computing platform needs to be called.
8. A calling method, comprising:
identifying information called by an application program deployed on an edge computing platform to obtain the information type of the information; sending the information to an execution unit according to the information type;
executing processing operation according to the information;
the execution unit specifically includes any combination of the following:
the system comprises a capability acquisition module, a capability calling module, a capability combination module and a local processing module; wherein,
the capability obtaining module is configured to perform at least one of the following processes according to the information: authenticating the request equipment sending the request to the application program, carrying out protocol conversion, acquiring parameters of a physical channel and acquiring network throughput;
the capability calling module is used for executing forwarding operation on the information according to the capability open platform;
the capability combination module is used for combining the data of the remote end and processing the information;
the local processing module is used for processing local data according to the information;
and receiving the information fed back by the execution unit in any combination, and forwarding the fed back information to the application program.
9. A computer-readable storage medium, storing a computer program, wherein the computer program, when executed by a processor, implements the calling method of claim 8.
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| CN113259930A (en) * | 2020-02-10 | 2021-08-13 | 大唐移动通信设备有限公司 | Calling request, inquiry and authorization processing method, device and apparatus, and medium |
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| CN112769897B (en) * | 2020-12-21 | 2023-04-18 | 北京百度网讯科技有限公司 | Synchronization method and device of edge calculation message, electronic equipment and storage medium |
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| EP3065374B1 (en) * | 2013-10-31 | 2018-12-12 | Huawei Technologies Co., Ltd. | Network capability invoking method |
| CN108353067B (en) * | 2015-11-30 | 2020-06-02 | 华为技术有限公司 | Method, system and related equipment for realizing capability openness |
| EP3531747B1 (en) * | 2016-10-27 | 2021-02-24 | Huawei Technologies Co., Ltd. | Communication method and device |
| US10884808B2 (en) * | 2016-12-16 | 2021-01-05 | Accenture Global Solutions Limited | Edge computing platform |
| CN107766889B (en) * | 2017-10-26 | 2021-06-04 | 浪潮集团有限公司 | Cloud edge computing fused deep learning computing system and method |
| CN108804668A (en) * | 2018-06-08 | 2018-11-13 | 珠海格力智能装备有限公司 | Data processing method and device |
| CN108847981A (en) * | 2018-06-26 | 2018-11-20 | 咸宁职业技术学院 | Distributed computer cloud computing processing method |
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