Edge computing node device

An edge computing node device able to process and respond to data received in real-time includes at least one input interface and at least one output interface. The device obtains an identification of the at least one input interface and determines a functional service algorithm corresponding to the identification of at least one input interface by querying a service relationship table. The device further processes the data to obtain a calculation result according to the functional service algorithm and transmits the calculation of the data or the basic data to the output interface. The at least one output interface sends the basic data or the calculation result of the data by the second communication unit.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application claims priority to Chinese Patent Application No. 202010367754.6 filed on Apr. 30, 2020, the contents of which are incorporated by reference herein.

FIELD

The subject matter herein generally relates to the data processing field, especially to an edge computing node device.

BACKGROUND

The cloud computing platform of the existing Internet model not only consumes a lot of power, but also suffers from lack of bandwidth, so returning data in real-time is problematic for cloud computing. Besides, data is usually analyzed and processed at the edge layer by an edge computing node device. However, the existing definition of edge computing node device is vague, and there is no uniform edge computing node device technology architecture and functional architecture.

DETAILED DESCRIPTION

The present disclosure, including the accompanying drawings, is illustrated by way of examples and not by way of limitation. Several definitions that apply throughout this disclosure will now be presented. It should be noted that references to “an” or “one” embodiment in this disclosure are not necessarily to the same embodiment, and such references mean “at least one.”

FIG. 1illustrates a running environment of an edge computing node device1. The edge computing node device1communicates with at least one external device2and an edge cloud3. The edge computing node device1can receive and process data sent by the external device2. The edge computing node device1can further send the data from the external device2or the data after processing to the edge cloud3. The edge computing node device1communicates with a data center4, a cloud computing platform5, and a second edge cloud6respectively, and can send the data sent by the external device2or the data after processing to the data center4, the cloud computing platform5, and the second edge cloud6. In at least one embodiment, each of the edge cloud3and the second edge cloud6is a cloud platform server. In at least one embodiment, the external device2can be a data collector, a data acquisition card, a sensor, or an image collector (e.g. a camera, an endoscope, a light field camera, etc.). In at least one embodiment, the edge computing node device1is a logical abstraction of a basic ability of an edge gateway, an edge controller, an edge server, and other product forms. The edge computing node device1can perform real-time data analysis, local data storage, real-time network connection, and other functions.

FIG. 2illustrates another running environment of the edge computing node device1. The edge computing node device1communicates with the cloud computing platform5. The edge computing node device1receives data sent by the external device2, processes the data sent by the external device2, and obtains a first calculation result of the data. The edge computing node device1further sends the data sent by the external device2or the first calculation result to the cloud computing platform5. The cloud computing platform5further analyzes the first calculation result or the data sent by the edge computing node device1to obtain a second calculation result of the data and sends the second calculation result of the data to the edge computing node device1. The edge cloud3sends the second calculation result of the data to the data center4and the second edge cloud6.

FIG. 3illustrates the edge computing node device1. The edge computing node device1includes a first communication unit11, at least one input interface12, a second communication unit13, at least one output interface14, a storage15, and a processor16. In at least one embodiment, the at least one input interface12connects to the first communication unit11. The least one output interface14connects to the second communication unit13. The processor16connects to the at least one input interface12, the at least one output interface14, and the storage15. The at least one input interface12receives the data sent by the external device2through the first communication unit11.

In at least one embodiment, the input interface12corresponds to a preset access mode and a preset access service. The input interface12receives the data sent by the external device2according to the preset access mode and the preset access service. The preset access mode is a certain way in which the input interface12receives the data, and the preset access service is a functional service of the data. In one embodiment, the preset access mode includes a wired access mode and a wireless access mode. The wired access mode includes a PROFIBUS access mode, a MODBUS access mode, a CANBUS access mode, and an ETHERCAT bus access mode. The wireless access mode includes a 4G access mode, a 5G access mode, a WIFI access mode, a LORA access mode, and an NBIOT access mode. In one embodiment, the preset access service includes, but is not limited to, a data collaboration service, a data computing service, a data analysis service, a rapid data model ingenuity service, a deep learning service, a speech recognition service, a semantic understanding service, a speech synthesis service, an image analysis service, an image analysis service, an entertainment service, a game service, a streaming service, and a translation service. In one embodiment, the first communication unit11can be a wireless communication module, such as a 4G communication module, a 5G communication module, a WIFI communication module, a LORA communication module, or an NBIOT communication module. In another embodiment, the first communication unit11can be a wired communication module, such as a PROFIBUS, a MODBUS, a CANBUS, or an ETHERCAT bus.

In at least one embodiment, the storage15stores data or soft code of the edge computing node device1. The storage15can include various types of non-transitory computer-readable storage mediums. For example, the storage15can be an internal storage system of the edge computing node device1, such as a flash memory, a random access memory (RAM) for the temporary storage of information, and/or a read-only memory (ROM) for permanent storage of information. In another embodiment, the storage15can also be an external storage system of the edge computing node device1, such as a hard disk, a storage card, or a data storage medium. In one embodiment, the processor16can be a central processing unit, a common processor, a digital signal processor, a dedicated integrated circuit, a ready-made programmable gate array, another programmable logic device, discrete door or transistor logic device, discrete hardware component, or the like. In another embodiment, the processor16can be any conventional processor. The processor16can also be a control center of the edge computing node device1, using various interfaces and lines to connect the various parts of the edge computing node device1.

In one embodiment, the processor16obtains an identification of the input interface12, and determines a functional service algorithm corresponding to the identification of the input interface12by querying a service relationship table20of the input interface12. The data received by the input interface12is processed to obtain a calculation result of the data according to the functional service algorithm. In at least one embodiment, the service relationship table20includes a number of identifications of the input interface12and a number of functional service algorithms and defines a correspondence between the number of identifications of the input interface12and the number of functional service algorithms.

FIG. 4illustrates the service relationship table20. In service relationship table20, the functional service algorithm corresponding to identification P1is a speech recognition algorithm, and the functional service algorithm corresponding to identification P2is an image analysis algorithm. For example, when the identification of the input interface12is P1, the processor16determines that the functional service algorithm should be the speech recognition algorithm by querying the service relationship table20. For example, when the identification of the input interface12is P2, the processor16determines that the functional service algorithm should be the image analysis algorithm by querying the service relationship table20.

In one embodiment, the processor16stores the calculation of the data or the data received by the input interface12according to a preset storage rule. In detail, the processor16sets a data storage path, a data storage cycle, and a data storage starting time, and stores the calculation of the data or the data received by the input interface12according to the data storage path, the data storage cycle, and the data storage start time. In at least one embodiment, the data storage path can be set in an on-premises database of the edge computing node device1, the edge cloud3, the data center4, the cloud computing platform5, or the second edge cloud6.

In at least one embodiment, the data received by the input interface12includes an identification of the external device2, and the processor16obtains the identification of the external device2from the data. In at least one embodiment, the identification of the external device2includes a device name information, an application area information, a company name information, and an equipment number information. For example, when the external device2is an instrument, the identification of the external device2can be T_Instrument_domain_company_name_device name_equipment number. When the external device2is a sensor, the identification of the external device2can be T_Sensor_domain_company_name_device name_equipment number.

In at least one embodiment, the processor16receives a first instruction, and modifies the functional service algorithm in response to the first instruction. In detail, the processor16queries an algorithm permission modification table30to determine an algorithm modification mode of the external device2corresponding to the identification of the external device2. The processor16determines whether the algorithm modification mode is a dynamic modification mode, and modifies the functional service algorithm according to the first instruction when determining that the algorithm modification mode is a dynamic modification mode. The algorithm modification mode includes a fixed mode and a dynamic modification mode. The fixed mode indicates that the functional service algorithm cannot be modified. The dynamic modification mode indicates that the algorithm mode can be modified.FIG. 5illustrates the algorithm permission modification table30. The algorithm permission modification table includes a number of identifications of multiple external devices2and a number of algorithm modification modes, and defines a correspondence between the number of identifications of multiple external devices2and the number of algorithm modification modes. For example, when the identification of the external device2is T1, the algorithm modification mode corresponding to T1is the fixed mode, when the identification of the external device2is T2, the algorithm modification mode corresponding to T2is the dynamic modification mode.

The processor16receives a second instruction sent by the edge cloud3or the cloud computing platform5, verifies an authority of the edge cloud3or the cloud computing platform5, and receives the functional service algorithm sent by the edge cloud3or the cloud computing platform5after the edge cloud3or the cloud computing platform5has passed verification. The received functional service algorithm is taken as a target algorithm, all the data of the edge computing node device1is stored, and the functional service algorithm of the edge computing node device1is updated according to the target algorithm. In one embodiment, the processor16records a successful updating information of the functional service algorithm or a failed updating information of the functional service algorithm in a log.

In at least one embodiment, the processor16receives the second instructions generated by the edge computing node device1, and selects one functional service algorithm from the multiple functional service algorithms stored in the edge computing node device1as the target algorithm. All the data of the edge computing node device1is stored, and the functional service algorithm of the edge computing node device1is updated according to the target algorithm.

In at least one embodiment, the processor16provides property information of the edge computing node device1. The property information includes identification of the edge computing node device1, calculation ability and capacity, functional service, processing delay time, storage capacity, and data structure. In one embodiment, the functional service includes, but is not limited to, data collaboration, data computing, data analysis, rapid data modeling, deep learning, speech recognition, semantic understanding, speech synthesis, image analysis, image analysis, entertainment services, game service, streaming service, and translation service. The present disclosure ensures that the property information of the edge computing node device1is collected, and facilitates a selection by the external device2of a suitable edge computing node device1to provide services according to the property information of the edge computing node device1.

In at least one embodiment, the processor16carries out a security check on the data received by the input interface12. In detail, the processor16selects one checking mode from three checking modes of virus scanning, whitelist scanning, and security authentication, and checks the data according to the selected checking mode. The processor16records abnormal data if the result of a security check is abnormal and distinguishes and reports the abnormal data. In one embodiment, when checking the data according to the checking mode of virus scanning, the processor16compares the data with virus files in a virus database and acquires the result of the security check of the data. The processor16can determine that the data is abnormal if the result of a security check of the data indicates that the data is consistent with virus files in the virus database, otherwise determining that the data is not abnormal. In one embodiment, when checking the data according to the checking mode of whitelist scanning, the processor16compares the data with lists in a whitelist database and acquires the result of the security check of the data, determining that the data is abnormal if the security check result is that the data is consistent with the lists in the whitelist database, otherwise determining that the data is not abnormal. In one embodiment, when checking the data according to the checking mode of the security authentication, the processor16can determine that the data is abnormal if the data does not pass security authentication, otherwise determining that the data is not abnormal.

In one embodiment, the processor16transmits the calculation of the data or the data received by the input interface12to the output interface14. The output interface14corresponds to a preset output mode and a preset output service. The output interface14sends the data or the calculation results of the data by the second communication unit13according to the preset output mode and the preset output service.

In one embodiment, the preset output mode is a certain way in which the output interface14sends the data. The preset output service is a functional service of the data. In one embodiment, the preset output mode includes a wired output mode and a wireless output mode. The wired output mode includes a PROFIBUS access mode, a MODBUS access mode, a CANBUS access mode, and an ETHERCAT bus access mode. The wireless output mode includes a 4G output mode, a 5G output mode, a WIFI access mode, a LORA access mode, and an NBIOT access mode. In one embodiment, the preset output service includes, but is not limited to, a data collaboration service, a data computing service, a data analysis service, a rapid data model ingenuity service, a deep learning service, a speech recognition service, a semantic understanding service, a speech synthesis service, an image analysis service, an image analysis service, an entertainment service, a game service, a streaming service, and a translation service. In one embodiment, the second communication unit13can be a wireless communication module such as a 4G communication module, a 5G communication module, a WIFI communication module, a LORA communication module or an NBIOT communication module. In another embodiment, the second communication unit13can be a PROFIBUS, a MODBUS, a CANBUS, or an ETHERCAT bus.