CN114697199A - High-robustness data acquisition method and system based on edge calculation - Google Patents
High-robustness data acquisition method and system based on edge calculation Download PDFInfo
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Abstract
The embodiment of the specification provides a high-robustness data acquisition method and system based on edge calculation, which belong to the technical field of intelligent traffic; a plurality of sensors for acquiring traffic information; an edge computing unit cluster comprising a plurality of edge computing units, the edge computing units being configured to determine a computing result based on traffic information acquired by a corresponding at least one sensor, the edge computing unit cluster being further configured to determine a replacement edge computing unit, the replacement failure edge computing unit determining the computing result; the data storage module comprises a local data center and a cloud data center, wherein the local data center is used for acquiring and storing calculation results from the edge calculation units based on the ring network architecture module, the cloud data center is used for acquiring and storing calculation results from the edge calculation units based on a public network or a private network, and the cloud data center has the advantages of ensuring high-reliability and high-robustness operation of intelligent traffic, preventing data loss and timely and effectively applying the data.
Description
Technical Field
The specification relates to the field of intelligent traffic, in particular to a high-robustness data acquisition method and system based on edge calculation.
Background
The current system architecture oriented to the intelligent transportation and vehicle-road cooperation is only applied to test points, no specific requirements are required for the high-reliability and high-robustness operation of the system, and no mature scheme is provided for large-scale and large-range sensor acquisition networks (car networking, internet of things and the like) oriented to the high-robustness requirements.
Therefore, it is necessary to provide a highly robust data acquisition method and system based on edge calculation, which are used to ensure highly reliable and highly robust operation of intelligent traffic, no data loss, and timely and effective application.
Disclosure of Invention
In order to solve the technical problem that a large-scale and large-scale sensor acquisition network (internet of vehicles, internet of things, and the like) oriented to a high robustness requirement in the prior art does not have a mature scheme, one of the embodiments of the present specification provides a high robustness data acquisition system based on edge computing, including: the ring network architecture module is used for providing a local ring network; a plurality of sensors for acquiring traffic information; an edge computing unit cluster, said edge computing unit cluster comprising a plurality of edge computing units, said plurality of edge computing units communicating with each other via said ring network infrastructure module, the edge computing unit corresponds to at least one sensor, and is used for acquiring the traffic information from the corresponding at least one sensor based on the ring network architecture module, the edge calculation unit is further configured to determine a calculation result based on the traffic information acquired by the corresponding at least one sensor, the edge computing unit cluster is further configured to determine a replacement edge computing unit from the plurality of edge computing units if a failed edge computing unit exists, the replacement edge calculation unit is used for replacing the failure edge calculation unit, receiving the traffic information acquired by at least one sensor corresponding to the failure edge calculation unit and determining a calculation result; the data storage module comprises a local data center and a cloud data center, the local data center is used for acquiring and storing the calculation results from the edge calculation units based on the ring network architecture module, and the cloud data center is used for acquiring and storing the calculation results from the edge calculation units based on a public network or a private network.
It can be understood that the system provides a local ring network through a ring network architecture module, so that the redundancy of the network architecture is ensured, and the connection of the whole network is not influenced even if a certain point position in the local ring network is disconnected; when a failure edge computing unit exists in an edge computing unit cluster, a replacement edge computing unit is determined from a plurality of edge computing units, the replacement failure edge computing unit receives traffic information acquired by at least one sensor corresponding to the failure edge computing unit and determines a computing result, data loss is avoided, failure of a single point (certain edge computing unit) can be avoided, data acquired by the sensor cannot be processed, meanwhile, hardware redundancy of the edge computing unit is not needed to be provided, for example, a spare hardware (such as a processor) for determining the computing result is not needed to be arranged in each edge computing unit, and therefore hardware cost of the edge computing unit cluster and power consumption cost in the using process are reduced; by providing the local data center and the cloud data center, storage redundancy can be realized, so that when the local data center or the cloud data center fails, the calculation results of a plurality of edge calculation units can be stored, and data loss is avoided; further, by providing two network elements (i.e., a public network and a private network), network redundancy is provided, and a single point of failure of the network is avoided. In summary, the system can realize data acquisition, calculation and storage of uninterrupted operation, and the whole beneficial effects can include: 1. the system has high robustness (reliability), can quickly and effectively deal with the conditions of network failure, edge computing unit failure and the like which are possibly generated, and automatically and intelligently switches the corresponding edge computing unit of the sensor; 2. the method is green and energy-saving, reduces the hardware requirement of the edge computing unit cluster, and further reduces the power consumption cost of the system; 3. the system saves cost, can independently operate on the built local ring network, avoids repeated network construction, has lower cost, and is mutually isolated from the equipment in the existing network without mutual influence.
In some embodiments, a plurality of the edge computing units communicate with each other through the ring network architecture module, and the plurality of the edge computing units determine whether the failed edge computing unit exists through a communication result.
It can be understood that a plurality of edge computing units communicate with each other through the ring network architecture module, so that the edge computing units can acquire states from each other, and when a certain edge computing unit fails, the state can be found in time. Meanwhile, the ring network architecture module can provide two communication links based on the Ethernet ring redundancy technology, so that when one communication link fails, the other sound communication link is started, and the reliability of network communication between a plurality of edge computing units and corresponding sensors is greatly improved.
In some embodiments, said determining a replacement edge computation unit from said plurality of edge computation units comprises: acquiring transmission delay of at least one sensor corresponding to the failure edge calculation unit and other edge calculation units; determining a calculation force requirement; determining the replacement edge calculation unit from the plurality of edge calculation units based on the propagation delay and the computation force requirement.
It can be understood that, based on the transmission delay, the determined replacement edge calculation unit can calculate the traffic information acquired by the at least one sensor in real time after taking over the at least one sensor corresponding to the failed edge calculation unit, thereby avoiding the calculation result delay and causing the calculation result to be invalid, and based on the calculation force requirement, the determined replacement edge calculation unit can avoid overload operation after taking over the at least one sensor corresponding to the failed edge calculation unit, thereby influencing the calculation efficiency and ensuring the timely validity of the calculation result.
In some embodiments, the computing power requirement is determined based on the at least one sensor to which the failure edge calculation unit corresponds.
It is understood that different failure edge calculation units may have different numbers and types of corresponding sensors, and the determination calculation force requirement of the failure edge calculation unit can be accurately determined based on at least one sensor corresponding to the failure edge calculation unit.
In some embodiments, the edge calculation unit is further configured to: when the local ring network is disconnected or the local data center is offline, caching the calculation result; and when the local ring network is recovered or the local data center is recovered, storing the cached calculation result into the local data center.
It can be understood that, when the local ring network is disconnected or the local data center is offline, the edge computing unit may cache the computing result, so as to avoid the loss of the computing result.
In some embodiments, the edge calculation unit is further configured to: caching the calculation result when the public network is disconnected, the private network is disconnected or the cloud data center is offline; and when the public network, the private network or the cloud data center is recovered, storing the cached calculation result into the cloud data center.
It can be understood that by arranging the two network units, network redundancy is provided, the situation that a single point of a network fails to work, and the edge computing unit cannot store a computing result to the cloud data center is avoided.
In some embodiments, the data storage module is further configured to store the traffic information collected by the plurality of sensors in a distributed manner.
It can be understood that, through distributed storage, any one device does not have the complete traffic information collected by a plurality of sensors, and the complete traffic information is prevented from being stolen.
In some embodiments, the system further comprises a self-matching module, wherein the self-matching module is used for calculating the distance between the edge calculation unit and the sensor, dynamically allocating the calculation force of the edge calculation unit and at least one sensor corresponding to the edge calculation unit, and generating a topological graph; the self-matching module is further used for automatically adjusting the calculation force distribution of each edge calculation unit and at least one sensor corresponding to the edge calculation unit when the edge calculation units and/or the sensors are increased or decreased.
It can be understood that the corresponding relation between each edge computing unit and each sensor can be dynamically adjusted rapidly and accurately through the self-matching module, normal operation of the edge computing units is guaranteed, overload of the edge computing units is avoided, and the corresponding relation between each edge computing unit and each sensor can be rapidly obtained by an operator through generating a topological graph.
In some embodiments, the traffic information includes at least one of image information, video information, and radar point clouds.
It can be understood that the road condition can be accurately acquired through at least one of the image information, the video information and the radar point cloud.
One of the embodiments of the present specification provides a high-robustness data acquisition method based on edge calculation, including: acquiring traffic information through a plurality of sensors; judging whether a failure edge computing unit exists or not, if so, determining a replacement edge computing unit, wherein the replacement edge computing unit is used for replacing the failure edge computing unit and receiving the traffic information acquired by at least one sensor corresponding to the failure edge computing unit; the sensor sends the acquired traffic information to a corresponding edge computing unit through a local ring network; the edge calculation unit determines a calculation result based on the traffic information acquired by the corresponding at least one sensor; the edge computing unit stores the computing result to a local data center through the local ring network; and the edge computing unit stores the computing result to a cloud data center through a public network or a private network.
It can be understood that the method ensures the redundancy of the network architecture through the local ring network, and even if a certain point in the local ring network is disconnected, the connection of the whole network is not affected; when the failure edge calculation unit exists, a replacement edge calculation unit is determined from the plurality of edge calculation units, the replacement failure edge calculation unit receives the traffic information acquired by at least one sensor corresponding to the failure edge calculation unit and determines a calculation result, and the problem that data acquired by the sensor cannot be processed due to failure of a single point (a certain edge calculation unit) can be avoided; by providing the local data center and the cloud data center, storage redundancy can be realized, so that when the local data center or the cloud data center fails, the calculation results of a plurality of edge calculation units can be stored, and data loss is avoided; further, by providing two network elements (i.e., a public network and a private network), network redundancy is provided, and a single point of failure of the network is avoided.
Drawings
The present description will be further explained by way of exemplary embodiments, which will be described in detail by way of the accompanying drawings. These embodiments are not intended to be limiting, and in these embodiments like numerals are used to indicate like structures, wherein:
FIG. 1 is a block diagram of a highly robust data acquisition system based on edge computation according to some embodiments of the present disclosure;
FIG. 2 is a schematic diagram of a topology shown in accordance with some embodiments of the present description;
fig. 3 is a flow diagram illustrating a method for highly robust data acquisition based on edge computation according to some embodiments of the present disclosure.
Detailed Description
In order to more clearly illustrate the technical solutions of the embodiments of the present disclosure, the drawings used in the description of the embodiments will be briefly described below. It is obvious that the drawings in the following description are only examples or embodiments of the present description, and that for a person skilled in the art, the present description can also be applied to other similar scenarios on the basis of these drawings without inventive effort. Unless otherwise apparent from the context, or otherwise indicated, like reference numbers in the figures refer to the same structure or operation.
It should be understood that "system", "apparatus", "unit" and/or "module" as used herein is a method for distinguishing different components, elements, parts, portions or assemblies at different levels. However, other words may be substituted by other expressions if they accomplish the same purpose.
As used in this specification and the appended claims, the terms "a," "an," "the," and/or "the" are not intended to be inclusive in the singular, but rather are intended to be inclusive in the plural, unless the context clearly dictates otherwise. In general, the terms "comprises" and "comprising" merely indicate that steps and elements are included which are explicitly identified, that the steps and elements do not form an exclusive list, and that a method or apparatus may include other steps or elements.
Flow charts are used in this description to illustrate operations performed by a system according to embodiments of the present description. It should be understood that the preceding or following operations are not necessarily performed in the exact order in which they are performed. Rather, the various steps may be processed in reverse order or simultaneously. Meanwhile, other operations may be added to the processes, or a certain step or several steps of operations may be removed from the processes.
Fig. 1 is a schematic diagram of a highly robust data acquisition system based on edge calculation according to some embodiments of the present disclosure.
As shown in fig. 1, a highly robust data acquisition system based on edge computing may include a ring network architecture module, a plurality of sensors (e.g., sensor 1, sensor n, sensor m, sensor x, etc.), an edge computing unit cluster, and a data storage module.
And the ring network architecture module can be used for providing a local ring network. The system utilizes the physical network of the local looped network to establish an independent network for communication between the sensor and the edge computing unit, and is isolated from the previous equipment on the local looped network without influencing the normal work of other hardware equipment on the local looped network.
Sensors may be used to acquire traffic information. In some embodiments, the traffic information may include at least one of image information, video information, and radar point clouds. For example, the traffic information may include image information, video information, and radar point clouds of the lanes. It will be appreciated that the system may include a variety of types of sensors, for example, the sensor may be a camera for acquiring image or video information. For another example, the sensor may be a lidar configured to acquire a radar point cloud.
The edge calculation unit cluster may be a set of a plurality of edge calculation units (e.g., edge calculation unit 1, edge calculation unit n, edge calculation unit m, etc.). The edge computing unit may correspond to the at least one sensor, and the edge computing unit may obtain traffic information from the corresponding at least one sensor based on the ring network architecture module.
In some embodiments, the system may further include a self-matching module, configured to calculate a distance between the edge calculation unit and the sensor, dynamically allocate a calculation power (i.e., a calculation capability) of the edge calculation unit and at least one sensor corresponding to the edge calculation unit, and generate a topological graph, where the topological graph may represent a correspondence relationship between the sensor and the edge calculation unit. For example, fig. 2 is a schematic diagram of a topological diagram according to some embodiments of the present disclosure, and as shown in fig. 2, it can be known that the edge calculation unit 1 corresponds to sensors such as the sensor 1 and the sensor n, and the edge calculation unit n corresponds to sensors such as the sensor m and the sensor x. In some embodiments, the self-matching module may determine an edge calculation unit corresponding to a sensor from a plurality of edge calculation units that are closer to the sensor. For example, the self-matching module may determine an edge calculation unit that meets the calculation force requirement of the sensor from a plurality of edge calculation units that are closer to the sensor, and use the edge calculation unit as the edge calculation unit corresponding to the sensor. For example, for the sensor 1, the distance between the edge calculation unit 1 and the sensor 1 is 1 km, the distance between the edge calculation unit n and the sensor 1 is 2 km, the distance between the edge calculation unit m and the sensor 1 is 1.5 km, the edge calculation unit n does not meet the calculation power requirement of the sensor 1, both the edge calculation unit 1 and the edge calculation unit m meet the calculation power requirement of the sensor 1, and then the self-matching module may use the edge calculation unit 1 with the closer distance as the edge calculation unit corresponding to the sensor 1.
The edge calculation unit may determine a calculation result based on the traffic information acquired by the corresponding at least one sensor. The calculation result may at least include a timestamp, a vehicle number, a location, a vehicle speed, and the like corresponding to the traffic information acquisition time. In some embodiments, the edge calculation unit may perform image recognition on image information or video information acquired by the sensor, thereby acquiring a vehicle number, a position, a vehicle speed, and the like. In some embodiments, the edge calculation unit may identify the lidar acquired by the sensor, and determine the vehicle number, position, speed, etc. by acquiring point cloud data of the vehicle.
In some embodiments, the edge calculation unit may include a processor, and the processor may be configured to determine the calculation result based on traffic information acquired by the corresponding at least one sensor. A processor may include one or more sub-processors (e.g., a single core processing device or a multi-core processing device). Merely by way of example, a processor may include a Central Processing Unit (CPU), an Application Specific Integrated Circuit (ASIC), an Application Specific Instruction Processor (ASIP), a Graphics Processor (GPU), a Physical Processor (PPU), a Digital Signal Processor (DSP), a Field Programmable Gate Array (FPGA), a programmable logic circuit (PLD), a controller, a microcontroller unit, a Reduced Instruction Set Computer (RISC), a microprocessor, and the like or any combination thereof.
The plurality of edge computing units can communicate with each other through a local ring network provided by the ring network architecture module. In some embodiments, whether a failure edge computing unit exists is determined among the plurality of edge computing units through the communication result. For example, when a certain edge computing unit does not send a signal indicating normal operation to other edge computing units for a period of time, it may be determined that the edge computing unit is failed. For another example, when the edge computing unit sends a code representing a device failure to another edge computing unit, it may be determined that the edge computing unit is failed.
When the failure edge calculation unit exists, a replacement edge calculation unit may be determined from the plurality of edge calculation units, and the replacement edge calculation unit is configured to replace the failure edge calculation unit, receive traffic information acquired by at least one sensor corresponding to the failure edge calculation unit, and determine a calculation result.
In some embodiments, determining a replacement edge computation unit from a plurality of edge computation units comprises: acquiring transmission delay of at least one sensor corresponding to the failure edge calculation unit and other edge calculation units; determining a calculation force requirement; a replacement edge calculation unit is determined from the plurality of edge calculation units based on the propagation delay and the computational power requirements. Wherein the calculation force requirement may be determined based on at least one sensor corresponding to the failure edge calculation unit. In some embodiments, an edge calculation unit in which the transmission delay is less than a preset threshold and the calculation power of the edge calculation unit meets the calculation power requirement may be used as a replacement edge calculation unit. For example, when detecting that the edge calculation unit numbered 1 fails, the edge calculation unit numbered 2 detects that the edge calculation unit numbered 1 fails, and determines whether the edge calculation unit numbered 2 meets the calculation force requirement of the sensor corresponding to the edge calculation unit numbered 1, and if so, the nearest edge calculation unit numbered 2 takes over the sensors 1, 2, and 3 corresponding to the edge calculation unit numbered 1. Meanwhile, when the edge computing unit cluster detects that a failure edge computing unit exists in the ring network, a warning is immediately sent to prompt background management personnel to repair or replace the failure edge computing unit in time.
In some embodiments, the self-matching module may be further configured to automatically adjust the computing power distribution of each edge computing unit and the at least one sensor corresponding to the edge computing unit when the edge computing units and/or the sensors are added or subtracted. In some embodiments, after the edge computing unit and the sensor are connected to the system, the self-matching module may generate a data table of the tensor force distribution and the communication delay (including other parameters such as network quality), and the self-matching module may set different weights according to the emphasis of the requirement, for example, if the priority of the delay is high, the weight of the delay may be set to be high. The total computing power of the edge computing unit is generally always greater than the total computing power required by the sensor. Under special conditions, when the total computing power of the normally working edge computing unit is smaller than the total computing power required by the sensors, the system starts a low computing power algorithm mode, the core function requirement is guaranteed, the computing power requirement of each sensor is reduced, and therefore the system can stably run until the system is overhauled or the computing power redundancy state is achieved again after the edge computing units are added.
In some embodiments, the system comprises a device and a network state monitoring and pre-diagnosis module, when abnormal network packet loss occurs or a device fault code is monitored, the system switches a sensor in charge of calculation to another edge calculation unit in charge of calculation before a certain edge calculation unit fails, and simultaneously sends an alarm to arrange personnel to repair or replace the device.
The data storage module can comprise a local data center and a cloud data center. The local data center is used for acquiring and storing calculation results from the edge calculation units based on the ring network architecture module. In some embodiments, when the local ring network is disconnected or the local data center is offline, the edge computing unit may cache the computing result; when the local ring network is restored or the local data center is restored, the edge computing unit may store the cached computing result in the local data center.
The cloud data center is used for acquiring and storing calculation results from the edge calculation units based on a public network or a private network. In some embodiments, the edge computing unit may cache the computation result when the public network is disconnected, the private network is disconnected, or the cloud data center is offline; when the public network, the private network or the cloud data center is recovered, the edge computing unit can store the cached computing result to the cloud data center. In some embodiments, both the primary network element and the standby network element may provide the public network or the private network described above. When the main network unit is normal, the edge computing unit is connected with the cloud data center through a public network or a private network provided by the main network unit; when the main network unit is abnormal, the edge computing unit is connected with the cloud data center through a public network or a private network provided by the standby network unit. By arranging the two network units, network redundancy is provided, single-point failure of the network is avoided, and meanwhile, the system alarms to timely repair or replace the public network or private network connection of the main network unit, so that connection redundancy of the public network or private network is provided. In some embodiments, the public or private network may be any type of wired or wireless network. For example, a public or private network may include a cable network, a wired network, a fiber optic network, a telecommunications network, an intranet, the internet, a Wireless Local Area Network (WLAN), a Public Switched Telephone Network (PSTN), a bluetooth network, a ZigBee network, a Near Field Communication (NFC) network, the like, or any combination thereof.
In some embodiments, the data storage module may also be used to store traffic information collected by multiple sensors in a distributed manner. For example, the data storage module may store the traffic information collected by the plurality of sensors in a distributed manner in a block chain manner. In some embodiments, the edge computing units may participate in distributed storage, and any one of the distributed storage units does not have a complete copy of data, and the complete data may be stored in a physically secure computer room.
FIG. 3 is a flow diagram illustrating a method for highly robust data acquisition based on edge computation according to some embodiments of the present disclosure.
As shown in fig. 3, a highly robust data acquisition method based on edge calculation may include the following steps:
acquiring traffic information through a plurality of sensors;
judging whether a failure edge computing unit exists or not, if so, determining a replacement edge computing unit, wherein the replacement edge computing unit is used for replacing the failure edge computing unit and receiving traffic information acquired by at least one sensor corresponding to the failure edge computing unit;
the sensor sends the acquired traffic information to a corresponding edge computing unit through a local ring network;
the edge calculation unit determines a calculation result based on the traffic information acquired by the corresponding at least one sensor;
the edge computing unit stores the computing result to a local data center through a local ring network;
and the edge computing unit stores the computing result to the cloud data center through a public network or a special network.
It is understood that a highly robust data acquisition method based on edge calculation as shown in fig. 3 can be performed by a highly robust data acquisition system based on edge calculation as described above.
It should be noted that the above description of a highly robust data acquisition method based on edge calculation is for illustration and explanation only, and does not limit the scope of application of the present specification. It will be apparent to those skilled in the art from this disclosure that various modifications and variations can be made in a highly robust data acquisition method based on edge calculation. However, such modifications and variations are still within the scope of the present specification.
Having thus described the basic concept, it will be apparent to those skilled in the art that the foregoing detailed disclosure is to be regarded as illustrative only and not as limiting the present specification. Various modifications, improvements and adaptations to the present description may occur to those skilled in the art, although not explicitly described herein. Such modifications, improvements and adaptations are proposed in the present specification and thus fall within the spirit and scope of the exemplary embodiments of the present specification.
Also, the description uses specific words to describe embodiments of the description. Reference to "one embodiment," "an embodiment," and/or "some embodiments" means a feature, structure, or characteristic described in connection with at least one embodiment of the specification. Therefore, it is emphasized and should be appreciated that two or more references to "an embodiment" or "one embodiment" or "an alternative embodiment" in various places throughout this specification are not necessarily all referring to the same embodiment. Furthermore, certain features, structures, or characteristics may be combined as suitable in one or more embodiments of the specification.
Additionally, the order in which the elements and sequences of the process are recited in the specification, the use of alphanumeric characters or other designations, is not intended to limit the order in which the processes and methods of the specification occur, unless explicitly stated in the claims. While various presently contemplated embodiments of the invention have been discussed in the foregoing disclosure by way of example, it is to be understood that such detail is solely for that purpose and that the appended claims are not limited to the disclosed embodiments, but, on the contrary, are intended to cover all modifications and equivalent arrangements that are within the spirit and scope of the embodiments herein. For example, although the system components described above may be implemented by hardware devices, they may also be implemented by software-only solutions, such as installing the described system on an existing server or mobile device.
Similarly, it should be noted that in the preceding description of embodiments of the present specification, various features are sometimes grouped together in a single embodiment, figure, or description thereof for the purpose of streamlining the disclosure aiding in the understanding of one or more of the embodiments. This method of disclosure, however, is not intended to imply that more features than are expressly recited in a claim. Indeed, the embodiments may be characterized as having less than all of the features of a single disclosed embodiment.
For each patent, patent application publication, and other material, such as articles, books, specifications, publications, documents, etc., cited in this specification, the entire contents of each are hereby incorporated by reference into this specification. Except where the application history document is inconsistent or contrary to the present specification, and except where the application history document is inconsistent or contrary to the present specification, the application history document is not inconsistent or contrary to the present specification, but is to be read in the broadest scope of the present claims (either currently or hereafter added to the present specification). It is to be understood that the descriptions, definitions and/or uses of terms in the accompanying materials of this specification shall control if they are inconsistent or contrary to the descriptions and/or uses of terms in this specification.
Finally, it should be understood that the embodiments described herein are merely illustrative of the principles of the embodiments of the present disclosure. Other variations are also possible within the scope of the present description. Thus, by way of example, and not limitation, alternative configurations of the embodiments of the specification can be considered consistent with the teachings of the specification. Accordingly, the embodiments of the present description are not limited to only those embodiments explicitly described and depicted herein.
Claims (10)
1. A highly robust data acquisition system based on edge calculation, comprising:
the ring network architecture module is used for providing a local ring network;
a plurality of sensors for acquiring traffic information;
an edge computing unit cluster, the edge computing unit cluster comprising a plurality of edge computing units, the plurality of edge computing units communicating with each other via the ring network architecture module, the edge computing unit corresponds to at least one sensor, and is used for acquiring the traffic information from the corresponding at least one sensor based on the ring network architecture module, the edge calculation unit is further configured to determine a calculation result based on the traffic information acquired by the corresponding at least one sensor, the edge computing unit cluster is further configured to determine a replacement edge computing unit from the plurality of edge computing units if a failed edge computing unit exists, the replacement edge calculation unit is used for replacing the failure edge calculation unit, receiving the traffic information acquired by at least one sensor corresponding to the failure edge calculation unit and determining a calculation result;
the data storage module comprises a local data center and a cloud data center, the local data center is used for acquiring and storing the calculation results from the edge calculation units based on the ring network architecture module, and the cloud data center is used for acquiring and storing the calculation results from the edge calculation units based on a public network or a private network.
2. The system of claim 1, wherein a plurality of the edge computing units communicate with each other through the ring network architecture module, and the plurality of the edge computing units determine whether the failed edge computing unit exists according to a communication result.
3. The system of claim 2, wherein the determining a replacement edge calculation unit from the plurality of edge calculation units comprises:
acquiring transmission delay of at least one sensor corresponding to the failure edge calculation unit and other edge calculation units;
determining a calculation force requirement;
determining the replacement edge calculation unit from the plurality of edge calculation units based on the propagation delay and the computation force requirement.
4. The edge-computation-based highly robust data acquisition system of claim 3, wherein the computation force requirement is determined based on the at least one sensor corresponding to the failed edge computation unit.
5. The system of any of claims 1-4, wherein the edge calculation unit is further configured to:
when the local ring network is disconnected or the local data center is offline, caching the calculation result;
and when the local ring network is recovered or the local data center is recovered, storing the cached calculation result into the local data center.
6. The system of claim 5, wherein the edge computing unit is further configured to:
caching the calculation result when the public network is disconnected, the private network is disconnected or the cloud data center is offline;
and when the public network, the private network or the cloud data center is recovered, storing the cached calculation result into the cloud data center.
7. The edge-computing-based highly robust data collection system as claimed in any one of claims 1-4, wherein said data storage module is further configured to distributively store said traffic information collected by said plurality of sensors.
8. The system according to any one of claims 1 to 4, further comprising a self-matching module, wherein the self-matching module is configured to calculate a distance between the edge calculation unit and the sensor, dynamically allocate the calculation power of the edge calculation unit and at least one of the sensors corresponding to the edge calculation unit, and generate a topological graph;
the self-matching module is further used for automatically adjusting the calculation force distribution of each edge calculation unit and at least one sensor corresponding to the edge calculation unit when the edge calculation units and/or the sensors are increased or decreased.
9. The edge-computation-based highly robust data acquisition system as claimed in any one of claims 1-4, wherein the traffic information includes at least one of image information, video information and radar point clouds.
10. A high-robustness data acquisition method based on edge calculation is characterized by comprising the following steps:
acquiring traffic information through a plurality of sensors;
judging whether a failure edge computing unit exists or not, if so, determining a replacement edge computing unit, wherein the replacement edge computing unit is used for replacing the failure edge computing unit and receiving the traffic information acquired by at least one sensor corresponding to the failure edge computing unit;
the sensor sends the acquired traffic information to a corresponding edge computing unit through a local ring network;
the edge calculation unit determines a calculation result based on the traffic information acquired by the corresponding at least one sensor;
the edge computing unit stores the computing result to a local data center through the local ring network;
and the edge computing unit stores the computing result to a cloud data center through a public network or a private network.
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