CN116017613A - Method and device for carrying out soft handoff on internet-connected automobile at multiple edge cloud gateways - Google Patents
Method and device for carrying out soft handoff on internet-connected automobile at multiple edge cloud gateways Download PDFInfo
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Abstract
The invention discloses a method and a device for carrying out soft switching on a plurality of edge cloud gateways by an internet-connected automobile, which relate to the technical field of information and comprise the following steps: after receiving network connection (MQTT/TCP/UDP) of the network-connected automobile, the V2X message gateway proxy acquires the latest position information of the network-connected automobile from a home register of the motor vehicle according to the vehicle identification; determining a target edge cloud gateway corresponding to the current internet-connected automobile according to an AI model of the classifier of the edge cloud; and finally, forwarding the network connection (MQTT/TCP/UDP) to the target edge cloud gateway. By applying the technical scheme, smooth switching of the edge cloud gateway can be realized.
Description
Technical Field
The invention relates to the technical field of information, in particular to a method and a device for carrying out soft handoff on an internet-connected automobile at a plurality of edge cloud gateways.
Background
V2X message communication between the internet-connected automobile and the edge cloud gateway is an important component of the cloud control basic platform, and the low timeliness and high reliability of the V2X message determine the effectiveness of fusion perception, collaborative decision and collaborative control in the cloud control basic platform. In the related scheme of the cloud control basic platform, each edge cloud gateway is responsible for dynamic traffic data acquisition and calculation on roads in the corresponding area, so that real-time and weak real-time cloud control application basic services for enhancing safety and improving energy efficiency can be provided for the internet-connected automobile, but because the internet-connected automobile is in high-speed dynamic driving in most cases, if the internet-connected automobile is always connected with the same edge cloud gateway, the real-time of V2X message communication between the internet-connected automobile and the edge cloud gateway can be reduced.
At present, in the prior art, an on-board unit OBU of a network-connected automobile generally selects a road side device with a stronger signal to send a message according to the strength of a signal of an intersection PC5, and the road side device forwards the message to a designated edge cloud gateway, so that the switching of the edge cloud gateway is realized. However, in the hard switching manner in the prior art, the coupling degree between the on-board unit OBU and the road side device is higher, and once the signal of the intersection PC5 is weak or no signal is generated, the on-board unit OBU and the road side device may not be connected, so that the switching failure of the edge cloud gateway may be caused, that is, the hard switching manner may have a discontinuous switching problem of the edge cloud gateway.
Disclosure of Invention
The invention provides a method and a device for carrying out soft switching on a plurality of edge cloud gateways by a network-connected automobile, which mainly aims at avoiding the cooperation of an on-board unit (OBU) and road side equipment, realizing smooth switching of the edge cloud gateways, and ensuring that the switching process of the OBU is continuous and has no perception.
According to a first aspect of an embodiment of the present invention, a method for performing soft handover on a plurality of edge cloud gateways by an internet-connected vehicle is provided, and the method is applied to a gateway proxy, where the gateway proxy stores geographic coordinate information corresponding to the plurality of edge cloud gateways, and includes:
Receiving a V2X message sent by an internet-connected automobile, wherein the V2X message carries a vehicle identifier of the internet-connected automobile;
acquiring the latest position information of the internet-connected automobile from a corresponding home location register according to the vehicle identifier, wherein the home location register stores basic information of the motor vehicle of the internet-connected automobile;
calculating the distance between the internet-connected automobile and the current edge cloud gateway according to the latest position information and the geographic coordinate information of the edge cloud gateway corresponding to the internet-connected automobile currently;
if the distance is greater than a preset distance, determining a target edge cloud gateway matched with the internet-connected automobile in the other edge cloud gateways according to the latest position information and geographic coordinate information corresponding to the other edge cloud gateways in the plurality of edge cloud gateways;
and forwarding the V2X message to the target edge cloud gateway.
According to a second aspect of the embodiment of the present invention, there is provided a device for performing soft handover on a plurality of edge cloud gateways by an internet-connected vehicle, where the gateway proxy stores geographic coordinate information corresponding to each of the plurality of edge cloud gateways, and the device includes:
the receiving unit is used for receiving a V2X message sent by the internet-connected automobile, wherein the V2X message carries a vehicle identifier of the internet-connected automobile;
The acquisition unit is used for acquiring the latest position information of the internet-connected automobile from a corresponding home location register according to the vehicle identifier, wherein the home location register stores the basic information of the motor vehicle of the internet-connected automobile;
the computing unit is used for computing the distance between the internet-connected automobile and the current edge cloud gateway according to the latest position information and the geographic coordinate information of the edge cloud gateway corresponding to the internet-connected automobile currently;
the determining unit is used for determining target edge cloud gateways matched with the internet-connected automobile in other edge cloud gateways according to the latest position information and geographic coordinate information corresponding to the other edge cloud gateways in the plurality of edge cloud gateways if the distance is larger than a preset distance;
and the forwarding unit is used for forwarding the V2X message to the target edge cloud gateway.
According to a third aspect of embodiments of the present invention, there is provided a computer-readable storage medium having stored thereon a computer program which, when executed by a processor, performs the steps of:
receiving a V2X message sent by an internet-connected automobile, wherein the V2X message carries a vehicle identifier of the internet-connected automobile;
Acquiring the latest position information of the internet-connected automobile from a corresponding home location register according to the vehicle identifier, wherein the home location register stores basic information of the motor vehicle of the internet-connected automobile;
calculating the distance between the internet-connected automobile and the current edge cloud gateway according to the latest position information and the geographic coordinate information of the edge cloud gateway corresponding to the internet-connected automobile currently;
if the distance is greater than a preset distance, determining a target edge cloud gateway matched with the internet-connected automobile in the other edge cloud gateways according to the latest position information and geographic coordinate information corresponding to the other edge cloud gateways in the plurality of edge cloud gateways;
and forwarding the V2X message to the target edge cloud gateway.
According to a fourth aspect of embodiments of the present invention, there is provided an electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, the processor implementing the following steps when executing the program:
receiving a V2X message sent by an internet-connected automobile, wherein the V2X message carries a vehicle identifier of the internet-connected automobile;
acquiring the latest position information of the internet-connected automobile from a corresponding home location register according to the vehicle identifier, wherein the home location register stores basic information of the motor vehicle of the internet-connected automobile;
Calculating the distance between the internet-connected automobile and the current edge cloud gateway according to the latest position information and the geographic coordinate information of the edge cloud gateway corresponding to the internet-connected automobile currently;
if the distance is greater than a preset distance, determining a target edge cloud gateway matched with the internet-connected automobile in the other edge cloud gateways according to the latest position information and geographic coordinate information corresponding to the other edge cloud gateways in the plurality of edge cloud gateways;
and forwarding the V2X message to the target edge cloud gateway.
The innovation points of the embodiment of the invention include:
1. the soft switching method for realizing the edge cloud gateway through the gateway proxy can be used for switching the edge cloud gateway of the internet-connected automobile without depending on the cooperation of OBU hardware and road side equipment, and is one of the innovation points of the embodiment of the invention, namely, the method is continuous and has no perception
2. The AI algorithm is adopted to automatically select the edge cloud gateway closest to the internet-connected automobile so as to ensure low-latency and high-reliability of V2X message communication between the internet-connected automobile and the edge cloud gateway, and the method is one of innovation points of the embodiment of the invention.
3. It is one of the innovative points of the embodiments of the present invention to enable multi-classification of a strong learning classifier consisting of a plurality of weak learning classifiers by employing a softmax function and a cross entropy loss function.
Compared with a hard switching mode in the prior art, the method and the device for carrying out soft switching on a plurality of edge cloud gateways by the internet-connected automobile can receive V2X information sent by the internet-connected automobile, the V2X information carries vehicle identification of the internet-connected automobile, the latest position information of the internet-connected automobile is obtained from a corresponding home location register according to the vehicle identification, meanwhile, the distance between the internet-connected automobile and the current edge cloud gateway is calculated according to the latest position information and geographic coordinate information of the edge cloud gateway corresponding to the internet-connected automobile, and if the distance is larger than the preset distance, a target edge cloud gateway matched with the internet-connected automobile in the other edge cloud gateways is determined according to the latest position information and geographic coordinate information corresponding to other edge cloud gateways in the plurality of edge cloud gateways, and finally the V2X information is forwarded to the target edge cloud gateway. The method and the device have the advantages that the V2X information of the network-connected automobile is forwarded to the edge cloud gateway matched with the network-connected automobile through the configuration gateway proxy, the smooth switching of the edge cloud gateway can be realized without depending on the matching of OBU hardware and road side equipment, the switching process is continuous and is not perceived for the OBU, and meanwhile, the edge cloud gateway matched with the network-connected automobile can be determined through acquiring the latest position information of the network-connected automobile, so that the distance between the network-connected automobile and the edge cloud gateway is nearest, and the low-delay performance and the high-reliability of V2X information communication between the network-connected automobile and the edge cloud gateway can be ensured.
The foregoing description is only an overview of the technical solutions of the present application, and may be implemented according to the content of the specification in order to make the technical means of the present application more clearly understood, and in order to make the above-mentioned and other objects, features and advantages of the present application more clearly understood, the following detailed description of the present application will be given.
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In order to more clearly illustrate the embodiments of the invention or the technical solutions in the prior art, the drawings that are required in the embodiments or the description of the prior art will be briefly described, it being obvious that the drawings in the following description are only some embodiments of the invention, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
Fig. 1 is a schematic flow chart of a method for performing soft handover on a plurality of edge cloud gateways by an internet-connected vehicle according to an embodiment of the present invention;
fig. 2 shows an interaction diagram between a gateway proxy, an OBU and an edge cloud gateway provided by an embodiment of the present invention;
fig. 3 is a schematic flow chart of a method for performing soft handover on a plurality of edge cloud gateways by using another internet-connected vehicle according to an embodiment of the present invention;
Fig. 4 is a schematic flow chart of a method for performing soft handover on a plurality of edge cloud gateways by using another internet-connected vehicle according to an embodiment of the present invention;
fig. 5 is a schematic flow chart of a method for performing soft handover on a plurality of edge cloud gateways by using another internet-connected vehicle according to an embodiment of the present invention;
fig. 6 is a schematic structural diagram of an apparatus for performing soft handover on a plurality of edge cloud gateways by using an internet-connected vehicle according to an embodiment of the present invention;
fig. 7 is a schematic structural diagram of an apparatus for performing soft handover on a plurality of edge cloud gateways by using another internet-connected vehicle according to an embodiment of the present invention;
fig. 8 shows a schematic entity structure of an electronic device according to an embodiment of the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without any inventive effort, are intended to be within the scope of the invention.
It should be noted that the terms "comprising" and "having" and any variations thereof in the embodiments of the present invention and the accompanying drawings are intended to cover non-exclusive inclusions. For example, a process, method, system, article, or apparatus that comprises a list of steps or elements is not limited to only those listed steps or elements but may include other steps or elements not listed or inherent to such process, method, article, or apparatus.
In the hard switching manner in the prior art, the coupling degree between the on-board unit OBU and the road side equipment is higher, and once the signal of the intersection PC5 is weaker or no signal is generated, the on-board unit OBU and the road side equipment may not be connected, so that the switching failure of the edge cloud gateway is caused, that is, the hard switching manner has the problem of discontinuous switching of the edge cloud gateway.
In order to solve the above problem, an embodiment of the present invention provides a method for performing soft handover on a plurality of edge cloud gateways by an internet-connected vehicle, which is applied to a gateway proxy, as shown in fig. 1, and the method includes:
The gateway agent is deployed at the cloud, and the vehicle identifier may specifically be a vehicle ID or a vehicle identification code, and the V2X message mainly includes a BSM message (Basic Safety Message, basic security message), an RSI message (Road Side Information ), an RSM message (Road Safety Message, road side security message), an SPAT message (Signal phase and timing message, traffic light phase and timing message), and a MAP message (MAP message), etc. The BSM message specifically includes speed, steering, braking, double flashing, position, etc., and is mostly used in V2V scenes, i.e., lane change early warning, blind zone early warning, intersection collision early warning, etc.; the RSI message is used for reporting and issuing events, road side RSU integration, platform issuing and is mostly used for V2I scenes, namely road construction, speed limit signs, overspeed early warning, bus lane early warning and the like; the RSM message is mainly used for identifying an event, such as an accident of a vehicle, an abnormality of the vehicle, intrusion of foreign matters and the like, on edge equipment of a butt joint side; the SPAT message is used for guiding the vehicle speed, pushing green waves, and the like, and the road side RSU integrates the annunciator, or the annunciator is transmitted to the platform in a UU mode; the MAP message is used for describing an intersection and a lane, and the corresponding relationship exists between the MAP message and the traffic lights of the intersection.
The embodiment of the invention is mainly suitable for switching the scenes of the edge cloud gateway of the network-connected automobile. The implementation main body of the embodiment of the invention is a device capable of switching the edge cloud gateway of the internet-connected automobile, such as a gateway proxy.
In order to solve the problem of discontinuous switching of the edge cloud gateway, the embodiment of the invention uses the gateway agent deployed at the cloud to forward the V2X message of the internet-connected vehicle to the edge cloud gateway matched with the internet-connected vehicle, and the matching of the on-board unit OBU and the road side equipment is not needed any more, so that smooth switching of the edge cloud gateway is realized, and the switching process is continuous and has no perception to the OBU.
For the embodiment of the invention, when the internet-connected vehicle signs up (opens an account), the OBU on-board unit of the internet-connected vehicle configures sign-on information of a traffic operator, such as a gateway proxy domain name, then the internet-connected vehicle can be connected with a gateway proxy through the gateway proxy domain name, or the internet-connected vehicle cloud Lu Yun gateway proxy can be connected through a specified public ip address, after connection, the gateway proxy can be respectively communicated with the internet-connected vehicle and an edge cloud gateway, as shown in fig. 2, and geographic coordinate information corresponding to a plurality of edge cloud gateways respectively can be stored in the gateway proxy in advance. The proxy implementation scheme of the gateway proxy in the embodiment of the invention is based on that the nginx is used as a reverse proxy, and relates to the lua script language, and the proxy protocol supports the TCP protocol and the MQTT protocol.
Specifically, when the internet-connected vehicle needs to send a V2X message to the edge cloud gateway, the internet-connected vehicle will send the V2X message to the gateway proxy first, so that the gateway proxy forwards the V2X message to the edge cloud gateway that is most adapted to the internet-connected vehicle.
Wherein, the home location register stores the basic information of the motor vehicle of the internet-connected automobile, and the method comprises the following steps: the latest position information of the internet-connected automobile can be longitude and latitude information or map coordinate information.
For the embodiment of the invention, in order to determine the edge cloud gateway which is most matched with the internet-connected automobile, the gateway agent needs to acquire the latest position information of the internet-connected automobile. Specifically, after receiving the V2X message of the gateway automobile, the gateway proxy may send a latest location information acquisition request to a home location register of the internet-connected automobile, where the latest location information acquisition request carries a vehicle ID or a vehicle identification code of the internet-connected automobile, and after receiving the request, the home location register queries, according to the vehicle ID or the vehicle identification code of the internet-connected automobile, the latest location information corresponding to the internet-connected automobile, and feeds back the latest location information to the proxy gateway, so that the proxy gateway determines an edge cloud gateway matched with the internet-connected automobile according to the latest location information of the internet-connected automobile.
And step 103, calculating the distance between the internet-connected automobile and the current edge cloud gateway according to the latest position information and the geographic coordinate information of the edge cloud gateway corresponding to the internet-connected automobile currently.
For the embodiment of the invention, before gateway switching is performed on the internet-connected automobile, an edge cloud gateway may be corresponding at present, and because the internet-connected automobile is always in a dynamic driving state, if the distance between the internet-connected automobile and the currently corresponding edge cloud gateway is greater than a preset distance, the real-time performance of V2X message communication is reduced, and at the moment, gateway switching is required; if the distance between the internet-connected automobile and the currently corresponding edge cloud gateway is smaller than or equal to the preset distance, the real-time performance of V2X message communication is not affected, and gateway switching is not needed at this time. Therefore, before executing the gateway switching flow, the embodiment of the invention needs to calculate the distance between the internet-connected automobile and the currently corresponding edge cloud gateway so as to judge whether to switch the gateway according to the calculated distance, thereby saving the system resources of the gateway proxy.
Specifically, since the gateway proxy has currently acquired the latest position information of the internet-connected vehicle and simultaneously knows the geographic coordinate information of the edge cloud gateway corresponding to the internet-connected vehicle, the linear distance between the gateway proxy and the edge cloud gateway can be calculated, and whether gateway switching is required is determined according to the calculated distance.
It should be noted that, geographic coordinate information of a plurality of edge cloud gateways may be stored in the gateway proxy in advance, or may be obtained by the gateway proxy in real time, which is not particularly limited in the embodiment of the present invention.
And 104, if the distance is greater than a preset distance, determining a target edge cloud gateway matched with the internet-connected automobile in the other edge cloud gateways according to the latest position information and geographic coordinate information corresponding to the other edge cloud gateways in the plurality of edge cloud gateways.
For the embodiment of the invention, if the distance between the internet-connected automobile and the currently corresponding edge cloud gateway is smaller than or equal to the preset distance, the gateway proxy can continuously forward the V2X message to the currently corresponding edge cloud gateway, and the real-time performance of V2X message communication is not affected at this time; if the distance between the internet-connected automobile and the currently corresponding edge cloud gateway is larger than the preset distance, the gateway agent determines a target edge cloud gateway matched with the internet-connected automobile from other edge cloud gateways to switch the gateways.
The embodiment of the invention provides two ways of determining a target edge cloud gateway, one way is through AI model analysis, the other way is through calculation of shortest path distance, in the first embodiment, a specific method for determining the target edge cloud gateway matched with an internet-connected automobile through calculation of shortest path distance is introduced, as shown in fig. 3, the method specifically comprises the following steps: calculating the path distance between the internet-connected automobile and other edge cloud gateways according to the latest position information and the geographic coordinate information corresponding to the other edge cloud gateways; and determining target edge cloud gateways matched with the internet-connected automobile in the other edge cloud gateways according to the path distance between the internet-connected automobile and the other edge cloud gateways. Further, the determining, according to the path distance between the internet-connected vehicle and other edge cloud gateways, a target edge cloud gateway matched with the internet-connected vehicle in the other edge cloud gateways includes: determining a minimum path distance from path distances between the internet-connected automobile and other edge cloud gateways; and determining the edge cloud gateway corresponding to the minimum path distance as a target edge cloud gateway matched with the internet-connected automobile.
For example, the other edge cloud gateways include an edge cloud gateway a, an edge cloud gateway B, and an edge cloud gateway C, then, according to the latest position information of the internet-connected vehicle and the geographic coordinate information corresponding to the edge cloud gateways A, B and C, path distances between the internet-connected vehicle and the edge cloud gateways A, B and C are calculated respectively, then, a minimum path distance is determined from the calculated path distances, and if the path distance between the internet-connected vehicle and the edge cloud gateway C is the minimum, the edge cloud gateway C is determined to be the target edge cloud gateway.
Therefore, the path distance between the target edge cloud gateway and the internet-connected automobile is shortest, and the real-time performance of V2X message communication between the internet-connected automobile and the target edge cloud gateway can be ensured.
For the embodiment of the invention, after determining the target edge cloud gateway with the shortest distance to the internet-connected automobile path, the gateway proxy can forward the V2X message to the target edge cloud gateway.
It should be noted that, in order to ensure the real-time performance of V2X message communication, the cloud gateway proxy needs to pre-determine even the edge cloud gateway that the internet-connected vehicle may need to switch in advance.
According to the method for carrying out soft switching on the plurality of edge cloud gateways by the network-connected automobile, the V2X information of the network-connected automobile is forwarded to the edge cloud gateway matched with the network-connected automobile through the configuration gateway proxy, so that smooth switching of the edge cloud gateway can be realized without depending on matching of OBU hardware and road side equipment, the switching process of the OBU is continuous and not perceived, and meanwhile, the most matched edge cloud gateway with the network-connected automobile can be determined through obtaining the latest position information of the network-connected automobile, so that the distance between the network-connected automobile and the edge cloud gateway is nearest, and low delay and high reliability of V2X information communication between the network-connected automobile and the edge cloud gateway can be ensured.
Further, as a refinement and extension of the foregoing embodiment, the embodiment of the present invention provides another method for performing soft handoff of an internet-connected vehicle at a plurality of edge cloud gateways, as shown in fig. 4, where the method includes:
For the embodiment of the invention, when the internet-connected vehicle needs to send the V2X message to the edge cloud gateway, the internet-connected vehicle can send the V2X message to the gateway proxy so that the gateway proxy forwards the V2X message to the edge cloud gateway which is most suitable for the internet-connected vehicle.
It should be noted that, in the embodiment of the present invention, the gateway proxy is developed by using the openResity and the Lua scripting language, where openResity is a powerful Web application server, and a Web developer can use the Lua scripting language to mobilize various C and Lua modules supported by Nginx, and more importantly, in terms of performance, openResity can quickly construct an ultra-high performance Web application system that is sufficient to be more than 10K for concurrent connection response.
According to the embodiment of the invention, by adopting the technical scheme of combining openResity and Lua, a high-performance and high-intelligent switching process can be realized, and the switching requirements of a large number of network-connected automobiles can be supported.
Step 202, obtaining the latest position information of the internet-connected automobile from a corresponding home location register according to the vehicle identification.
Wherein, the home location register stores the basic information of the motor vehicle of the internet-connected automobile.
For the embodiment of the present invention, in order to determine the target edge cloud gateway matched with the internet-connected vehicle, the latest position information of the internet-connected vehicle needs to be acquired, and the acquiring manner of the latest position information is identical to that of step 102, which is not described herein.
And 203, calculating the distance between the internet-connected automobile and the current edge cloud gateway according to the latest position information and the geographic coordinate information of the edge cloud gateway corresponding to the internet-connected automobile currently.
For the embodiment of the invention, the proxy gateway can calculate the linear distance between the two because the latest position information of the internet-connected automobile is acquired currently and the geographic coordinate information of the edge cloud gateway corresponding to the internet-connected automobile is known at the same time, and whether gateway switching is needed is judged according to the calculated distance.
And 204, if the distance is greater than the preset distance, inputting the latest position information into a strong learning classifier formed by a plurality of weak learning classifiers to classify, and obtaining classification results corresponding to the weak learning classifiers respectively.
The strong learning classifier can be specifically an ABC Boost model, the weak learning classifiers are all neural network models, the last layer of the neural network models is a softmax function, and the neural network models use a cross entropy loss function in the training process.
In the second embodiment, a specific method for determining a target edge cloud gateway matched with an internet-connected automobile through AI model analysis is described, and as shown in fig. 5, the method specifically includes: inputting the latest position information into the strong learning classifier formed by a plurality of weak learning classifiers to classify, so as to obtain probability values of different edge cloud gateways corresponding to the internet-connected vehicles respectively output by the weak learning classifiers; screening a maximum probability value from each probability value for any one of the plurality of weak learning classifiers; and determining a classification result output by any one weak learning classifier according to the edge cloud gateway corresponding to the maximum probability value.
For example, the output of a weak learning classifier in the ABC Boost model is that the probability value of the internet-connected automobile corresponding to the edge cloud gateway a is 0.25, the probability value of the corresponding edge cloud gateway B is 0.15, and the probability value of the corresponding edge cloud gateway C is 0.60, and since the probability value corresponding to the edge cloud gateway C is the largest, it can be determined that the classification result corresponding to the weak learning classifier is the edge cloud gateway C, that is, the internet-connected automobile is adapted to the edge cloud gateway C. Therefore, the classification result output by each weak learning classifier can be obtained in the mode so as to synthesize the classification result of each weak learning classifier and obtain the classification result of the strong learning classifier.
For the embodiment of the invention, before classifying by using the ABC Boost model, the ABC Boost model (strong learning classifier) needs to be trained in advance, and for the process, the method comprises the following steps: collecting geographic coordinate information samples of different internet-connected automobiles and edge cloud gateway domain names corresponding to the geographic coordinate information samples; labeling the geographic coordinate information samples of the different internet-connected vehicles by using the edge cloud gateway domain name to obtain labeled geographic coordinate information samples; and taking the marked geographic coordinate information sample as a sample training set, training the sample training set, and constructing the strong learning classifier.
Further, the training the sample training set to construct the strong learning classifier includes: determining initial weight distribution corresponding to the sample training set; training a first weak learning classifier according to the sample training set and the initial weight distribution corresponding to the sample training set; calculating the cross entropy loss corresponding to the first weak learning classifier according to the classification result output by the first weak learning classifier and the actual classification result corresponding to the sample training set; calculating a weight value corresponding to the first weak learning classifier based on the cross entropy loss; updating the initial weight distribution based on the weight value of the first weak learning classifier to obtain the updated weight distribution of the sample training set; and continuing to train the second weak learning classifier according to the sample training set and the updated weight distribution, repeating the training process of the weak learning classifier until the preset training times are reached, and adding the trained multiple weak learning classifiers according to the corresponding weight values to obtain the strong learning classifier.
Specifically, a sample training set t= { (x) is first constructed 1 ,y 1 ),(x 2 ,y 2 ),…,(x m ,y m ) And determining the training times of the strong learning classifier to be K+1, wherein x m For a geographic coordinate information sample, y m For the corresponding edge cloud gateway domain name, the constructed sample training set is as follows:
(116.397128,39.916521,a1.gw.cicv.com)
(116.397128,39.916522,a1.gw.cicv.com)
(116.397128,39.916523,a1.gw.cicv.com)
(116.397128,39.916524,a2.gw.cicv.com)
(116.397128,39.916525,a3.gw.cicv.com)
(116.397128,39.916526,a4.gw.cicv.com)
…
further, the weight distribution of the initial sample training set is initialized as follows:
D(1)＝(w 11 ,w 12 ,…,w 1m )；w 1i ＝1/m；i＝1,2,…,m
training the first weak learning classifier G using the initial weight distribution 1 (X) and calculating the cross entropy loss e corresponding to the first weak learning classifier 1 Further, based on cross entropy loss e 1 Calculate a first weak learning classifier G 1 Weight value a of (X) 1 Finally based on the first weak learning classifier G 1 Weight value a of (X) 1 Updating the initial weight distribution D (1) to obtain the weight distribution of the updated sample training set, and repeating the process to continuously train the second weak learning classifier G 2 (X)。
Because the existing ABC Boost model mainly carries out two classifications, the loss function is an exponential function, and the sample training set shows that the embodiment of the invention needs to carry out multiple classifications, on the basis of the fact that the weak learning classifier in the implementation of the invention adopts a neural network model, in order to realize multiple classifications, the last layer of each neural network model adopts a softmax function in the training process, the softmax function has the function of normalizing output components corresponding to each category, the sum of the components is 1, and the loss function adopts a cross entropy loss function. Therefore, the improved ABC Boost model can be utilized to realize multi-classification, and the edge cloud gateway matched with the internet-connected automobile is determined through the multi-classification.
G for kth training k (X) whose corresponding weight distribution is D (k) = (w) k1 ,w k2 ,…,w km ) Computing a weak learning classifier G k (X) corresponding Cross entropy loss e k The method comprises the following steps:
wherein p is i Classifier G for weak learning k (X) the output classification result, yi is the actual classification result, and C is the sample label.
Further, a weak learning classifier G is calculated k Weight value a of (X) k The specific formula is as follows:
further, the weight distribution of the sample training set is updated, and the specific formula is as follows:
wherein w is k+1,i Z for updated weight distribution k Is a normalization factor. Further, the updated weight distribution w of the sample training set may be utilized k+1,i Training weak learning classifier G k+1 And (X) finally adding all the weak learning classifiers according to the weight values corresponding to all the trained weak learning classifiers to obtain strong learning classifiers as follows:
therefore, according to the formula, the strong learning classifier can be trained, and the edge cloud gateway domain name which is most suitable for the internet-connected automobile can be determined by using the strong learning classifier.
Step 205, according to the weight values respectively corresponding to the weak learning classifiers, synthesizing the classification results respectively corresponding to the weak learning classifiers to obtain the classification result finally output by the strong learning classifier.
For the embodiment of the invention, after determining the classification result output by each weak learning classifier, the classification result output by the weak learning classifier can be synthesized according to the weight values respectively corresponding to the weak learning classifiers, so as to obtain the classification result output by the strong learning classifier.
And 206, determining a target edge cloud gateway matched with the internet-connected automobile according to the classification result finally output by the strong learning classifier.
For example, in the classification result, 1 represents an edge cloud gateway domain name a1.Gw.cicv.com,2 represents an edge cloud gateway domain name a2.Gw.cicv.com,3 represents an edge cloud gateway domain name a3.Gw.cicv.com, and if the classification result output by the strong learning classifier is 3, the domain name of the target edge cloud gateway is determined to be a3.Gw.cicv.com.
According to the method for carrying out soft switching on the plurality of edge cloud gateways by the network-connected automobile, the V2X information of the network-connected automobile is forwarded to the edge cloud gateway matched with the network-connected automobile through the configuration gateway proxy, and therefore smooth switching of the edge cloud gateway can be achieved without depending on matching of OBU hardware and road side equipment.
Further, as a specific implementation of fig. 1, an embodiment of the present invention provides a device for performing soft handover of an internet-connected vehicle at a plurality of edge cloud gateways, that is, gateway agents, as shown in fig. 6, where the device includes: a receiving unit 31, an acquiring unit 32, a calculating unit 33, a determining unit 34 and a forwarding unit 35.
The receiving unit 31 may be configured to receive a V2X message sent by an internet-connected vehicle, where the V2X message carries a vehicle identifier of the internet-connected vehicle.
The obtaining unit 32 may be configured to obtain, according to the vehicle identifier, the latest location information of the internet-connected vehicle from a corresponding home location register, where the home location register stores basic information of the internet-connected vehicle.
The calculating unit 33 may be configured to calculate a distance between the internet-connected vehicle and the current edge cloud gateway according to the latest location information and geographic coordinate information of the edge cloud gateway corresponding to the internet-connected vehicle currently.
The determining unit 34 may be configured to determine, if the distance is greater than a preset distance, a target edge cloud gateway matched with the internet-connected vehicle in the other edge cloud gateways according to the latest location information and geographic coordinate information corresponding to the other edge cloud gateways in the plurality of edge cloud gateways.
The forwarding unit 35 may be configured to forward the V2X message to the target edge cloud gateway.
In a specific application scenario, the determining unit 34, as shown in fig. 7, includes: a calculation module 341 and a determination module 342.
The calculating module 341 may be configured to calculate a path distance between the internet-connected vehicle and the other edge cloud gateways according to the latest location information and geographic coordinate information corresponding to the other edge cloud gateways.
The determining module 342 may be configured to determine, according to a path distance between the internet-connected vehicle and another edge cloud gateway, a target edge cloud gateway matched with the internet-connected vehicle in the other edge cloud gateway.
Further, the determining module 342 may be specifically configured to determine a minimum path distance from path distances between the internet-connected vehicle and other edge cloud gateways; and determining the edge cloud gateway corresponding to the minimum path distance as a target edge cloud gateway matched with the internet-connected automobile.
In a specific application scenario, the determining unit 34 further includes: a classification module 343 and a synthesis module 344.
The classification module 343 may be configured to synthesize classification results corresponding to the weak learning classifiers according to the weight values corresponding to the weak learning classifiers, so as to obtain a classification result finally output by the strong learning classifier.
The integration module 344 may be configured to determine, according to the classification result finally output by the strong learning classifier, a target edge cloud gateway that matches the online automobile.
Further, the integrating module 344 may be specifically configured to input the latest position information into the strong learning classifier formed by the weak learning classifiers to classify, so as to obtain probability values of different edge cloud gateways corresponding to the internet-connected vehicles respectively output by the weak learning classifiers; screening a maximum probability value from each probability value for any one of the plurality of weak learning classifiers; and determining a classification result output by any one weak learning classifier according to the edge cloud gateway corresponding to the maximum probability value.
In a specific application scenario, the apparatus further includes: a collection unit 36, a labeling unit 37 and a training unit 38.
The collecting unit 36 may be configured to collect geographic coordinate information samples of different internet-connected vehicles, and edge cloud gateway domain names corresponding to the geographic coordinate information samples.
The labeling unit 37 may be configured to label the geographic coordinate information samples of the different internet-connected vehicles by using the edge cloud gateway domain name, to obtain labeled geographic coordinate information samples.
The training unit 38 may be configured to use the labeled geographic coordinate information sample as a sample training set, and train the sample training set to construct the strong learning classifier.
Further, the training unit 38 may be specifically configured to determine an initial weight distribution corresponding to the sample training set; training a first weak learning classifier according to the sample training set and the initial weight distribution corresponding to the sample training set; calculating the cross entropy loss corresponding to the first weak learning classifier according to the classification result output by the first weak learning classifier and the actual classification result corresponding to the sample training set; calculating a weight value corresponding to the first weak learning classifier based on the cross entropy loss; updating the initial weight distribution based on the weight value of the first weak learning classifier to obtain the updated weight distribution of the sample training set; and continuing to train the second weak learning classifier according to the sample training set and the updated weight distribution, repeating the training process of the weak learning classifier until the preset training times are reached, and adding the trained multiple weak learning classifiers according to the corresponding weight values to obtain the strong learning classifier.
It should be noted that, for other corresponding descriptions of each functional module related to the gateway proxy provided by the embodiment of the present invention, reference may be made to corresponding descriptions of the method shown in fig. 1, which are not repeated herein.
Based on the above method as shown in fig. 1, correspondingly, the embodiment of the present invention further provides a computer readable storage medium, on which a computer program is stored, which when being executed by a processor, implements the following steps: receiving a V2X message sent by an internet-connected automobile, wherein the V2X message carries a vehicle identifier of the internet-connected automobile; acquiring the latest position information of the internet-connected automobile from a corresponding home location register according to the vehicle identifier, wherein the home location register stores basic information of the motor vehicle of the internet-connected automobile; calculating the distance between the internet-connected automobile and the current edge cloud gateway according to the latest position information and the geographic coordinate information of the edge cloud gateway corresponding to the internet-connected automobile currently; if the distance is greater than a preset distance, determining a target edge cloud gateway matched with the internet-connected automobile in the other edge cloud gateways according to the latest position information and geographic coordinate information corresponding to the other edge cloud gateways in the plurality of edge cloud gateways; and forwarding the V2X message to the target edge cloud gateway.
Based on the embodiment of the method shown in fig. 1 and the device shown in fig. 6, the embodiment of the invention further provides a physical structure diagram of an electronic device, as shown in fig. 8, where the electronic device includes: a processor 41, a memory 42, and a computer program stored on the memory 42 and executable on the processor, wherein the memory 42 and the processor 41 are both arranged on a bus 43, the processor 41 performing the following steps when said program is executed: receiving a V2X message sent by an internet-connected automobile, wherein the V2X message carries a vehicle identifier of the internet-connected automobile; acquiring the latest position information of the internet-connected automobile from a corresponding home location register according to the vehicle identifier, wherein the home location register stores basic information of the motor vehicle of the internet-connected automobile; calculating the distance between the internet-connected automobile and the current edge cloud gateway according to the latest position information and the geographic coordinate information of the edge cloud gateway corresponding to the internet-connected automobile currently; if the distance is greater than a preset distance, determining a target edge cloud gateway matched with the internet-connected automobile in the other edge cloud gateways according to the latest position information and geographic coordinate information corresponding to the other edge cloud gateways in the plurality of edge cloud gateways; and forwarding the V2X message to the target edge cloud gateway.
According to the embodiment of the invention, the V2X message of the internet-connected automobile is forwarded to the edge cloud gateway matched with the internet-connected automobile by configuring the gateway proxy, so that the smooth switching of the edge cloud gateway can be realized without depending on the cooperation of OBU hardware and road side equipment, the switching process is continuous and is not perceived for the OBU, and meanwhile, the most matched edge cloud gateway of the internet-connected automobile can be determined by acquiring the latest position information of the internet-connected automobile, so that the distance between the internet-connected automobile and the edge cloud gateway is nearest, and the low-delay performance and the high-reliability of V2X message communication of the internet-connected automobile and the edge cloud gateway can be ensured.
Those of ordinary skill in the art will appreciate that: the drawing is a schematic diagram of one embodiment and the modules or flows in the drawing are not necessarily required to practice the invention.
Those of ordinary skill in the art will appreciate that: the modules in the apparatus of the embodiments may be distributed in the apparatus of the embodiments according to the description of the embodiments, or may be located in one or more apparatuses different from the present embodiments with corresponding changes. The modules of the above embodiments may be combined into one module, or may be further split into a plurality of sub-modules.
Finally, it should be noted that: the above embodiments are only for illustrating the technical solution of the present invention, and are not limiting; although the invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some of the technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit and scope of the technical solutions of the embodiments of the present invention.
Claims (10)
1. The method for carrying out soft handoff on a plurality of edge cloud gateways by an internet-connected automobile is characterized by being applied to a gateway proxy, wherein the gateway proxy stores geographic coordinate information corresponding to the plurality of edge cloud gateways respectively and comprises the following steps:
receiving a V2X message sent by an internet-connected automobile, wherein the V2X message carries a vehicle identifier of the internet-connected automobile;
acquiring the latest position information of the internet-connected automobile from a corresponding home location register according to the vehicle identifier, wherein the home location register stores basic information of the motor vehicle of the internet-connected automobile;
calculating the distance between the internet-connected automobile and the current edge cloud gateway according to the latest position information and the geographic coordinate information of the edge cloud gateway corresponding to the internet-connected automobile currently;
If the distance is greater than a preset distance, determining a target edge cloud gateway matched with the internet-connected automobile in the other edge cloud gateways according to the latest position information and geographic coordinate information corresponding to the other edge cloud gateways in the plurality of edge cloud gateways;
and forwarding the V2X message to the target edge cloud gateway.
2. The method of claim 1, wherein the determining, according to the latest location information and geographic coordinate information corresponding to other edge cloud gateways in the plurality of edge cloud gateways, a target edge cloud gateway that matches the internet-connected vehicle in the other edge cloud gateways includes:
calculating the path distance between the internet-connected automobile and other edge cloud gateways according to the latest position information and the geographic coordinate information corresponding to the other edge cloud gateways;
and determining target edge cloud gateways matched with the internet-connected automobile in the other edge cloud gateways according to the path distance between the internet-connected automobile and the other edge cloud gateways.
3. The method according to claim 2, wherein the determining a target edge cloud gateway of the other edge cloud gateways that matches the internet-connected vehicle according to a path distance between the internet-connected vehicle and the other edge cloud gateway comprises:
Determining a minimum path distance from path distances between the internet-connected automobile and other edge cloud gateways;
and determining the edge cloud gateway corresponding to the minimum path distance as a target edge cloud gateway matched with the internet-connected automobile.
4. The method of claim 1, wherein the determining, according to the latest location information and geographic coordinate information corresponding to other edge cloud gateways in the plurality of edge cloud gateways, a target edge cloud gateway that matches the internet-connected vehicle in the other edge cloud gateways includes:
inputting the latest position information into a strong learning classifier formed by a plurality of weak learning classifiers to classify, and obtaining classification results respectively corresponding to the plurality of weak learning classifiers, wherein the plurality of weak learning classifiers are all neural network models, the last layer of the neural network models is a softmax function, and the neural network models use a cross entropy loss function in the training process;
according to the weight values respectively corresponding to the weak learning classifiers, synthesizing classification results respectively corresponding to the weak learning classifiers to obtain a classification result finally output by the strong learning classifier;
And determining a target edge cloud gateway matched with the internet-connected automobile according to the classification result finally output by the strong learning classifier.
5. The method of claim 4, wherein inputting the latest position information into a strong learning classifier composed of a plurality of weak learning classifiers for classification, to obtain classification results respectively corresponding to the plurality of weak learning classifiers, comprises:
inputting the latest position information into the strong learning classifier formed by a plurality of weak learning classifiers to classify, so as to obtain probability values of different edge cloud gateways corresponding to the internet-connected vehicles respectively output by the weak learning classifiers;
screening a maximum probability value from each probability value for any one of the plurality of weak learning classifiers;
and determining a classification result output by any one weak learning classifier according to the edge cloud gateway corresponding to the maximum probability value.
6. The method according to claim 4, wherein the method further comprises:
collecting geographic coordinate information samples of different internet-connected automobiles and edge cloud gateway domain names corresponding to the geographic coordinate information samples;
Labeling the geographic coordinate information samples of the different internet-connected vehicles by using the edge cloud gateway domain name to obtain labeled geographic coordinate information samples;
and taking the marked geographic coordinate information sample as a sample training set, training the sample training set, and constructing the strong learning classifier.
7. The method of claim 6, wherein training the sample training set to construct the strong learning classifier comprises:
determining initial weight distribution corresponding to the sample training set;
training a first weak learning classifier according to the sample training set and the initial weight distribution corresponding to the sample training set;
calculating the cross entropy loss corresponding to the first weak learning classifier according to the classification result output by the first weak learning classifier and the actual classification result corresponding to the sample training set;
calculating a weight value corresponding to the first weak learning classifier based on the cross entropy loss;
updating the initial weight distribution based on the weight value of the first weak learning classifier to obtain the updated weight distribution of the sample training set;
and continuing to train the second weak learning classifier according to the sample training set and the updated weight distribution, repeating the training process of the weak learning classifier until the preset training times are reached, and adding the trained multiple weak learning classifiers according to the corresponding weight values to obtain the strong learning classifier.
8. The device for carrying out soft switching on a plurality of edge cloud gateways by an internet-connected automobile is characterized in that the gateway proxy stores geographic coordinate information corresponding to the plurality of edge cloud gateways respectively and comprises:
the receiving unit is used for receiving a V2X message sent by the internet-connected automobile, wherein the V2X message carries a vehicle identifier of the internet-connected automobile;
the acquisition unit is used for acquiring the latest position information of the internet-connected automobile from a corresponding home location register according to the vehicle identifier, wherein the home location register stores the basic information of the motor vehicle of the internet-connected automobile;
the computing unit is used for computing the distance between the internet-connected automobile and the current edge cloud gateway according to the latest position information and the geographic coordinate information of the edge cloud gateway corresponding to the internet-connected automobile currently;
the determining unit is used for determining target edge cloud gateways matched with the internet-connected automobile in other edge cloud gateways according to the latest position information and geographic coordinate information corresponding to the other edge cloud gateways in the plurality of edge cloud gateways if the distance is larger than a preset distance;
and the forwarding unit is used for forwarding the V2X message to the target edge cloud gateway.
9. A computer readable storage medium, on which a computer program is stored, characterized in that the computer program, when being executed by a processor, implements the steps of the method of any of claims 1 to 7.
10. An electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, characterized in that the computer program when executed by the processor implements the steps of the method of any one of claims 1 to 7.
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| US20190159106A1 (en) * | 2016-07-29 | 2019-05-23 | Huawei Technologies Co., Ltd. | Anchor gateway switching method, apparatus, and system |
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