CN108667922A - A kind of car networking data cloud method for pushing for trusting optimization based on Liapunov - Google Patents
A kind of car networking data cloud method for pushing for trusting optimization based on Liapunov Download PDFInfo
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- H—ELECTRICITY
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- H04W4/40—Services specially adapted for particular environments, situations or purposes for vehicles, e.g. vehicle-to-pedestrians [V2P]
- H04W4/44—Services specially adapted for particular environments, situations or purposes for vehicles, e.g. vehicle-to-pedestrians [V2P] for communication between vehicles and infrastructures, e.g. vehicle-to-cloud [V2C] or vehicle-to-home [V2H]
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Abstract
The invention discloses a kind of car networking data cloud method for pushing for trusting optimization based on Liapunov, before time quantum, are determined from the user that needed cloud pushes and trust user, the additional trust factor before the data packet for trusting user；In current time unit, the data packet for meeting the user of Liapunov drift penalty term minimum is selected to be pushed to cloud server from the user that needed cloud pushes；It calculates best service in current time unit and pushes number；Number, which is pushed, according to best service judges whether trust user is successful to cloud server propelling data in the time quantum, if unsuccessful, then update trust-factor, it recycles successively, until trusting user in the time quantum to the success of cloud server propelling data, cancels the label to trusting user, update the data backlog, into future time unit, until data packet pushes successfully in all time quantums.The present invention optimizes progress car networking data cloud push using Liapunov reduces the interference of energy consumption and reduction channel oneself state when user is to terminal transmission data.
Description
Technical Field
The invention relates to a vehicle networking data cloud pushing method based on Lyapunov trust optimization.
Background
With the development of the 5G technology, the internet of everything is more and more realized, the internet of vehicles technology is a topic of research of people, and the cloud pushing in the internet of vehicles is a product of the integration of cloud computing and mobile internet of vehicles, and has higher requirements on accuracy and real-time performance. Due to the fact that the car networking scene is complex and various interferences exist, the traditional mobile cloud pushing strategy is limited to be applied in the car networking scene. Therefore, how to perform cloud pushing on user data in a car networking scene in the car networking scene still remains an important technical problem to be solved urgently.
Disclosure of Invention
In order to overcome the defects of high energy consumption, low real-time performance and the like of a traditional mobile cloud service pushing strategy, the invention provides a vehicle networking data cloud pushing method based on Lyapunov trust optimization, the method combining trust transmission and Lyapunov optimization is applied to a vehicle networking scene, the vehicle networking data cloud pushing is carried out by utilizing the Lyapunov optimization, an optimal channel for data pushing is selected according to a channel state and a trust mark, a Lyapunov trust function is defined, and energy consumption and interference of the channel self state are reduced when a user transmits data to a terminal.
The technical scheme adopted by the invention is as follows:
a Internet of vehicles data cloud pushing method based on Lyapunov trust optimization comprises the following steps:
step 1: determining a trust user from all users to be pushed by the cloud, and adding a trust factor in front of a data packet of the trust user;
step 2: in the current time unit, selecting a data packet of a user which meets the smallest Lyapunov drift-penalty term from all users to be pushed to a cloud server for pushing;
and step 3: calculating the optimal service push number in the current time unit;
and 4, step 4: judging whether the trust user successfully pushes the data to the cloud server in the time unit according to the optimal service pushing number, if not, updating the trust factor and the data backlog, returning to the step 2 until the trust user successfully pushes the data to the cloud server in the time unit, canceling the mark of the trust user, updating the data backlog, entering the next time unit, and repeating the steps 1-4 until the data packet in all the time units is successfully pushed.
In the foregoing method for pushing data cloud in the internet of vehicles based on lyapunov trust optimization, in step 1, the method for determining a trust user is as follows:
the proxy server sends an inquiry signal to the user terminal;
the user terminal sends a response signal after receiving the inquiry signal;
and the proxy server marks the user terminal corresponding to the received response signal as a trusted user.
In the aforementioned method for pushing data cloud in the internet of vehicles based on lyapunov trust optimization, in step 2, the method for obtaining the lyapunov drift-penalty term includes:
establishing a relational expression of data backlog of a user in a corresponding channel and total user energy consumption in a time unit;
introducing a trust factor, and establishing a Lyapunov trust function by combining a relational expression of data backlog;
and introducing penalty functions at two ends of the expression of the Lyapunov trust function to obtain a Lyapunov drift-penalty item in the time unit.
According to the Internet of vehicles data cloud pushing method based on Lyapunov trust optimization, the step of establishing the relational expression of data backlog quantity of the user in the corresponding channel and total user energy consumption in the time unit comprises the following steps:
the traffic volume, the data backlog volume and the channel state of a given user on a channel in the current time unit are given;
calculating the transmission rate of the user in the channel and the time slot of the channel according to the channel state, and multiplying the transmission rate of the channel and the time slot to obtain the service rate of the channel;
establishing a data backlog quantity relational expression of the user in the corresponding Internet of vehicles channel based on the traffic quantity, the data backlog quantity and the service rate of the channel of the user in the time unit;
and given the data transmission rate of the channel in the time unit, multiplying and summing the data transmission rate of the channel in the time unit and the time slot of the channel to obtain the total energy consumption relational expression of the user on the channel.
The Internet of vehicles data cloud pushing method based on Lyapunov trust optimization comprises the following steps:
relational expression L based on data backlog quantityk(Ti+1), establishing a Lyapunov function C1(Ti)；
Introducing a trust factor X (j), and combining the trust factor with the data backlog quantity relational expression to obtain a new data backlog quantity relational expression
Relational expression based on new data backlogEstablishing a new Lyapunov function C (T)i)；
Logarithm of the Lyapunov function C (T)i) Computing to obtain Lyapunov letter of trustNumber deltaT(Ti)。
In the aforementioned method for pushing data cloud in the internet of vehicles based on lyapunov trust optimization, in step 1, an expression of the lyapunov drift-penalty term is as follows:
where Y is the control threshold, YE { E (T)i)|Lj(Ti) Is a penalty function related to the control threshold Y;Ck(Ti) In time unit TiThe backlog of trust data of the inner user k; vk(Ti) As a unit of time TiA service rate of the inner channel; c (T)i) Is a new lyapunov function.
In the aforementioned method for pushing data in the internet of vehicles based on lyapunov trust optimization, in step 3, the step of judging whether the trust user successfully pushes data to the cloud server in the time unit according to the optimal service push number includes:
if the optimal service pushing number in the time unit is the same as the data packet number of the trust user, the trust user successfully pushes data to the cloud server, and the mark of the trust user is cancelled; otherwise, if the data is unsuccessful, the trust factor and the data backlog are updated.
The internet of vehicles data cloud pushing method based on Lyapunov trust optimization as described above, wherein in step 3, the calculation formula of the optimal service pushing number in the current time unit is as follows:
in the formula, nbestIs time of dayUnit TiThe number of the best service push; x (n) is the amount of trusted packet data; ck(Ti) In time unit TiThe backlog of trust data of the inner user k; thetak(T-i) the amount of data arriving on the channel is subject to averagingPoisson distribution of (a);
YE(Ti) The penalty is expected for this time cell portion, α is the mean of the poisson distribution, and N is the number of time cells.
A Lyapunov trust optimization-based vehicle networking data cloud pushing device, comprising a proxy server including 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, including:
determining a trust user from all users to be pushed by the cloud, and adding a trust factor in front of a data packet of the trust user;
in the current time unit, selecting a data packet of a user which meets the smallest Lyapunov drift-penalty term from all users to be pushed to a cloud server for pushing;
calculating the optimal service push number in the current time unit;
and judging whether the trust user successfully pushes data to the cloud server in the time unit according to the optimal service pushing number, if not, updating the trust factor, and circulating in sequence until the trust user successfully pushes data to the cloud server in the time unit, canceling the mark of the trust user, updating the data backlog, entering the next time unit, and until the data packet pushing in all the time units is successful.
Compared with the prior art, the invention has the beneficial effects that:
(1) according to the invention, a Lyapunov function is introduced in a complex car networking scene, the optimal cloud pushing service number of a certain time unit is controlled through a Lyapunov drift-punishment item, the optimal user is selected for carrying out cloud pushing, and the energy consumption for pushing a certain number of services in a certain time by a car networking system is effectively reduced;
(2) according to the cloud pushing method, the trust function is provided on the basis of the Lyapunov function, and some users with high real-time requirements and unstable channel states can carry out self-adaptive pushing in time through the proxy server, so that the real-time performance of cloud pushing of the Internet of vehicles is effectively improved, and the cloud pushing method is better suitable for the complex cloud pushing characteristics of the Internet of vehicles;
(3) the method disclosed by the invention has the advantages that the Lyapunov function is subjected to logarithm, the interference effect of the transmission noise of the channel is effectively reduced, the sensitivity of the noise is reduced, and the accuracy of cloud pushing of the user is improved, so that the method is applied to a complex Internet of vehicles cloud pushing scene.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this application, illustrate exemplary embodiments of the application and, together with the description, serve to explain the application and are not intended to limit the application.
FIG. 1 is a flow chart of a Lyapunov trust optimization-based vehicle networking data cloud pushing method disclosed by the embodiment of the invention;
FIG. 2 is a graph of trusted user packets as a function of push times;
FIG. 3 is a diagram of a Lyapunov trust optimization-based data cloud pushing scenario for the Internet of vehicles, disclosed by the embodiment of the invention.
Detailed Description
The invention is further described with reference to the following figures and examples.
It should be noted that the following detailed description is exemplary and is intended to provide further explanation of the disclosure. Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs.
It is noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of example embodiments in accordance with the present application. As used herein, the singular forms "a", "an" and "the" are intended to include the plural forms as well, and it should be understood that when the terms "comprises" and/or "comprising" are used in this specification, they specify the presence of stated features, steps, operations, devices, components, and/or combinations thereof, unless the context clearly indicates otherwise.
As shown in fig. 1, an embodiment of the present invention provides a vehicle networking data cloud pushing method based on lyapunov trust optimization, including the following steps:
step 1: in time unit TiThe method comprises the steps that firstly, a vehicle networking proxy server determines a trust user from all users to be pushed by the cloud, and a trust factor is added in front of a data packet of the trust user;
step 2: in time unit TiThe Internet of vehicles proxy server selects a data packet of a user which meets the smallest Lyapunov drift-penalty term from all users to be pushed to the cloud server;
and step 3: the vehicle networking proxy server calculates the current time unit TiThe internal optimal service pushing number is sent to a vehicle-mounted user terminal in the vehicle networking system;
and 4, step 4: the Internet of vehicles proxy server judges whether the trust user successfully pushes data to the cloud server in the time unit according to the optimal service pushing number, if not, the trust factor and the data backlog are updated, the step 2 is returned until the trust user successfully pushes data to the cloud server in the time unit, the mark for the trust user is cancelled, and the data is updatedThe backlog amount is entered into the next time unit Ti+1；
And 5: and repeating the steps 1-4 until the data packet is successfully pushed in all the time units.
In order to enable those skilled in the art to better understand the present invention, a more detailed embodiment is listed below, and an embodiment of the present invention provides a vehicle networking data cloud pushing method based on lyapunov trust optimization, the method including the following steps:
1. establishing a Lyapunov trust optimization control strategy, wherein the strategy is realized by the following steps:
step 101: and obtaining a relational expression of data backlog and total user energy consumption by giving time slots, rates and the like of the Internet of vehicles cloud push channel.
The specific implementation process of step 101 is as follows:
step 1011: given user in time unit TiThe traffic of the inter-arrival channel is nkθ(Ti) Wherein n iskThe total amount of service subscribed to per unit of time for a subscriber, θ (T)i) The amount of data arriving at the channel follows a poisson distribution with an average value of α.
Step 1012: given Lk(Ti) For the user in time unit TiData backlog on the upper channel and user k in time unit TiThe time channel state is vector rk(Ti)＝(r1(Ti),r2(Ti),...,rn(Ti))。
Step 1013: calculating the transmission rate v of the user k in the channel according to the channel state of the userk(Ti) The channel can adaptively determine that the number of time slots for transmitting data in the current time interval tau is omegak(Ti) Then the service rate of the channel is Vk(Ti)＝ωk(Ti)uk(Ti) And forming a vector:
V(Ti)＝(V1(Ti),V2(Ti),.....,VN(Ti) And, satisfy
Step 1014: the dynamic relationship of the data backlog quantity of the user k in the corresponding vehicle networking channel system can be obtained by the first three steps as follows:
Lk(Ti+1)＝max[Lk(Ti)-Vk(Ti)，0]+nk(Ti)
wherein L isk(Ti) For the user in time unit TiData backlog on the upper channel; n isk(Ti) User is in time unit TiTraffic of an inter-arrival channel; vk(Ti) Is the service rate of the channel;
the stable condition of the vehicle networking channel system is as follows:
step 1015: suppose that in time unit TiThe data transmission rate of the inner user channel is mu (T)i) Then the total energy consumption of the user is
Wherein, the parameter tau is the time slot length;
step 102: through the deduced Lyapunov function, a trust function is defined, channel interference is reduced, and the situation that data cannot be uploaded for many times is prevented.
The specific implementation manner of step 102 is as follows:
step 1021: obtaining a Lyapunov function based on the Internet of vehicles cloud push strategy on the basis of the data backlog quantity relational expression obtained in the step 101:
step 1022: due to the fact that timeliness is needed for uploading vehicle user data to a cloud terminal in a vehicle networking scene, when an optimal transmission channel is selected by Lyapunov optimization, some users with high requirements on instantaneity and unstable channel states cannot push timely, a trust factor is definedWhere j ∈ (1, 2.... j). In a car networking scenario, it is assumed that a data packet only containing a trust factor x (j) is added when user data with real-time performance is pushed, and meanwhile, the user becomes a trusted user, that is, a system backlog formula becomes:
the lyapunov function obtained at step 1021 becomes:
step 1023: and combining the changed new Lyapunov function, and giving a Lyapunov trust function:
ΔT(Ti)＝E{ln(C(Ti+1)-C(Ti))|Lj(Ti+1)}
wherein,the trust function firstly carries out logarithm operation on the Lyapunov function and utilizes the logarithmThe logarithmic growth characteristic of the function reduces noise interference of complex channels in the car networking scene, and reduces the influence of noise. Meanwhile, the real-time cloud pushing of the user is controlled by the trust factor as follows:
in a car networking scene, if a certain user requires real-time cloud pushing on data, the user adds a data packet only containing a trust factor X (j) to the data to become a trusted user of a car networking cloud agent. If the cloud push request of a trusted user is not the best push due to poor channel state when transmitted in the first time unit, the trust factor x (j) in the data packet is increased to 1 and also increased, as shown in fig. 2. And adding one to the next in sequence each time when the push is not carried out until the push can become the optimal push.
The trust factor utilizes the characteristic that the logarithmic function has obvious variation amplitude in the range of 0< x <1, and increases the probability of the trust user being selected by the channel by using the mode of taking e as the reciprocal of the base power function and squaring the times, so that the vehicle networking agency can effectively push some users with high real-time requirements and unstable channel states in time when selecting the optimal transmission channel.
Step 103: for any time unit TiIntroducing a penalty function YE { E (T) related to a control threshold value Y into two sections of an expression of a Lyapunov trust functioni)|Lj(Ti) And obtaining a Lyapunov transfer-penalty item.
Combining the formula of trust queue backlog and formula (max [ X,0 ]])2≤x2Obtaining:
and combining it with the lyapunov function and the trust function in step 102 to obtain:
because the amount of data and the amount of subscribed traffic per time unit is bounded, i.e. thetak(Ti)≤θmax，0≤nk≤nmaxThen the above formula can be written as
Order toAnd VE { E (T) is added on both sides of the equal sign of the above formulai) It can be obtained that, in the scenario of internet of vehicles, given any controllable threshold V is greater than or equal to 0, at any service rate, number of subscribed services and data volume, there are:
wherein,y is a control threshold, YE { E (T)i)|Lj(Ti) Is a penalty function related to the control threshold Y;Ck(Ti) Is the present time unit TiThe backlog of trust data of the user k in the interior vehicle network; vk(Ti) As a unit of time TiA service rate of the inner channel; c (T)i) Is a new lyapunov function.
Will be provided withAs a lyapunov transfer-penalty term.
In an Internet of vehicles scenario, energy consumption is reduced by minimizing the right side of the equation of equation (1), while selecting the minimum amount based on the differential transmission decision of the channel, if and only if
The channel delivers the data.
In order to avoid the problem that the energy consumption of cloud pushing is increased due to overlarge channel data backlog in the scene of Internet of vehicles, a reasonable value range is assumed, namely, when the right side of an equation is in a right side
When the right side of the equation is minimum, the optimal cloud pushing service number of the vehicle networking proxy server in the current time unit is
In the formula, nbestAs a unit of time TiThe number of the best service push; n isbestAs a unit of time TiThe number of the best service push; x (n) is the amount of trusted packet data; ck(Ti) In time unit TiThe backlog of trust data of the user k in the interior vehicle network; thetak(T-i) the amount of data arriving on the channel is subject to averagingPoisson distribution of (a); YE (T)i) The penalty is expected for this time cell portion, α is the mean of the poisson distribution, and N is the number of time cells.
The invention constructs the Lyapunov trust function and the drift-penalty item, controls the optimal cloud pushing service number of a certain time unit through the Lyapunov drift-penalty item, selects the optimal user to carry out cloud pushing and reduces the energy consumption of cloud pushing.
2. The Internet of vehicles data cloud pushing method based on the Lyapunov trust optimization control strategy comprises the implementation steps of:
step 201: at each time unit TiThe method comprises the steps that firstly, a vehicle-mounted user terminal sends data to a vehicle networking proxy server according to a channel state, the vehicle networking proxy server sends inquiry signals of 'real-time performance' to all vehicle-mounted user terminals, the vehicle-mounted user terminals with real-time performance send response signals after receiving the inquiry signals, and after receiving responses of the vehicle-mounted user terminals with high real-time performance requirements, the vehicle networking proxy server adds data of trust factors in front of data packets of users and marks the users as trust users.
Step 202: at each time unit TiAnd in addition, the Internet of vehicles proxy server selects all users for preparing cloud pushing, and selects the user with the smallest Lyapunov drift-punishment item to push data to the cloud.
Step 203: internet of vehicles agent broadcasts current time unit T to all users preparing cloud pushingiThe optimal cloud push service number in the cloud.
Step 204: the Internet of vehicles proxy server judges the last time unit T according to the optimal cloud pushing service numberiThe push situation of the trusted user. If the pushing of the cloud of the trusted user is successful, the Internet of vehicles proxy server sends a 'cancel' command to cancel the trusted user mark of the user; if the trusted user does not have cloud pushing, sending a +1 command, updating the trust factor, and returning to the step 202 until the trusted user successfully pushes the cloud;
step 205: and updating the data backlog condition in the Internet of vehicles system according to the cloud pushing condition of the proxy server and the trust factor, and continuing to step 201 until the data pushing in all time units is successful.
Compared with the traditional cloud pushing technology, the technical scheme adopted by the invention has the following beneficial technical effects:
(1) according to the invention, a Lyapunov function is introduced in a complex car networking scene, the optimal cloud pushing service number of a certain time unit is controlled through a Lyapunov drift-punishment item, the optimal user is selected for carrying out cloud pushing, and the energy consumption for pushing a certain number of services in a certain time by a car networking system is effectively reduced;
(2) according to the cloud pushing method, the trust function is provided on the basis of the Lyapunov function, and some users with high real-time requirements and unstable channel states can carry out self-adaptive pushing in time through the proxy server, so that the real-time performance of cloud pushing of the Internet of vehicles is effectively improved, and the cloud pushing method is better suitable for the complex cloud pushing characteristics of the Internet of vehicles;
(3) the method disclosed by the invention has the advantages that the Lyapunov function is subjected to logarithm, the interference effect of the transmission noise of the channel is effectively reduced, the sensitivity of the noise is reduced, and the accuracy of cloud pushing of the user is improved, so that the method is applied to a complex Internet of vehicles cloud pushing scene.
As shown in fig. 3, an embodiment of the present invention provides a vehicle networking data cloud pushing apparatus based on lyapunov trust optimization, the apparatus includes a proxy server, the proxy server includes a memory, a processor, and a computer program stored on the memory and executable on the processor, and the processor implements the following steps when executing the program, including:
determining a trust user from all users to be pushed by the cloud, and adding a trust factor in front of a data packet of the trust user;
in the current time unit, selecting a data packet of a user which meets the smallest Lyapunov drift-penalty term from all users to be pushed to a cloud server for pushing;
calculating the optimal service push number in the current time unit;
and judging whether the trust user successfully pushes data to the cloud server in the time unit according to the optimal service pushing number, if not, updating the trust factor, and circulating in sequence until the trust user successfully pushes data to the cloud server in the time unit, canceling the mark of the trust user, updating the data backlog, entering the next time unit, and until the data packet pushing in all the time units is successful.
Although the embodiments of the present invention have been described with reference to the accompanying drawings, it is not intended to limit the scope of the present invention, and it should be understood by those skilled in the art that various modifications and variations can be made without inventive efforts based on the technical solutions of the present invention.
Claims (9)
1. A Internet of vehicles data cloud pushing method based on Lyapunov trust optimization is characterized by comprising the following steps:
step 1: determining a trust user from all users to be pushed by the cloud, and adding a trust factor in front of a data packet of the trust user;
step 2: in the current time unit, selecting a data packet of a user which meets the smallest Lyapunov drift-penalty term from all users to be pushed to a cloud server for pushing;
and step 3: calculating the optimal service push number in the current time unit;
and 4, step 4: and judging whether the trust user successfully pushes data to the cloud server in the time unit according to the optimal service pushing number, if not, updating the trust factor and the data backlog, returning to the step 2 until the trust user successfully pushes the data to the cloud server in the time unit, canceling the mark of the trust user, updating the data backlog, entering the next time unit, and repeating the steps 1-4 until the data packets in all the time units are successfully pushed.
2. The Internet of vehicles data cloud pushing method based on Lyapunov trust optimization of claim 1, wherein in the step 1, the method for determining the trusted user comprises the following steps:
the proxy server sends an inquiry signal to the user terminal;
the user terminal sends a response signal after receiving the inquiry signal;
and the proxy server marks the user terminal corresponding to the received response signal as a trusted user.
3. The Internet of vehicles data cloud pushing method based on Lyapunov trust optimization of claim 1, wherein in the step 2, the Lyapunov drift-penalty item obtaining method comprises the following steps:
establishing a relational expression of data backlog of a user in a corresponding channel and total user energy consumption in a time unit;
introducing a trust factor, and establishing a Lyapunov trust function by combining a relational expression of data backlog;
and introducing penalty functions at two ends of the expression of the Lyapunov trust function to obtain a Lyapunov drift-penalty item in the time unit.
4. The Internet of vehicles data cloud pushing method based on Lyapunov trust optimization of claim 3, wherein the step of establishing a relational expression between data backlog of the user in the corresponding channel in the time unit and total energy consumption of the user comprises the following steps:
the traffic volume, the data backlog volume and the channel state of a given user on a channel in the current time unit are given;
calculating the transmission rate of the user in the channel and the time slot of the channel according to the channel state, and multiplying the transmission rate of the channel and the time slot to obtain the service rate of the channel;
establishing a data backlog quantity relational expression of the user in the corresponding Internet of vehicles channel based on the traffic quantity, the data backlog quantity and the service rate of the channel of the user in the time unit;
and given the data transmission rate of the channel in the time unit, multiplying and summing the data transmission rate of the channel in the time unit and the time slot of the channel to obtain the total energy consumption relational expression of the user on the channel.
5. The Internet of vehicles data cloud pushing method based on Lyapunov trust optimization of claim 3, wherein the Lyapunov trust function establishing method comprises:
relational expression L based on data backlog quantityk(Ti+1), establishing a Lyapunov function C1(Ti)；
Introducing a trust factor X (j), and combining the trust factor with the data backlog quantity relational expression to obtain a new data backlog quantity relational expression
Relational expression based on new data backlogEstablishing a new Lyapunov function C (T)i)；
Logarithm of the Lyapunov function C (T)i) Computing to obtain the Lyapunov trust function deltaT(Ti)。
6. The Internet of vehicles data cloud pushing method based on Lyapunov trust optimization of claim 1, wherein in the step 1, an expression of a Lyapunov drift-penalty term is as follows:
where Y is the control threshold, YE { E (T)i)|Lj(Ti) Is a penalty function related to the control threshold Y;Ck(Ti) In time unit TiThe backlog of trust data of the inner user k; vk(Ti) As a unit of time TiA service rate of the inner channel; c (T)i) Is a new lyapunov function.
7. The Internet of vehicles data cloud pushing method based on Lyapunov trust optimization of claim 1, wherein in the step 3, the step of judging whether the trust user successfully pushes data to the cloud server in the time unit according to the optimal service pushing number comprises the following steps:
if the optimal service pushing number in the time unit is the same as the data packet number of the trust user, the trust user successfully pushes data to the cloud server, and the mark of the trust user is cancelled; otherwise, if the data is unsuccessful, the trust factor and the data backlog are updated.
8. The Internet of vehicles data cloud pushing method based on Lyapunov trust optimization of claim 1, wherein in step 3, the calculation formula of the optimal service pushing number in the current time unit is as follows:
in the formula, nbestAs a unit of time TiThe number of the best service push; x (n) is the amount of trusted packet data; ck(Ti) In time unit TiThe backlog of trust data of the inner user k; thetak(T-i) Poisson distribution with mean value of α for the amount of data arriving on the channel, YE (T-i)i) Is the time unit TiThe part expectation penalty, α is the mean of the poisson distribution, and N is the time unit number.
9. A Lyapunov trust optimization-based vehicle networking data cloud pushing device is characterized by comprising a proxy server, wherein the proxy server comprises a memory, a processor and a computer program which is stored on the memory and can run on the processor, and the processor executes the program to realize the following steps, including:
determining a trust user from all users to be pushed by the cloud, and adding a trust factor in front of a data packet of the trust user;
in the current time unit, selecting a data packet of a user which meets the smallest Lyapunov drift-penalty term from all users to be pushed to a cloud server for pushing;
calculating the optimal service push number in the current time unit;
and judging whether the trust user successfully pushes data to the cloud server in the time unit according to the optimal service pushing number, if not, updating the trust factor, and circulating in sequence until the trust user successfully pushes data to the cloud server in the time unit, canceling the mark of the trust user, updating the data backlog, entering the next time unit, and until the data packet in all the time units is successfully pushed.
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