A dynamic pricing method based on vehicle networking multimedia content transaction

Abstract

The present application belongs to the field of internet energy transaction, and particularly relates to a dynamic pricing method based on vehicle networking multimedia content transaction, comprising: constructing a multimedia content pricing framework among RSU, relay vehicle and user vehicle; formulating user vehicle utility according to transmission rate, QoE evaluation standard and RSU service cost; formulating relay vehicle utility according to commission paid to RSU and transmission energy consumption cost; formulating RSU utility according to obtained service cost and commission paid by relay vehicle and transmission power cost; modeling the exchange and cooperation among RSU, relay vehicle and user vehicle as a non-cooperative Stackelberg game model, and calculating optimal strategy according to the utility of the three parties. The present application simultaneously considers the interaction among relay vehicle, user vehicle and RSU, not only improves QoE and the enthusiasm of relay vehicle, but also solves the problem of limited storage space of relay vehicle.

Description

Technical Field

[0001] This invention belongs to the field of Internet energy trading technology, specifically relating to a dynamic pricing method based on vehicle-to-everything (V2X) multimedia content trading. Background Technology

[0002] With the rapid development of vehicle communication networks, the rise of Intelligent Transport Systems (ITS) can effectively solve road traffic problems. The communication mechanisms of the Internet of Vehicles (IoV) within ITS include Vehicle-to-Infrastructure (V2I) and Vehicle-to-Vehicle (V2V) communication. IoV enables autonomous data exchange between vehicles and roadside access points (APs). On this network, user vehicles have increasingly higher demands for Quality of Experience (QoE), which places higher demands on the pricing of computing and storage space for vehicles and roadside infrastructure. Therefore, balancing the interests of all parties within the IoV system is particularly crucial.

[0003] Currently, organizations such as the International Telecommunication Union (ITU) use anthropomorphic evaluations to assess the entire QoE service process for users, relying on users' subjective perceptions to determine service satisfaction. However, many methods evaluate QoE from a single user perspective, rather than considering the impact of the entire system model on QoE from multiple angles. Furthermore, the lack of a pricing mechanism in the system may lead to the over-utilization of network resources.

[0004] To better balance the benefits in the system model, researchers have proposed a two-party intelligent pricing model that combines QoE and economic pricing. After pricing, the IoV system can prevent vehicles from attempting to offer services above their required level, thus selecting the service that best meets their needs. However, these solutions only consider the information exchange between the infrastructure and the end user, without addressing the communication blind spots between the vehicle and the infrastructure.

[0005] To address the aforementioned issues, some scholars have proposed V2I cooperative uplink communication schemes to improve the performance of users located far from the infrastructure. However, these schemes idealize the storage space of relay vehicles without considering their limited space, resulting in low QoE for end users and low data forwarding enthusiasm from relay vehicles, which in turn affects the user's QoE to some extent.

[0006] In summary, the existing solution does not take into account the problem of limited storage space and low data forwarding enthusiasm of relay vehicles, which in turn affects the QoE of user vehicles. Summary of the Invention

[0007] To address the aforementioned technical problems, this invention proposes a dynamic pricing method for multimedia content transactions based on the Internet of Vehicles, comprising the following steps:

[0008] S1: Construct a multimedia content pricing framework based on the three parties: RSU, relay vehicle, and user vehicle;

[0009] S2: For user vehicles, the utility of user vehicles is determined based on the QoE evaluation criteria set according to the transmission rate and content size, and the RSU service cost.

[0010] S3: For relay vehicles, the utility of relay vehicles is determined based on the commission paid to the RSU and the cost of transmitting energy consumption.

[0011] S4: For RSU, the utility of RSU is obtained by modeling the difference between the service cost obtained and the commission paid by the relay vehicle and the transmission power cost.

[0012] S5: Model the communication and cooperation between RSU, relay vehicle, and user vehicle as a non-cooperative Stackelberg game model. For the three parties, the Nash equilibrium is obtained by using back induction based on the utility of RSU, relay vehicle, and user vehicle, thus obtaining the optimal strategy of the three parties.

[0013] The beneficial effects of this invention are:

[0014] This invention considers the interaction between relay vehicles, user vehicles, and RSUs simultaneously. It establishes a utility function based on storage space utilization, content data size, and cost, and uses back induction to obtain the optimal content data size, optimal space utilization, and optimal cost. This not only improves QoE and the enthusiasm of relay vehicles, but also solves the problem of limited storage space for relay vehicles, and has certain advantages over traditional vehicle-to-everything (V2X) dynamic multimedia content pricing methods. Attached Figure Description

[0015] Figure 1 This is a flowchart of the dynamic multimedia pricing process based on the Internet of Vehicles (IoV) of the present invention.

[0016] Figure 2 This is a three-party interaction diagram of dynamic multimedia pricing based on the Internet of Vehicles in this invention. Detailed Implementation

[0017] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0018] A dynamic pricing method for multimedia content transactions based on the Internet of Vehicles, such as Figure 1 As shown, it includes:

[0019] S1: Construct a multimedia content pricing framework based on the three parties: RSU, relay vehicle, and user vehicle;

[0020] S2: For user vehicles, the utility of user vehicles is determined based on the QoE evaluation criteria set according to the transmission rate and content size, and the RSU service cost.

[0021] S3: For relay vehicles, the utility of relay vehicles is determined based on the commission paid to the RSU and the cost of transmitting energy consumption.

[0022] S4: For RSU, the utility of RSU is obtained by modeling the difference between the service cost obtained and the commission paid by the relay vehicle and the transmission power cost.

[0023] S5: Model the communication and cooperation between RSU, relay vehicle, and user vehicle as a non-cooperative Stackelberg game model. For the three parties, the Nash equilibrium is obtained by using back induction based on the utility of RSU, relay vehicle, and user vehicle, thus obtaining the optimal strategy of the three parties.

[0024] This invention assumes that the number of user vehicles entering the communication range of the RSU follows a Poisson distribution, and that user vehicles enter the communication range of the RSU at a speed v to share content. Vehicles within the RSU coverage area are considered to be in a steady state, where the speed of each vehicle remains the same and stable.

[0025] During V2V and V2I communication, wireless signals may experience issues such as shadowing fading, multipath fading, and path loss during transmission, which will affect the uplink and downlink transmission rates. Therefore, the V2X wireless data transmission rate is shown in the formula:

[0026]

[0027] Where B represents the channel bandwidth, P represents the average power of the transmitted signal in the channel, N0 represents the Gaussian noise power inside the channel, and h represents the channel gain.

[0028] like Figure 2 As shown, within the coverage area of ​​an RSU, there is a three-way interaction between the RSU, the relay vehicle, and the user vehicle regarding pricing; if the user vehicle wants to obtain multimedia content... j It is necessary to send d to RSU j Upon receiving the request from the user's vehicle, the RSU will... jThe data is sent to relay vehicles for sharing with surrounding user vehicles. Since sharing with user vehicles incurs costs, user vehicles must pay a certain price to the relay vehicle to receive d. j The relay vehicle uses its spare storage space to cache the RSU's d j And when forwarding to other vehicles, a commission of ε must be paid to the RSU. This commission is also used by the RSU to determine whether the forwarding meets its strategy, and will be used to transfer the vehicle's d. j Send to relay vehicle.

[0029] Moving vehicles, seeking to enhance comfort during operation, have diverse multimedia needs and desire high-quality multimedia content. In this invention, the user's satisfaction with content is transformed into RSU-based content pricing and the cost of relay vehicles transmitting content, selecting an appropriate request... j This addresses the issue while reasonably assuming that the user's vehicle experience follows the law of diminishing marginal utility. Therefore, the user's vehicle utility can be evaluated using QoE criteria based on transmission rate and content size, as shown in the equation:

[0030]

[0031] Where α1 represents the adjustable positive parameter used for the QoE model, The frame sequence J representing the user vehicle requesting content d from the RSU. j Size, l j Indicates request content d j The transmitted content is a data frame, where r represents the wireless channel data transmission rate. This indicates that the user's vehicle has obtained content d. j The time T required j .

[0032] Assuming that each user's vehicle is independent of the others, C u The service cost paid by the user's vehicle to the RSU can be modeled as the unit cost y of the transmitted content size. j With content size The product is shown in the formula:

[0033]

[0034] The utility function U of the user's vehicle User It can be defined as the difference between user vehicle satisfaction and RSU service cost, as shown in the formula:

[0035]

[0036] The profit of a relay vehicle primarily comes from the price set by the RSU for the content. Costs consist of two parts: commission payments to the RSU and transmission energy consumption. The overall utility of a relay vehicle is U. Relay The model can be modeled as shown in the following equation:

[0037] U Relay =P R -εP R -E r

[0038] Among them, P R and εP R E represents the content cost paid by the content user vehicle and the commission paid by the relay vehicle to the RSU, respectively. r This represents the unit energy cost required to transmit content over a wireless channel.

[0039] Relay vehicle revenue P R Based on the size of the content received by the vehicle within a certain time period Unit cost y of the transmitted content size j Defined as the product of, as shown in the equation:

[0040]

[0041] Where θ represents the storage space utilization rate of the relay vehicle. Considering the limited free storage space of the relay vehicle, the maximum amount of content that can be received... It should not exceed the storage capacity S of the relay vehicle. J Then the following constraints apply, as shown in the equation:

[0042]

[0043] The energy cost E required to transmit content via wireless channels r The model is based on the unit energy consumption cost, transmission power, and transmission rate under the condition of transmitting all stored content, as shown in the equation.

[0044]

[0045] Where λ represents the unit energy consumption cost generated by transmitting data, ω m This indicates the transmission power of the relay vehicle.

[0046] The total utility equation for the relay vehicle is expressed as:

[0047]

[0048] RSUs (Roadside Units) facilitate content forwarding through relay vehicles, increasing vehicle-to-vehicle communication frequency, reducing the communication burden on RSUs, and lowering operating costs. The utility equation for an RSU is U. RSUBased on the cost of the service obtained C u Commission εP paid by relay vehicles R With transmission power cost ψ R The difference is used to model the process, as shown in the equation:

[0049] U RSU =C u +εR T -ψ R

[0050] The cost of RSU transmission of multimedia content can be modeled as a function of spectrum allocation, and ψ is given. R Spectrum. Transmission costs and operating costs γ, pricing function φ, and the size of the transmitted content. Proportional. The cost coefficient τ is a non-zero natural number, and the cost function for allocating the spectrum is a monotonically increasing convex function, as shown in the equation:

[0051]

[0052] The total utility equation for RSU can be derived as shown in the following equation:

[0053]

[0054] To maximize profits for all parties within the system, this invention further models the communication and cooperation between the RSU, relay vehicles, and user vehicles as a non-cooperative Stackelberg game model. The RSU acts as the leader for both the relay and user vehicles, which are the followers. The leader adjusts its own strategy by predicting the followers' strategies, and the followers optimize their own interests based on the leader's strategies.

[0055] In this embodiment, the optimal strategy of the followers is first predicted using backward induction, and then the optimal strategy of the leader is derived. The optimal strategies of the three parties are denoted by {l}. * ,θ * ,y *} is used to represent this.

[0056] Given the commission rate ε for relay vehicles and the cost of RSUs, to maximize their utility, firstly U User right Taking the first derivative, we get the following equation:

[0057]

[0058] Then, the second derivative of the user's vehicle utility is taken, as shown in the formula:

[0059]

[0060] As can be seen from the first derivative formula, the data transmission rate is not negative and Since the numerator is always positive and the total cost of transmitted content is also non-negative, the utility function of the user's vehicle is monotonic. Because the denominator of the second derivative formula is squared and the numerator is a non-negative positive parameter, the second derivative is negative overall. It can be proven that the utility function of the user's vehicle is a convex function, and according to convex optimization theory, Nash equilibrium exists. This can be verified using the first derivative. Solve the equation to obtain the optimal strategy l * .

[0061]

[0062] The relay vehicle will adjust its own strategy accordingly based on the user vehicle's strategy, derived from the first phase. * Substituting the original utility formula, as shown below:

[0063]

[0064] To facilitate subsequent calculations, express.

[0065] The relay vehicle aims to determine its space utilization rate based on the user vehicle's optimal strategy. Assuming the cost of the Relay Unit (RSU), by observing the results of its first and second derivatives, we can deduce that the relay vehicle's utility yields the optimal strategy θ. * As shown in the following formula:

[0066]

[0067]

[0068]

[0069] As the leader of the three parties, RSU determines its optimal strategy based on the optimal strategies of the two followers. The optimal strategies of the two followers are as follows: * and θ * After substituting into the original utility formula and simplifying, we get the following formula:

[0070]

[0071] The above equation is a multivariate nonlinear function equation, and proving its convexity by calculating its second derivative is difficult. We will use Newton's method to prove the existence of a Nash equilibrium. First, we will verify whether the above equation is differentiable to determine if the utility equation is a continuous function, taking differentiability for U... RSU and about First, we take the first derivative, then observe the results, and confirm that all formulas are continuously differentiable functions, because y *The result is constrained by the space utilization rate θ, thus yielding the RSU cost-optimal strategy y. * The existing intervals are shown in the equation:

[0072]

[0073]

[0074]

[0075] In this embodiment, for the aforementioned three-party Stackelberg game process, this invention also proposes a global search iterative algorithm to determine the optimal strategies for each of the three parties. This algorithm finds the optimal cost, optimal space ratio, and optimal content data size for mutual responses among the RSU, user vehicle, and relay vehicle, respectively. The proposed algorithm follows the reverse order of inverse induction, calculating the three-party decisions in the order of RSU, relay vehicle, and user vehicle: first, the parameters are initialized; second, let Ψ = y min :M:y max Where M is the maximum step size, for i = 1: M, design y * =Ψ(i) and calculate U RSU The zero point corresponding to the first derivative at M, if the iteration satisfies U RSU (y i )-U RSU (y i-1 If ) > 0, then update U. RSU =U RSU (y i ), set y * =y i Again, the obtained y * Substitute U Relay and U User In the middle, if the judgment formula U is satisfied Relay (y * ,θ * )>U Relay (y * ,θ i-1 ) and U User (θ * ,l * )>U User (θ * ,l i-1 ), then we get θ * , l * Finally, {y} * ,θ * ,l * Substitute U into each RSU U Relay and U User Calculate the utility value.

[0076] The specific global search iterative calculation algorithm for Nash equilibrium is shown in Table 1:

[0077] Table 1 Global Search Iterative Calculation of Nash Equilibrium Algorithm

[0078]

[0079] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A dynamic pricing method for multimedia content transactions based on the Internet of Vehicles, characterized in that, include: S1: Construct a multimedia content pricing framework based on the three parties: RSU, relay vehicle, and user vehicle; S2: For user vehicles, the utility of user vehicles is determined based on the QoE evaluation criteria set according to the transmission rate and content size, and the RSU service cost. S3: For relay vehicles, the utility of relay vehicles is determined based on the commission paid to the RSU and the cost of transmitting energy consumption. The utility of relay vehicles is determined based on the commission paid to RSUs and the cost of transmitting energy consumption, including: in, This indicates the utility of the relay vehicle. and These represent the content costs paid by content users' vehicles and the commissions paid by relay vehicles to RSUs, respectively. Indicates the commission rate. This represents a sequence of frames in which a user vehicle requests content from an RSU. Requested content Size, Indicates the request content The transmitted content data frames, Indicates the content to be transmitted Unit cost per size This indicates the storage space utilization rate of the relay vehicle. This represents the unit energy cost required to transmit content over a wireless channel. Indicates the data transmission rate of the wireless channel. This represents the unit energy cost generated during data transmission. Indicates the transmission power of the relay vehicle; S4: For RSU, the utility of RSU is obtained by modeling the difference between the service cost obtained and the commission paid by the relay vehicle and the transmission power cost. The benefits of the RSU include: in, This indicates the utility of RSU. This represents the service cost paid by the user's vehicle to the RSU. This indicates the commission paid by the relay vehicle to the RSU. Indicates transmission power cost, Indicates operating costs, Represents the pricing function. Indicates a non-zero cost coefficient; S5: Model the communication and cooperation between RSU, relay vehicle, and user vehicle as a non-cooperative Stackelberg game model. For the three parties, the Nash equilibrium is obtained by using back induction based on the utility of RSU, relay vehicle, and user vehicle, thus obtaining the optimal strategy of the three parties.

2. The dynamic pricing method for multimedia content transactions based on the Internet of Vehicles as described in claim 1, characterized in that, Construct a multimedia content pricing framework based on three parties: RSU, relay vehicle, and user vehicle, including: Within the coverage area of ​​an RSU (Roadside Unit), a three-way interaction occurs between the RSU, the relay vehicle, and the user vehicle regarding pricing. For example, if the user vehicle wants to access multimedia content... It needs to be sent to the RSU. Upon receiving the request from the user's vehicle, the RSU will... The data is sent to relay vehicles for sharing with surrounding user vehicles. Since sharing with user vehicles incurs costs, user vehicles must pay a certain price to the relay vehicle to receive the multimedia content. The relay vehicle uses its spare storage space to cache RSUs. If the vehicle is forwarded to other vehicles, a corresponding percentage must be paid to the RSU. The commission at this point is also used by RSUs to determine whether their strategy is met, and they will transfer the commission accordingly. Send to relay vehicle.

3. The dynamic pricing method for multimedia content transactions based on the Internet of Vehicles as described in claim 1, characterized in that, The utility of the user vehicle includes: in, QoE represents the utility of a user's vehicle, and it refers to the evaluation criteria set based on transmission rate and content size. This represents the proportionality coefficient of the QoE evaluation standard. This represents a sequence of frames in which a user vehicle requests content from an RSU. Requested content Size, Indicates the request content The transmitted content data frames, Indicates the data transmission rate of the wireless channel. Indicates that the user's vehicle obtains content. Time required , This represents the service cost paid by the user's vehicle to the RSU. Indicates the content to be transmitted Unit cost per size.

4. The dynamic pricing method for multimedia content transactions based on the Internet of Vehicles as described in claim 1, characterized in that, The communication and cooperation between RSUs, relay vehicles, and user vehicles are modeled as a non-cooperative Stackelberg game model, including: The Relay Unit (RSU) acts as the leader of both relay vehicles and user vehicles, which are the followers. The leader adjusts its own strategy by predicting the strategies of the followers, and the followers optimize their own interests based on the leader's strategy. The optimal strategy of the leader is first predicted by backward induction, and then the optimal strategy of the followers is derived.

5. A dynamic pricing method for multimedia content transactions based on the Internet of Vehicles (IoV) according to claim 4, characterized in that, The optimal strategies for following user vehicles include: in, This represents the optimal strategy for follower user vehicles. This represents the proportionality coefficient of the QoE evaluation standard. Indicates the content to be transmitted Unit cost per size Indicates the data transmission rate of the wireless channel. This represents the frame sequence in which a user vehicle requests content from the RSU.

6. The dynamic pricing method for multimedia content transactions based on the Internet of Vehicles as described in claim 4, characterized in that, The optimal strategies for follower relay vehicles include: in, This represents the optimal strategy for the follower relay vehicle. Indicates the data transmission rate of the wireless channel. Indicates the commission rate. Indicates the content to be transmitted Unit cost per size This represents the unit energy cost generated during data transmission. This indicates the transmission power of the relay vehicle. This represents the optimal strategy for the user's vehicle segment. , This represents the frame sequence in which a user vehicle requests content from the RSU.

7. A dynamic pricing method for multimedia content transactions based on the Internet of Vehicles (IoV) according to claim 4, characterized in that, The optimal strategies for the leader's RSU include: in, This represents the leader's optimal strategy for RSU. This represents the proportionality coefficient of the QoE evaluation standard. Indicates the data transmission rate of the wireless channel. Indicates the commission rate. Indicates the data transmission rate of the wireless channel. This represents the unit energy cost generated during data transmission. This indicates the transmission power of the relay vehicle. This represents the frame sequence in which a user vehicle requests content from the RSU.

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