Heterogeneous Internet of Vehicles network selection method and related device based on global benefit decision

Abstract

The present invention provides a heterogeneous vehicle network selection method and related devices based on global benefit decision-making, comprising the following steps: according to the currently connected wireless network base station, obtaining the network topology map and base station parameters of the surrounding wireless network; according to the relative position of the base station and the distance between the base station and the road, selecting a candidate network set; according to the obtained base station parameter information, calculating the angle between the candidate network and the road, predicting and calculating the transmission rate of each position, and finding the position with equal transmission rate, calculating the switching position and switching time; according to the network transmission rate and switching delay, calculating the transmission volume of different switching schemes; according to the transmission volume calculated by different schemes, combined with the network switching loss rate, selecting a suitable network and recording it; judging whether there is an adjacent base station subset according to the base station position and radius, and calculating the switching position and switching time of the adjacent base stations; executing network switching according to the calculated switching position and switching time.

Description

Technical Field

[0001] The present invention belongs to the field of intelligent transportation technology and relates to a method and related devices for selecting a heterogeneous vehicle network network strategy based on global benefit decision. Background Art

[0002] In recent years, due to the rapid increase in the number of vehicles in urban traffic, various problems have arisen in urban traffic. How to solve the congestion and peak period problems in urban traffic has become an urgent issue. The development of wireless network technology has enabled researchers to find new solutions. Wireless network technology has brought new solutions to urban traffic problems. Wireless network technology can provide Internet of Vehicles users with current traffic status information and driving assistance information, such as navigation and positioning technologies, which has brought great convenience to people's travel.

[0003] As people's needs change, wireless networks have gradually formed a variety of wireless network technology standards, such as cellular networks, Wi-Fi, and DSRC, and then developed into heterogeneous wireless networks with multiple networks coexisting and overlapping coverage. However, different network technologies have different advantages and disadvantages, and different wireless network technologies have different characteristics and disadvantages. These technologies complement each other, providing different services for wireless network users and meeting all user needs as much as possible.

[0004] When wireless networks are applied to vehicles and transportation, the communication status between vehicles and base stations will change as the vehicle's position changes. When the vehicle's position changes, the relative position with the base station changes, which causes the wireless link status between the base station and the vehicle to change, and then the service quality of the base station changes. In addition, the service quality of the base station will be restricted by the number of users and changes in the surrounding environment. The number of service users of a wireless network base station is limited. More users will cause changes in the service quality of each link, and the wireless link quality of the base station will be restricted by the surrounding environment. In addition, there is a continuous switching process during the driving process of the vehicle. Due to the high driving speed of the vehicle, the vehicle's residence time in a single base station is short, so the service time of a single base station is short. Therefore, how to choose a suitable network for switching is an important issue.

[0005] For heterogeneous IOV networks, researchers have proposed a variety of network selection technologies to improve the quality of service that IOV can provide to users through different wireless network technologies. However, the mobility of vehicles poses new challenges to wireless network services, such as short residence time and large switching loss. Therefore, in view of the mobility of vehicles and the differences in heterogeneous networks, a heterogeneous IOV network selection strategy based on global benefit decision-making is proposed. Summary of the invention

[0006] In order to solve the problems existing in the prior art, the present invention provides a network selection method based on the moving speed of the vehicle and the relative position of the vehicle and the network base station. Considering the different speeds of the vehicle under the same network and the transmission volume of the same speed under different networks, different wireless networks are selected for switching, and the switching delay existing in the vehicle during the switching process is analyzed. Considering whether the access of the micro base station can bring higher benefits to the Internet of Vehicles users, the switching impact caused by the transmission volume loss caused by the switching delay and the network switching failure caused by the link failure is analyzed, it is judged whether the network selection is beneficial to the Internet of Vehicles users, and the network is selected according to the results.

[0007] In order to achieve the above object, the technical solution adopted by the present invention is: a heterogeneous vehicle network selection method based on global benefit decision-making, comprising the following steps:

[0008] S1, according to the currently connected wireless network base station, obtain the network topology map and base station parameters M of the surrounding wireless networks i ={L i , R i ,h i , P i , B i} and according to the relative position R of the base station i and the distance between the base station and the road h i , select the candidate network set M={M1, M2, ..., M n} T ;

[0009] S2, based on the obtained network topology and base station parameter information, calculate the candidate network M = {M1, M2, ..., M n} T Angle θ with the road i , predict and calculate the transmission rate C of each location i , and find the position where the transmission rate is equal, and calculate the switching position r i ;

[0010] S3, according to the network transmission rate C i and switching delay S, calculate the transmission volume of different switching schemes;

[0011] S4, based on the transmission volume calculated by different schemes and the network switching loss rate G(v,n,p), the cell attractor algorithm is used to select base stations that can bring benefits to users as candidate subsets, and the candidate network subset BU = {BS1, BS2, ..., BS k};

[0012] S5: Determine whether there is an adjacent base station subset BU = {BS1, BS2, ..., BS k} and update the candidate subset selected by the network, repeat S2, S3, S4, S5 to calculate the switching position r of the adjacent base station i ;

[0013] S6, according to the calculated switching position r i and the candidate network subset BU = {BS1, BS2, ..., BS k}Perform network switching.

[0014] When looking for locations with equal transmission rates, use distance to find locations with equal transmission rates, using the formula:

[0015]

[0016] where r i is the hand-off position of the ith base station. If there is C i (r i )=C j (r j ), at the i-th base station r i Switching between base station i and base station j is performed at the switching process, and it is determined that the transmission rate during the switching process is the part where the transmission rates of the two base stations in the overlapping area are the lowest. In S4, the cell attractor algorithm is defined as follows:

[0017]

[0018] m1 and m2 represent the concentration of protein products under different operons, i.e., the attractor state, A represents the activity of the cell, and S(A) and D(A) are the rate coefficients of synthetic cells and decomposition cells, respectively. Both rate coefficients are increasing functions, and η1 and η2 are Gaussian white noises. When the attractor states are not much different, the attractor value will be disturbed by the noise, making it impossible for the cell to make a choice. When the attractor states are greatly different, the noise interference loses its effect, and the cell will choose to approach the attractor with a large value.

[0019] When determining the update position of the cell attractor, it is also necessary to calculate the value of the attractor, associating the benefits of the Internet of Vehicles with a pair of time-varying variables m1 and m2:

[0020]

[0021] D i is the transmission amount of the i-th base station, D Hi is the transmission volume of the macro base station during the corresponding base station access time, and the speed of the vehicle meets the condition

[0022] Through the attractor selection model, m1, m2 and D i , D Hi is associated with each other and updated through the cell attractor model; when new time-varying variables m1 and m2 appear, analyze whether the state of the attractor changes; if the state of the attractor is not updated, then the Internet of Vehicles users will not choose to access the micro base station; when the state of the attractor changes, the micro base station can provide better services for the Internet of Vehicles users, and the Internet of Vehicles users will choose to access the micro base station network to guarantee their own services, such as Figure 6 When S(A) / D(A)>2, there will be two different attractors. When S(A) / D(A)≤2, there is a unique attractor. The synthesis rate and decomposition rate functions of the cell are:

[0023]

[0024] In S4, the network switching loss rate G(v,n,p) is:

[0025]

[0026] Where x is the probability of network switching failure, n is the number of switching failures, f(x) is the probability of successful switching for the n+1th time, and n<Nx-2. The network switching loss rate is affected by vehicle speed, number of switching failures and link failure probability. The mean of the network switching loss rate is selected as the loss rate, and the average loss G is defined as:

[0027]

[0028] In S5, there are two types of transmission volume calculations for different switching schemes: the first is whether a single base station needs to be switched, and compares the transmission volume that the Internet of Vehicles can provide to users before and after the switch; the second is when there are multiple adjacent micro base station networks, consider the selection of the next target network of the network. When the next micro base station network of the network is not unique, calculate the network selection results under different network selection situations to further screen the wireless network.

[0029] The transmission volume of different switching schemes is calculated by integrating the transmission rate and the time during which the vehicle resides in the network signal range. The trigonometric function relationship is used to obtain:

[0030]

[0031]

[0032]

[0033] s i is the distance from the base station, ri is the distance between the vehicle and the base station, T i is the duration of access to the base station, and

[0034]

[0035] Among them, D i is the transmission amount of the i-th base station, B i is the wireless network bandwidth, and the result is

[0036]

[0037] D i for:

[0038]

[0039] in

[0040] Use Shannon's formula to calculate the transmission capacity of Internet of Vehicles users:

[0041] C i =B i log2(1+φ i )

[0042]

[0043] Among them, φ i is the signal-to-noise ratio, N is the power of Gaussian white noise, P i is the transmission power of the ith wireless network base station, c is the propagation speed, r i is the distance between the vehicle and base station i, α is the distance attenuation exponent, which ranges from 2 to 6, and the propagation speed and frequency are constants. The above formula is simplified to:

[0044]

[0045] Based on the technical concept of the present invention, a heterogeneous vehicle network selection system based on global benefit decision is provided, including a base station parameter acquisition module, a first calculation module, a second calculation module, a candidate subset calculation module, a switching position acquisition module and a network switching module;

[0046] The base station parameter acquisition module is used to obtain the network topology map and base station parameters of the surrounding wireless network based on the currently connected wireless network base station. i ={L i , R i ,h i , P i , B i} and according to the relative position R of the base station i and the distance between the base station and the road hi , select the candidate network set M={M1, M2, ..., M n} T ;

[0047] The first calculation module is used to calculate the candidate network M={M1, M2, ..., M n} T Angle θ with the road i , predict and calculate the transmission rate C of each location i , and find the position where the transmission rate is equal, and calculate the switching position r i ;

[0048] The second calculation module is used to calculate the network transmission rate C i and switching delay S, calculate the transmission volume of different switching schemes;

[0049] The candidate subset calculation module is used to select base stations that can bring benefits to users as candidate subsets based on the transmission volume calculated by different schemes and the network switching loss rate G(v,n,p) using the cell attractor algorithm, and record the candidate network subset BU = {BS1, BS2, ..., BS k};

[0050] The handover position acquisition module is used to determine whether there is an adjacent base station subset BU = {BS1, BS2, ..., BS k} and update the candidate subset selected by the network, repeat S2, S3, S4, S5 to calculate the switching position r of the adjacent base station i ;

[0051] The network switching module is used to switch the position r according to the calculation i and the candidate network subset BU = {BS1, BS2, ..., BS k}Perform network switching.

[0052] In addition, a computer device is provided, including a processor and a memory, wherein an executable program is stored in the memory, and when the processor executes the executable program, the heterogeneous vehicle network selection method based on global benefit decision-making described in the present invention can be executed.

[0053] At the same time, a computer-readable storage medium is provided, in which a computer program is stored. When the computer program is executed by a processor, the heterogeneous vehicle network selection method based on global benefit decision-making described in the present invention can be implemented.

[0054] Compared with the prior art, the present invention has at least the following beneficial effects: first, the location of the cell attractor update is found for the transmission rate, and secondly, the speed and residence time of the vehicle in the micro base station are considered to calculate the transmission volume of the micro base station, and by updating the cell attractor, it is selected whether to access the micro base station network, thereby increasing the transmission volume provided to users by the Internet of Vehicles network. Through the analysis of simulation results, this strategy can effectively improve the transmission volume of the Internet of Vehicles and increase the amount of data available to Internet of Vehicles users. The present invention aims to increase the transmission volume that the Internet of Vehicles can provide to users, provide more data for Internet of Vehicles users, and provide better data transmission services. BRIEF DESCRIPTION OF THE DRAWINGS

[0055] Figure 1 The loss of transmission volume at different base stations in different locations;

[0056] Figure 2 Update the position for the attractor;

[0057] Figure 3 is the calculation range of the transmission volume;

[0058] Figure 4 The impact of different link failure probabilities on the loss rate;

[0059] Figure 5 The effect of different speeds on the loss rate;

[0060] Figure 6 is the change of state variables m1, m2;

[0061] Figure 7 The change of transmission volume of different micro base stations;

[0062] Figure 8 is the relationship between speed and transmission volume;

[0063] Fig. 9 It is the change of transmission volume during vehicle driving. DETAILED DESCRIPTION

[0064] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0065] In the description of the present invention, it should be understood that the terms “include” and “comprises” indicate the presence of described features, wholes, steps, operations, elements and / or components, but do not exclude the presence or addition of one or more other features, wholes, steps, operations, elements, components and / or collections thereof.

[0066] The network selection method provided by the present invention for the moving speed of the vehicle and the relative position between the vehicle and the network base station comprises the following steps:

[0067] S1, obtaining the network topology and base station parameters of the surrounding wireless networks according to the currently connected wireless network base station;

[0068] S2, based on the relative position R of the base station i The distance between the base station and the road h i , select a set of candidate networks;

[0069] S3, calculate the angle θ between the network and the road based on the obtained parameter information i , predict and calculate the transmission rate at each location And look for C i (r i )=C j (r j ), calculate the switching position r i and switching time t i2 ;

[0070] S4, according to the network transmission rate C i and switching delay S, calculate the transmission volume of different switching schemes;

[0071] S5, select a suitable network based on the transmission volume calculated by different schemes and the network switching loss rate G(v,n,p) and record it;

[0072] S6: Determine whether there is an adjacent base station subset BU={BS1, BS2, ..., BS k}, repeat the above steps 2, 3, 4, and 5, considering the switching position r of the adjacent base station i and switching time t i2 .

[0073] S7, according to the calculated switching position r i and switching time t i2 Perform a network switch.

[0074] Macro base stations replace networks with larger coverage, such as cellular network macro base stations and wireless metropolitan area networks, while micro base stations replace networks with smaller coverage, such as Wi-Fi and cellular network micro base stations. When a vehicle enters from the previous intersection and there is no fork in the road before it reaches the next intersection; the vehicle travels on the road at a uniform speed, and the relative position of the road and the micro base station can be used to replace the relative position of the vehicle. It is assumed that the vehicle can obtain all micro base station network information within the coverage of the macro base station based on the current macro base station network.

[0075] The network scenario selected by the present invention is in the city, so the attenuation coefficient of the wireless network signal strength with distance is large. In the city, the buildings are very dense, resulting in the shielding between most wireless network base station signals and users, so the network attenuation with distance is very serious. In the present invention, the Shannon formula is used to calculate the transmission capacity of the Internet of Vehicles users:

[0076]

[0077] Among them, φ i is the signal-to-noise ratio, N is the power of the noise, c is the propagation speed, r i is the distance between the vehicle and base station i, α is the distance attenuation exponent, which is generally within 2-6. Since the propagation speed and frequency are generally constant, formula (1) is simplified to:

[0078]

[0079] First, the losses caused to Internet of Vehicles users during the wireless network switching process are analyzed. Since there is a switching delay between heterogeneous networks, the wireless network terminal cannot receive data transmission from any base station during the switching delay of the wireless network. Therefore, the transmission loss during the network switching process is inevitable. If access to micro base stations can make up for these losses, then switching is beneficial to users. However, if switching cannot bring higher benefits, then switching is actually ineffective. Therefore, for users, choosing this network is not beneficial, so users will choose to give up access to this network.

[0080] The switching delay is divided into three cases: switching when entering base station B, switching when the transmission rates are equal, and switching before leaving base station A. Figure 1 As shown, the transmission loss of different switching times is calculated:

[0081]

[0082]

[0083] refer to Figure 2 , t1, t2 are the time points of the switching position, which are the time points before and after the switching respectively, and there are also four time points t3, t4, t5, and t6. a , D b , D c The transmission loss of three different switching situations are shown respectively. Since the switching time is short and there are points with equal transmission rates between t3 and t4, the transmission loss of the two base stations is equal between t3 and t4. a and D c Right D bThe difference is:

[0084]

[0085]

[0086] Since in the t1 and t3 regions, C i >C j , i is the currently connected base station, j is the target switching base station, and in the t4 and t6 areas, C i <C j ,Since the switching time is short and there are points with equal transmission rates between t3 and t4, it is assumed that the transmission loss of the two base stations is equal in t3 and t4. The formula calculates that switching at the position with equal transmission rate can reduce the transmission loss caused by switching delay and increase the transmission volume that the Internet of Vehicles can provide to users.

[0087] Therefore, according to Theorem 1, we need to find the position where the transmission rates of the two base stations are equal before and after the switch to reduce the loss caused by the network switch. Define each micro base station to have a vehicle entry point r i1 With the cut-out point r i2 ,like Figure 3 As shown, there will be the following three situations:

[0088]

[0089] be, af Represents the numbers of the two base stations before and after the switch, B be , P be represents the bandwidth and transmission power of the previous base station connected, B af , P af is the bandwidth and transmission power of the next base station. be1 、r af2 is the position updated by the attractor state. When the vehicle's position reaches the corresponding r i1 , r i2 When the cell position is reached, the value of the cell attractor is updated, and the network selection is performed based on the attractor state.

[0090] Analyze the impact of network switching failure. There are two situations in which network switching fails. One is that the signal-to-noise ratio is lower than the threshold, resulting in the base station being unable to effectively provide services to the vehicle after the switching is successful. The other is that the network switching fails due to a network link failure, requiring a secondary switching. For the first scenario, there are:

[0091]

[0092] in is the signal-to-noise ratio threshold that can guarantee the service, τ is the switching delay, The access condition.

[0093] When a wireless network switches multiple times due to link failure, there are:

[0094]

[0095] Where N i is the maximum number of handovers that base station i can accept. Assuming that the link failure probability of each handover is independent of each other during the network handover process, n+1 The probability of successful switching follows a binomial distribution:

[0096] Assuming that the probability of link failure in each switch is independent of each other during the network switching process, the probability of successful switching for the n+1th time follows a binomial distribution:

[0097] f(x)=x n (1-x) (2)

[0098] x is the probability of network switching failure, n is the number of switching failures, f(x) is the probability of successful switching for the n+1th time, and n<N i -2.

[0099] Therefore, the network switching loss G(v,n,x) is defined as:

[0100]

[0101] Where G(v,n,p) is the network switching loss rate, which is affected by speed, number of switching failures and link failure probability, such as Figure 4 Figure 5 As shown. The mean of the network switching loss rate is selected as the loss rate, so the average loss G is defined as:

[0102]

[0103] The cell attractor algorithm is defined as follows:

[0104]

[0105] m1 and m2 represent the concentration of protein products under different operons, that is, the attractor state. A represents the activity of the cell, while S(A) and D(A) are the rate coefficients of synthetic cells and decomposition cells, respectively. Both rate coefficients are increasing functions, and η1 and η2 are Gaussian white noise. When the attractor states are not much different, the attractor value will be disturbed by the noise, making it impossible for the cell to make a choice. When the attractor states are greatly different, the noise interference loses its effect, and the cell will choose to approach the attractor with a large value.

[0106] When determining the update position of the cell attractor, the value of the attractor needs to be calculated at the same time. The benefits of the Internet of Vehicles are associated with a pair of time-varying variables m1 and m2:

[0107]

[0108] D i is the transmission amount of the i-th base station, D Hi is the transmission volume of the macro base station during the corresponding base station access time, and the speed of the vehicle meets the condition

[0109] Through the attractor selection model, m1, m2 and D i , D Hi are associated and updated through the cell attractor model. When new time-varying variables m1 and m2 appear, analyze whether the state of the attractor changes. If the state of the attractor is not updated, then the Internet of Vehicles users will not choose to access the micro base station; when the state of the attractor changes, it means that the micro base station can provide better services for Internet of Vehicles users, and Internet of Vehicles users will choose to access the micro base station network to ensure their own services. According to the literature

[22] , when S(A) / D(A)>2, there will be two different attractors, and when S(A) / D(A)≤2, there will be a unique attractor. Define the synthesis rate and decomposition rate functions of the cell:

[0110]

[0111] Network switching loss, consider the necessity of network switching, and consider the transmission volume that the Internet of Vehicles can provide to the vehicle before and after the switching, such as Figure 4 As shown. For the relative position of the vehicle and the network, consider the relationship between distance and speed:

[0112]

[0113] Where v is the vehicle's speed, t represents the vehicle's travel time from the entry base station to the current position, and

[0114] Distance i It will change continuously as the vehicle moves. Use formula (13) to convert r i In connection with the speed of the vehicle, the transmission capacity that the Internet of Vehicles can provide to users is the product of the transmission rate and the time during which the vehicle resides in the network signal range. By integrating the transmission rate, we can get the following using the trigonometric function relationship:

[0115]

[0116]

[0117]

[0118] s i is the distance from the base station, r i is the distance between the vehicle and the base station, T i is the duration of access to the base station, and

[0119] For macro base stations, define r Hi is the distance between the macro base station and point M. When the vehicle is on the left side of the base station, the vehicle is close to the macro base station, r Hi Gradually decreases. When the vehicle is on the right side of the base station, the vehicle is far away from the macro base station. Hi Therefore, according to the relative position of the vehicle and the macro base station, s is defined Hi for:

[0120]

[0121] Integrating the transmission rate gives:

[0122]

[0123] Among them, D i is the transmission amount of the i-th base station, B i is the wireless network bandwidth. The result is

[0124]

[0125] D i for:

[0126]

[0127] in

[0128] Due to the randomness of micro base station deployment, there are mainly two scenarios: the first is whether a single base station needs to be switched, and the transmission volume that the Internet of Vehicles can provide to users before and after the switch is compared, such as Figure 7 ,The changes of transmission volume under different h conditions are compared.,The second scenario is when there are multiple adjacent micro base station networks, the selection of the next target ,network needs to be considered. When the next micro base station network is not unique, the ,network selection results under different network selection conditions are calculated ,and the appropriate wireless network is screened.

[0129] Through the above network selection method, the micro base stations of the macro base station are screened, and the micro base stations that can increase the transmission volume of the Internet of Vehicles users are selected for switching. In addition, the switching time is optimized to reduce the impact of the switching delay on the transmission volume. The impact of the micro base station on the transmission volume of the Internet of Vehicles is considered through the vehicle speed and switching delay, and the micro base station network that can increase the transmission volume is selected, such as Figure 8 and Fig. 9 As shown, the practicability of this method is demonstrated.

[0130] The present invention also provides a heterogeneous vehicle networking network selection system based on global benefit decision-making, including a base station parameter acquisition module, a first calculation module, a second calculation module, a candidate subset calculation module, a switching position acquisition module and a network switching module;

[0131] The base station parameter acquisition module is used to obtain the network topology map and base station parameters of the surrounding wireless network based on the currently connected wireless network base station. i ={L i , R i ,h i , P i , B i} and according to the relative position R of the base station i and the distance between the base station and the road h i , select the candidate network set M={M1, M2, ..., M n} T ;

[0132] The first calculation module is used to calculate the candidate network M={M1, M2, ..., M n} T Angle θ with the road i , predict and calculate the transmission rate C of each location i , and find the position where the transmission rate is equal, and calculate the switching position r i ;

[0133] The second calculation module is used to calculate the network transmission rate C i and switching delay S, calculate the transmission volume of different switching schemes;

[0134] The candidate subset calculation module is used to select base stations that can bring benefits to users as candidate subsets based on the transmission volume calculated by different schemes and the network switching loss rate G(v,n,p) using the cell attractor algorithm, and record the candidate network subset BU = {BS1, BS2, ..., BS k};

[0135] The handover position acquisition module is used to determine whether there is an adjacent base station subset BU = {BS1, BS2, ..., BS k} and update the candidate subset selected by the network, repeat S2, S3, S4, S5 to calculate the switching position r of the adjacent base station i ;

[0136] The network switching module is used to switch the position r according to the calculation i and the candidate network subset BU = {BS1, BS2, ..., BS k}Perform network switching.

[0137] In addition, the present invention can also provide a computer device, including a processor and a memory, the memory is used to store a computer executable program, the processor reads part or all of the computer executable program from the memory and executes it, and when the processor executes part or all of the computer executable program, it can implement the heterogeneous vehicle network selection method based on global benefit decision-making described in the present invention.

[0138] The computer device may be a laptop computer, a desktop computer or a workstation.

[0139] The processor may be a central processing unit (CPU), a graphics processing unit (GPU), a digital signal processor (DSP), an application specific integrated circuit (ASIC), or an off-the-shelf field programmable gate array (FPGA).

[0140] At the same time, a computer-readable storage medium is provided, in which a computer program is stored. When the computer program is executed by a processor, the heterogeneous vehicle network selection method based on global benefit decision-making described in the present invention can be implemented.

[0141] The memory of the present invention may be an internal storage unit of a laptop computer, a desktop computer or a workstation, such as a memory or a hard disk; or an external storage unit, such as a mobile hard disk or a flash memory card.

[0142] Computer-readable storage media may include computer storage media and communication media. Computer storage media include volatile and non-volatile, removable and non-removable media implemented by any method or technology for storing information such as computer-readable instructions, data structures, program modules or other data. Computer-readable storage media may include: read-only memory (ROM), random access memory (RAM), solid-state drive (SSD) or optical disk, etc. Among them, random access memory may include resistance random access memory (ReRAM) and dynamic random access memory (DRAM).

Claims

1. A heterogeneous vehicle network selection method based on global benefit decision, characterized in that: The following steps are involved: S1, according to the currently connected wireless network base station, obtain the network topology map and base station parameters M of the surrounding wireless networks i ={L i , R i ,h i , P i , B i } and according to the relative position R of the base station i and the distance between the base station and the road h i , select the candidate network set M={M1, M2, ..., M n } T ; S2, based on the obtained network topology and base station parameter information, calculate the candidate network M = {M1, M2, ..., M n } T Angle θ with the road i , predict and calculate the transmission rate C of each location i , and find the position where the transmission rate is equal, and calculate the switching position r i ; S3, according to the network transmission rate C i and switching delay S, calculate the transmission volume of different switching schemes; S4, based on the transmission volume calculated by different schemes and the network switching loss rate G(v,n,p), the cell attractor algorithm is used to select base stations that can bring benefits to users as candidate subsets, and the candidate network subset BU = {BS1, BS2, ..., BS k }; The cell attractor algorithm is defined as follows: m1 , m2 They represent the concentration of protein products under different operons, i.e., the attractor state, A represents the activity of the cell, and S(A) and D(A) are the rate coefficients of synthetic cells and decomposition cells, respectively. Both rate coefficients are increasing functions, and η1 and η2 are Gaussian white noises. When the attractor states are not much different, the attractor value will be disturbed by the noise, making it impossible for the cell to make a choice. When the attractor states are greatly different, the noise interference loses its effect, and the cell will choose to approach the attractor with a large value. When determining the update position of the cell attractor, it is also necessary to calculate the value of the attractor and compare the benefit of the Internet of Vehicles with a pair of time-varying variables m1 , m2 Related: D i is the transmission amount of the i-th base station, D Hi is the transmission volume of the macro base station during the corresponding base station access time, and the speed of the vehicle meets the condition Through the attractor selection model, m1, m2 and D i , D Hi is associated with each other and updated through the cell attractor model; when new time-varying variables m1 and m2 appear, analyze whether the state of the attractor changes; if the state of the attractor is not updated, then the Internet of Vehicles users will not choose to access the micro base station; when the state of the attractor changes, the micro base station can provide better services for the Internet of Vehicles users, and the Internet of Vehicles users will choose to access the micro base station network to ensure their own services. When S(A) / D(A)>2, there will be two different attractors. When S(A) / D(A)≤2, there is a unique attractor. The synthesis rate and decomposition rate functions of the cell are: The network switching loss rate G(v,n,p) is: Where x is the probability of network switching failure, n is the number of switching failures, and n<N i -2, the network switching loss rate is affected by vehicle speed, number of switching failures and link failure probability. The mean of the network switching loss rate is selected as the loss rate, and the average loss G is defined as: S5: Determine whether there is an adjacent base station subset BU = {BS1, BS2, ..., BS k } and update the candidate subset selected by the network, repeat S2, S3, S4, S5 to calculate the switching position r of the adjacent base station i There are two types of transmission volume calculation for different switching schemes: the first is whether a single base station needs to be switched, and compares the transmission volume that the Internet of Vehicles can provide to users before and after the switch; the second is when there are multiple adjacent micro base station networks, consider the selection of the next target network of the network. When the next micro base station network of the network is not unique, calculate the network selection results under different network selection conditions, and further screen the wireless network; the transmission volume of different switching schemes is calculated by integrating the transmission rate and the time of the vehicle's residence time in the network signal range, and using the trigonometric function relationship, it can be obtained: s i is the distance from the base station, r i is the distance between the vehicle and the base station, T i is the duration of access to the base station, and Among them, D i is the transmission amount of the i-th base station, B i is the wireless network bandwidth, and the result is D i for: in S6, according to the calculated switching position r i and the candidate network subset BU = {BS1, BS2, ..., BS k }Perform network switching.

2. The heterogeneous vehicle network selection method based on global benefit decision according to claim 1 is characterized in that: When looking for locations with equal transmission rates, use distance to find locations with equal transmission rates, using the formula: where r i is the hand-off position of the ith base station. If there is C i (r i )=C j (r j ), at the i-th base station r i Switching is performed between base station i and base station j, and it is determined that the transmission rate during the switching process is the part with the lowest transmission rate of the two base stations in the overlapping area, α is the distance attenuation index, and N is the power of the noise.

3. The heterogeneous vehicle network selection method based on global benefit decision according to claim 1 is characterized in that: Use Shannon's formula to calculate the transmission capacity of Internet of Vehicles users: C i =B i log2(1+φ i ) Among them, φ i is the signal-to-noise ratio, N is the power of Gaussian white noise, P i is the transmission power of the i-th wireless network base station, c is the propagation speed, r i is the distance between the vehicle and base station i, α is the distance attenuation index, which ranges from 2 to 6, and the propagation speed and frequency are constants. The above formula is simplified to:

4. A heterogeneous Internet of Vehicles network selection system based on global benefit decision, characterized in that: A method for selecting a heterogeneous vehicle network based on global benefit decision-making according to any one of claims 1 to 3, comprising a base station parameter acquisition module, a first calculation module, a second calculation module, a candidate subset calculation module, a switching position acquisition module, and a network switching module; The base station parameter acquisition module is used to obtain the network topology map and base station parameters of the surrounding wireless network based on the currently connected wireless network base station. i ={L i , R i ,h i , P i , B i } and according to the relative position R of the base station i and the distance between the base station and the road h i , select the candidate network set M={M1, M2, ..., M n } T ; The first calculation module is used to calculate the candidate network M={M1, M2, ..., M n } T Angle θ with the road i , predict and calculate the transmission rate C of each location i , and find the position where the transmission rate is equal, and calculate the switching position r i ; The second calculation module is used to calculate the network transmission rate C i and switching delay S, calculate the transmission volume of different switching schemes; The candidate subset calculation module is used to select base stations that can bring benefits to users as candidate subsets based on the transmission volume calculated by different schemes and the network switching loss rate G(v,n,p) using the cell attractor algorithm, and record the candidate network subset BU = {BS1, BS2, ..., BS k }; The handover position acquisition module is used to determine whether there is an adjacent base station subset BU = {BS1, BS2, ..., BS k } and update the candidate subset selected by the network, repeat S2, S3, S4, S5 to calculate the switching position r of the adjacent base station i ; The network switching module is used to switch the position r according to the calculation i and the candidate network subset BU = {BS1, BS2, ..., BS k }Perform network switching.

5. A computer device, characterized in that: It includes a processor and a memory, wherein an executable program is stored in the memory, and when the processor executes the executable program, it can execute the heterogeneous vehicle network selection method based on global benefit decision as described in any one of claims 1 to 3.

6. A computer-readable storage medium, characterized in that: A computer program is stored in a computer-readable storage medium. When the computer program is executed by a processor, it can implement the heterogeneous vehicle network selection method based on global benefit decision as described in any one of claims 1 to 3.

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