CN112929850A - Internet of vehicles data returning method facing edge computing environment - Google Patents

Internet of vehicles data returning method facing edge computing environment Download PDF

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CN112929850A
CN112929850A CN202110141757.2A CN202110141757A CN112929850A CN 112929850 A CN112929850 A CN 112929850A CN 202110141757 A CN202110141757 A CN 202110141757A CN 112929850 A CN112929850 A CN 112929850A
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vehicle
vehicles
node
link
lane
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张德干
曹利香
张捷
张婷
赵彭真
赵德新
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Tianjin University of Technology
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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
    • H04W4/30—Services specially adapted for particular environments, situations or purposes
    • 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]
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W24/00—Supervisory, monitoring or testing arrangements
    • H04W24/02—Arrangements for optimising operational condition
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
    • H04W4/30—Services specially adapted for particular environments, situations or purposes
    • H04W4/40—Services specially adapted for particular environments, situations or purposes for vehicles, e.g. vehicle-to-pedestrians [V2P]
    • H04W4/46—Services specially adapted for particular environments, situations or purposes for vehicles, e.g. vehicle-to-pedestrians [V2P] for vehicle-to-vehicle communication [V2V]
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W40/00—Communication routing or communication path finding
    • H04W40/02—Communication route or path selection, e.g. power-based or shortest path routing
    • H04W40/026—Route selection considering the moving speed of individual devices
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W40/00—Communication routing or communication path finding
    • H04W40/02—Communication route or path selection, e.g. power-based or shortest path routing
    • H04W40/12—Communication route or path selection, e.g. power-based or shortest path routing based on transmission quality or channel quality
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W40/00—Communication routing or communication path finding
    • H04W40/02—Communication route or path selection, e.g. power-based or shortest path routing
    • H04W40/20—Communication route or path selection, e.g. power-based or shortest path routing based on geographic position or location
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W40/00—Communication routing or communication path finding
    • H04W40/02—Communication route or path selection, e.g. power-based or shortest path routing
    • H04W40/22—Communication route or path selection, e.g. power-based or shortest path routing using selective relaying for reaching a BTS [Base Transceiver Station] or an access point

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Abstract

An Internet of vehicles data returning method oriented to an edge computing environment belongs to the field of Internet of things. The method provides a reliable transmission strategy based on V2I direct transmission and V2V auxiliary transmission aiming at the return problem faced by vehicles in the internet of vehicles already driving out of the RSU communication range before the unloading task is completed. Firstly, estimating the maximum transmission delay of the unloaded task amount and calculating the effective service life of a link to judge whether the auxiliary transmission is invalid. Secondly, the speed, direction and position factors of the vehicle are comprehensively considered when an auxiliary transmission strategy is designed, the indexes are quantized into a stable effective value, and a communication link is established by calculating the stable effective value of the neighbor nodes and comparing the stable effective value, so that high-quality transmission of data is guaranteed to be completed within limited time. Experiments show that compared with other algorithms, the method has better performance and certain practical value.

Description

Internet of vehicles data returning method facing edge computing environment
Technical Field
The invention belongs to the field of Internet of things, and particularly relates to an Internet of vehicles data returning method facing an edge computing environment.
Background
In the context of the Internet of everything, the Internet of vehicles (IOV) is gradually coming into public view. Through processing devices such as a Global Positioning System (GPS), a Radio Frequency Identification (RFID) technology, and a sensor, the Vehicle can acquire the environment and the state information of the Vehicle, and through a mobile ad hoc and communication technology, multi-directional network connection and resource sharing between the Vehicle and the Vehicle (V2V), between the Vehicle and the Person (V2P), between the Vehicle and the roadside intelligence (V2I), and an application platform can be achieved. The Internet of vehicles gradually realizes intelligent management of traffic, intelligent dynamic acquisition of information and intelligent control of vehicles. With the rapid development of the internet of vehicles and the increase of the number of vehicles, the generation of massive data can cause that local computing and storage resources cannot effectively meet the requirements in time, and the cloud computing-based solution of the problems can cause a great amount of time delay and high consumption.
Edge computing refers to a new model that provides computing and storage capabilities at the edge of a network. The basic idea is to transfer partial computing and storage capacity of the original cloud computing model to edge devices of the network, such as base stations, gateways, routers and the like, so that end-to-end time delay is reduced, the internal capacity of the bottom sensing network is excavated, the intellectualization of the bottom devices is improved, and the computing and storage pressure of the bottom devices is relieved.
In an internet of vehicles environment, after the edge server has processed the computing task, it needs to be transferred from the edge server to the moving vehicle. For some emergency messages and road dangerous situations, the emergency messages and the road dangerous situations can be timely and effectively transmitted to the vehicles in the target area. The data transmission and calculation research under the edge calculation architecture can effectively solve the problems of transmission delay and reliability caused by insufficient calculation and storage resources of the Internet of things equipment. Therefore, the research on the return strategy of vehicle task unloading in the edge computing complex environment has important theoretical value and practical significance.
Disclosure of Invention
The invention aims to solve the problem of return transmission selection when unloading tasks return in an internet of vehicles, due to the moving characteristics of vehicles and the limited communication range of roadside units and vehicles, the vehicles already leave the communication range of RSUs (Road Side units) before the unloading tasks are completed. The invention provides a reliable transmission strategy based on V2I direct transmission and V2V auxiliary transmission. Firstly, estimating the maximum transmission delay of the unloaded task quantity and calculating the effective service life of a link to judge whether the auxiliary transmission is invalid. Secondly, the speed, direction and position factors of the vehicle are comprehensively considered when an auxiliary transmission strategy is designed, the indexes are quantized into a stable effective value, and a communication link is established by calculating the stable effective value of the neighbor nodes and comparing the stable effective value, so that high-quality transmission of data is guaranteed to be completed within limited time. Experiments show that compared with other algorithms, the method has better performance and certain practical value.
The invention relates to a vehicle networking data returning method facing to an edge computing environment, which mainly comprises the following key steps:
1, establishing a model:
1.1, establishing a road and vehicle region model;
1.2, establishing a calculation region model;
1.3, establishing a data transmission area model;
the design of the Internet of vehicles data returning method facing the edge computing environment comprises the following steps:
2.1, initializing a state;
2.2, link maintenance time evaluation;
2.3, defining and calculating a stable effect value;
2.4, V2V auxiliary strategy algorithm description;
2.5, backhaul algorithm description.
Step 1.1, a road and vehicle region model is established, namely, a scene that two opposite lanes exist on the road is considered, one lane is called as a lane (forward direction) from west to east, the other lane is called as a lane (reverse direction) from east to west, N _ vehicle vehicles are assumed to be randomly distributed on the road in the road, and the vehicle speed of the lane A is a formula vaThe speed of lane B is vbThe density of the vehicles is rho, N _ RSU roadside units are randomly distributed in the region, meanwhile, all RSUs are provided with edge servers with certain computing and storage capacities, and for most computing scenes, the vehicles are required to unload computing tasks to the RSUs for computing.
The method for establishing the calculation region model in the step 1.2 is as follows, the method mainly researches scenes needing vehicles to unload calculation tasks to RSU for calculation, defaults that data to be calculated unloaded to an edge server is larger than data output after calculation, and assumes that the number of the unloading tasks is CtaskThe total bandwidth of the uplink data is BupThe resource needed for completing a certain computing task is M, and the computing speed of the server is SMECThen the time from unload to task completion is as shown in equation 1:
Figure BDA0002928844370000021
the method for establishing the data transmission region model in the step 1.3 comprises the following steps, the data transmission modes in the model comprise V2I and V2V, and the data transmission modes in the model have respective advantages and disadvantages, and the method uses a V2I waiting strategy and a V2V auxiliary return strategy:
(1) V2I wait policy: the RSU transmits the data to be transmitted back to the next RSU through the core network, and waits for the vehicle to enter the coverage range of the RSU and establishes communication for transmission in a V2I mode;
(2) V2V assisted backhaul strategy: in the area uncovered by the RSU, communication is performed by finding a relay node, and there are two ways of finding a relay node, because in a bidirectional lane, transmission can be performed through nodes in the same direction, or transmission can be performed by nodes in an opposite lane, and transmission through the opposite lane requires the RSU to transmit data to the next RSU first.
Further, in step 2.1 the vehicle is state initialized, assuming that the average speed of the source vehicle S _ vehicle is vsThe average speed of the destination vehicle D _ vehicle is vdAt the initial time (the time when the source node and the destination node establish a connection), the initial position of the vehicle S _ vehicle is ps(0) The initial position of the vehicle D _ vehicle is pd(0) The maximum distance radius of the connection established between the source node and the destination node is R, and the initial distance between the two workshops is d0Is expressed as shown in equation 2:
d0＝||pd(0)-ps(0)||，(0<d0≤R) (2)
suppose Xs(t) and Xd(t) represents the displacement amounts of the two vehicles within the time interval t, respectively, as shown in equation 3:
Xs(t)＝vst,Xd(t)＝vdt (3)
assume the size of the backhaul task is CdownThe bandwidth of the communication channel between vehicles is Bv2vThen, the transmission delay of the backhaul task is as shown in equation 4:
Figure BDA0002928844370000031
the vehicles are randomly distributed on the road, assuming that the vehicles are driven into a poisson distribution and the parameter is λ (λ represents the average number of events occurring within a certain time or unit time), then at time 0, t]Within the range, the probability of m vehicles entering is prAs shown in equation 5:
Figure BDA0002928844370000032
in the same-direction double-lane environment, the distribution parameter of the lane 1 is assumed to be lambda1Distribution parameter λ of the traffic lane 22Let R' be δ R, where 0 < δ ≦ 1, then
The cumulative distribution function expression of the source vehicle node and the closest node distance within the same lane in the communication range thereof is shown in equation 6:
Figure BDA0002928844370000033
the cumulative distribution function expression of the distances between the source vehicle node and the nearest nodes in different lanes within its communication range is shown in equation 7:
Figure BDA0002928844370000034
assuming that the reference node has M inter-layer neighbors, and the distance between the reference node and the farthest inter-layer neighbor is defined as Y, Y can be expressed as shown in equation 8:
Figure BDA0002928844370000035
the cumulative distribution function expression of Y is shown in equation 9:
Figure BDA0002928844370000036
Figure BDA0002928844370000041
in the V2V-assisted transmission strategy, relay nodes are selected in a stripe-by-stripe manner, and the selection of the ith relay node depends on the (l-1) th relay. Assuming that there are k neighbors on lane 1 and the distance of one hop on lane 1 is X, the conditional assignment for the second hop is shown in equation 10:
Figure BDA0002928844370000042
in step 2.2, a link maintenance time evaluation mode is provided, two scenes of a same-direction lane and a reverse lane are considered, when the relay node is searched in the same direction, the target vehicle D _ vehicle drives out of an RSU coverage area and drives in the same direction with the relay vehicle S _ vehicle, and the initial distance between the two vehicles is D0(0＜d0R is less than or equal to R), then
(1) When v iss＞vdIn the process, the distance between the two vehicles is smaller and smaller, the rear vehicle gradually exceeds the front vehicle and increases the distance between the two vehicles until the rear vehicle drives away from each other, the distance relation is shown as a formula 11, and the link survival time is shown as a formula 12:
Xs-Xd＝d0+R (11)
Figure BDA0002928844370000043
(2) when v iss＜vdIn the meantime, the distance between the two vehicles is increased, and when the distance between the vehicles is greater than the communication distance between the vehicles, the connection is disconnected, the relationship between the distances is shown in formula 13, and the link survival time is shown in formula 14:
Xs-Xd+d0＝R (13)
Figure BDA0002928844370000051
(3) when v iss＝vdWhen the two vehicles are in a relatively stationary state, the time for which link establishment is effective is considered infinite, and t ∞ assumes that the maximum speed of the forward road is vmaxMinimum velocity vmin,vmin＜vd＜vmaxService life t of a link established in a forward lanepAs shown in equation 15:
Figure BDA0002928844370000052
when a relay node is searched on an opposite lane, the destination vehicle D _ vehicle drives away from the RSU coverage area, and the destination vehicle D _ vehicle and the relay vehicle S _ vehicle drive in different directions to establish a link, wherein the initial distance between the two vehicles is D0(0＜d0R is less than or equal to R), then
Let the average speed of the source vehicle S _ vehicle be vsThe average speed of the destination vehicle D _ vehicle is vdRegardless of the relationship between the speed of the source node and the speed of the target node, the distance relationship is shown in equation 16, and the link lifetime is shown in equation 17:
Xs+Xd＝d0 (16)
Figure BDA0002928844370000053
assuming that the speed ranges of the reverse road and the forward road are the same, the maximum speed is vmaxMinimum velocity vmin,vmin＜vd＜vmaxService life t of a link established in a forward lanenAs shown in equation 18:
Figure BDA0002928844370000054
the stable values in step 2.3 are defined and calculated as follows, the stable values (Link stability and efficiency) are mainly used to evaluate the stability and transmission efficiency of the Link, and the larger the value is, the more ideal the Link status is, otherwise, the less ideal the Link status is, and the definition is shown in formula 19:
Figure BDA0002928844370000055
wherein rho is the density of the vehicles of the candidate node i, the unit is vehicle/kilometer, and other influence factors can be known by an observation formulaFixed, vehicle flow density is proportional to LSE, viIs a vector of velocity, has directivity, and has a value of an integer,
Figure BDA0002928844370000056
is a relative speed influence factor for considering the influence of relative speed on the stable effect of the link, when other factors are fixed, the relative speed is inversely proportional to the LSE, diDThe Euclidean distance from a node i to a target node is represented, when other factors are fixed, the relative distance is in direct proportion to the LSE, and meanwhile, alpha + beta + gamma is 1;
for the weight estimation of the index, a network layer Analysis (ANP) method is used, as shown in fig. 4, the objective of this step is to find the best next hop forwarding node, compare the result comparison matrix of the influence factor size of the element, and for the judgment matrix, sum the elements in each matrix by a summation method to obtain a vector α ═ (α ═ α1，α2…αi)τ；
Summarizing each vector to obtain unweighted hypermatrices, normalizing each vector in the unweighted hypermatrices, and defining
Figure BDA0002928844370000061
Wherein alpha isiIs a vector value of the corresponding element,
Figure BDA0002928844370000062
the sum of m vectors is used to obtain the feature vector corresponding to the maximum feature value, wherein the feature vector is omega (omega)1，ω2…ωi)τ；
The weighted super-matrix can be obtained by summarizing c ═ α ω, and then the weighted super-matrix is subjected to stability processing by the formula 20 on the basis of the weighted super-matrix
Figure BDA0002928844370000063
Step 2.4 the V2V assist strategy algorithm is described as follows:
Figure BDA0002928844370000064
Figure BDA0002928844370000071
step 2.5 the backhaul algorithm is described as follows:
Figure BDA0002928844370000072
the invention has the advantages and positive effects that:
the invention mainly designs a data returning method of the Internet of vehicles facing to an edge computing environment, and mainly researches the returning selection problem of vehicles which are driven out of the RSU communication range before the unloading task is completed. The invention considers the position of the vehicle and the effective service life of the link, provides a reliable transmission strategy for adaptively selecting a V2I direct transmission mode and a V2V auxiliary transmission mode according to the actual situation, estimates the maximum transmission time delay through the unloaded task amount and judges which transmission mode is used. The speed, direction and position factors of the vehicle are comprehensively considered when an auxiliary transmission strategy is designed, the indexes are quantized into a stable effective value, and an optimal scheme is established by calculating the stable effective value of the neighbor nodes and comparing the stable effective values, so that high-timeliness and high-reliability transmission of data is guaranteed. Experiments show that the invention has certain practical value.
Drawings
FIG. 1 is a diagram of a network of vehicles edge computing model;
FIG. 2 is a co-directional lane scene diagram;
FIG. 3 is a reverse lane scene diagram;
FIG. 4 is a network analytic hierarchy process diagram;
FIG. 5 is a graph of different vehicle densities versus data delivery delays;
FIG. 6 is a graph of different vehicle densities versus package delivery rate;
FIG. 7 is a graph of different vehicle densities versus forwarding node ratios;
FIG. 8 is a graph of different speeds versus data delivery latency;
FIG. 9 is a graph of different speeds versus packet delivery rate;
FIG. 10 is a graph of different speeds versus forwarding node ratios;
FIG. 11 is a graph of the relationship between different RSU spacing and data delivery latency;
FIG. 12 is a graph of the relationship between different RSU spacing and packet delivery rate;
FIG. 13 is a flowchart of the data returning method of the Internet of vehicles oriented to the edge computing environment of the present invention.
Detailed Description
Example 1:
in this embodiment, a NS-2.35 platform is used to perform a simulation experiment, perform a simulation analysis on the algorithm provided by the present invention, and perform a comparison analysis on the auxiliary backhaul strategy provided by the present invention, and a no-co (without using an auxiliary vehicle) backhaul strategy, a ra-co (randomly selecting a vehicle for auxiliary download), a CPB (based on a connectivity probability), a DSRelay (dynamic timeslot-based assistance method), and an NICDM (gapless assisted backhaul algorithm). The simulation parameters are shown in table 1.
TABLE 1 simulation parameters
Figure BDA0002928844370000081
Referring to fig. 13, the data returning method of the internet of vehicles for the edge computing environment in the embodiment mainly includes the following key steps:
1, establishing a model:
1.1, establishing a road and vehicle region model;
1.2, establishing a calculation region model;
1.3, establishing a data transmission area model;
the design of the Internet of vehicles data returning method facing the edge computing environment comprises the following steps:
2.1, initializing a state;
2.2, link maintenance time evaluation;
2.3, defining and calculating a stable effect value;
2.4, V2V auxiliary strategy algorithm description;
2.5, backhaul algorithm description.
Step 1.1, a road and vehicle region model is established, namely, a scene that two opposite lanes exist on the road is considered, one lane is called as a lane (forward direction) from west to east, the other lane is called as a lane (reverse direction) from east to west, N _ vehicle vehicles are assumed to be randomly distributed on the road in the road, and the vehicle speed of the lane A is a formula vaThe speed of lane B is vbThe density of the vehicles is rho, N _ RSU roadside units are randomly distributed in the region, meanwhile, all RSUs are provided with edge servers with certain computing and storage capacities, and for most computing scenes, the vehicles are required to unload computing tasks to the RSUs for computing.
The method for establishing the calculation region model in the step 1.2 is as follows, the method mainly researches scenes needing vehicles to unload calculation tasks to RSU for calculation, defaults that data to be calculated unloaded to an edge server is larger than data output after calculation, and assumes that the number of the unloading tasks is CtaskThe total bandwidth of the uplink data is BupThe resource needed for completing a certain computing task is M, and the computing speed of the server is SMECThen the time from unload to task completion is as shown in equation 1:
Figure BDA0002928844370000091
the method for establishing the data transmission region model in the step 1.3 comprises the following steps, the data transmission modes in the model comprise V2I and V2V, and the data transmission modes in the model have respective advantages and disadvantages, and the method uses a V2I waiting strategy and a V2V auxiliary return strategy:
(1) V2I wait policy: the RSU transmits the data to be transmitted back to the next RSU through the core network, and waits for the vehicle to enter the coverage range of the RSU and establishes communication for transmission in a V2I mode;
(2) V2V assisted backhaul strategy: in the area uncovered by the RSU, communication is performed by finding a relay node, and there are two ways of finding a relay node, because in a bidirectional lane, transmission can be performed through nodes in the same direction, or transmission can be performed by nodes in an opposite lane, and transmission through the opposite lane requires the RSU to transmit data to the next RSU first.
In step 2.1 the vehicle is state initialized, assuming that the average speed of the source vehicle S _ vehicle is vsThe average speed of the destination vehicle D _ vehicle is vdAt the initial time (the time when the source node and the destination node establish a connection), the initial position of the vehicle S _ vehicle is ps(0) The initial position of the vehicle D _ vehicle is pd(0) The maximum distance radius of the connection established between the source node and the destination node is R, and the initial distance between the two workshops is d0Is expressed as shown in equation 2:
d0＝||pd(0)-ps(0)||，(0<d0≤R) (2)
suppose Xs(t) and Xd(t) represents the displacement amounts of the two vehicles within the time interval t, respectively, as shown in equation 3:
Xs(t)＝vst,Xd(t)＝vdt(3)
assume the size of the backhaul task is CdownThe bandwidth of the communication channel between vehicles is Bv2vThen, the transmission delay of the backhaul task is as shown in equation 4:
Figure BDA0002928844370000101
the vehicles are randomly distributed on the road, assuming that the vehicles are driven into a poisson distribution and the parameter is λ (λ represents the average number of events occurring within a certain time or unit time), then at time 0, t]Within the range, the probability of m vehicles entering is prAs shown in equation 5:
Figure BDA0002928844370000102
in the same-direction double-lane environment, the distribution parameter of the lane 1 is assumed to be lambda1Distribution parameter λ of the traffic lane 22Let R' be δ R, where 0 < δ ≦ 1, then the cumulative distribution function expression for the source vehicle node and its closest node spacing in the lane within communication range is shown in equation 6:
Figure BDA0002928844370000103
the cumulative distribution function expression of the distances between the source vehicle node and the nearest nodes in different lanes within its communication range is shown in equation 7:
Figure BDA0002928844370000104
assuming that the reference node has M inter-layer neighbors, and the distance between the reference node and the farthest inter-layer neighbor is defined as Y, Y can be expressed as shown in equation 8:
Figure BDA0002928844370000105
the cumulative distribution function expression of Y is shown in equation 9:
Figure BDA0002928844370000106
Figure BDA0002928844370000111
in the V2V assisted transmission strategy, relay nodes are selected in a stripe-by-stripe manner, the selection of the ith relay node depends on the (l-1) th relay, and assuming that there are k neighbors on the 1 st lane, and the distance of one hop on the 1 st lane is X, the conditional assignment of the second hop is as shown in equation 10:
Figure BDA0002928844370000112
in step 2.2, a link maintenance time evaluation mode is provided, two scenes of a same-direction lane and a reverse lane are considered, when the relay node is searched in the same direction, the target vehicle D _ vehicle drives out of an RSU coverage area and drives in the same direction with the relay vehicle S _ vehicle, and the initial distance between the two vehicles is D0(0＜d0R is less than or equal to R), then
(1) When v iss＞vdIn the process, the distance between the two vehicles is smaller and smaller, the rear vehicle gradually exceeds the front vehicle and increases the distance between the two vehicles until the rear vehicle drives away from each other, the distance relation is shown as a formula 11, and the link survival time is shown as a formula 12:
Xs-Xd＝d0+R (11)
Figure BDA0002928844370000113
(2) when v iss＜vdIn the meantime, the distance between the two vehicles is increased, and when the distance between the vehicles is greater than the communication distance between the vehicles, the connection is disconnected, the relationship between the distances is shown in formula 13, and the link survival time is shown in formula 14:
Xs-Xd+d0＝R (13)
Figure BDA0002928844370000114
(3) when v iss＝vdWhen the two vehicles are in a relatively static state, the effective time for link establishment is considered infinite, and t ∞
Suppose that the maximum speed of the forward road is vmaxMinimum velocity vmin,vmin＜vd＜vmaxService life t of a link established in a forward lanepAs shown in equation 15:
Figure BDA0002928844370000121
when a relay node is searched on an opposite lane, the destination vehicle D _ vehicle drives away from the RSU coverage area, and the destination vehicle D _ vehicle and the relay vehicle S _ vehicle drive in different directions to establish a link, wherein the initial distance between the two vehicles is D0(0＜d0R is less than or equal to R), then
Let the average speed of the source vehicle S _ vehicle be vsThe average speed of the destination vehicle D _ vehicle is vdRegardless of the relationship between the speed of the source node and the speed of the target node, the distance relationship is shown in equation 16, and the link lifetime is shown in equation 17:
Xs+Xd＝d0 (16)
Figure BDA0002928844370000122
assuming that the speed ranges of the reverse road and the forward road are the same, the maximum speed is vmaxMinimum velocity vmin,vmin＜vd＜vmaxService life t of a link established in a forward lanenAs shown in equation 18:
Figure BDA0002928844370000123
the stable values in step 2.3 are defined and calculated as follows, the stable values (Link stability and efficiency) are mainly used to evaluate the stability and transmission efficiency of the Link, and the larger the value is, the more ideal the Link status is, otherwise, the less ideal the Link status is, and the definition is shown in formula 19:
Figure BDA0002928844370000124
where ρ is the density of vehicles at the candidate node i in units of vehicles/thousandMeter, the observation formula shows that when other influencing factors are fixed, the traffic flow density is in direct proportion to the LSE, and viIs a vector of velocity, has directivity, and has a value of an integer,
Figure BDA0002928844370000125
is a relative speed influence factor for considering the influence of relative speed on the stable effect of the link, when other factors are fixed, the relative speed is inversely proportional to the LSE, diDThe Euclidean distance from a node i to a target node is represented, when other factors are fixed, the relative distance is in direct proportion to the LSE, and meanwhile, the value of alpha t beta + gamma is 1;
the weight estimation of the index uses a network layer Analysis (ANP) method, the aim of the step is to find the optimal next hop transmitting node, compare the result comparison matrix of the influence factor size of the element, and for the judgment matrix, the element in each matrix is summed by a summation method to obtain the vector alpha (alpha ═ alpha [ (. alpha.) ]1，α2…αi)τ；
Summarizing each vector to obtain unweighted hypermatrices, normalizing each vector in the unweighted hypermatrices, and defining
Figure BDA0002928844370000131
Wherein alpha isiIs a vector value of the corresponding element,
Figure BDA0002928844370000132
the sum of m vectors is used to obtain the feature vector corresponding to the maximum feature value, wherein the feature vector is omega (omega)1，ω2…ωi)τ；
The weighted super-matrix can be obtained by summarizing c ═ α ω, and then the weighted super-matrix is subjected to stability processing by the formula 20 on the basis of the weighted super-matrix
Figure BDA0002928844370000133
Step 2.4 the V2V assist strategy algorithm is described as follows:
Figure BDA0002928844370000134
step 2.5 the backhaul algorithm is described as follows:
Figure BDA0002928844370000141
the present invention contemplates an environment in which a vehicle network is combined with edge computing, as illustrated in the FIG. 1 diagram of an edge computing model of a vehicle network. Referring to fig. 2 and 3, to simplify the model, consider a scenario in which there are two opposite lanes on the road, one from west to east and the other from east to west, the former being referred to as the a lane (forward) and the latter being the B lane (reverse). In the road, assuming that N _ vehicle are randomly distributed on the road, the speed of the lane A is the formula vaThe speed of lane B is vb. The density of the vehicle is ρ. In the region, N _ RSU roadside units are randomly distributed, meanwhile, all RSUs are provided with edge servers with certain computing and storing capabilities, and for most computing scenes, vehicles are required to unload computing tasks onto the RSUs for computing.
This example was tested in a simulation experiment. The transmission strategy provided by the invention is evaluated by changing the density and the speed factor of vehicles entering a lane, researching the distribution density of RSUs and other factors and utilizing three performance indexes of a data packet delivery rate, a data delivery time delay and a forwarding node ratio.
The experimental procedure will consider three performance indicators, which are:
1. the delivery rate of the data package. Is defined as the ratio between the number of data packets successfully transmitted to the destination node and the number of data packets transmitted by the source node. The index reflects data transmission reliability.
2. Data delivery latency. Also called end-to-end transmission delay, refers to the time delay of a data packet from packet generation to delivery to the destination. This metric indicates the speed at which the target receives a data packet after it is sent from the source node and is used to evaluate the efficiency of the transmission.
3. The forwarding node ratio. The total node number ratio of the relay nodes participating in forwarding on the lane is defined, the overhead for the reverse link is used, and the more relay nodes participating in forwarding, the greater the overhead of the network.
The simulation experiment results of this example are as follows:
1. under the condition of changing the vehicle density on the lane, the consistency of other factors is ensured, and the three performances of the five methods are compared
1) Relationship between different vehicle densities and data delivery delays
As is clear from the graph of fig. 5 showing the relationship between different vehicle densities and data delivery delays, no-co without vehicle-assisted transmission has performance independent of vehicle density due to the transmission using V2I. While the remaining four methods all decrease the delivery delay of the data as the density of the vehicles increases. When the relay node is selected, the algorithm provided by the invention ensures that the data transmission is finished in the life cycle of the link, prevents the time consumed by the link interruption caused by the movement of the node, and preferentially considers the node closest to the target node as the relay node under the condition of equal LSE. Experimental analysis shows that the feedback algorithm provided by the invention has greater advantage in timeliness.
2) Relationship between different vehicle densities and package delivery rates
Fig. 6 shows the relationship between different vehicle densities and packet delivery rates. As can be seen from fig. 6, as the vehicle density increases, the delivery rate of R-packs tends to increase for all four methods except no-co. Experiments prove that when the vehicle density is the same, the delivery rate of the data packet of the algorithm provided by the invention is always higher than that of other methods.
3) Relationship between different vehicle densities and forwarding node ratios
Fig. 7 shows the relationship between different vehicle densities and forwarding node ratios. As can be seen from fig. 7, the auxiliary transmission strategy herein is also minimal in terms of link overhead, because the present invention comprehensively considers factors such as relative distance and speed factor when constructing a link, and guarantees the minimum number of hops on the premise of guaranteeing quality when constructing the link.
2. Under the condition of changing the average speed of the vehicle, other factors are ensured to be consistent, and the performance indexes of the five methods are compared
1) Relationship between differential speed and data delivery latency
Fig. 8 shows the relationship between different speeds and data delivery delays. As is clear from fig. 8, no-co, which does not use vehicle-assisted transmission, has a speed-independent performance because it uses V2I for transmission. As the vehicle speed increases, the average end-to-end delay becomes larger because the speed increases, resulting in a change in the network topology, and the existing path may no longer meet the communication requirement, resulting in a need to restart the route discovery process, which undoubtedly increases the transmission delay, but the algorithm of the present invention has better performance than other algorithms.
2) Relationship between different speeds and packet delivery rates
Figure 9 shows the relationship between different speeds and packet delivery rates. As can be seen from fig. 9, the delivery rate of R-packs for all four methods except no-co tends to decrease as the speed factor increases. This is because as the vehicle speed increases, the effective link time of the link decreases, which may cause frequent reconnection and even increase the network hop count, but the packet delivery rate of the algorithm proposed by the present invention is always higher than that of the other methods.
3) Relationship between different speeds and forwarding node ratios
Figure 10 is a graph of the relationship between different speeds and forwarding node ratios. It can be seen from fig. 10 that an increase in link overhead with increasing speed leads to an increase in the number of hops, which also validates the previous analysis.
3. Under the condition of changing the RSU coverage density, other factors are ensured to be consistent, and three performances of the five methods are compared
Fig. 11 and fig. 12 show the relationship between different RSU spacings and data delivery delays and the relationship between different RSU spacings and packet delivery rates, respectively. As shown in fig. 11 and 12, it can be seen from the experimental results that as the RSU spacing is enlarged, the performance of each transmission strategy is reduced, and when the deployment density of RSUs is increased, the development of the internet of vehicles is better promoted.
Experiments show that the return algorithm provided by the invention achieves better effect. According to the actual situation, a V2I direct transmission mode and a reliable transmission strategy of V2V auxiliary transmission are selected in a self-adaptive mode, the maximum transmission delay is estimated according to the unloaded task amount, and the transmission mode is judged. The speed, direction and position factors of the vehicle are comprehensively considered when an auxiliary transmission strategy is designed, the indexes are quantized into a stable effective value, and an optimal scheme is established by calculating the stable effective value of the neighbor nodes and comparing the stable effective values, so that the stability of data is ensured.

Claims (9)

1. A vehicle networking data returning method facing to an edge computing environment is characterized by mainly comprising the following steps:
1, establishing a model:
1.1, establishing a road and vehicle region model;
1.2, establishing a calculation region model;
1.3, establishing a data transmission area model;
the design of the Internet of vehicles data returning method facing the edge computing environment comprises the following steps:
2.1, initializing a state;
2.2, link maintenance time evaluation;
2.3, defining and calculating a stable effect value;
2.4, V2V auxiliary strategy algorithm description;
2.5, backhaul algorithm description.
2. The method for returning data of internet of vehicles facing to edge computing environment as claimed in claim 1, wherein the road and vehicle region model is established in step 1.1, that is, the scene of two opposite lanes on the road is considered, one from west to east and the other from east to west, the former is called as lane a (forward) and the latter is called as lane B (reverse), the data of internet of vehicles facing to edge computing environment is returned to the roadIn the interior, assuming that N _ vehicle are randomly distributed on the road, the speed of the lane A is the formula vaThe speed of lane B is vbThe density of the vehicles is rho, N _ RSU roadside units are randomly distributed in the region, meanwhile, all RSUs are provided with edge servers with certain computing and storage capacities, and for most computing scenes, the vehicles are required to unload computing tasks to the RSUs for computing.
3. The method for returning data of internet of vehicles facing edge computing environment as claimed in claim 1, wherein the method for establishing the computing area model in step 1.2 is as follows, the method focuses on the research of the scene that the vehicle needs to unload the computing task to the RSU for computing, the default data to be computed that is unloaded to the edge server is larger than the data that is output after computing, and it is assumed that the number of unloaded tasks is CtaskThe total bandwidth of the uplink data is BupThe resource needed for completing a certain computing task is M, and the computing speed of the server is SMECThen the time from unload to task completion is as shown in equation 1:
Figure FDA0002928844360000011
4. the method for returning data in internet of vehicles facing edge computing environment in claim 1, wherein the method for establishing data transmission area model in step 1.3 is as follows, the data transmission mode in the model has V2I and V2V, which have both advantages and disadvantages, and the method uses V2I waiting strategy and V2V auxiliary returning strategy:
(1) V2I wait policy: the RSU transmits the data to be transmitted back to the next RSU through the core network, and waits for the vehicle to enter the coverage range of the RSU and establishes communication for transmission in a V2I mode;
(2) V2V assisted backhaul strategy: in the area uncovered by the RSU, communication is performed by finding a relay node, and there are two ways of finding a relay node, because in a bidirectional lane, transmission can be performed through nodes in the same direction, or transmission can be performed by nodes in an opposite lane, and transmission through the opposite lane requires the RSU to transmit data to the next RSU first.
5. The method for returning data to internet of vehicles facing edge computing environment as claimed in claim 1, wherein in step 2.1, the vehicle is initialized to state, assuming that the average speed of the source vehicle S _ vehicle is vsThe average speed of the destination vehicle D _ vehicle is vdAt the initial time (the time when the source node and the destination node establish a connection), the initial position of the vehicle S _ vehicle is ps(0) The initial position of the vehicle D _ vehicle is pd(0) The maximum distance radius of the connection established between the source node and the destination node is R, and the initial distance between the two workshops is d0Is expressed as shown in equation 2:
d0＝||pd(0)-ps(0)||，(0＜d0≤R) (2)
suppose Xs(t) and Xd(t) represents the displacement amounts of the two vehicles within the time interval t, respectively, as shown in equation 3:
Xs(t)＝vst,Xd(t)＝vdt (3)
assume the size of the backhaul task is CdownThe bandwidth of the communication channel between vehicles is Bv2vThen, the transmission delay of the backhaul task is as shown in equation 4:
Figure FDA0002928844360000021
the vehicles are randomly distributed on the road, assuming that the vehicles are driven into a poisson distribution and the parameter is λ (λ represents the average number of events occurring within a certain time or unit time), then at time 0, t]Within the range, the probability of m vehicles entering is prAs shown in equation 5:
Figure FDA0002928844360000022
in the same-direction double-lane environment, the distribution parameter of the lane 1 is assumed to be lambda1Distribution parameter λ of the traffic lane 22Let R' be δ R, where 0 < δ ≦ 1, then the cumulative distribution function expression for the source vehicle node and its closest node spacing in the lane within communication range is shown in equation 6:
Figure FDA0002928844360000023
the cumulative distribution function expression of the distances between the source vehicle node and the nearest nodes in different lanes within its communication range is shown in equation 7:
Figure FDA0002928844360000024
assuming that the reference node has M inter-layer neighbors, and the distance between the reference node and the farthest inter-layer neighbor is defined as Y, Y can be expressed as shown in equation 8:
Figure FDA0002928844360000025
the cumulative distribution function expression of Y is shown in equation 9:
Figure FDA0002928844360000026
Figure FDA0002928844360000031
in the V2V assisted transmission strategy, relay nodes are selected in a stripe-by-stripe manner, the selection of the ith relay node depends on the (1-1) th relay, and assuming that there are k neighbors on the 1 st lane, and the distance of one hop on the 1 st lane is X, the conditional assignment of the second hop is as shown in equation 10:
Figure FDA0002928844360000032
6. the method for returning data of internet of vehicles facing edge computing environment as claimed in claim 1, wherein in step 2.2 we propose a link maintenance time evaluation method, and considering two scenarios of same-direction lane and reverse lane, when finding relay node in same direction, the destination vehicle D _ vehicle moves out of RSU coverage area, and travels in same direction with relay vehicle S _ vehicle, and the initial distance between two vehicles is D0(0＜d0R is less than or equal to R), then
(1) When v iss＞vdIn the process, the distance between the two vehicles is smaller and smaller, the rear vehicle gradually exceeds the front vehicle and increases the distance between the two vehicles until the rear vehicle drives away from each other, the distance relation is shown as a formula 11, and the link survival time is shown as a formula 12:
Xs-Xd＝d0+R (11)
Figure FDA0002928844360000041
(2) when v iss＜vdIn the meantime, the distance between the two vehicles is increased, and when the distance between the vehicles is greater than the communication distance between the vehicles, the connection is disconnected, the relationship between the distances is shown in formula 13, and the link survival time is shown in formula 14:
Xs-Xd+d0＝R (13)
Figure FDA0002928844360000042
(3) when v iss＝vdWhen the two vehicles are in a relatively static state, the effective time for link establishment is considered infinite, and t ∞
Suppose that the maximum speed of the forward road is vmaxMinimum velocity vmin，vmin＜vd＜vmaxService life t of a link established in a forward lanepAs shown in equation 15:
Figure FDA0002928844360000043
when a relay node is searched on an opposite lane, the destination vehicle D _ vehicle drives away from the RSU coverage area, and the destination vehicle D _ vehicle and the relay vehicle S _ vehicle drive in different directions to establish a link, wherein the initial distance between the two vehicles is D0(0＜d0R is less than or equal to R), then
Let the average speed of the source vehicle S _ vehicle be vsThe average speed of the destination vehicle D _ vehicle is vdRegardless of the relationship between the speed of the source node and the speed of the target node, the distance relationship is shown in equation 16, and the link lifetime is shown in equation 17:
Xs+Xd＝d0 (16)
Figure FDA0002928844360000044
assuming that the speed ranges of the reverse road and the forward road are the same, the maximum speed is vmaxMinimum velocity vmin，vmin＜vd＜vmaxService life t of a link established in a forward lanenAs shown in equation 18:
Figure FDA0002928844360000045
7. the method for returning data of internet of vehicles towards edge computing environment as claimed in claim 1, wherein said stable value in step 2.3 is defined and calculated as follows, the stable value (Link stability and efficiency) is mainly used to evaluate the stability and transmission efficiency of the Link, and the larger the value is, the more ideal the Link status is, otherwise, the less ideal it is, and its definition is shown in formula 19:
Figure FDA0002928844360000046
wherein rho is the density of the vehicles of the candidate node i, the unit is vehicle/kilometer, and the observation formula shows that when other influence factors are fixed, the traffic flow density is in direct proportion to the LSE, and v isiIs a vector of velocity, has directivity, and has a value of an integer,
Figure FDA0002928844360000047
is a relative speed influence factor for considering the influence of relative speed on the stable effect of the link, when other factors are fixed, the relative speed is inversely proportional to the LSE, diDThe Euclidean distance from a node i to a target node is represented, when other factors are fixed, the relative distance is in direct proportion to the LSE, and meanwhile, alpha + beta + gamma is 1;
the weight estimation of the index uses a network layer Analysis (ANP) method, the aim of the step is to find the optimal next hop transmitting node, compare the result comparison matrix of the influence factor size of the element, and for the judgment matrix, the element in each matrix is summed by a summation method to obtain the vector alpha (alpha ═ alpha [ (. alpha.) ]1,α2…αi)τ；
Summarizing each vector to obtain unweighted hypermatrices, normalizing each vector in the unweighted hypermatrices, and defining
Figure FDA0002928844360000051
Wherein alpha isiIs a vector value of the corresponding element,
Figure FDA0002928844360000052
the sum of m vectors is used to obtain the feature vector corresponding to the maximum feature value, wherein the feature vector is omega (omega)1,ω2…ωi)τ；
The weighted super-matrix can be obtained by summarizing c ═ α ω, and then the weighted super-matrix is subjected to stability processing by the formula 20 on the basis of the weighted super-matrix
Figure FDA0002928844360000053
8. The edge-computing-environment-oriented internet of vehicles data backhaul method according to claim 1, wherein the V2V auxiliary policy algorithm described in step 2.4 is described as follows:
V2V-based auxiliary backhaul strategy for Algorithm 1
1) Initializing road vehicle density rho, returned data volume CdownInformation of vehicle nodes (speed, direction, location), road maximum speed vmaxMinimum velocity vmin；
2) Calculating the minimum link time t according to equation (4)transIf, if
Figure FDA0002928844360000054
Figure FDA0002928844360000055
3) Repetition of
4) Calculating a reverse speed influence factor;
5) calculating a reverse distance factor;
6) updating the LSE according to equation (19);
7) until all neighbor nodes are calculated, selecting the node with the maximum LSE value from the neighbor nodes as a relay node, and repeatedly executing the previous process;
8) if a communication link is established with the node D within the time threshold range, returning to the state of correctly establishing the link;
9) otherwise
10) Repetition of
11) Calculating a forward speed influence factor;
12) calculating a forward distance factor;
13) updating the LSE according to equation (19);
14) and until all the neighbor nodes are calculated, selecting the node with the maximum LSE value from the neighbor nodes as a relay node, repeatedly executing the previous process, if a communication link is established with the node D within the time threshold range, returning the link to correctly establish a state value, and otherwise, returning to establish a failure state value.
9. The method for returning data in internet of vehicles towards edge computing environment according to claim 1, wherein the returning algorithm in step 2.5 is described as follows:
algorithm 2 complete backhaul algorithm
Inputting: vehicle attribute value
And (3) outputting: link state code
1) Judging the position of the target vehicle, if the target vehicle is still in the coverage range of the unit, directly transmitting the V2I, returning to the link success state and exiting, if the vehicle runs to an adjacent roadside unit, directly switching to the third step, and if the target vehicle is located in the range not covered by the roadside unit, performing the second step;
2) calling an algorithm 1, judging according to the returned state value, and if the returned link is successfully established, directly returning to the state and exiting the algorithm;
3) and the roadside unit transmits the data to be transmitted back to the same-direction roadside unit closest to the vehicle, if the vehicle drives in, the V2I is directly transmitted, if the vehicle does not drive in, a monitoring state is set, the vehicle is waited to drive in the coverage range to directly communicate, and a link establishment state code is returned.
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