CN112737840A - Internet of vehicles relay selection and safe transmission method based on unmanned aerial vehicle assistance - Google Patents

Internet of vehicles relay selection and safe transmission method based on unmanned aerial vehicle assistance Download PDF

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CN112737840A
CN112737840A CN202011589537.8A CN202011589537A CN112737840A CN 112737840 A CN112737840 A CN 112737840A CN 202011589537 A CN202011589537 A CN 202011589537A CN 112737840 A CN112737840 A CN 112737840A
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node
relay
expressed
transmission
nodes
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CN112737840B (en
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王大伟
何亦昕
张若南
翟道森
唐晓
黄方慧
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Northwestern Polytechnical University
Shenzhen Institute of Northwestern Polytechnical University
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Shenzhen Institute of Northwestern Polytechnical University
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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L41/00—Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks
    • H04L41/14—Network analysis or design
    • H04L41/145—Network analysis or design involving simulating, designing, planning or modelling of a network
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B7/00—Radio transmission systems, i.e. using radiation field
    • H04B7/14—Relay systems
    • H04B7/15—Active relay systems
    • H04B7/185—Space-based or airborne stations; Stations for satellite systems
    • H04B7/18502—Airborne stations
    • H04B7/18504—Aircraft used as relay or high altitude atmospheric platform
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L63/00—Network architectures or network communication protocols for network security
    • H04L63/16—Implementing security features at a particular protocol layer
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
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    • Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
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Abstract

The invention discloses an unmanned aerial vehicle-assisted vehicle networking relay selection and safety transmission method, which comprises the steps of firstly constructing an unmanned aerial vehicle-assisted vehicle networking model, secondly analyzing and modeling a link service quality model from a source node to a relay node, a node forwarding capability model from the relay node to a target node, a physical layer safety model from the source node to the relay node, from the relay node to the target node, and from the relay node to the target node, formalizing a vehicle networking relay selection and safety transmission problem into a multi-target optimization problem related to link service quality, node forwarding capability and physical layer safety, and solving the problem by a greedy algorithm. The method can improve the success rate of network transmission, reduce the routing overhead and transmission delay, can ensure the safety of user information, and is more suitable for an intelligent transportation system compared with other Internet of vehicles transmission methods.

Description

Internet of vehicles relay selection and safe transmission method based on unmanned aerial vehicle assistance
Technical Field
The invention belongs to the technical field of Internet of vehicles, and particularly relates to a relay selection and safe transmission method for the Internet of vehicles.
Background
Nowadays, society has entered a new era of informatization and intellectualization, and the unmanned aerial vehicle technology also draws high attention of the public. The unmanned aerial vehicle is an unmanned aerial vehicle controlled by a radio system remote control and a self-contained program, can be used for aerial photography to obtain high-definition images by combining remote sensing and remote measuring technologies, and has wide application in the fields of military use, civil use and the like, such as transportation, monitoring, shooting, searching and the like. Unmanned aerial vehicles have gained wide application in the field of internet of vehicles as wireless relays in recent years. Compare with the car networking based on ground communication infrastructure, the car networking based on unmanned aerial vehicle is supplementary has obvious advantage:
(1) the low cost and the miniaturization of the equipment make the practical deployment of unmanned aerial vehicles more feasible. Under the condition that there is large-scale barrier to shelter from and make link quality deteriorate or because natural disasters lead to communication interruption, accessible deployment unmanned aerial vehicle provides wireless stadia connection for remote vehicle, but the vehicle networking application of auxiliary processing emergency and low delay.
(2) The unmanned aerial vehicle with high mobility supports quick response, has good scalability and survivability, can optimally adapt to a communication environment by dynamically adjusting the position of the unmanned aerial vehicle, provides wireless service for a plurality of ground vehicles, and realizes signal coverage.
(3) The unmanned aerial vehicle is used for assisting mobile communication, so that the capacity of the Internet of vehicles communication system can be greatly improved, limited frequency spectrum resources are fully utilized, the energy of the mobile terminal is effectively saved to a great extent, and the continuous normal working time of the Internet of vehicles is greatly prolonged.
However, practical wireless communication environments for internet of vehicles have a variable complexity, where there are many uncertain and non-human controlled interference factors, and relay selection and security issues have to be considered for communication using drones.
In the prior art, a relay selection scheme based on multi-parameter decision is provided, bandwidth and time delay of candidate relay nodes, a node switching predicted value and corresponding requirements of user nodes are comprehensively considered, performance of the candidate relays is evaluated by using a simple linear weighting function, and the optimal relays are finally obtained. The scheme has better advantages than the traditional scheme in the aspects of system throughput and relay switching times.
In the second prior art, the problem of eavesdropping nodes in the relay system of the unmanned aerial vehicle is solved by adopting a mode that an information source end sends an artificial interference signal to improve the safety capacity of the system. The result shows that the method has better safety capacity than the traditional fixed relay form, and can have the optimal power distribution scheme under the condition that the signal power transmitted by the information source end is certain.
But the problems of the prior art are as follows:
(1) the wireless channel used in the prior art is open, so that when a vehicle transmits private information, all vehicles within a signal coverage range can receive the signal, and a communication system is extremely vulnerable to various security threats, such as eavesdropping, interference, tampering and the like, and information is leaked at risk.
(2) In the second prior art, a decoding and forwarding protocol is adopted, the relay unmanned aerial vehicle demodulates, samples and judges, stores and decodes the received signals into original information, and then retransmits the original information after signal coding and frequency modulation are carried out again. However, the relay unmanned aerial vehicle adopting the scheme needs to completely and correctly decode the original signal before making a forwarding action, which causes a certain signal transmission delay, and fails to utilize the maneuverability of the unmanned aerial vehicle to transmit information in a storage-carrying-forwarding manner.
Disclosure of Invention
In order to overcome the defects of the prior art, the invention provides an unmanned aerial vehicle-assisted vehicle networking relay selection and safe transmission method, which comprises the steps of firstly constructing an unmanned aerial vehicle-assisted vehicle networking network model, secondly analyzing and modeling a link service quality model from a source node to a relay node, a node forwarding capability model from the relay node to a destination node, a physical layer safety model from the source node to the relay node, the relay node to the relay node and the relay node to the destination node, formalizing the vehicle networking relay selection and safe transmission problem into a multi-objective optimization problem related to link service quality, node forwarding capability and physical layer safety, and solving the problem through a greedy algorithm. The method can improve the success rate of network transmission, reduce the routing overhead and transmission delay, can ensure the safety of user information, and is more suitable for an intelligent transportation system compared with other Internet of vehicles transmission methods.
The technical scheme adopted by the invention for solving the technical problem comprises the following steps:
step 1: constructing an Internet of vehicles network model based on unmanned aerial vehicle assistance;
step 1-1: an unmanned aerial vehicle-assisted vehicle network is formed by M network nodes, and the M network nodes form a network node set NkK is 1, 2.. times, M, the network node is a vehicle node or an unmanned aerial vehicle node; the communication range of the unmanned aerial vehicle node is ruThe communication range of the vehicle node is rvNodes within communication range are able to communicate with each other; periodically interacting Hello messages among the network nodes, and discovering available neighbor nodes and real-time link states; the Hello message comprises an information interaction time delay THChannel capacity C and position information, and updating the information after each Hello message interaction;
when source node NaWhen data is sent, the source node N is calculatedaAnd destination node NbDistance L betweena,b：
Figure BDA0002868205570000031
Wherein N isaHas the coordinates of (N)a(x),Na(y),Na(z))，NbHas the coordinates of (N)b(x),Nb(y),Nb(z)); if L isa,b<r, then directly sending, otherwise, the source node NaSelecting neighbor node N according to subsequent stepsjThe relay node is used as a relay node for relay forwarding;
the selection method of r is as follows:
when source node NaWhen being an unmanned plane node, r is ru；
When source node NaWhen being a vehicle node, r ═ rv；
Step 1-2: the information transmission is carried out by utilizing the mobility of the unmanned aerial vehicle and the vehicle in a storage-carrying-forwarding mode, and the transmission path is expressed as follows:
path{Na,tn,kn,Nb}＝{(Na,t1,k1,Nb),...,(Na,tn,kn,Nb)} (2)
wherein k isnRelay node representing the nth hop, tnRepresents the time of the nth hop;
step 1-3: from the source node NaTo the destination node NbEnd-to-end transmission delay Ta,bExpressed as:
Figure BDA0002868205570000032
wherein, i represents the ith hop,
Figure BDA0002868205570000033
indicating the transmission delay of the ith hop,
Figure BDA0002868205570000034
indicating the transmission delay of the ith hop,
Figure BDA0002868205570000035
indicating the propagation delay of the i-th hop,
Figure BDA0002868205570000036
indicating the processing delay of the ith hop,
Figure BDA0002868205570000037
representing the carried time delay of the ith hop;
step 2: constructing a link service quality model from a source node to a relay node based on an unmanned aerial vehicle-assisted Internet of vehicles network model;
step 2-1: according to the Shannon formula, source node NaAnd relay node NjChannel capacity C betweena,jComprises the following steps:
Figure BDA0002868205570000038
where B denotes bandwidth, P denotes transmission power, ha,jRepresenting a slave source node NaTo the relay node NjA distance of n0Power spectral density representing channel noise, gamma represents path loss factor, ha,jRepresenting a slave source node NaTo the relay node NjSmall scale fading of ha,jExpressed as:
Figure BDA0002868205570000039
wherein h isa,jObeying an exponential distribution, i.e. | ha,j|2～E(λ)；
Step 2-2: definition R as source node NaWhen the transmission rate of Ca,jThe successful forwarding of the information can be realized when the transmission rate is more than or equal to R, and the successful transmission probability is Pa,j，Pa,jExpressed as:
Figure BDA0002868205570000041
wherein the content of the first and second substances,
Figure BDA0002868205570000042
step 2-3: a source node NaTo the relay node NjIs defined as the link quality of service I of the vehicle network based on the assistance of the unmanned planea,j，Ia,jExpressed as:
Figure BDA0002868205570000043
wherein, Ta,jRepresenting a source node NaTo the destination node NbThe end-to-end transmission delay of the network,
Figure BDA0002868205570000044
and
Figure BDA0002868205570000045
respectively represent source nodes NaTo the relay node NjThe transmission delay, the propagation delay and the processing delay;
and step 3: constructing a node forwarding capability model from a relay node to a destination node based on an unmanned aerial vehicle-assisted Internet of vehicles network model;
step 3-1: dividing the effective survival time of the information into l time intervals with the time unit of tau, wherein the mth time interval is expressed as taum(m is less than or equal to l); node liveness Dj(τm) Is pointed at taumTime, relay node N in the networkjThe frequency of encounters with other nodes is expressed as:
Figure BDA0002868205570000046
wherein S isj(τm) Is expressed at taumNode N in timejSet of meeting nodes, Sj(τm-1) Is expressed at taum-1Node N in timejA set of encountered nodes;
step 3-2: node NjAt taumTime and destination node NbInter-node encounter frequency degree Fj,b(τm) Expressed as:
Figure BDA0002868205570000047
wherein E isj,b(τm) Is expressed at taumNode N in timejAnd destination node NbThe number of times of the meeting is counted,
Figure BDA0002868205570000048
is expressed at taumNode N in timejThe number of encounters with all nodes in the network;
step 3-3: relay node N in networkjFrequency of encounters with other nodes Dj(τm) Frequency of encounters with nodes Fj,b(τm) Defined as the node forwarding capability Q of the drone-based assisted vehicle networkingj,b(τm)，Qj,b(τm) Expressed as:
Figure BDA0002868205570000051
in the formula (10), Dj(τm) Reflect node NjAt taumThe ratio of the number of new nodes encountered in time to the total number, Fj,b(τm) Reflect node NjAt taumThe ratio of the number of encounters with a specific node to the total number of encounters with other nodes in time;
and 4, step 4: based on an unmanned aerial vehicle-assisted Internet of vehicles network model, physical layer security models from a source node to a relay node, from the relay node to the relay node and from the relay node to a destination node are constructed;
step 4-1: assuming that an interception node Eve exists in the Internet of vehicles, intercepting the transmitted Internet of vehicles information; assuming that the codebooks employed by the different network nodes are different, the slave source node NaSecure transmission rate to first hop of first relay node
Figure BDA0002868205570000052
Expressed as:
Figure BDA0002868205570000053
wherein L isa,eRepresenting a source node NaDistance to eavesdropping node Eve, ha,eRepresenting a slave source node NaSmall scale fading, R, to eavesdropping node EvethRepresents the maximum allowable transmission rate, i.e., the safe transmission rate;
step 4-2: the safe transmission rate from the ith-1 relay node to the ith relay node hop
Figure BDA0002868205570000054
Expressed as:
Figure BDA0002868205570000055
wherein L isi-1,eRepresents the distance h from the i-1 th relay node to the eavesdropping node Evei-1,eThe small-scale fading from the i-1 th relay node to the eavesdropping node Eve is represented;
step 4-3: the safe transmission rate of the nth hop from the last relay node to the destination node
Figure BDA0002868205570000056
Expressed as:
Figure BDA0002868205570000061
wherein L isrelay-end,eRepresents the distance h from the last relay node to the eavesdropping node Everelay-end,eSmall-scale fading from the last relay node to the eavesdropping node Eve is represented;
and 5: constructing a target function and an optimization condition of relay selection and safe transmission based on a link service quality model, a node forwarding capability model and a physical layer safety model;
the objective function and optimization condition of relay selection and safe transmission are formalized into an optimization problem under a multi-constraint condition:
Figure BDA0002868205570000062
wherein E isjIndicating the quality of service of the link Ia,jAnd node forwarding capability Qj,b(τm) δ represents the minimum probability of successful transmission, δ ∈ (0, 1)]，MthA valid time representing the information;
step 6: solving by a greedy algorithm based on an objective function and an optimization condition of relay selection and safe transmission to construct an unmanned aerial vehicle assisted vehicle networking relay selection and safe transmission method;
step 6-1: for the source node NaThe number of its neighbor nodes is limited, so equation (14) is expressed as:
Figure BDA0002868205570000063
wherein r represents the number of neighbor nodes, EjIs a matrix of order r, i.e. Ej＝[Ia,1Q1,b(τm),Ia,2Q2,b(τm),...,Ia,rQr,b(τm)]1×r；
According to equation (5), the optimization problem under one multi-constraint condition formalized by relay selection and secure transmission method is expressed as:
Figure BDA0002868205570000071
step 6-2: using greedy algorithm, from the objective function
Figure BDA0002868205570000072
Of medium selection value Ia,rQr,b(τm) The largest neighbor node is used as a relay node, and the relay node meets constraint conditions C3.1-C3.5;
and 7: and (6) repeating the step (2) to the step (6) and selecting the relay node of the next hop until the information is transmitted to the destination node.
The invention has the following beneficial effects:
aiming at the problems in the prior art, the invention provides wireless line-of-sight connection for remote vehicles by deploying the unmanned aerial vehicle, can assist in processing emergency and low-delay Internet of vehicles application, and can effectively improve the success rate of network transmission, limit the routing overhead and reduce the transmission delay compared with the existing mechanism on the premise of ensuring the communication safety, the link reliability and the message effectiveness; meanwhile, the signal transmission delay is reduced by adopting a storage-carrying-forwarding mode, and aiming at the problem that the unmanned aerial vehicle relay system has eavesdropping nodes, the safety of information transmission is improved by utilizing a physical layer security technology, the information security of a user is guaranteed, and the method is more suitable for an intelligent transportation system compared with other Internet of vehicles transmission methods.
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FIG. 1 is a flow chart of the method of the present invention.
Fig. 2 is a performance comparison graph comparing transmission success rates of the unmanned-vehicle-assisted-based internet of vehicles, which is provided by the embodiment of the present invention, with a ground-based internet of vehicles (a relay selection and transmission method is adopted in the present invention) and relay selection and transmission are performed by an Epidemic method.
Fig. 3 is a performance comparison graph comparing transmission delay with a ground-based vehicle networking (the relay selection and transmission method of the present invention) and with a vehicle networking based on unmanned aerial vehicle assistance that performs relay selection and transmission by using an Epidemic method according to an embodiment of the present invention.
Fig. 4 is a performance comparison graph comparing the routing overhead with the ground-based internet of vehicles (the relay selection and transmission method of the present invention) and the unmanned-vehicle-assisted-based internet of vehicles that use the Epidemic method for relay selection and transmission, according to the embodiment of the present invention.
Detailed Description
The invention is further illustrated with reference to the following figures and examples.
As shown in fig. 1, a method for relay selection and secure transmission in internet of vehicles based on unmanned aerial vehicle assistance includes the following steps:
step 1: constructing an Internet of vehicles network model based on unmanned aerial vehicle assistance;
step 1-1: an unmanned aerial vehicle-assisted vehicle network is formed by M network nodes, and the M network nodes form a network node set NkK is 1, 2.. times, M, the network node is a vehicle node or an unmanned aerial vehicle node; the communication range of the unmanned aerial vehicle node is ruThe communication range of the vehicle node is rvNodes within communication range are able to communicate with each other; periodically interacting Hello messages among the network nodes, and discovering available neighbor nodes and real-time link states; the Hello message comprises an information interaction time delay THChannel capacity C and position information, and updating the information after each Hello message interaction;
when source node NaWhen data is sent, the source node N is calculatedaAnd destination node NbDistance L betweena,b：
Figure BDA0002868205570000081
Wherein N isaHas the coordinates of (N)a(x),Na(y),Na(z))，NbHas the coordinates of (N)b(x),Nb(y),Nb(z)); if L isa,b<r, then directly sending, otherwise, the source node NaSelecting neighbor node N according to subsequent stepsjThe relay node is used as a relay node for relay forwarding;
the selection method of r is as follows:
when source node NaWhen being an unmanned plane node, r is ru；
When source node NaWhen being a vehicle node, r ═ rv；
Step 1-2: the information transmission is carried out by utilizing the mobility of the unmanned aerial vehicle and the vehicle in a storage-carrying-forwarding mode, and the transmission path is expressed as follows:
path{Na,tn,kn,Nb}＝{(Na,t1,k1,Nb),...,(Na,tn,kn,Nb)} (2)
wherein k isnRelay node representing the nth hop, tnRepresents the time of the nth hop;
step 1-3: from the source node NaTo the destination node NbEnd-to-end transmission delay Ta,bExpressed as:
Figure BDA0002868205570000082
wherein, i represents the ith hop,
Figure BDA0002868205570000083
indicating the transmission delay of the ith hop,
Figure BDA0002868205570000084
indicating the transmission delay of the ith hop,
Figure BDA0002868205570000085
indicating the propagation delay of the i-th hop,
Figure BDA0002868205570000091
indicating the processing delay of the ith hop,
Figure BDA0002868205570000092
representing the carried time delay of the ith hop;
step 2: constructing a link service quality model from a source node to a relay node based on an unmanned aerial vehicle-assisted Internet of vehicles network model;
step 2-1: according to the Shannon formula, source node NaAnd relay node NjChannel capacity C betweena,jComprises the following steps:
Figure BDA0002868205570000093
where B denotes bandwidth, P denotes transmission power, ha,jRepresenting a slave source node NaTo the relay node NjA distance of n0Power spectral density representing channel noise, gamma represents path loss factor, ha,jRepresenting a slave source node NaTo the relay node NjSmall scale fading of ha,jExpressed as:
Figure BDA0002868205570000094
wherein h isa,jObeying an exponential distribution, i.e. | ha,j|2～E(λ)；
Step 2-2: definition R as source node NaWhen the transmission rate of Ca,jThe successful forwarding of the information can be realized when the transmission rate is more than or equal to R, and the successful transmission probability is Pa,j，Pa,jExpressed as:
Figure BDA0002868205570000095
wherein the content of the first and second substances,
Figure BDA0002868205570000096
step 2-3: a source node NaTo the relay node NjIs defined as the link quality of service I of the vehicle network based on the assistance of the unmanned planea,j，Ia,jExpressed as:
Figure BDA0002868205570000097
wherein, Ta,jRepresenting a source node NaTo the destination node NbThe end-to-end transmission delay of the network,
Figure BDA0002868205570000098
and
Figure BDA0002868205570000099
respectively represent source nodes NaTo the relay node NjThe transmission delay, the propagation delay and the processing delay;
and step 3: constructing a node forwarding capability model from a relay node to a destination node based on an unmanned aerial vehicle-assisted Internet of vehicles network model;
step 3-1: dividing the effective survival time of the information into l time intervals with the time unit of tau, wherein the mth time interval is expressed as taum(m is less than or equal to l); node liveness Dj(τm) Is pointed at taumTime, relay node N in the networkjThe frequency of encounters with other nodes is expressed as:
Figure BDA0002868205570000101
wherein S isj(τm) Is expressed at taumNode N in timejSet of meeting nodes, Sj(τm-1) Is expressed at taum-1Node N in timejA set of encountered nodes;
step 3-2: node NjAt taumTime and destination node NbInter-node encounter frequency degree Fj,b(τm) Expressed as:
Figure BDA0002868205570000102
wherein E isj,b(τm) Is expressed at taumNode N in timejAnd destination node NbThe number of times of the meeting is counted,
Figure BDA0002868205570000103
is expressed at taumNode N in timejThe number of encounters with all nodes in the network;
step (ii) of3-3: relay node N in networkjFrequency of encounters with other nodes Dj(τm) Frequency of encounters with nodes Fj,b(τm) Defined as the node forwarding capability Q of the drone-based assisted vehicle networkingj,b(τm)，Qj,b(τm) Expressed as:
Figure BDA0002868205570000104
in the formula (10), Dj(τm) Reflect node NjAt taumThe ratio of the number of new nodes encountered in time to the total number, Fj,b(τm) Reflect node NjAt taumThe ratio of the number of encounters with a specific node to the total number of encounters with other nodes in time;
and 4, step 4: based on an unmanned aerial vehicle-assisted Internet of vehicles network model, physical layer security models from a source node to a relay node, from the relay node to the relay node and from the relay node to a destination node are constructed;
step 4-1: assuming that an interception node Eve exists in the Internet of vehicles, intercepting the transmitted Internet of vehicles information; assuming that the codebooks employed by the different network nodes are different, the slave source node NaSecure transmission rate to first hop of first relay node
Figure BDA0002868205570000105
Expressed as:
Figure BDA0002868205570000111
wherein L isa,eRepresenting a source node NaDistance to eavesdropping node Eve, ha,eRepresenting a slave source node NaSmall scale fading, R, to eavesdropping node EvethRepresents the maximum allowable transmission rate, i.e., the safe transmission rate;
step 4-2: from the ith-1 relay node to the ith relaySafe transmission rate of ith hop of node
Figure BDA0002868205570000112
Expressed as:
Figure BDA0002868205570000113
wherein L isi-1,eRepresents the distance h from the i-1 th relay node to the eavesdropping node Evei-1,eThe small-scale fading from the i-1 th relay node to the eavesdropping node Eve is represented;
step 4-3: the safe transmission rate of the nth hop from the last relay node to the destination node
Figure BDA0002868205570000114
Expressed as:
Figure BDA0002868205570000115
wherein L isrelay-end,eRepresents the distance h from the last relay node to the eavesdropping node Everelay-end,eSmall-scale fading from the last relay node to the eavesdropping node Eve is represented;
and 5: constructing a target function and an optimization condition of relay selection and safe transmission based on a link service quality model, a node forwarding capability model and a physical layer safety model;
the objective function and optimization condition of relay selection and safe transmission are formalized into an optimization problem under a multi-constraint condition:
Figure BDA0002868205570000116
wherein E isjIndicating the quality of service of the link Ia,jAnd node forwarding capability Qj,b(τm) δ represents the minimum probability of successful transmission, δ ∈ (0, 1)]，MthA valid time representing the information;
step 6: solving by a greedy algorithm based on an objective function and an optimization condition of relay selection and safe transmission to construct an unmanned aerial vehicle assisted vehicle networking relay selection and safe transmission method;
step 6-1: for the source node NaThe number of its neighbor nodes is limited, so equation (14) is expressed as:
Figure BDA0002868205570000121
wherein r represents the number of neighbor nodes, EjIs a matrix of order r, i.e. Ej＝[Ia,1Q1,b(τm),Ia,2Q2,b(τm),...,Ia,rQr,b(τm)]1×r；
According to equation (5), the optimization problem under one multi-constraint condition formalized by relay selection and secure transmission method is expressed as:
Figure BDA0002868205570000122
step 6-2: using greedy algorithm, from the objective function
Figure BDA0002868205570000123
Of medium selection value Ia,rQr,b(τm) The largest neighbor node is used as a relay node, and the relay node meets constraint conditions C3.1-C3.5;
and 7: and (6) repeating the step (2) to the step (6) and selecting the relay node of the next hop until the information is transmitted to the destination node.
The specific embodiment is as follows:
the embodiment simulates the vehicle networking relay selection and safety transmission method based on unmanned aerial vehicle assistance and the existing mechanism based on the same network parameters, and verifies the superiority of the method. The method comprises the following specific steps: the same network parameter is 45km multiplied by 35km, vehicles and unmanned planes are randomly placed in a simulation area, the communication range of the vehicles is 200m, the communication range of the unmanned planes and parked vehicle groups is 1000m, the number of the vehicles in the environment varies from 0 to 500, the number of the unmanned planes is 20, the driving speed of the vehicles is 0-50km/h, the flying speed of the unmanned planes is 0-70km/h, the flying height of the unmanned planes is 200m, the Hello packet interval is 0.1s, the information generation frequency is 30 s/piece, the information size is 1MB-5MB, the information effective time is 5h, and each node cache is 50 MB. The data of the following three aspects are counted: 1. a transmission success rate; 2. a transmission delay; 3. the routing overhead. And randomly selecting the target node and the source node, wherein the result is an average value after 10000 times of simulation.
The present invention is compared with performance (transmission success rate, transmission delay, routing overhead) of a ground-based vehicle networking (the relay selection and transmission method is the present invention), and an unmanned-plane-assisted vehicle networking based vehicle networking that performs relay selection and transmission by using an Epidemic method, as shown in fig. 2 to 4.
As can be seen from fig. 2 to 4, the present invention is superior to the existing mechanism in terms of transmission success rate, transmission delay, and routing overhead. Specifically, compared with the ground-based internet of vehicles (the relay selection and transmission method adopts the invention), the invention makes full use of flexible deployment of unmanned planes to select the relay nodes, when the number of vehicles reaches 150, the transmission success rate of the invention can be 96%, and at the moment, the transmission success rate of the ground-based internet of vehicles is only 78%. For the unmanned aerial vehicle-assisted vehicle networking based on relay selection and transmission by adopting the Epidemic method, the transmission delay is close to that of the unmanned aerial vehicle-assisted vehicle networking, but the routing overhead is far higher than that of the unmanned aerial vehicle-assisted vehicle networking based on the flood technology, the exponential rise trend is presented, network resources are rapidly consumed in the vehicle networking environment with limited resources, and the network survival time is reduced. In addition, the invention also considers the problem of information security in the transmission process, limits the transmission rate, prevents an eavesdropper from eavesdropping the information by utilizing the physical layer security technology, can effectively reduce the risk of information leakage, and can better meet the requirements of users on future intelligent traffic systems.
In summary, the relay selection and safe transmission method based on unmanned aerial vehicle assistance in the vehicle networking provided by the embodiment of the invention is to solve the problems in the prior art, firstly, a vehicle networking model based on unmanned aerial vehicle assistance is constructed, secondly, analyzing and modeling a link service quality model from a source node to a relay node, a node forwarding capability model from the relay node to a destination node, and physical layer security models from the source node to the relay node, from the relay node to the relay node, and from the relay node to the destination node, formalizing the relay selection and security transmission problem of the Internet of vehicles into a multi-target optimization problem related to link service quality, node forwarding capability and physical layer security, and solving the problem by a greedy algorithm, the method can improve the success rate of network transmission, reduce the routing overhead and transmission delay, can ensure the safety of user information, and is more suitable for an intelligent transportation system compared with other Internet of vehicles transmission methods.

Claims (1)

1. A relay selection and safe transmission method in Internet of vehicles based on unmanned aerial vehicle assistance is characterized by comprising the following steps:
step 1: constructing an Internet of vehicles network model based on unmanned aerial vehicle assistance;
step 1-1: an unmanned aerial vehicle-assisted vehicle network is formed by M network nodes, and the M network nodes form a network node set NkK is 1, 2.. times, M, the network node is a vehicle node or an unmanned aerial vehicle node; the communication range of the unmanned aerial vehicle node is ruThe communication range of the vehicle node is rvNodes within communication range are able to communicate with each other; periodically interacting Hello messages among the network nodes, and discovering available neighbor nodes and real-time link states; the Hello message comprises an information interaction time delay THChannel capacity C and position information, and updating the information after each Hello message interaction;
when source node NaWhen data is sent, the source node N is calculatedaAnd destination node NbDistance L betweena,b：
Figure FDA0002868205560000011
Wherein N isaHas the coordinates of (N)a(x),Na(y),Na(z))，NbHas the coordinates of (N)b(x),Nb(y),Nb(z)); if L isa,b<r, then directly sending, otherwise, the source node NaSelecting neighbor node N according to subsequent stepsjThe relay node is used as a relay node for relay forwarding;
the selection method of r is as follows:
when source node NaWhen being an unmanned plane node, r is ru；
When source node NaWhen being a vehicle node, r ═ rv；
Step 1-2: the information transmission is carried out by utilizing the mobility of the unmanned aerial vehicle and the vehicle in a storage-carrying-forwarding mode, and the transmission path is expressed as follows:
path{Na,tn,kn,Nb}＝{(Na,t1,k1,Nb),...,(Na,tn,kn,Nb)} (2)
wherein k isnRelay node representing the nth hop, tnRepresents the time of the nth hop;
step 1-3: from the source node NaTo the destination node NbEnd-to-end transmission delay Ta,bExpressed as:
Figure FDA0002868205560000012
wherein, i represents the ith hop,
Figure FDA0002868205560000013
indicating the transmission delay of the ith hop,
Figure FDA0002868205560000014
indicating the transmission delay of the ith hop,
Figure FDA0002868205560000015
indicating the propagation delay of the i-th hop,
Figure FDA0002868205560000016
indicating the processing delay of the ith hop,
Figure FDA0002868205560000017
representing the carried time delay of the ith hop;
step 2: constructing a link service quality model from a source node to a relay node based on an unmanned aerial vehicle-assisted Internet of vehicles network model;
step 2-1: according to the Shannon formula, source node NaAnd relay node NjChannel capacity C betweena,jComprises the following steps:
Figure FDA0002868205560000021
where B denotes bandwidth, P denotes transmission power, ha,jRepresenting a slave source node NaTo the relay node NjA distance of n0Power spectral density representing channel noise, gamma represents path loss factor, ha,jRepresenting a slave source node NaTo the relay node NjSmall scale fading of ha,jExpressed as:
Figure FDA0002868205560000022
wherein h isa,jObeying an exponential distribution, i.e. | ha,j|2～E(λ)；
Step 2-2: definition R as source node NaWhen the transmission rate of Ca,jThe successful forwarding of the information can be realized when the transmission rate is more than or equal to R, and the successful transmission probability is Pa,j，Pa,jExpressed as:
Figure FDA0002868205560000023
wherein the content of the first and second substances,
Figure FDA0002868205560000024
step 2-3: a source node NaTo the relay node NjIs defined as the link quality of service I of the vehicle network based on the assistance of the unmanned planea,j，Ia,jExpressed as:
Figure FDA0002868205560000025
wherein, Ta,jRepresenting a source node NaTo the destination node NbThe end-to-end transmission delay of the network,
Figure FDA0002868205560000026
and
Figure FDA0002868205560000027
respectively represent source nodes NaTo the relay node NjThe transmission delay, the propagation delay and the processing delay;
and step 3: constructing a node forwarding capability model from a relay node to a destination node based on an unmanned aerial vehicle-assisted Internet of vehicles network model;
step 3-1: dividing the effective survival time of the information into l time intervals with the time unit of tau, wherein the mth time interval is expressed as taum(m is less than or equal to l); node liveness Dj(τm) Is pointed at taumTime, relay node N in the networkjThe frequency of encounters with other nodes is expressed as:
Figure FDA0002868205560000031
wherein S isj(τm) Is expressed at taumNode N in timejSet of meeting nodes, Sj(τm-1) Is expressed at taum-1Node N in timejA set of encountered nodes;
step 3-2: node NjAt taumTime and destination node NbInter-node encounter frequency degree Fj,b(τm) Expressed as:
Figure FDA0002868205560000032
wherein E isj,b(τm) Is expressed at taumNode N in timejAnd destination node NbThe number of times of the meeting is counted,
Figure FDA0002868205560000033
is expressed at taumNode N in timejThe number of encounters with all nodes in the network;
step 3-3: relay node N in networkjFrequency of encounters with other nodes Dj(τm) Frequency of encounters with nodes Fj,b(τm) Defined as the node forwarding capability Q of the drone-based assisted vehicle networkingj,b(τm)，Qj,b(τm) Expressed as:
Figure FDA0002868205560000034
in the formula (10), Dj(τm) Reflect node NjAt taumThe ratio of the number of new nodes encountered in time to the total number, Fj,b(τm) Reflect node NjAt taumThe ratio of the number of encounters with a specific node to the total number of encounters with other nodes in time;
and 4, step 4: based on an unmanned aerial vehicle-assisted Internet of vehicles network model, physical layer security models from a source node to a relay node, from the relay node to the relay node and from the relay node to a destination node are constructed;
step 4-1: assuming that an interception node Eve exists in the Internet of vehicles, intercepting the transmitted Internet of vehicles information; assuming that the codebooks employed by the different network nodes are different, the slave source node NaSecure transmission rate to first hop of first relay node
Figure FDA0002868205560000035
Expressed as:
Figure FDA0002868205560000036
wherein L isa,eRepresenting a source node NaDistance to eavesdropping node Eve, ha,eRepresenting a slave source node NaSmall scale fading, R, to eavesdropping node EvethRepresents the maximum allowable transmission rate, i.e., the safe transmission rate;
step 4-2: the safe transmission rate from the ith-1 relay node to the ith relay node hop
Figure FDA0002868205560000041
Expressed as:
Figure FDA0002868205560000042
wherein L isi-1,eRepresents the distance h from the i-1 th relay node to the eavesdropping node Evei-1,eThe small-scale fading from the i-1 th relay node to the eavesdropping node Eve is represented;
step 4-3: the safe transmission rate of the nth hop from the last relay node to the destination node
Figure FDA0002868205560000043
Expressed as:
Figure FDA0002868205560000044
wherein L isrelay-end,eRepresents the distance h from the last relay node to the eavesdropping node Everelay-end,eSmall-scale fading from the last relay node to the eavesdropping node Eve is represented;
and 5: constructing a target function and an optimization condition of relay selection and safe transmission based on a link service quality model, a node forwarding capability model and a physical layer safety model;
the objective function and optimization condition of relay selection and safe transmission are formalized into an optimization problem under a multi-constraint condition:
Figure FDA0002868205560000045
wherein E isjIndicating the quality of service of the link Ia,jAnd node forwarding capability Qj,b(τm) δ represents the minimum probability of successful transmission, δ ∈ (0, 1)]，MthA valid time representing the information;
step 6: solving by a greedy algorithm based on an objective function and an optimization condition of relay selection and safe transmission to construct an unmanned aerial vehicle assisted vehicle networking relay selection and safe transmission method;
step 6-1: for the source node NaThe number of its neighbor nodes is limited, so equation (14) is expressed as:
Figure FDA0002868205560000051
wherein r represents the number of neighbor nodes, EjIs a matrix of order r, i.e. Ej＝[Ia,1Q1,b(τm),Ia,2Q2,b(τm),...,Ia,rQr,b(τm)]1×r；
According to equation (5), the optimization problem under one multi-constraint condition formalized by relay selection and secure transmission method is expressed as:
Figure FDA0002868205560000052
step 6-2: using greedy algorithm, from the objective function
Figure FDA0002868205560000053
Of medium selection value Ia,rQr,b(τm) The largest neighbor node is used as a relay node, and the relay node meets constraint conditions C3.1-C3.5;
and 7: and (6) repeating the step (2) to the step (6) and selecting the relay node of the next hop until the information is transmitted to the destination node.
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