CN115150325A - Reliable routing method applied to B5G vehicle-mounted network - Google Patents
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Abstract
The invention discloses a reliable routing method applied to a B5G vehicle-mounted network, relating to the technical field of vehicle-mounted network routing; by designing a B5G-based software-defined vehicle network architecture, a 5G base station based on a machine learning technology is used for predicting vehicle tracks, and time delay is reduced; a link performance detection mechanism is designed, the control overhead and the accuracy are balanced, and the link performance can be measured more accurately; a QoS routing algorithm of an improved genetic algorithm is utilized, cross-generation selection, a small environment strategy and a traditional genetic algorithm are combined, and a global view of an SDN controller is utilized to obtain a more reliable transmission path.
Description
Technical Field
The invention relates to the technical field of vehicle-mounted network routing, in particular to a reliable routing method applied to a B5G vehicle-mounted network.
Background
With the rapid development of economy, mobile networks and internet of things technology are gradually mature, how to realize intelligent driving, man-vehicle interconnection and vehicle-vehicle interconnection becomes a research hotspot, but the problems of vehicle surge, connection instability, effective signal transmission and the like are solved, the requirements on the safety and reliability of vehicle-mounted networks are gradually increased, and still great challenges are brought to the research of vehicle-mounted networks. The Software Defined Network (SDN) separates the control function from the forwarding function, is an emerging network architecture, improves the resource utilization efficiency and realizes the programmability of the network. The SDN is applied to the vehicle-mounted network, becomes Software Defined Vehicle Networks (SDVNs), and provides an effective solution for processing vehicle interconnection requirements, vehicle-mounted network topology management and network cost management.
The development of the 5G technology covers a plurality of fields such as industry, agriculture and traffic service industry, wherein the vehicle-mounted network is an important application field of 5G, but with the development of the vehicle-mounted network, the vehicle-mounted network becomes a heterogeneous large-scale network, and the B5G technology can provide an effective solution for the existing vehicle-mounted network. The B5G communication uses a higher frequency band for communication, so that the global coverage under the scene of sea, land, air and space is realized, different application scenes are processed by adopting technologies such as artificial intelligence and the like, the higher safety is further improved, and the network resource management and network intelligence level are improved.
The patent 'a cross-layer vehicle-mounted network routing method based on link transmission capability' discloses a cross-layer vehicle-mounted network routing method based on link transmission capability. The method comprehensively considers the routing method influencing the transmission capability of the link under the urban environment, calculates the data sending probability, the channel occupation probability and the like of the nodes, respectively discusses the condition of whether barriers exist among the nodes, expands the basic cross-layer routing protocol AODV protocol, and continuously updates the routing table according to the feedback information in the routing process. However, the method has the problems of large amount of broadcast information, unstable link transmission and the like, and cannot ensure reliable routing and uninterrupted transmission of data streams.
Disclosure of Invention
In order to solve the defects of the prior art, the invention aims to provide a reliable routing method applied to a B5G vehicle-mounted network, a B5G-based software-defined vehicle network architecture is designed, and a 5G base station based on a machine learning technology is used for predicting vehicle tracks; and a link performance detection mechanism is designed, and a reliable transmission path is calculated by using an improved genetic algorithm, so that the network performance is improved.
In order to achieve the purpose, the technical scheme adopted by the invention is as follows:
a reliable routing method applied to a B5G vehicle-mounted network comprises the following steps: designing an SDN network framework based on a B5G technology, and applying a WSMP protocol to a 5G system; establishing a self-adaptive monitoring mechanism; the route is calculated using a QoS routing algorithm based on a modified genetic algorithm.
The design of the SDN network framework based on the B5G technology specifically comprises the following steps:
the method comprises the steps of adopting an SDN framework based on a B5G technology, predicting a vehicle motion track by using a 5G base station, providing real-time data processing by using Multi-access Edge Computing (MEC), and predicting a next base station to be connected by a vehicle through machine learning.
The WSMP protocol is applied to the 5G system, and specifically comprises the following steps:
the WSMP protocol is applied to a 5G system, and a WSMP protocol framework comprises an NTPS module, an adaptation module and a 5G module; the NTPS module realizes the packaging and transmission of the WSMP protocol by broadcasting the WSA, and the adaptation module is used for adapting the WSMP protocol to the 5G module; the 5G module implements the MAC layer and the physical layer of the protocol stack, and sends data and filters and receives data.
The establishing of the self-adaptive monitoring mechanism specifically comprises the following steps:
controlling the balance between overhead and accuracy according to the network scale and link load change dynamic concept polling interval; calculating the update of the detection interval according to the bandwidth change rate and the last monitoring interval, wherein the bandwidth change rate is shown as a formula (1):
where Δ b is the rate of change of bandwidth, band is the width currently occupied by the link, lastBand is the last occupied bandwidth, ε 1 A real number greater than 0;
updating the detection interval as shown in equation (2):
wherein minPed is the minimum polling interval determined by the network scale; lasted is the last polling interval, maxPed is the maximum argument interval; alpha is alpha 1 And alpha 2 Is a set constant, and different polling interval changing strategies are adopted by judging the bandwidth change rate.
The self-adaptive monitoring mechanism comprises a monitoring point setting and a monitoring point traversing and message sending.
The set monitoring points are specifically: operating an LLDP protocol and setting a link;
the monitoring time for all links of the initialized link is minPed, and adding the monitoring queue;
and the controller receives the OpenFlow message of one link and updates the corresponding link bandwidth, link delay, packet loss rate and monitoring points.
The traversal monitoring points are specifically as follows: initializing global time;
detecting whether the monitoring queue is empty or not, and traversing all monitoring points if the monitoring queue is not empty;
and (4) continuously increasing the global time point by 1 until the time of the monitoring point is equal to the global time point, measuring the corresponding link and removing the monitoring point.
The QoS routing algorithm based on the improved genetic algorithm calculates the route, and comprises the following steps:
s1: network preprocessing, chromosome coding and fitness function construction are carried out;
s2: initializing a plurality of paths from a source node to a target node by adopting a depth-first traversal algorithm, and selecting an adjacent node which is not randomly accessed as a next node;
s3: selecting generation-crossing selection, namely selecting excellent chromosomes in the population of the iteration and the last iteration through a roulette method;
s4: cross selection, for any two chromosomes, randomly selecting a gene point as a cross point to generate two new chromosomes;
s5: performing mutation operation, namely randomly selecting a gene from a chromosome as a mutation point, and then generating a new path from the burst point to a target node by using a depth-first search algorithm;
s6: the microenvironment strategy increases a contrast mechanism of two generations of chromosomes in the crossing and mutation operations, if the fitness of offspring is higher than that of parent generation, the chromosomes are updated, otherwise, the chromosomes are not changed;
s7: deletion of chromosomes, wherein loops existing in chromosomes are caused by twice traversal deletion crossing or mutation operations;
by combining cross-generation selection, a microenvironment strategy and an original genetic algorithm and applying the cross-generation selection, the microenvironment strategy and the original genetic algorithm to a QoS routing algorithm, when the flow is injected into a network, an SDN controller runs an improved genetic algorithm to generate a path on the basis of a self-adaptive monitoring mechanism and sends the path to a flow table entry on a switch.
The specific process of S1 comprises the following steps:
s1.1: network preprocessing is carried out, edge nodes which do not meet the bandwidth requirement in the network are eliminated, the SDN controller deletes links which do not meet the data flow, and a virtual network which meets the bandwidth requirement is constructed;
s1.2: chromosome coding, namely, a variable-length chromosome coding mechanism is adopted, each chromosome represents a routing path, the first gene represents a source node, the last gene represents a target node, the chromosome sequence represents a path network node sequence, and the nodes on the chromosomes are ensured to be single;
s1.3: and constructing a fitness function and selecting link bandwidth, link time delay and packet loss rate as performance evaluation indexes.
The performance evaluation index calculation specifically comprises the following steps:
s1.3.1: the link bandwidth adopts a passive mode, the occupied bandwidth is measured according to the statistical data of a counter of a switch port, the bandwidth is measured by using the return information of rxBytes and txBytes, the bit number received and sent by the port is respectively represented, the switch s1 and the switch s2 are connected through the ports p1 and p2, the bandwidth is calculated in the time periods of t1 and t2, and the formula (3) and the formula (4) are shown as follows:
wherein the content of the first and second substances,
and
txBytes for port p1 at times t2 and t1 respectively,
and
rxBytes for p1 at times t2 and t1, respectively; data at the port p2 are respectively represented in formula (4);
T p1 and T p2 Respectively representing the total bit number of the ports p1 and p2 in the time period from t1 to t2, and taking the average value of the two ports as a linkA calculated value of occupied bandwidth;
s1.3.2: the link delay is measured by sending a Packet _ out message and an Echo request message, respectively.
And sending a Packet _ out message, sending the Packet _ out message carrying the timestamp to a switch s1 by the SDN controller, and forwarding the message to a switch s2 by the switch s1.
The sending of the Echo request message, the SDN controller respectively sends Echo request messages with timestamps to a switch s1 and a switch s2; the link delay calculation between the switches is as shown in equation (6):
where t is the path delay and t1 and t2 are the controller-to-switch delays, respectively.
S1.3.3: the packet loss rate, which is calculated by using txPackets and rxPackets information to respectively indicate the number of transmitted and received data packets, is shown in equations (7) and (8):
wherein the content of the first and second substances,
and
respectively representing the number of packets sent by the p1 port at times t2 and t1,
and
are respectively provided withRepresenting the number of data packets received by the p2 port at t2 and t 1; TP is the total number of data packets sent in the time period from the port t1 to the port t2, and RP represents the total number of data packets received in the time period from the port t1 to the port t 2; calculating the packet loss rate as shown in equation (9):
normalizing the performance evaluation indexes, setting different weights for different indexes, and calculating a fitness function as shown in a formula (10):
f(x)＝q 1 ×f band (x)+q 2 ×(1-f loss (x))+q 3 ×(1-f delay (x)) (10)
wherein, f band Is the ratio of the bandwidth of a chromosome to the sum of all chromosomes, q 1 Is f band The weight of (c); f. of loss Is the chromosome packet loss rate, q 2 Is composed of loss The weight of (c); f. of delay Is the chromosome delay ratio, q 2 Is f delay The weight of (c); q. q of 1 +q 2 +q 3 =1; value of fitness function of chromosome the largest is the routing path.
Adopt the produced beneficial effect of above-mentioned technical scheme to lie in:
1. the invention utilizes the 5G base station to position the vehicle and utilizes the machine learning technology to predict the vehicle, thereby reducing the time delay.
2. The invention designs a self-adaptive link detection mechanism, which balances control overhead and accuracy and can more accurately measure the performance of a link.
3. The QoS routing algorithm based on the improved genetic algorithm is used for obtaining a more reliable transmission path by combining cross-generation selection, a small environment strategy and a traditional genetic algorithm and by means of a global view of an SDN controller.
Drawings
Fig. 1 is a flowchart of a reliable routing method applied to a B5G vehicular network according to an embodiment of the present invention;
FIG. 2 is a diagram of a network architecture provided by an embodiment of the present invention;
fig. 3 is a simple topology diagram of a routing performance test according to an embodiment of the present invention;
fig. 4 is a complex topology diagram of a routing performance test provided by the embodiment of the present invention;
fig. 5 is a link performance design topology diagram provided by the embodiment of the present invention.
Detailed Description
The following detailed description of the present invention is provided in connection with the accompanying drawings and examples.
A reliable routing method applied to a B5G vehicle-mounted network comprises the following steps: designing an SDN network framework based on B5G technology, as shown in fig. 2, applying the WSMP protocol to a 5G system; establishing a self-adaptive monitoring mechanism; the route is calculated using a QoS routing algorithm based on a modified genetic algorithm.
The design of the SDN network framework based on the B5G technology specifically comprises the following steps:
the method comprises the steps of adopting an SDN framework based on a B5G technology, predicting the motion track of a vehicle by using a 5G base station, providing real-time data processing by using Multi-access Edge Computing (MEC), and predicting the next base station to be connected by the vehicle through machine learning.
The WSMP protocol is applied to the 5G system, and specifically comprises the following steps:
the WSMP protocol is applied to a 5G system, and the WSMP protocol framework comprises an NTPS module, an adaptation module and a 5G module; the NTPS module realizes the packaging and transmission of the WSMP protocol through broadcasting the WSA, and the adaptation module is used for adapting the WSMP protocol to the 5G module; the 5G module implements the MAC layer and the physical layer of the protocol stack, and sends data and filters and receives data.
The establishing of the self-adaptive monitoring mechanism specifically comprises the following steps:
controlling the balance between overhead and accuracy according to the network scale and link load change dynamic concept polling interval; calculating the update of the detection interval according to the bandwidth change rate and the last monitoring interval, wherein the bandwidth change rate is shown as a formula (1):
where Δ b is the rate of change of bandwidth, band is the width currently occupied by the link, lastBand is the last occupied bandwidth, ε 1 A real number greater than 0;
updating the detection interval as shown in equation (2):
wherein minPed is the minimum polling interval determined by the network scale; lasted is the last polling interval, maxPed is the maximum argument interval; alpha is alpha 1 And alpha 2 Is a set constant, and different polling interval changing strategies are adopted by judging the bandwidth change rate.
The self-adaptive monitoring mechanism comprises a monitoring point setting and a monitoring point traversing and message sending.
The set monitoring points are specifically as follows: operating an LLDP protocol and setting a link;
initializing the monitoring time of all links of the link to be minPed, and adding the minPed into a monitoring queue;
and the controller receives the OpenFlow message of one link and updates the corresponding link bandwidth, link delay, packet loss rate and monitoring points.
The traversal monitoring points are specifically as follows: initializing global time;
detecting whether the monitoring queue is empty or not, and traversing all monitoring points if the monitoring queue is not empty;
and (4) continuously increasing the global time point by 1 until the time of the monitoring point is equal to the global time point, measuring the corresponding link and removing the monitoring point.
The QoS routing algorithm based on the improved genetic algorithm calculates a route, as shown in fig. 1, including the following steps:
s1: performing network preprocessing, chromosome coding and fitness function construction, wherein the designed network topology is shown as figure 3 and figure 4;
s1.1: network preprocessing is carried out, edge nodes which do not meet the bandwidth requirement in the network are eliminated, the SDN controller deletes links which do not meet the data flow, and a virtual network which meets the bandwidth requirement is constructed;
s1.2: chromosome coding, namely, a variable-length chromosome coding mechanism is adopted, each chromosome represents a routing path, the first gene represents a source node, the last gene represents a target node, the chromosome sequence represents a path network node sequence, and the nodes on the chromosomes are ensured to be single;
s1.3: constructing a fitness function and selecting link bandwidth, link time delay and packet loss rate as performance evaluation indexes;
in this embodiment, a network topology is designed as shown in fig. 5, and includes a ryu controller, two switches, and four hosts.
The performance evaluation index calculation specifically comprises the following steps:
s1.3.1: the link bandwidth adopts a passive mode, the occupied bandwidth is measured according to the statistical data of a counter of a switch port, the bandwidth is measured by using the return information of rxBytes and txBytes, the bit number received and sent by the port is respectively represented, the switch s1 and the switch s2 are connected through the ports p1 and p2, the bandwidth is calculated in the time periods of t1 and t2, and the formula (3) and the formula (4) are shown as follows:
wherein the content of the first and second substances,
and
txBytes for port p1 at times t2 and t1 respectively,
and
rxBytes for p1 at times t2 and t1, respectively; data at the port p2 are respectively represented in formula (4);
T p1 and T p2 The total bit number of the ports p1 and p2 in the time period from t1 to t2 is respectively represented, and the average value of the two ports is taken as a calculated value of the occupied bandwidth of the link.
S1.3.2: the link delay is measured by respectively sending a Packet _ out message and an Echo request message;
the Packet _ out message is sent, the SDN controller sends the Packet _ out message carrying the timestamp to a switch s1, and the switch s1 forwards the message to a switch s2;
the sending of the Echo request message, the SDN controller respectively sends Echo request messages with timestamps to a switch s1 and a switch s2; the link delay calculation between the switches is as shown in equation (6):
where t is the path delay and t1 and t2 are the controller-to-switch delays, respectively.
S1.3.3: the packet loss rate, which represents the calculation of the number of the transmitted and received data packets by using the txPackets and the rxPackets information, is as shown in equations (7) and (8):
wherein the content of the first and second substances,
and
respectively representing the number of packets sent by the p1 port at times t2 and t1,
and
respectively representing the number of data packets received by the p2 port at t2 and t 1; TP is the total number of data packets sent in the time period from the port t1 to the port t2, and RP represents the total number of data packets received in the time period from the port t1 to the port t 2; calculating the packet loss rate as shown in equation (9):
normalizing the performance evaluation indexes, setting different weights for different indexes, and calculating a fitness function as shown in a formula (10):
f(x)＝q 1 ×f band (x)+q 2 ×(1-f loss (x))+q 3 ×(1-f delay (x)) (10)
wherein f is band Is the ratio of the bandwidth of a chromosome to the sum of all chromosomes, q 1 Is f band The weight of (c); f. of loss Is the chromosome loss ratio, q 2 Is f loss The weight of (c); f. of delay Is the chromosome delay ratio, q 2 Is f delay The weight of (c); q. q.s 1 +q 2 +q 3 =1; the routing path with the largest chromosome fitness function value is selected;
s2: initializing a plurality of paths from a source node to a target node by adopting a depth-first traversal algorithm, and selecting an adjacent node which is not randomly accessed as a next node;
s3: selecting generation-crossing selection, namely selecting excellent chromosomes in the population of the iteration and the last iteration through a roulette method;
s4: cross selection, for any two chromosomes, randomly selecting a gene point as a cross point to generate two new chromosomes;
s5: mutation operation, namely randomly selecting a gene from a chromosome as a mutation point, and then generating a new path from the burst point to a target node by using a depth-first search algorithm;
in this embodiment, the mutation rate is set to 0.1, a point is randomly selected as a mutation point for any chromosome, and a new path from the burst point to the destination node is generated by using a depth-first search algorithm. E.g., h1, s7, s4, s9, h7, mutation at s4, regenerating a new path for s4, s2, s6, s9, h 7;
s6: the microenvironment strategy increases a contrast mechanism of two generations of chromosomes in the crossing and mutation operations, if the fitness of offspring is higher than that of parent generation, the chromosomes are updated, otherwise, the chromosomes are not changed;
s7: deletion of chromosomes, wherein loops existing in chromosomes are caused by twice traversal deletion crossing or mutation operations;
in this embodiment, for chromosomes h1, s4, s2, s6, s8, s4, s2, s5, s9, and h7, such chromosomes have loops, which affect the performance of the algorithm, and the loops are deleted by using a double traversal method;
by combining cross-generation selection, a microenvironment strategy and an original genetic algorithm and applying the cross-generation selection, the microenvironment strategy and the original genetic algorithm to a QoS routing algorithm, when the flow is injected into a network, an SDN controller runs an improved genetic algorithm to generate a path on the basis of a self-adaptive monitoring mechanism and sends the path to a flow table entry on a switch.
Claims (10)
1. A reliable routing method applied to a B5G vehicle-mounted network is characterized by comprising the following steps: the method comprises the following steps: designing an SDN network framework based on a B5G technology, and applying a WSMP protocol to a 5G system; establishing a self-adaptive monitoring mechanism; calculating a route by adopting a QoS routing algorithm based on an improved genetic algorithm;
the design of the SDN network framework based on the B5G technology specifically comprises the following steps:
predicting a vehicle motion track by using a 5G base station by adopting an SDN (software defined network) frame based on a B5G technology, providing real-time data processing by using Multi-access Edge Computing (MEC), and predicting a next base station to be connected by the vehicle through machine learning;
the WSMP protocol is applied to the 5G system, and specifically comprises the following steps:
the WSMP protocol is applied to a 5G system, and the WSMP protocol framework comprises an NTPS module, an adaptation module and a 5G module; the NTPS module realizes the packaging and transmission of the WSMP protocol by broadcasting the WSA, and the adaptation module is used for adapting the WSMP protocol to the 5G module; the 5G module implements the MAC layer and the physical layer of the protocol stack, and sends data and filters and receives data.
2. The reliable routing method applied to the B5G vehicular network according to claim 1, wherein:
the establishing of the self-adaptive monitoring mechanism specifically comprises the following steps:
controlling the balance between overhead and accuracy according to the network scale and link load change dynamic concept polling interval; calculating the update of the detection interval according to the bandwidth change rate and the last monitoring interval, wherein the bandwidth change rate is shown as a formula (1):
where Δ b is the rate of change of bandwidth, band is the width currently occupied by the link, lastBand is the last occupied bandwidth, ε 1 A real number greater than 0;
updating the detection interval as shown in equation (2):
wherein minPed is the minimum polling interval determined by the network scale; lasted is the last polling interval, maxPed is the maximum argument interval; alpha is alpha 1 And alpha 2 Is a set constant, by judgmentThe broken bandwidth change rate adopts different polling interval change strategies.
3. The reliable routing method applied to the B5G vehicular network according to claim 1, wherein: the self-adaptive monitoring mechanism comprises a monitoring point setting and a monitoring point traversing and a message sending.
4. The reliable routing method applied to the B5G vehicle-mounted network according to claim 3, wherein:
the set monitoring points are specifically as follows:
operating an LLDP protocol and setting a link;
initializing the monitoring time of all links of the link to be minPed, and adding the minPed into a monitoring queue;
and the controller receives the OpenFlow message of one link and updates the corresponding link bandwidth, link delay, packet loss rate and monitoring points.
5. The reliable routing method applied to the B5G vehicular network according to claim 1, wherein:
initializing global time by traversing the monitoring points;
detecting whether the monitoring queue is empty or not, and traversing all monitoring points if the monitoring queue is not empty;
and (4) continuously increasing the global time point by 1 until the time of the monitoring point is equal to the global time point, measuring the corresponding link and removing the monitoring point.
6. The reliable routing method applied to the B5G vehicular network according to claim 1, wherein: the QoS routing algorithm based on the improved genetic algorithm calculates the route, and comprises the following steps:
s1: network preprocessing, chromosome coding and fitness function construction are carried out;
s2: initializing and adopting a depth-first traversal algorithm to generate a plurality of paths from a source node to a target node, and selecting an adjacent node which is not randomly accessed as a next node;
s3: selecting generation-crossing selection, namely selecting excellent chromosomes in the population of the iteration and the last iteration through a roulette method;
s4: cross selection, for any two chromosomes, randomly selecting a gene point as a cross point to generate two new chromosomes;
s5: mutation operation, namely randomly selecting a gene from a chromosome as a mutation point, and then generating a new path from the burst point to a target node by using a depth-first search algorithm;
s6: the microenvironment strategy increases a contrast mechanism of two generations of chromosomes in the crossing and mutation operations, if the fitness of offspring is higher than that of parent generation, the chromosomes are updated, otherwise, the chromosomes are not changed;
s7: deletion of chromosomes, wherein loops existing in chromosomes are caused by twice traversal deletion crossing or mutation operations;
by combining cross-generation selection, a microenvironment strategy and an original genetic algorithm, the method is applied to a QoS routing algorithm, when the flow is injected into a network, an SDN controller runs an improved genetic algorithm to generate a path on the basis of a self-adaptive monitoring mechanism, and the path is sent to a flow table entry on a switch.
7. The reliable routing method applied to the B5G vehicular network according to claim 1, wherein:
the specific process of S1 comprises the following steps:
s1.1: network preprocessing is carried out, edge nodes which do not meet the bandwidth requirement in the network are eliminated, the SDN controller deletes links which do not meet the data flow, and a virtual network which meets the bandwidth requirement is constructed;
s1.2: chromosome coding, namely, a variable-length chromosome coding mechanism is adopted, each chromosome represents a routing path, the first gene represents a source node, the last gene represents a target node, the chromosome sequence represents a path network node sequence, and the nodes on the chromosomes are ensured to be single;
s1.3: and constructing a fitness function and selecting link bandwidth, link time delay and packet loss rate as performance evaluation indexes.
8. The reliable routing method applied to the B5G vehicular network according to claim 7, wherein:
the link bandwidth adopts a passive mode, the occupied bandwidth is measured according to the statistical data of a counter of a switch port, the bandwidth is measured by utilizing the return information of rxBytes and txBytes, the bit number received and sent by the port is respectively represented, a switch s1 and a switch s2 are connected through ports p1 and p2, the bandwidth is calculated in the time periods of t1 and t2, and the formula (3) and the formula (4) are shown as follows:
wherein, the first and the second end of the pipe are connected with each other,
and
are respectively time t2 and t1 txBytes for port p1 at time,
and
rxBytes for p1 at times t2 and t1, respectively; data at the port p2 are respectively represented in formula (4);
T p1 and T p2 Respectively representing the total bit number of the ports p1 and p2 in the time period from t1 to t2, and taking the average value of the two ports as the meter of the occupied bandwidth of the linkAnd (4) calculating a value.
9. The reliable routing method applied to the B5G vehicular network according to claim 7, wherein:
the link delay is measured by respectively sending a Packet _ out message and an Echo request message;
the Packet _ out message is sent, the SDN controller sends the Packet _ out message carrying the timestamp to a switch s1, and the switch s1 forwards the message to a switch s2;
the sending of the Echo request message, the SDN controller respectively sends Echo request messages with timestamps to a switch s1 and a switch s2; the link delay calculation between the switches is as shown in equation (6):
where t is the path delay and t1 and t2 are the controller-to-switch delay, respectively.
10. The reliable routing method applied to the B5G vehicular network according to claim 7, wherein:
the packet loss rate utilizes txpackers and rxpackers information to respectively represent the calculation of the number of the sent and received data packets, and the formula (7) and the formula (8) are shown as follows:
wherein the content of the first and second substances,
and
respectively representing the number of packets sent by the p1 port at times t2 and t1,
and
respectively representing the number of data packets received by the p2 port at the time t2 and the time t 1; TP is the total number of data packets sent in the time period from the port t1 to the port t2, and RP represents the total number of data packets received in the time period from the port t1 to the port t 2; calculating the packet loss rate as shown in equation (9):
normalizing the performance evaluation indexes, setting different weights for different indexes, and calculating a fitness function as shown in a formula (10):
f(x)＝q 1 ×f band (x)+q 2 ×(1-f loss (x))+q 3 ×(1-f delay (x)) (10)
wherein f is band Is the ratio of the bandwidth of a chromosome to the sum of all chromosomes, q 1 Is f band The weight of (c); f. of loss Is the chromosome loss ratio, q 2 Is f loss The weight of (c); f. of delay Is the chromosome delay ratio, q 2 Is f delay The weight of (c); q. q.s 1 +q 2 +q 3 =1; the largest value of the fitness function of the chromosome is the routing path.
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