CN115033371A - Method, equipment and system for service migration in vehicle network - Google Patents

Method, equipment and system for service migration in vehicle network Download PDF

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Publication number
CN115033371A
CN115033371A CN202210961471.3A CN202210961471A CN115033371A CN 115033371 A CN115033371 A CN 115033371A CN 202210961471 A CN202210961471 A CN 202210961471A CN 115033371 A CN115033371 A CN 115033371A
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service
migration
time slot
resource node
resource
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CN115033371B (en
Inventor
王晓伟
邱子贤
边有钢
胡满江
秦晓辉
徐彪
秦兆博
谢国涛
秦洪懋
丁荣军
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Jiangsu Jicui Qinglian Intelligent Control Technology Co ltd
Wuxi Institute Of Intelligent Control Hunan University
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Jiangsu Jicui Qinglian Intelligent Control Technology Co ltd
Wuxi Institute Of Intelligent Control Hunan University
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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F9/00—Arrangements for program control, e.g. control units
    • G06F9/06—Arrangements for program control, e.g. control units using stored programs, i.e. using an internal store of processing equipment to receive or retain programs
    • G06F9/46—Multiprogramming arrangements
    • G06F9/48—Program initiating; Program switching, e.g. by interrupt
    • G06F9/4806—Task transfer initiation or dispatching
    • G06F9/4843—Task transfer initiation or dispatching by program, e.g. task dispatcher, supervisor, operating system
    • G06F9/485—Task life-cycle, e.g. stopping, restarting, resuming execution
    • G06F9/4856—Task life-cycle, e.g. stopping, restarting, resuming execution resumption being on a different machine, e.g. task migration, virtual machine migration
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/10—Complex mathematical operations
    • G06F17/11—Complex mathematical operations for solving equations, e.g. nonlinear equations, general mathematical optimization problems
    • G06F17/12—Simultaneous equations, e.g. systems of linear equations
    • 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]
    • 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
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • 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
    • Y02D30/00—Reducing energy consumption in communication networks
    • Y02D30/70—Reducing energy consumption in communication networks in wireless communication networks

Abstract

The invention discloses a method, equipment and a system for service migration in a vehicle network, wherein the method comprises the following steps: defining a vehicle time slot
Figure 383959DEST_PATH_IMAGE001
Internal use service
Figure 505499DEST_PATH_IMAGE002
The migration scheme of (a) generates a cost of
Figure 937617DEST_PATH_IMAGE003
(ii) a Setting constraint conditions; according to time slot of vehicle
Figure 93792DEST_PATH_IMAGE001
Internal use service
Figure 457558DEST_PATH_IMAGE002
Cost of migration scheme
Figure 66394DEST_PATH_IMAGE003
The calculation formula and the constraint condition of (2), the calculation is in the time slot
Figure 36624DEST_PATH_IMAGE001
Migration policy that minimizes the total cost of migration of all services within. In the embodiment of the invention, different migration schemes are provided for the instant service and the continuous service, different migration schemes and constraint conditions corresponding to different service types are comprehensively considered, and the lowest migration cost is realized under the condition of ensuring the service quality.

Description

Method, equipment and system for service migration in vehicle network
Technical Field
The invention relates to the technical field of vehicle networking, in particular to a method, equipment and a system for service migration in a vehicle network.
Background
In a vehicle-road cloud cooperative computing scene, the dynamic mobility of an intelligent networked automobile challenges the continuity and stability of services of resource nodes deployed at roadside edges of the intelligent networked automobile, and along with the dynamic change of the position of the intelligent networked automobile in the driving process, the distance between the intelligent networked automobile and the roadside edge resource nodes is changed, the coverage range of base station signals of the roadside edge resource nodes is limited, so that the services running in the intelligent networked automobile face transmission delay which is obviously increased due to the increase of the distance, even the services are interrupted, and the service quality is difficult to guarantee. By means of the existing virtual machine migration or container migration technology, the service instance of the intelligent networked automobile in the roadside edge resource node can be migrated from the source resource node to the target resource node close to the intelligent networked automobile along with the movement of the intelligent networked automobile, the distance between the service instance and the intelligent networked automobile is kept or reduced, low communication delay is guaranteed, and the service quality is improved.
In the actual scene of the intelligent networked automobile, various services (usually provided by various applications) required by the intelligent networked automobile are different, wherein part of the general services only need to process data transmitted by the intelligent networked automobile and then return results, for example, the general target detection service only needs to operate a deep learning target detection example of a roadside edge resource node to detect, classify and mark original data of sensors such as a camera of the automobile and return the detection results to the automobile for subsequent operation, and the service is characterized in that the operation of the current service does not depend on information such as past data results and has instantaneity; the operation of the other part of services requires that the information has forward and backward continuity, for example, in the case of the space prediction service such as the road pedestrian intention prediction service, the pedestrian intention prediction needs certain prior information to effectively predict the subsequent behavior, so that the continuity of the information in the processing process of the service needs to be maintained in the operation of the service, and the service has continuity.
For the continuity service, two options exist because the continuity of information needs to be maintained, namely service instances including information such as a CPU, a memory and the like also need to be consistent before and after migration. The first method is to migrate the service acquired by the intelligent networked automobile from the source roadside edge resource node to the roadside edge resource node closer to the vehicle, which is referred to as a migration mode for short, as shown in fig. 1. The second option is to continue to keep the service operation in the source roadside edge resource node, perform data interaction with the source roadside edge resource node by taking the roadside edge node near the intelligent networked automobile as a data relay node, forward the service request data of the intelligent networked automobile to the service instance of the source roadside edge resource node, and forward the processing result to the intelligent networked automobile, which is referred to as a relay node mode for short, as shown in fig. 2.
For the instant service, the instant service has no requirement on past data information such as a memory and the like, so that the migration scheme does not need to forcibly require that the service instances are the same in the moving process of the intelligent networked automobile.
In order to guarantee user experience, ensure the continuity and stability of the service of the intelligent internet automobile in the driving process, and simultaneously ensure lower migration cost, a service migration strategy which is reasonable and efficient and moves along with the user is very necessary.
Disclosure of Invention
It is an object of the present invention to provide a method, apparatus and system for service migration in a vehicle network that overcomes or mitigates at least one of the above-mentioned disadvantages of the prior art.
In order to achieve the above object, an embodiment of the present invention provides a method for service migration in a vehicle network, where the method is applied to a scene including a vehicle and roadside edge resource nodes, and the method includes:
step S1, defining a vehicle time slot
Figure 133670DEST_PATH_IMAGE001
Internal use service
Figure 163943DEST_PATH_IMAGE002
The migration scheme of (a) generates a cost of
Figure 322392DEST_PATH_IMAGE003
；
Figure 33996DEST_PATH_IMAGE004
For the instant service, the calculation formula is as follows:
Figure 227080DEST_PATH_IMAGE005
wherein, the first and the second end of the pipe are connected with each other,
Figure 365937DEST_PATH_IMAGE006
Figure 250497DEST_PATH_IMAGE007
representing services on a vehicle
Figure 765792DEST_PATH_IMAGE008
And connecting resource nodes
Figure 813383DEST_PATH_IMAGE009
A wireless transmission cost generated by transmitting service data between the resource nodes and the service
Figure 123141DEST_PATH_IMAGE008
The roadside edge resource nodes are connected with the vehicle;
Figure 990603DEST_PATH_IMAGE010
setting adjusting parameters for presetting;
Figure 44010DEST_PATH_IMAGE011
for connecting resource nodes
Figure 946107DEST_PATH_IMAGE012
To serve
Figure 426767DEST_PATH_IMAGE008
The amount of network resources provided;
Figure 548569DEST_PATH_IMAGE013
to serve
Figure 140087DEST_PATH_IMAGE008
Located vehicle and connection resource node
Figure 162270DEST_PATH_IMAGE012
The distance between them;
wherein the content of the first and second substances,
Figure 813831DEST_PATH_IMAGE014
Figure 655885DEST_PATH_IMAGE015
presentation to service
Figure 51094DEST_PATH_IMAGE016
Adopting the wired transmission cost generated by a transit node mode;
Figure 927783DEST_PATH_IMAGE017
setting adjusting parameters for presetting;
Figure 750246DEST_PATH_IMAGE018
to serve
Figure 578131DEST_PATH_IMAGE016
In that
Figure 839348DEST_PATH_IMAGE019
Deployment and operation resource node of time slot
Figure 508227DEST_PATH_IMAGE020
And service
Figure 563908DEST_PATH_IMAGE016
In that
Figure 318237DEST_PATH_IMAGE021
Connection resource node of time slot
Figure 383145DEST_PATH_IMAGE012
Network hop count therebetween, wherein the deployment run resource node is a deployment run service
Figure 906530DEST_PATH_IMAGE016
Roadside edge resource nodes of (1); the coefficient 2 represents the transmission process of the forwarding data and the result;
wherein, the first and the second end of the pipe are connected with each other,
Figure 634577DEST_PATH_IMAGE022
Figure 876203DEST_PATH_IMAGE023
presentation to service
Figure 479222DEST_PATH_IMAGE016
Migration costs generated by adopting a migration mode;
Figure 857114DEST_PATH_IMAGE024
presetting adjustment parameters;
Figure 520177DEST_PATH_IMAGE025
to serve
Figure 983519DEST_PATH_IMAGE026
In that
Figure 390229DEST_PATH_IMAGE019
Deployment and operation resource node of time slot
Figure 622628DEST_PATH_IMAGE020
And service
Figure 949267DEST_PATH_IMAGE026
In that
Figure 899906DEST_PATH_IMAGE021
Deployment and operation resource node of time slot
Figure 844728DEST_PATH_IMAGE027
Network hop count in between;
Figure 259529DEST_PATH_IMAGE028
is presetCost of restarting the service instance after migrating to the target node;
wherein the content of the first and second substances,
Figure 202077DEST_PATH_IMAGE029
Figure 702329DEST_PATH_IMAGE030
representing vehicle and resource nodes
Figure 952307DEST_PATH_IMAGE012
Costs incurred in connecting and rebuilding instances by applying mirroring;
Figure 159297DEST_PATH_IMAGE031
create instance costs for presets;
Figure 335063DEST_PATH_IMAGE032
as a resource node
Figure 260294DEST_PATH_IMAGE012
A set of offered service types;
Figure 546919DEST_PATH_IMAGE033
presentation service
Figure 873995DEST_PATH_IMAGE026
Is of the type of a resource node
Figure 955083DEST_PATH_IMAGE012
A set of offered service types;
Figure 367610DEST_PATH_IMAGE024
setting adjusting parameters for presetting;
Figure 395609DEST_PATH_IMAGE034
as a resource node
Figure 138044DEST_PATH_IMAGE035
And resource node
Figure 593296DEST_PATH_IMAGE012
Network hop count in between;
Figure 289856DEST_PATH_IMAGE036
as a resource node
Figure 855967DEST_PATH_IMAGE035
A set of offered service types;
Figure 219952DEST_PATH_IMAGE037
,
Figure 908423DEST_PATH_IMAGE038
presentation service
Figure 656061DEST_PATH_IMAGE026
Is not of a resource node type
Figure 88179DEST_PATH_IMAGE012
Set of offered service types, but belonging to resource nodes
Figure 306671DEST_PATH_IMAGE035
A set of offered service types;
wherein the content of the first and second substances,
Figure 670437DEST_PATH_IMAGE039
presentation service
Figure 403907DEST_PATH_IMAGE026
In that
Figure 374137DEST_PATH_IMAGE021
The mode selection of the time slot is performed,
Figure 384818DEST_PATH_IMAGE040
presentation service
Figure 916556DEST_PATH_IMAGE026
In that
Figure 75005DEST_PATH_IMAGE021
The time slot adopts a migration mode;
Figure 848926DEST_PATH_IMAGE041
presentation service
Figure 714114DEST_PATH_IMAGE026
In that
Figure 915288DEST_PATH_IMAGE021
The time slot adopts a transit node mode;
Figure 59568DEST_PATH_IMAGE042
presentation service
Figure 637180DEST_PATH_IMAGE026
In that
Figure 419191DEST_PATH_IMAGE021
The time slot adopts an application mirror image reconstruction instance mode;
step S2, setting constraint conditions; the method comprises the following steps:
Figure 355048DEST_PATH_IMAGE043
Figure 425772DEST_PATH_IMAGE044
Figure 541496DEST_PATH_IMAGE045
Figure 443593DEST_PATH_IMAGE046
wherein the content of the first and second substances,
Figure 924253DEST_PATH_IMAGE047
represents a collection of all services; binary variable
Figure 544590DEST_PATH_IMAGE048
Is shown in
Figure 136108DEST_PATH_IMAGE021
Time slot service
Figure 408825DEST_PATH_IMAGE026
Whether to deploy and run on resource nodes
Figure 325966DEST_PATH_IMAGE049
In (1),
Figure 168020DEST_PATH_IMAGE050
presentation service
Figure 563229DEST_PATH_IMAGE026
In that
Figure 439918DEST_PATH_IMAGE021
Time slot deployment running on resource node
Figure 262380DEST_PATH_IMAGE049
In the step (1), the first step,
Figure 591731DEST_PATH_IMAGE051
then represents the service
Figure 790631DEST_PATH_IMAGE052
In that
Figure 23291DEST_PATH_IMAGE021
The time slot is not deployed and operated on the resource node
Figure 16655DEST_PATH_IMAGE049
The preparation method comprises the following steps of (1) performing; binary variable
Figure 833301DEST_PATH_IMAGE053
Is shown in
Figure 570313DEST_PATH_IMAGE021
Time slot service
Figure 156015DEST_PATH_IMAGE026
Whether the vehicle is in contact with the resource node
Figure 648177DEST_PATH_IMAGE049
The connection is carried out by connecting the two parts,
Figure 889802DEST_PATH_IMAGE054
is shown in
Figure 725778DEST_PATH_IMAGE021
Time slot service
Figure 369249DEST_PATH_IMAGE026
Vehicle and resource node
Figure 766732DEST_PATH_IMAGE049
The connection is carried out by connecting the two parts,
Figure 557970DEST_PATH_IMAGE055
then it is indicated at
Figure 636785DEST_PATH_IMAGE021
Time slot service
Figure 197079DEST_PATH_IMAGE026
The vehicle is not connected with the resource node
Figure 968726DEST_PATH_IMAGE049
Connecting;
Figure 483146DEST_PATH_IMAGE056
and
Figure 365652DEST_PATH_IMAGE011
respectively representing services
Figure 780452DEST_PATH_IMAGE052
The amount of computing, storage, and network resources required;
Figure 785318DEST_PATH_IMAGE057
and
Figure 285569DEST_PATH_IMAGE058
respectively representing resource nodes
Figure 706186DEST_PATH_IMAGE049
In time slot
Figure 745467DEST_PATH_IMAGE021
The amount of available computing, storage, and network resources;
Figure 858917DEST_PATH_IMAGE059
，
Figure 846464DEST_PATH_IMAGE060
represents a collection of all resource nodes;
Figure 70772DEST_PATH_IMAGE061
to serve
Figure 194586DEST_PATH_IMAGE026
In that
Figure 478937DEST_PATH_IMAGE021
Deployment and operation resource node of time slot
Figure 953780DEST_PATH_IMAGE027
And service
Figure 981779DEST_PATH_IMAGE026
In that
Figure 727144DEST_PATH_IMAGE062
Connection resource node of time slot
Figure 916817DEST_PATH_IMAGE012
Network hop count in between;
Figure 878956DEST_PATH_IMAGE063
to serve
Figure 445067DEST_PATH_IMAGE052
The preset maximum connection distance between the connection resource node and the deployment operation resource node;
step S3, according to the time slot of vehicle
Figure 809052DEST_PATH_IMAGE021
Internal use service
Figure 169626DEST_PATH_IMAGE008
Cost of migration scheme
Figure 619062DEST_PATH_IMAGE064
The calculation formula and the constraint condition of (2), the calculation is in the time slot
Figure 988864DEST_PATH_IMAGE021
Migration policy that minimizes the total cost of migration of all services within.
An embodiment of the present invention further provides an apparatus for service migration in a vehicle network, which is applied to a scene including a vehicle and roadside edge resource nodes, and the apparatus includes a processing module, configured to:
defining a vehicle time slot
Figure 440311DEST_PATH_IMAGE021
Internal use service
Figure 237366DEST_PATH_IMAGE016
The migration scheme of (a) generates a cost of
Figure 908519DEST_PATH_IMAGE064
；
For the continuity service, the calculation formula is as follows:
Figure 82011DEST_PATH_IMAGE065
for the instant service, the calculation formula is as follows:
Figure 92693DEST_PATH_IMAGE066
wherein the content of the first and second substances,
Figure 122965DEST_PATH_IMAGE067
Figure 219097DEST_PATH_IMAGE007
representing services on a vehicle
Figure 993018DEST_PATH_IMAGE016
And connecting resource nodes
Figure 858206DEST_PATH_IMAGE012
A wireless transmission cost generated by transmitting service data between the resource nodes and the service
Figure 997064DEST_PATH_IMAGE016
The roadside edge resource nodes are connected with the vehicle;
Figure 144273DEST_PATH_IMAGE010
presetting adjustment parameters;
Figure 393989DEST_PATH_IMAGE011
for connecting resource nodes
Figure 441580DEST_PATH_IMAGE012
To serve
Figure 751338DEST_PATH_IMAGE026
The amount of network resources provided;
Figure 884379DEST_PATH_IMAGE013
to serve
Figure 937786DEST_PATH_IMAGE026
The vehicle and the connection resourceNode point
Figure 777566DEST_PATH_IMAGE012
The distance therebetween;
wherein, the first and the second end of the pipe are connected with each other,
Figure 320543DEST_PATH_IMAGE068
Figure 612984DEST_PATH_IMAGE015
presentation to service
Figure 25074DEST_PATH_IMAGE026
Adopting the wired transmission cost generated by a transit node mode;
Figure 719361DEST_PATH_IMAGE069
presetting adjustment parameters;
Figure 433239DEST_PATH_IMAGE070
to serve
Figure 478555DEST_PATH_IMAGE026
In that
Figure 936081DEST_PATH_IMAGE019
Deployment and operation resource node of time slot
Figure 484874DEST_PATH_IMAGE020
And service
Figure 572916DEST_PATH_IMAGE026
And service in
Figure 902266DEST_PATH_IMAGE021
Connection resource node of time slot
Figure 101166DEST_PATH_IMAGE012
Network hop count therebetween, wherein the deployment run resource node is a deployment run service
Figure 68247DEST_PATH_IMAGE026
Roadside edge resource nodes of (1); the coefficient 2 represents the transmission process of the forwarding data and the result;
wherein the content of the first and second substances,
Figure 327191DEST_PATH_IMAGE071
Figure 143837DEST_PATH_IMAGE023
presentation to service
Figure 880849DEST_PATH_IMAGE026
Migration cost generated by adopting a migration mode;
Figure 404234DEST_PATH_IMAGE024
setting adjusting parameters for presetting;
Figure 896395DEST_PATH_IMAGE025
to serve
Figure 872441DEST_PATH_IMAGE026
In that
Figure 475461DEST_PATH_IMAGE019
Deployment and operation resource node of time slot
Figure 679784DEST_PATH_IMAGE020
And service
Figure 77267DEST_PATH_IMAGE026
In that
Figure 806189DEST_PATH_IMAGE021
Deployment and operation resource node of time slot
Figure 947320DEST_PATH_IMAGE027
Network hop count in between;
Figure 507615DEST_PATH_IMAGE028
after the preset is migrated to the target nodeCost of restarting a service instance;
wherein the content of the first and second substances,
Figure 13682DEST_PATH_IMAGE072
Figure 855999DEST_PATH_IMAGE030
representing vehicle and resource nodes
Figure 800821DEST_PATH_IMAGE012
Costs incurred in connecting and rebuilding instances by applying mirroring;
Figure 153305DEST_PATH_IMAGE031
creating an instance cost for a preset;
Figure 158170DEST_PATH_IMAGE032
as a resource node
Figure 596104DEST_PATH_IMAGE012
A set of offered service types;
Figure 583433DEST_PATH_IMAGE033
presentation service
Figure 56003DEST_PATH_IMAGE026
Is of the type of a resource node
Figure 966190DEST_PATH_IMAGE012
A set of offered service types;
Figure 891420DEST_PATH_IMAGE024
presetting adjustment parameters;
Figure 115728DEST_PATH_IMAGE073
as a resource node
Figure 505121DEST_PATH_IMAGE035
And resource node
Figure 789472DEST_PATH_IMAGE012
Network hop count in between;
Figure 264316DEST_PATH_IMAGE074
as a resource node
Figure 26736DEST_PATH_IMAGE035
A set of offered service types;
Figure 772100DEST_PATH_IMAGE075
Figure 227352DEST_PATH_IMAGE076
Figure 189492DEST_PATH_IMAGE077
presentation service
Figure 755602DEST_PATH_IMAGE026
Is not of a resource node type
Figure 791691DEST_PATH_IMAGE012
Set of offered service types, but belonging to resource nodes
Figure 480162DEST_PATH_IMAGE035
A set of offered service types;
wherein the content of the first and second substances,
Figure 867281DEST_PATH_IMAGE078
presentation service
Figure 33820DEST_PATH_IMAGE008
In that
Figure 189995DEST_PATH_IMAGE062
The mode selection of the time slot is performed,
Figure 610218DEST_PATH_IMAGE079
presentation service
Figure 219054DEST_PATH_IMAGE008
In that
Figure 454864DEST_PATH_IMAGE062
The time slot adopts a migration mode;
Figure 465545DEST_PATH_IMAGE080
presentation service
Figure 495818DEST_PATH_IMAGE008
In that
Figure 591950DEST_PATH_IMAGE021
The time slot adopts a transit node mode;
Figure 601756DEST_PATH_IMAGE081
presentation service
Figure 732523DEST_PATH_IMAGE008
In that
Figure 933698DEST_PATH_IMAGE021
The time slot adopts an application mirror image reconstruction instance mode;
setting constraint conditions; the method comprises the following steps:
Figure 517126DEST_PATH_IMAGE082
Figure 766841DEST_PATH_IMAGE083
Figure 814432DEST_PATH_IMAGE084
Figure 124190DEST_PATH_IMAGE085
wherein the content of the first and second substances,
Figure 257232DEST_PATH_IMAGE047
represents a collection of all services; binary variable
Figure 310638DEST_PATH_IMAGE086
Is shown in
Figure 728848DEST_PATH_IMAGE021
Time slot service
Figure 209508DEST_PATH_IMAGE016
Whether to deploy and run in resource node
Figure 501949DEST_PATH_IMAGE049
In the step (1), the first step,
Figure 421364DEST_PATH_IMAGE050
presentation service
Figure 115650DEST_PATH_IMAGE016
In that
Figure 829528DEST_PATH_IMAGE021
Time slot deployment running on resource node
Figure 874845DEST_PATH_IMAGE049
In (1),
Figure 270054DEST_PATH_IMAGE087
then represents the service
Figure 881164DEST_PATH_IMAGE088
In that
Figure 969206DEST_PATH_IMAGE021
The time slot is not deployed and operated on the resource node
Figure 800021DEST_PATH_IMAGE049
Performing the following steps; binary variable
Figure 733342DEST_PATH_IMAGE089
Is shown in
Figure 402220DEST_PATH_IMAGE021
Time slot service
Figure 723480DEST_PATH_IMAGE016
Whether the vehicle is in contact with the resource node
Figure 212231DEST_PATH_IMAGE049
The connection is carried out by connecting the two parts,
Figure 277138DEST_PATH_IMAGE054
is shown in
Figure 800524DEST_PATH_IMAGE021
Time slot service
Figure 27106DEST_PATH_IMAGE016
Vehicle and resource node
Figure 268731DEST_PATH_IMAGE090
The connection is carried out by connecting the two parts,
Figure 370286DEST_PATH_IMAGE055
then it is indicated at
Figure 748178DEST_PATH_IMAGE021
Time slot service
Figure 411240DEST_PATH_IMAGE016
The located vehicle has no node with the resource
Figure 874583DEST_PATH_IMAGE049
Connecting;
Figure 218976DEST_PATH_IMAGE091
and
Figure 779271DEST_PATH_IMAGE011
respectively representing services
Figure 285338DEST_PATH_IMAGE052
The amount of computing, storage, and network resources required;
Figure 563873DEST_PATH_IMAGE092
and
Figure 446378DEST_PATH_IMAGE058
respectively representing resource nodes
Figure 362644DEST_PATH_IMAGE049
In a time slot
Figure 39613DEST_PATH_IMAGE021
The amount of available computing, storage, and network resources;
Figure 477547DEST_PATH_IMAGE093
，
Figure 226061DEST_PATH_IMAGE094
represents a collection of all resource nodes;
Figure 433051DEST_PATH_IMAGE095
to serve
Figure 608817DEST_PATH_IMAGE026
In that
Figure 534048DEST_PATH_IMAGE021
Deploying and operating resource nodes of time slots
Figure 820673DEST_PATH_IMAGE027
And service
Figure 147749DEST_PATH_IMAGE026
In that
Figure 432100DEST_PATH_IMAGE021
Connection resource node of time slot
Figure 145759DEST_PATH_IMAGE012
Network hop count in between;
Figure 173758DEST_PATH_IMAGE096
to serve
Figure 417657DEST_PATH_IMAGE052
The preset maximum connection distance between the connection resource node and the deployment operation resource node;
according to time slot of vehicle
Figure 872909DEST_PATH_IMAGE021
Internal use service
Figure 772732DEST_PATH_IMAGE026
Cost of migration scheme
Figure 401160DEST_PATH_IMAGE064
The calculation formula and the constraint condition of (2), the calculation is in the time slot
Figure 437249DEST_PATH_IMAGE097
Migration policy that minimizes the total cost of migration of all services within.
The embodiment of the invention also provides a system for service migration in a vehicle network, which comprises the vehicle, the roadside edge resource nodes and the equipment.
Due to the adoption of the technical scheme, the invention has the following advantages:
in the embodiment of the invention, different migration schemes are provided for instant services and continuous services, different migration schemes and constraint conditions corresponding to different service types are comprehensively considered, and the lowest migration cost is realized under the condition of ensuring the service quality.
Drawings
Fig. 1 is a schematic diagram of a service migration scheme of a migration mode of a continuation service and an instantaneity service.
Fig. 2 is a schematic diagram of a service migration scheme of a transit node mode of a continuation service and an instantaneity service.
Fig. 3 is a schematic diagram of a service migration scheme in an application image reconstruction instance of a just-in-time service.
Fig. 4 is a flowchart illustrating a method for service migration in a vehicle network according to an embodiment of the present invention.
Fig. 5 is a flowchart illustrating a method for service migration in a vehicle network according to an embodiment of the present invention.
Fig. 6 is a schematic diagram of a specific implementation process of step S51 in the flowchart shown in fig. 5.
FIG. 7 is a schematic diagram of chromosomes and gene segments in the method provided by the embodiment of the invention.
FIG. 8 is a schematic diagram of chromosome crossing operations in the method according to the embodiment of the present invention.
FIG. 9 is a schematic diagram of chromosome mutation operations in the method according to the embodiment of the present invention.
Fig. 10 is a schematic structural diagram of an apparatus for service migration in a vehicle network according to an embodiment of the present invention.
Fig. 11 is a schematic diagram of a cost comparison of a solution for service migration in a vehicle network provided by an embodiment of the present invention and a prior art service migration solution.
Fig. 12 is a schematic diagram of another cost comparison of a solution for service migration in a vehicle network provided by an embodiment of the present invention and a prior art service migration solution.
Detailed Description
In the drawings, the same or similar reference numerals are used to designate the same or similar elements or elements having the same or similar functions. Embodiments of the present invention will be described in detail below with reference to the accompanying drawings.
In the description of the present invention, the terms "central", "longitudinal", "lateral", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", etc., indicate orientations or positional relationships based on those shown in the drawings, and are only for convenience in describing the present invention and simplifying the description, but do not indicate or imply that the device or element being referred to must have a particular orientation, be constructed in a particular orientation, and be operated, and therefore, should not be construed as limiting the scope of the present invention.
In the present invention, the technical features of the embodiments and implementations may be combined with each other without conflict, and the present invention is not limited to the embodiments or implementations in which the technical features are located.
The present invention will be further described with reference to the accompanying drawings and specific embodiments, it should be noted that the technical solutions and design principles of the present invention are described in detail in the following only by way of an optimized technical solution, but the scope of the present invention is not limited thereto.
The following terms are referred to herein, and their meanings are explained below for ease of understanding. It will be understood by those skilled in the art that the following terms may have other names, but any other names should be considered consistent with the terms set forth herein without departing from their meaning.
For the instant service, there is an alternative to the continuation service, that is, a service instance is created again in a roadside edge resource node near the intelligent networked automobile through a service application mirror image to obtain a service, which is referred to as a rebuilt instance for short, as shown in fig. 3. In the process, if the resource node does not have the corresponding service application image, the application image file can be acquired from the surrounding resource nodes.
The embodiment of the invention provides a method for service migration in a vehicle network, which is applied to a scene comprising vehicles and roadside edge resource nodes, and as shown in fig. 4, the method comprises the following steps:
step S1, establishing a service migration problem model considering service characteristics, defining a vehicle time slot
Figure 125719DEST_PATH_IMAGE021
Internal use service
Figure 247259DEST_PATH_IMAGE049
The migration scheme of (a) generates a cost of
Figure 180842DEST_PATH_IMAGE098
。
For the continuity service, the calculation formula is as follows:
Figure 337017DEST_PATH_IMAGE099
for the instant service, the calculation formula is as follows:
Figure 134072DEST_PATH_IMAGE100
wherein the content of the first and second substances,
Figure 805224DEST_PATH_IMAGE101
Figure 713138DEST_PATH_IMAGE007
representing services on a vehicle
Figure 786136DEST_PATH_IMAGE026
And connecting resource nodes
Figure 754092DEST_PATH_IMAGE012
A wireless transmission cost generated by transmitting service data between the resource nodes and the service
Figure 912541DEST_PATH_IMAGE026
The roadside edge resource node is connected with the vehicle;
Figure 624145DEST_PATH_IMAGE102
setting adjusting parameters for presetting;
Figure 754912DEST_PATH_IMAGE011
for connecting resource nodes
Figure 454621DEST_PATH_IMAGE012
To serve
Figure 772470DEST_PATH_IMAGE026
The amount of network resources provided;
Figure 350082DEST_PATH_IMAGE103
to serve
Figure 335355DEST_PATH_IMAGE026
Located vehicle and connection resource node
Figure 707431DEST_PATH_IMAGE012
The distance between them;
wherein, the first and the second end of the pipe are connected with each other,
Figure 574893DEST_PATH_IMAGE104
Figure 628299DEST_PATH_IMAGE015
presentation to service
Figure 31861DEST_PATH_IMAGE026
Adopting the wired transmission cost generated by the transit node mode;
Figure 512521DEST_PATH_IMAGE069
setting adjusting parameters for presetting;
Figure 132858DEST_PATH_IMAGE070
to serve
Figure 724377DEST_PATH_IMAGE026
In that
Figure 746559DEST_PATH_IMAGE019
Deployment and operation resource node of time slot
Figure 398121DEST_PATH_IMAGE020
And service
Figure 240175DEST_PATH_IMAGE026
In that
Figure 190377DEST_PATH_IMAGE021
Connection resource node of time slot
Figure 4749DEST_PATH_IMAGE012
Network hop count therebetween, wherein the deployment run resource node is a deployment run service
Figure 889528DEST_PATH_IMAGE105
Roadside edge resource nodes of (1); the coefficient 2 represents the transmission process of forwarding data and results back and forth;
wherein the content of the first and second substances,
Figure 156561DEST_PATH_IMAGE106
Figure 417778DEST_PATH_IMAGE107
representation pair service
Figure 86657DEST_PATH_IMAGE008
Migration cost generated by adopting a migration mode;
Figure 142338DEST_PATH_IMAGE024
setting adjusting parameters for presetting;
Figure 896667DEST_PATH_IMAGE108
to serve
Figure 463040DEST_PATH_IMAGE008
In that
Figure 986425DEST_PATH_IMAGE019
Deployment and operation resource node of time slot
Figure 213007DEST_PATH_IMAGE109
And service
Figure 454633DEST_PATH_IMAGE008
In that
Figure 57652DEST_PATH_IMAGE021
Deployment and operation resource node of time slot
Figure 435544DEST_PATH_IMAGE027
Network hop count in between;
Figure 98607DEST_PATH_IMAGE028
cost for restarting the service instance after the preset migration to the target node;
wherein the content of the first and second substances,
Figure 561949DEST_PATH_IMAGE110
Figure 467195DEST_PATH_IMAGE030
representing vehicle and resource nodes
Figure 699593DEST_PATH_IMAGE012
Costs incurred in connecting and rebuilding instances by applying mirroring;
Figure 533557DEST_PATH_IMAGE031
creating an instance cost for a preset;
Figure 484195DEST_PATH_IMAGE032
as a resource node
Figure 429018DEST_PATH_IMAGE012
A set of offered service types;
Figure 781501DEST_PATH_IMAGE033
presentation service
Figure 724050DEST_PATH_IMAGE016
Is of the type of a resource node
Figure 224301DEST_PATH_IMAGE012
A set of offered service types;
Figure 910497DEST_PATH_IMAGE024
presetting adjustment parameters;
Figure 681270DEST_PATH_IMAGE073
as a resource node
Figure 794719DEST_PATH_IMAGE035
And resource node
Figure 782267DEST_PATH_IMAGE012
Network hop count in between;
Figure 6575DEST_PATH_IMAGE036
as a resource node
Figure 333651DEST_PATH_IMAGE035
A set of offered service types;
Figure 414739DEST_PATH_IMAGE037
，
Figure 827266DEST_PATH_IMAGE038
presentation service
Figure 917582DEST_PATH_IMAGE016
Is not of a resource node type
Figure 99164DEST_PATH_IMAGE012
Set of offered service types, but belonging to resource nodes
Figure 121128DEST_PATH_IMAGE035
A set of offered service types;
wherein, the first and the second end of the pipe are connected with each other,
Figure 755372DEST_PATH_IMAGE078
presentation service
Figure 383799DEST_PATH_IMAGE026
In that
Figure 685467DEST_PATH_IMAGE021
The mode selection of the time slot is performed,
Figure 311621DEST_PATH_IMAGE040
presentation service
Figure 495477DEST_PATH_IMAGE026
In that
Figure 865279DEST_PATH_IMAGE021
The time slot adopts a migration mode;
Figure 83771DEST_PATH_IMAGE041
presentation service
Figure 880825DEST_PATH_IMAGE026
In that
Figure 53443DEST_PATH_IMAGE021
The time slot adopts a transit node mode;
Figure 961356DEST_PATH_IMAGE042
presentation service
Figure 972037DEST_PATH_IMAGE026
In that
Figure 2310DEST_PATH_IMAGE021
The time slot adopts an application image reconstruction instance mode.
Step S2, setting constraint conditions; the method comprises the following steps:
Figure 98442DEST_PATH_IMAGE111
Figure 872363DEST_PATH_IMAGE044
Figure 737551DEST_PATH_IMAGE112
Figure 938725DEST_PATH_IMAGE113
wherein, the first and the second end of the pipe are connected with each other,
Figure 522153DEST_PATH_IMAGE047
represents a collection of all services; binary variable
Figure 37448DEST_PATH_IMAGE114
Is shown in
Figure 317995DEST_PATH_IMAGE021
Time slot service
Figure 627753DEST_PATH_IMAGE026
Whether to deploy and run in resource node
Figure 760794DEST_PATH_IMAGE049
In the step (1), the first step,
Figure 814201DEST_PATH_IMAGE050
presentation service
Figure 716298DEST_PATH_IMAGE026
In that
Figure 196958DEST_PATH_IMAGE021
Time slot deployment is operated on resource nodes
Figure 817295DEST_PATH_IMAGE049
In the step (1), the first step,
Figure 408813DEST_PATH_IMAGE087
then represents the service
Figure 103100DEST_PATH_IMAGE052
In that
Figure 584022DEST_PATH_IMAGE021
The time slot is not deployed and operated on the resource node
Figure 363759DEST_PATH_IMAGE049
Performing the following steps; binary system transformerMeasurement of
Figure 821285DEST_PATH_IMAGE115
Is shown in
Figure 635658DEST_PATH_IMAGE021
Time slot service
Figure 520437DEST_PATH_IMAGE026
Whether the located vehicle is connected with the resource node
Figure 787470DEST_PATH_IMAGE049
The connection is carried out by connecting the two parts,
Figure 986371DEST_PATH_IMAGE054
is shown in
Figure 717566DEST_PATH_IMAGE021
Time slot service
Figure 710930DEST_PATH_IMAGE026
Vehicle and resource node
Figure 43690DEST_PATH_IMAGE049
The connection is carried out by connecting the two parts,
Figure 780701DEST_PATH_IMAGE055
then it is indicated at
Figure 366404DEST_PATH_IMAGE021
Time slot service
Figure 796248DEST_PATH_IMAGE026
The vehicle is not connected with the resource node
Figure 100190DEST_PATH_IMAGE049
Connecting;
Figure 375314DEST_PATH_IMAGE091
and
Figure 18785DEST_PATH_IMAGE011
respectively representing services
Figure 416268DEST_PATH_IMAGE052
The amount of computing, storage, and network resources required;
Figure 145190DEST_PATH_IMAGE057
and
Figure 787786DEST_PATH_IMAGE058
respectively representing resource nodes
Figure 285763DEST_PATH_IMAGE049
In time slot
Figure 119727DEST_PATH_IMAGE021
The amount of available computing, storage, and network resources;
Figure 70365DEST_PATH_IMAGE059
，
Figure 15188DEST_PATH_IMAGE094
represents a collection of all resource nodes;
Figure 367672DEST_PATH_IMAGE061
to serve
Figure 372537DEST_PATH_IMAGE026
In that
Figure 810471DEST_PATH_IMAGE021
Deployment and operation resource node of time slot
Figure 231088DEST_PATH_IMAGE027
And service
Figure 264510DEST_PATH_IMAGE026
In that
Figure 377960DEST_PATH_IMAGE021
Connection resource node of time slot
Figure 365507DEST_PATH_IMAGE012
Network hop count in between;
Figure 589815DEST_PATH_IMAGE063
to serve
Figure 651312DEST_PATH_IMAGE052
The preset maximum connection distance between the connection resource node and the deployment operation resource node.
Step S3, according to the time slot of vehicle
Figure 997980DEST_PATH_IMAGE116
Internal use service
Figure 410507DEST_PATH_IMAGE026
Cost of migration scheme
Figure 500822DEST_PATH_IMAGE003
The calculation formula and the constraint condition of (2), the calculation is in the time slot
Figure 682405DEST_PATH_IMAGE021
Migration policy that minimizes the total cost of all services within.
Wherein, step S3 includes:
according to time slot
Figure 435860DEST_PATH_IMAGE021
Calculating candidate connection resource nodes of each service according to the position of each vehicle and the coverage range of each resource node and constructing a candidate connection resource node set;
determining a candidate migration scheme of each service according to the candidate connection resource node set;
and obtaining a plurality of candidate migration strategies according to the candidate migration scheme of each service, wherein each candidate migration strategy comprises one migration scheme of each service, and the migration strategy with the minimum total migration cost of all the services is selected from the candidate migration strategies.
The method for obtaining a plurality of candidate migration strategies according to the candidate migration scheme of each service and the correlation among different services, wherein each candidate migration strategy comprises one migration scheme of each service, and the migration strategy with the minimum total migration cost of all the services is selected from the plurality of candidate migration strategies, and comprises the following steps:
setting chromosomes, each chromosome corresponding to one migration strategy and each chromosome comprising
Figure 335682DEST_PATH_IMAGE117
The gene segments of the gene are divided into a plurality of gene segments,
Figure 901793DEST_PATH_IMAGE117
for the total number of all services, each gene fragment corresponds to one migration scheme of one service; each gene segment comprises a first part and a second part, wherein the first part represents the sequence of the connection resource node of the service in the candidate connection resource node set, and the second part represents whether the deployment operation resource node of the service is consistent with the connection resource node of the service;
setting a fitness function related to the cost, wherein if the fitness function value is larger, the cost is smaller, and if the fitness function value is smaller, the cost is larger;
initializing a preset number of chromosomes to form a population, continuously carrying out iterative evolution on the population by using a genetic algorithm, and finally determining a migration strategy corresponding to the optimal chromosomes in the population as a migration strategy with the minimum total migration cost of all services.
Wherein setting the fitness function comprises:
setting a penalty function: penalty function when constraint condition is satisfied
Figure 265778DEST_PATH_IMAGE118
And
Figure 626352DEST_PATH_IMAGE119
the function value of (1) is 0, and when the constraint condition is illegal, the penalty function value is set to be
Figure 75788DEST_PATH_IMAGE120
In which
Figure 445590DEST_PATH_IMAGE120
A fixed constant greater than 0;
Figure 398502DEST_PATH_IMAGE121
setting fitness function
Figure 195557DEST_PATH_IMAGE122
：
Figure 371104DEST_PATH_IMAGE123
Wherein the content of the first and second substances,
Figure 544597DEST_PATH_IMAGE124
to be a predetermined constant, it is generally necessary to be large enough,
Figure 555278DEST_PATH_IMAGE064
presentation service
Figure 585551DEST_PATH_IMAGE125
In a time slot
Figure 681683DEST_PATH_IMAGE021
The migration cost of (2).
Initializing a preset number of chromosomes to form a population, continuously performing iterative evolution on the population by using a genetic algorithm, and finally determining a migration strategy corresponding to the optimal chromosomes in the population, wherein the migration strategy with the minimum total migration cost of all services comprises the following steps:
calculating the fitness of each chromosome;
selecting at least two chromosomes from the population of all chromosomes according to fitness to perform cross operation and mutation operation of gene segments to obtain updated chromosomes;
calculating the fitness of the updated chromosome;
if the difference value between the maximum fitness of the chromosome after updating and the maximum fitness of the chromosome before updating is within a preset range, determining the time slot according to the chromosome after updating corresponding to the maximum fitness
Figure 455604DEST_PATH_IMAGE021
A migration strategy which minimizes the total migration cost of all the services;
and if the difference value between the maximum fitness of the updated chromosome and the maximum fitness of the chromosome before updating is not in the preset range, replacing the chromosome before updating with the updated chromosome, selecting the chromosome again to perform the crossover operation and mutation operation of the gene segments, and calculating the fitness of the chromosome again until the difference value between the maximum fitness of the chromosome and the last maximum fitness is in the preset range.
The following describes a method for service migration in a vehicle network according to an embodiment of the present invention, as shown in fig. 5, including:
step S51, a service migration problem model is established that takes into account the service characteristics.
Step S52, determine the candidate connection resource node set and the associated cost in each timeslot.
And step S53, carrying out binary gene coding on the total migration strategy of all services, initializing chromosomes and forming a population.
And step S54, setting a fitness function and a penalty function.
In step S55, a chromosome fitness function value is calculated.
Step S56, selecting, crossing and mutating chromosomes in the population;
and step S57, repeating the steps S55 and S56 until the end condition is met, and determining the migration scheme of each service according to the final chromosome.
It will be readily appreciated that after step 51, a migration policy may be calculated from the model that minimizes the total cost of all services. Steps S52-S57 provide an alternative but not limiting scheme to other migration policies that can compute the minimum total cost of all services.
In this example, the migration policy with the minimum total cost of all services is obtained through steps S52-S57.
As shown in fig. 6, step S51 includes:
step S51.1, modeling of vehicle services.
In this example, the time slot
Figure 320792DEST_PATH_IMAGE021
The interior vehicles correspond to the services one to one. The following parameters are defined
Figure 521966DEST_PATH_IMAGE126
Indicating that the vehicle is in the time slot
Figure 105394DEST_PATH_IMAGE021
Take over its service
Figure 918891DEST_PATH_IMAGE016
The state of (c). The services of the vehicles in different time slots may be the same or different. Wherein the content of the first and second substances,
Figure 904165DEST_PATH_IMAGE127
to serve
Figure 276240DEST_PATH_IMAGE026
Is of a type such that,
Figure 346965DEST_PATH_IMAGE035
the method comprises the steps of representing a service type set, and being divided into instantaneity service and continuity;
Figure 400371DEST_PATH_IMAGE012
indicating that the vehicle is in the time slot
Figure 302468DEST_PATH_IMAGE021
Connected roadside edge resource nodes, e.g. of a building
Figure 845445DEST_PATH_IMAGE128
Is indicated in a time slot
Figure 137886DEST_PATH_IMAGE021
Edge resource node for vehicle and road side
Figure 555836DEST_PATH_IMAGE049
Connecting;
Figure 250122DEST_PATH_IMAGE027
presentation service
Figure 964000DEST_PATH_IMAGE026
In a time slot
Figure 9317DEST_PATH_IMAGE021
At deploying operational roadside edge resource nodes, e.g.
Figure 466843DEST_PATH_IMAGE129
Is indicated in a time slot
Figure 15636DEST_PATH_IMAGE021
Office service
Figure 165995DEST_PATH_IMAGE026
Deploying and operating on roadside edge resource nodes
Figure 433028DEST_PATH_IMAGE049
A roadside edge resource node of a service deployment operation is called a deployment node for convenience of expression;
Figure 631928DEST_PATH_IMAGE130
and
Figure 599009DEST_PATH_IMAGE131
representing the coordinate position of the vehicle in a two-dimensional space, the moving position of which changes with time;
Figure 920269DEST_PATH_IMAGE132
and
Figure 674599DEST_PATH_IMAGE011
respectively representing services
Figure 411610DEST_PATH_IMAGE026
The amount of required computing, storage and network resources, in this example using blocks of computing resource elements, blocks of storage resource elements, radio resource blocks representing the basic units of computing, storage and network resources, respectively, such as
Figure 997312DEST_PATH_IMAGE133
Presentation service
Figure 427157DEST_PATH_IMAGE052
The number of required computing resource unit blocks is
Figure 465520DEST_PATH_IMAGE134
. Assume that before and after service migration, the service
Figure 6223DEST_PATH_IMAGE026
The required computing, storage and network resources do not change. In that
Figure 204686DEST_PATH_IMAGE021
Time slot, using
Figure 539853DEST_PATH_IMAGE135
Representing the set of all services.
And S51.2, modeling the resource nodes.
In a time slot
Figure 268774DEST_PATH_IMAGE021
A resource node
Figure 409906DEST_PATH_IMAGE049
Is particularly shown as
Figure 907883DEST_PATH_IMAGE136
Wherein, in the step (A),
Figure 476268DEST_PATH_IMAGE137
representing resource nodes
Figure 692485DEST_PATH_IMAGE049
The type of service provided (including the continuity service and the instantaneity service) and corresponding service application image (each resource node only deploys the type of intelligent networked automobile service which is running or possibly running, and in the example, all the servers are defaulted to have image files of all the types of services which are possibly running);
Figure 574991DEST_PATH_IMAGE138
and
Figure 989792DEST_PATH_IMAGE139
as a resource node
Figure 932340DEST_PATH_IMAGE049
A coordinate position in two-dimensional space;
Figure 934056DEST_PATH_IMAGE140
and
Figure 354673DEST_PATH_IMAGE058
respectively representing resource nodes
Figure 889560DEST_PATH_IMAGE049
In a time slot
Figure 737430DEST_PATH_IMAGE021
The amount of available computing, storage and network resources, in units consistent with the basic units in the vehicle service model, respectively. The resource nodes are connected by wired channels such as optical fibers. By using
Figure 662661DEST_PATH_IMAGE141
Representing a topology of a wired channel connection between resource nodes, wherein
Figure 949286DEST_PATH_IMAGE142
Is a set of resource nodes that are,
Figure 276362DEST_PATH_IMAGE143
for the network topological distance set between nodes, the nodes can be represented by an undirected graph due to bidirectional communication between the nodes, and the topological distance is represented by the network hop count between the nodes in the example
Figure 934614DEST_PATH_IMAGE144
And node
Figure 409458DEST_PATH_IMAGE145
Number of network hops in between
Figure 171877DEST_PATH_IMAGE146
Is a node
Figure 353460DEST_PATH_IMAGE147
And node
Figure 871029DEST_PATH_IMAGE148
Topological distance between. In that
Figure 770852DEST_PATH_IMAGE021
Time slot, using
Figure 399279DEST_PATH_IMAGE060
Representing a set of all resource nodes.
And step S51.3, modeling the service migration problem. The method comprises the following specific steps:
at step S51.3.1, a wireless transmission cost is calculated.
Since the amount of processing result data returned is small compared to the data to be processed that is transmitted, the cost of downlink transmission of results from the resource nodes back to the vehicle is negligible compared to the cost of uplink transmission of data from the vehicle to the resource nodes. In this example, it is assumed that the wireless transmission cost between the vehicle and the roadside edge resource node is proportional to the distance between the vehicle and the roadside edge resource node, so the service on the vehicle is
Figure 435368DEST_PATH_IMAGE021
And the road side edge resource nodes connected with the sameWireless transmission cost of transmission service data generation
Figure 628233DEST_PATH_IMAGE007
The definition is as follows:
Figure 15352DEST_PATH_IMAGE149
wherein, the first and the second end of the pipe are connected with each other,
Figure 181891DEST_PATH_IMAGE010
to adjust the parameters;
Figure 338066DEST_PATH_IMAGE011
serving resource nodes
Figure 197438DEST_PATH_IMAGE016
The amount of network resources provided;
Figure 806274DEST_PATH_IMAGE150
roadside edge resource node for vehicle and connection thereof
Figure 42083DEST_PATH_IMAGE012
The distance between the two can be calculated according to the coordinates of the two as follows:
Figure 52764DEST_PATH_IMAGE151
wherein, the first and the second end of the pipe are connected with each other,
Figure 584502DEST_PATH_IMAGE152
and
Figure 680634DEST_PATH_IMAGE153
time slots for vehicles
Figure 188976DEST_PATH_IMAGE021
A coordinate position in two-dimensional space;
Figure 319743DEST_PATH_IMAGE154
and
Figure 458600DEST_PATH_IMAGE155
as a resource node
Figure 104345DEST_PATH_IMAGE156
A coordinate position in two-dimensional space.
At step S51.3.2, a cost of the cable transmission is calculated.
In this example, it is assumed that the cost of wired transmission between resource nodes is proportional to the topological distance thereof, i.e., proportional to the number of network hops between the nodes. To the service
Figure 354061DEST_PATH_IMAGE021
In other words, if the resource node near the vehicle is selected not to be migrated and is used as the transfer node to continue the communication with the source resource node, the related data and results are transmitted between the transfer node and the source resource node, which results in a wired transmission cost. Assume vehicle service
Figure 401651DEST_PATH_IMAGE026
In a time slot
Figure 711410DEST_PATH_IMAGE019
Time and road side edge resource node
Figure 342986DEST_PATH_IMAGE049
Connect and deploy services to the node, i.e.
Figure 396393DEST_PATH_IMAGE157
In time slots
Figure 298490DEST_PATH_IMAGE021
Edge resource node entering road
Figure 779149DEST_PATH_IMAGE035
And select and node
Figure 133907DEST_PATH_IMAGE035
The connection serves as a transit node for transmitting relevant data and results, and the service is continuously maintained at the resource node
Figure 991005DEST_PATH_IMAGE049
In the middle run, then
Figure 685291DEST_PATH_IMAGE158
At this time, the cable transmission cost generated by adopting the transit node mode without transferring the service is not needed
Figure 399170DEST_PATH_IMAGE159
Comprises the following steps:
Figure 444486DEST_PATH_IMAGE160
wherein the content of the first and second substances,
Figure 403477DEST_PATH_IMAGE161
setting adjusting parameters for presetting;
Figure 952270DEST_PATH_IMAGE162
to serve
Figure 102629DEST_PATH_IMAGE026
In that
Figure 369662DEST_PATH_IMAGE019
Resource node where time slot deployment is located
Figure 302983DEST_PATH_IMAGE020
And service
Figure 34178DEST_PATH_IMAGE026
In that
Figure 293121DEST_PATH_IMAGE021
Resource node of time slot connection
Figure 844189DEST_PATH_IMAGE012
The number of network hops between; coefficient 2 represents forwardingData and results are transmitted back and forth.
At step S51.3.3, a migration instance cost is calculated.
In this example, the migration cost generated in the migration process is considered to be proportional to the network hop count from the source deployment resource node to the target deployment resource node, that is:
Figure 846780DEST_PATH_IMAGE163
wherein the content of the first and second substances,
Figure 948595DEST_PATH_IMAGE024
setting adjusting parameters for presetting;
Figure 112860DEST_PATH_IMAGE164
to serve
Figure 416802DEST_PATH_IMAGE026
In that
Figure 957505DEST_PATH_IMAGE019
Source deployment resource node of time slot
Figure 335397DEST_PATH_IMAGE020
And service
Figure 998459DEST_PATH_IMAGE026
In that
Figure 461802DEST_PATH_IMAGE021
Time slot deployment resource node
Figure 868512DEST_PATH_IMAGE027
The number of network hops between;
Figure 366490DEST_PATH_IMAGE028
the cost for restarting the service instance after migrating to the target node is a preset value.
At step S51.3.4, a transfer mirroring cost is calculated. When vehicle and resource node
Figure 436339DEST_PATH_IMAGE012
When connecting and choosing to rebuild an instance by applying mirroring, the cost incurred by the process is defined as follows:
Figure 652557DEST_PATH_IMAGE165
wherein the content of the first and second substances,
Figure 597379DEST_PATH_IMAGE032
as a resource node
Figure 949863DEST_PATH_IMAGE012
A set of offered service types;
Figure 689149DEST_PATH_IMAGE074
as a resource node
Figure 127084DEST_PATH_IMAGE035
A set of offered service types;
Figure 813280DEST_PATH_IMAGE166
as a resource node
Figure 82587DEST_PATH_IMAGE035
And resource node
Figure 196037DEST_PATH_IMAGE012
Network hop count therebetween;
Figure 682119DEST_PATH_IMAGE031
creating an instance cost for a preset;
at step S51.3.5, a problem model is built.
In this example, variables are used
Figure 906427DEST_PATH_IMAGE078
Presentation service
Figure 295820DEST_PATH_IMAGE008
In that
Figure 580171DEST_PATH_IMAGE021
Selection of time slots, and
Figure 727119DEST_PATH_IMAGE167
. Wherein the content of the first and second substances,
Figure 817435DEST_PATH_IMAGE168
presentation service
Figure 999017DEST_PATH_IMAGE008
In that
Figure 516586DEST_PATH_IMAGE021
The time slot adopts a service migration mode to migrate the service instance to a resource node connected nearby the current position;
Figure 416409DEST_PATH_IMAGE080
presentation service
Figure 546301DEST_PATH_IMAGE008
In that
Figure 582390DEST_PATH_IMAGE021
The time slot adopts a transfer node mode, the service is not migrated, the service is continuously kept to operate at a source deployment resource node, and the resource node connected at the current position is used as a transfer node to receive the service;
Figure 270861DEST_PATH_IMAGE042
presentation service
Figure 392401DEST_PATH_IMAGE008
In that
Figure 762202DEST_PATH_IMAGE021
The time slot adopts an application mirror image reconstruction example mode, the service of the resource node deployed by the source is suspended, and the resource node connected at the current position utilizes the local application mirror image or transmits the application mirror image through the nearby resource node to create a new resource nodeThe service instance provides a service.
According to the above discussion, defining at a time slot
Figure 980694DEST_PATH_IMAGE169
Service management system
Figure 777748DEST_PATH_IMAGE016
The total cost of migration decision generation is
Figure 448901DEST_PATH_IMAGE064
，
For the continuity service, the calculation formula is as follows:
Figure 923526DEST_PATH_IMAGE170
for the instant service, the calculation formula is as follows:
Figure 934207DEST_PATH_IMAGE171
during service migration, the computation, storage and network resources of each resource node are limited, and binary variables are defined
Figure 26797DEST_PATH_IMAGE172
Is shown in
Figure 122929DEST_PATH_IMAGE021
Time slot service
Figure 896850DEST_PATH_IMAGE026
Whether to deploy and run in resource node
Figure 27617DEST_PATH_IMAGE049
In the step (1), the first step,
Figure 730256DEST_PATH_IMAGE050
presentation service
Figure 110422DEST_PATH_IMAGE026
In that
Figure 688034DEST_PATH_IMAGE021
Time slot deployment running on resource node
Figure 735624DEST_PATH_IMAGE049
In (1),
Figure 606235DEST_PATH_IMAGE173
then it means none; defining binary variables
Figure 411380DEST_PATH_IMAGE115
Is shown in
Figure 527103DEST_PATH_IMAGE021
Time slot intelligent networking automobile
Figure 366883DEST_PATH_IMAGE026
Whether to communicate with a resource node
Figure 847543DEST_PATH_IMAGE049
The connection is carried out by connecting the two parts,
Figure 467880DEST_PATH_IMAGE054
intelligent network-connected automobile
Figure 59399DEST_PATH_IMAGE174
In that
Figure 81581DEST_PATH_IMAGE021
Time slot and resource node
Figure 733142DEST_PATH_IMAGE049
The connection is carried out by connecting the two parts,
Figure 76661DEST_PATH_IMAGE055
it means no. The resource node running the service instance will provide the computing and storage resources needed for the service, the resource node connected to the vehicle to transmit data and results will provide the network resources needed, the resource node providesCannot exceed its available resource capacity, to the resource node
Figure 471871DEST_PATH_IMAGE049
In other words, the capacity constraints are as follows:
Figure 348560DEST_PATH_IMAGE175
Figure 171022DEST_PATH_IMAGE176
Figure 500372DEST_PATH_IMAGE177
in addition, since the resource node connected to the vehicle and the resource node operated by service deployment may be different, and the excessive network hop count between the two may seriously affect the service quality, the maximum network hop count limit of the two also needs to be considered in the service migration decision process, and the maximum connection distance is set in this example
Figure 699273DEST_PATH_IMAGE063
And when the network hop count between the resource node connected with the vehicle and the resource node operated by service deployment is greater than the maximum connection distance, service migration is forcibly selected.
Figure 430468DEST_PATH_IMAGE178
Wherein the content of the first and second substances,
Figure 423832DEST_PATH_IMAGE061
is composed of
Figure 178161DEST_PATH_IMAGE021
Resource node for time slot vehicle connection
Figure 735745DEST_PATH_IMAGE012
And service
Figure 259130DEST_PATH_IMAGE026
Deploying a running resource node
Figure 485712DEST_PATH_IMAGE027
The connection distance between them, i.e. the number of network hops.
Based on the above discussion, a service migration optimization problem model is established with the system total cost minimization as the optimization target and with the factors of service characteristics, resource capacity, maximum connection distance and the like taken into consideration, and the time slot is calculated
Figure 727338DEST_PATH_IMAGE021
Migration policy that minimizes the total cost of all services within, i.e.
Figure 330358DEST_PATH_IMAGE179
Step S52 specifically includes: calculating connectable candidate nodes according to the position of each vehicle and the coverage range of the resource nodes in each time slot and constructing a node set
Figure 708249DEST_PATH_IMAGE180
And judging the service type of each service in each time slot, and calculating the cost of all migration schemes of all services.
Step S53 specifically includes: chromosomes are used to represent migration protocols.
The chromosomes and the gene segments in this example are common concepts in genetic algorithms, and the meaning and the like thereof are not described herein again. In this example, as shown in FIG. 7, a complete chromosome is composed of
Figure 371312DEST_PATH_IMAGE117
Individual gene fragment composition, number of gene fragments
Figure 834654DEST_PATH_IMAGE117
For total number of services in a service migration scenario, a gene fragment pairShould be a migration scheme for a service. A complete chromosome corresponds to one migration strategy for all services.
In this example, joint binary coding is performed on two optimization variables, namely a connection resource node and a deployment node in the service migration optimization problem. Setting the order of the connection resource node of each gene segment in the candidate connection resource node set, wherein the first part of each gene segment represents the order of the connection resource node of the service, and the second part of each gene segment represents whether the deployment resource node of the service is consistent with the connection resource node of the service.
Each gene fragment may represent a migration scenario for a service. As shown in fig. 7, the first part
Figure 179048DEST_PATH_IMAGE181
Candidate connected resource node representing selected vehicle
Figure 975228DEST_PATH_IMAGE181
And connecting the candidate nodes. For example, if the total number of resource nodes to which a vehicle can be connected at a certain location is 4, then
Figure 746875DEST_PATH_IMAGE181
The binary digit number of (2) is enough; the second part
Figure 759830DEST_PATH_IMAGE182
Then a binary variable is used
Figure 642335DEST_PATH_IMAGE183
Indicating whether a service deployment resource node is consistent with a service connection resource node, e.g.
Figure 57136DEST_PATH_IMAGE184
The connection resource node representing the service is consistent with the service deployment operation resource node, the corresponding decision at this time may be a migration service, the cost is the migration cost, for the instantaneity service, the instance may be created again on the connection resource node, because the calculation, storage and network resources occupied by the migration service and the instance created again are the same resource nodeThe two modes occupy the same amount of resources, so that the corresponding cost is the minimum value of the migration cost and the reconstruction cost;
Figure 999684DEST_PATH_IMAGE185
then, it means that the connection resource node of the vehicle is inconsistent with the service deployment operation resource node, and the corresponding decision is to regard the node as a transit node and keep the service operating in the source resource node, and the cost is the transit cost.
Step S54 specifically includes:
(1) and setting a penalty function.
Penalty function when constraint condition is satisfied
Figure 437619DEST_PATH_IMAGE186
And
Figure 186132DEST_PATH_IMAGE119
is set to 0, and when the constraint condition is violated, the function value of the penalty function is set to
Figure 953975DEST_PATH_IMAGE120
Wherein
Figure 129741DEST_PATH_IMAGE120
Is a preset fixed constant greater than 0.
Figure 54972DEST_PATH_IMAGE187
(2) Introduction of constants
Figure 341597DEST_PATH_IMAGE124
And setting a fitness function according to the migration cost and the penalty function, wherein the larger the fitness function is, the more the target is met.
Figure 668673DEST_PATH_IMAGE188
Wherein the content of the first and second substances,
Figure 749761DEST_PATH_IMAGE124
a constant is introduced for the purpose of presetting the time,
Figure 162288DEST_PATH_IMAGE189
presentation service
Figure 754069DEST_PATH_IMAGE026
In a time slot
Figure 935651DEST_PATH_IMAGE021
The migration cost of (2).
Step S55 specifically includes:
reducing a chromosome to
Figure 390903DEST_PATH_IMAGE117
Individual gene fragment, representative
Figure 87464DEST_PATH_IMAGE117
The intelligent network connects the requested service of the automobile. For each gene fragment, step S53, take its last binary digit
Figure 653574DEST_PATH_IMAGE190
The current migration scheme of the service is confirmed, and the remaining first few binary digits are converted into decimal numbers to confirm the current connected resource node of the service.
After the migration scheme of each service is obtained, the cost of the corresponding migration scheme is respectively calculated, and the total cost of all vehicle services in the current time slot is obtained.
And (3) applying the formulas (11) to (14) to judge whether the total decision violates the constraint, confirming the penalty function value, and finally calculating by the formula (15) to obtain the fitness function of the chromosome.
In the same way, fitness functions for the remaining chromosomes are obtained.
Step S56 specifically includes:
selecting operation: a roulette method was used to select two individuals (chromosomes) from a population (all chromosomes) for crossover operations. In rouletteIn the method, the selection probability of each individual is proportional to its fitness value. To the fitness of
Figure 17560DEST_PATH_IMAGE191
Of (2)
Figure 643713DEST_PATH_IMAGE192
In other words, the probability of being selected is
Figure 827570DEST_PATH_IMAGE193
I.e. the ratio of its fitness to the sum of the fitness of all individuals, the higher the fitness, the higher the probability of being selected.
And (3) cross operation: as shown in fig. 8, two intersections are randomly generated using a double-dot intersection pattern, and gene segments between intersections of two parents (chromosomes) are exchanged to generate new offspring, i.e., two new chromosomes, and the offspring is used instead of the parents.
Mutation operation: the operation simulates the gene mutation phenomenon in nature, the diversity of individuals in the population is increased, and only few genes of few individuals are changed. In the example, a multi-point mutation mode is adopted, for each individual, whether the individual has mutation or not is determined according to a preset mode (such as mutation probability), and if the individual has mutation, the number of gene mutations within the maximum number of the mutation is randomly generated
Figure 197371DEST_PATH_IMAGE194
Then randomly generated for the whole chromosome
Figure 920258DEST_PATH_IMAGE194
And (4) complementing the mutation sites, namely changing from 0 to 1 or changing from 1 to 0. As shown in FIG. 9, the individual had variation, and the number of variation sites was 2.
After the above operation, a new chromosome is obtained.
Step S57 specifically includes: steps S55 and S56 are repeated until the end condition is satisfied.
The ending condition set in this example is that the fitness function reaches the maximum value, that is, as the number of iterations increases, the fitness function does not increase any more, and at this time, the corresponding migration total cost reaches the minimum value, and the migration scheme of each service is obtained according to each gene fragment according to the final chromosome and step S55.
The embodiment of the invention also provides equipment for service migration in the vehicle network, which is applied to a scene comprising vehicles and roadside edge resource nodes. The equipment can be located in the cloud, and can also be located on a vehicle, and the specific setting position of the equipment is not limited as long as the scheme of the text can be realized. As shown in fig. 10, the apparatus comprises a processing module 101 for:
defining a vehicle time slot
Figure 717312DEST_PATH_IMAGE001
Internal use service
Figure 326148DEST_PATH_IMAGE002
The migration scheme of (2) generates a cost of
Figure 296378DEST_PATH_IMAGE195
；
For the continuity service, the calculation formula is as follows:
Figure 307059DEST_PATH_IMAGE196
for the instant service, the calculation formula is as follows:
Figure 337332DEST_PATH_IMAGE197
wherein the content of the first and second substances,
Figure 433464DEST_PATH_IMAGE198
Figure 207385DEST_PATH_IMAGE007
representing services on a vehicle
Figure 72573DEST_PATH_IMAGE026
And connecting resource nodes
Figure 211430DEST_PATH_IMAGE012
A wireless transmission cost generated by transmitting service data between the resource nodes and the service
Figure 358640DEST_PATH_IMAGE026
The roadside edge resource nodes are connected with the vehicle;
Figure 873935DEST_PATH_IMAGE102
setting adjusting parameters for presetting;
Figure 655946DEST_PATH_IMAGE199
for connecting resource nodes
Figure 965705DEST_PATH_IMAGE012
To serve
Figure 98746DEST_PATH_IMAGE026
The amount of network resources provided;
Figure 152153DEST_PATH_IMAGE150
to serve
Figure 54250DEST_PATH_IMAGE026
Located vehicle and connection resource node
Figure 534910DEST_PATH_IMAGE012
The distance between them;
wherein the content of the first and second substances,
Figure 653782DEST_PATH_IMAGE200
Figure 245300DEST_PATH_IMAGE015
presentation to service
Figure 939587DEST_PATH_IMAGE026
Adopting the wired transmission cost generated by a transit node mode;
Figure 919044DEST_PATH_IMAGE069
setting adjusting parameters for presetting;
Figure 698781DEST_PATH_IMAGE201
to serve
Figure 156307DEST_PATH_IMAGE026
In that
Figure 970680DEST_PATH_IMAGE019
Deploying and operating resource nodes of time slots
Figure 855459DEST_PATH_IMAGE020
And service
Figure 122492DEST_PATH_IMAGE026
In that
Figure 885174DEST_PATH_IMAGE021
Connection resource node of time slot
Figure 554053DEST_PATH_IMAGE012
Network hop count therebetween, wherein the deployment run resource node is a deployment run service
Figure 547417DEST_PATH_IMAGE026
Roadside edge resource nodes of (1); the coefficient 2 represents the transmission process of the forwarding data and the result;
wherein the content of the first and second substances,
Figure 364063DEST_PATH_IMAGE202
Figure 101075DEST_PATH_IMAGE107
presentation to service
Figure 686777DEST_PATH_IMAGE008
Migration cost generated by adopting a migration mode;
Figure 116621DEST_PATH_IMAGE024
presetting adjustment parameters;
Figure 420564DEST_PATH_IMAGE164
to serve
Figure 695687DEST_PATH_IMAGE008
In that
Figure 339158DEST_PATH_IMAGE019
Deployment and operation resource node of time slot
Figure 252755DEST_PATH_IMAGE109
And service
Figure 981676DEST_PATH_IMAGE008
In that
Figure 122808DEST_PATH_IMAGE021
Deployment and operation resource node of time slot
Figure 620785DEST_PATH_IMAGE027
Network hop count therebetween;
Figure 454749DEST_PATH_IMAGE028
cost for restarting the service instance after the preset migration to the target node;
wherein the content of the first and second substances,
Figure 405387DEST_PATH_IMAGE203
Figure 287893DEST_PATH_IMAGE204
representing vehicle and resource nodes
Figure 702694DEST_PATH_IMAGE012
Costs incurred in connecting and rebuilding instances by applying mirroring;
Figure 645242DEST_PATH_IMAGE205
creating an instance cost for a preset;
Figure 646958DEST_PATH_IMAGE032
as a resource node
Figure 67575DEST_PATH_IMAGE012
The set of service types that are provided,
Figure 602462DEST_PATH_IMAGE206
presentation service
Figure 715911DEST_PATH_IMAGE016
Is of the type of a resource node
Figure 703459DEST_PATH_IMAGE012
A set of offered service types;
Figure 927767DEST_PATH_IMAGE024
setting adjusting parameters for presetting;
Figure 989264DEST_PATH_IMAGE207
as a resource node
Figure 335931DEST_PATH_IMAGE192
And resource node
Figure 748458DEST_PATH_IMAGE012
Network hop count in between;
Figure 337309DEST_PATH_IMAGE036
as a resource node
Figure 518892DEST_PATH_IMAGE192
A set of offered service types;
Figure 770882DEST_PATH_IMAGE208
presentation service
Figure 670704DEST_PATH_IMAGE016
Is not of a resource node type
Figure 299132DEST_PATH_IMAGE012
Set of offered service types, but belonging to resource nodes
Figure 600800DEST_PATH_IMAGE209
A set of offered service types;
wherein the content of the first and second substances,
Figure 961374DEST_PATH_IMAGE210
presentation service
Figure 410810DEST_PATH_IMAGE026
In that
Figure 780612DEST_PATH_IMAGE021
The mode selection of the time slot is performed,
Figure 234989DEST_PATH_IMAGE040
presentation service
Figure 32044DEST_PATH_IMAGE026
In that
Figure 703197DEST_PATH_IMAGE021
The time slot adopts a migration mode;
Figure 876689DEST_PATH_IMAGE041
presentation service
Figure 887370DEST_PATH_IMAGE026
In that
Figure 917643DEST_PATH_IMAGE021
The time slot adopts a transit node mode;
Figure 13775DEST_PATH_IMAGE042
presentation service
Figure 787696DEST_PATH_IMAGE026
In that
Figure 652884DEST_PATH_IMAGE021
The time slot adopts an application mirror image reconstruction instance mode;
setting constraint conditions; the method comprises the following steps:
Figure 358453DEST_PATH_IMAGE111
Figure 941881DEST_PATH_IMAGE044
Figure 253913DEST_PATH_IMAGE211
Figure 239187DEST_PATH_IMAGE212
wherein, the first and the second end of the pipe are connected with each other,
Figure 548946DEST_PATH_IMAGE047
represents a collection of all services; binary variable
Figure 681987DEST_PATH_IMAGE213
Is shown in
Figure 735393DEST_PATH_IMAGE021
Time slot service
Figure 637490DEST_PATH_IMAGE026
Whether to deploy and run on resource nodes
Figure 118150DEST_PATH_IMAGE049
In (1),
Figure 974373DEST_PATH_IMAGE050
presentation service
Figure 831470DEST_PATH_IMAGE026
In that
Figure 525757DEST_PATH_IMAGE021
Time slot deployment running on resource node
Figure 239635DEST_PATH_IMAGE049
In the step (1), the first step,
Figure 284952DEST_PATH_IMAGE173
then represents the service
Figure 742478DEST_PATH_IMAGE052
In that
Figure 291271DEST_PATH_IMAGE021
The time slot is not deployed and operated on the resource node
Figure 441629DEST_PATH_IMAGE049
Performing the following steps; binary variable
Figure 269515DEST_PATH_IMAGE115
Is shown in
Figure 468415DEST_PATH_IMAGE021
Time slot service
Figure 934031DEST_PATH_IMAGE026
Whether the vehicle is in contact with the resource node
Figure 255291DEST_PATH_IMAGE049
The connection is carried out by connecting the two parts,
Figure 9620DEST_PATH_IMAGE054
is shown in
Figure 746632DEST_PATH_IMAGE021
Time slot service
Figure 332334DEST_PATH_IMAGE026
Vehicle and resource node
Figure 450594DEST_PATH_IMAGE049
The connection is carried out by connecting the two parts,
Figure 426641DEST_PATH_IMAGE214
then it is indicated at
Figure 29660DEST_PATH_IMAGE021
Time slot service
Figure 673131DEST_PATH_IMAGE026
The located vehicle has no node with the resource
Figure 563290DEST_PATH_IMAGE049
Connecting;
Figure 292212DEST_PATH_IMAGE056
and
Figure 371026DEST_PATH_IMAGE215
respectively representing services
Figure 931321DEST_PATH_IMAGE052
The amount of computing, storage, and network resources required;
Figure 437388DEST_PATH_IMAGE057
and
Figure 715923DEST_PATH_IMAGE058
respectively representing resource nodes
Figure 598428DEST_PATH_IMAGE049
In a time slot
Figure 950912DEST_PATH_IMAGE021
The amount of available computing, storage, and network resources;
Figure 955777DEST_PATH_IMAGE216
，
Figure 393712DEST_PATH_IMAGE094
represents a collection of all resource nodes;
Figure 378111DEST_PATH_IMAGE061
to serve
Figure 850680DEST_PATH_IMAGE026
In that
Figure 698551DEST_PATH_IMAGE021
Deployment and operation resource node of time slot
Figure 686098DEST_PATH_IMAGE217
And service
Figure 910406DEST_PATH_IMAGE174
In that
Figure 299799DEST_PATH_IMAGE021
Connection resource node of time slot
Figure 584150DEST_PATH_IMAGE156
Network hop count in between;
Figure 58994DEST_PATH_IMAGE218
to serve
Figure 444582DEST_PATH_IMAGE026
The preset maximum connection distance between the connection resource node and the deployment operation resource node;
according to time slot of vehicle
Figure 688482DEST_PATH_IMAGE001
Internal use service
Figure 143734DEST_PATH_IMAGE002
Cost of migration scheme
Figure 105874DEST_PATH_IMAGE219
The calculation formula and the constraint condition of (2), the calculation is in the time slot
Figure 671984DEST_PATH_IMAGE001
Migration policy that minimizes the total cost of migration of all services within.
Wherein the processing module 101 is further configured to:
according to time slot
Figure 708073DEST_PATH_IMAGE169
Calculating candidate connection resource nodes of each service according to the position of each vehicle and the coverage range of each resource node and constructing a candidate connection resource node set;
obtaining a candidate migration scheme of each service according to the candidate connection resource node set;
and obtaining a plurality of candidate migration strategies according to the candidate migration scheme of each service, wherein each candidate migration strategy comprises one migration scheme of each service, and the migration strategy with the minimum total migration cost of all the services is selected from the candidate migration strategies.
Wherein the processing module 101 is further configured to:
setting chromosomes, each chromosome corresponding to one migration strategy and each chromosome comprising
Figure 898008DEST_PATH_IMAGE117
The gene segments of the gene are divided into a plurality of gene segments,
Figure 285127DEST_PATH_IMAGE117
for the total number of all services, each gene fragment corresponds to one migration scheme of one service; each gene segment comprises a first part and a second part, wherein the first part represents the sequence of the connection resource node of the service in the candidate connection resource node set, and the second part represents whether the deployment operation resource node of the service is consistent with the connection resource node of the service;
setting a fitness function related to the cost, wherein the cost is smaller if the fitness function value is larger, and the cost is larger if the fitness function value is smaller;
initializing a preset number of chromosomes to form a population, continuously carrying out iterative evolution on the population by using a genetic algorithm, and finally determining a migration strategy corresponding to the optimal chromosomes in the population as the migration strategy with the minimum total migration cost of all services.
Initializing a preset number of chromosomes to form a population, continuously performing iterative evolution on the population by using a genetic algorithm, and finally determining a migration strategy corresponding to the optimal chromosomes in the population, wherein the migration strategy with the minimum total migration cost of all services comprises the following steps:
calculating the fitness of each chromosome;
selecting at least two chromosomes from the population of all chromosomes according to fitness to perform cross operation and mutation operation of gene segments to obtain updated chromosomes;
calculating the fitness of the updated chromosome;
if the difference value between the maximum fitness of the chromosome after updating and the maximum fitness of the chromosome before updating is within a preset range, determining the time slot according to the chromosome after updating corresponding to the maximum fitness
Figure 451667DEST_PATH_IMAGE021
A migration strategy which minimizes the total migration cost of all the services;
and if the difference value between the maximum fitness of the updated chromosome and the maximum fitness of the chromosome before updating is not in the preset range, replacing the chromosome before updating with the updated chromosome, selecting the chromosome again to perform the crossover operation and mutation operation of the gene segments, and calculating the fitness of the chromosome again until the difference value between the maximum fitness of the chromosome and the last maximum fitness is in the preset range.
Wherein the processing module 101 is further configured to:
setting a penalty function: penalty function when constraint condition is satisfied
Figure 607841DEST_PATH_IMAGE220
And
Figure 404896DEST_PATH_IMAGE119
has a function value of 0, violatesPenalty function when beam condition is met
Figure 76049DEST_PATH_IMAGE186
And
Figure 249541DEST_PATH_IMAGE119
has a function value of
Figure 322540DEST_PATH_IMAGE120
Wherein
Figure 290496DEST_PATH_IMAGE120
A fixed constant greater than 0;
Figure 386627DEST_PATH_IMAGE221
setting fitness function
Figure 399364DEST_PATH_IMAGE222
：
Figure 530131DEST_PATH_IMAGE223
Wherein the content of the first and second substances,
Figure 731305DEST_PATH_IMAGE124
is a constant value which is preset by the user,
Figure 314733DEST_PATH_IMAGE189
presentation service
Figure 626766DEST_PATH_IMAGE026
In a time slot
Figure 612039DEST_PATH_IMAGE062
The migration cost of (2).
The embodiment of the invention also provides a system for service migration in the vehicle network, which comprises a vehicle, roadside edge resource nodes and the equipment for service migration in the vehicle network.
In the device and the system provided by the embodiment of the invention, different migration schemes are provided for the instant service and the continuous service, different migration schemes and constraint conditions corresponding to different service types are comprehensively considered, and the lowest migration cost is realized under the condition of ensuring the service quality.
To illustrate the superiority of the scheme provided in the embodiment of the present invention, the following describes a cost comparison between Migration-first (MF) mode priority and Transit-first (TF) mode priority in the prior art and the scheme (represented by SMSC) provided in the embodiment of the present invention.
As shown in fig. 11, for each timeslot, the system cost generated by the service migration method SMSC according to the present invention, which determines the service migration policy, is always less than the system cost generated by the two existing methods, i.e., the migration mode priority MF and the transit node mode priority TF, because the reason is that compared with the prior selection of migration or transit, the method according to the present invention finely divides the service according to the service characteristics, comprehensively considers all the selections to reduce the cost, and finally selects the global optimal scheme, and the experimental result proves the effectiveness and the practicability of the method according to the present invention.
As shown in fig. 12, as the number of services increases, the average system cost obtained by the three methods gradually increases, and the system cost of the SMSC method provided by the present invention is significantly lower than that of the other two existing methods, which is reduced by about 40% of the system cost compared to the migration-priority MF method and reduced by about 50% of the system cost compared to the transition-priority TF method, and it is proved that the service migration method considering the service characteristics can significantly and effectively reduce the system cost.
Finally, it should be pointed out that: the above examples are only for illustrating the technical solutions of the present invention, and are not limited thereto. Those of ordinary skill in the art will understand that: modifications can be made to the technical solutions described in the foregoing embodiments, or some technical features may be equivalently replaced; such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present invention.

Claims (10)

1. A method for service migration in a vehicle network, applied to a scene comprising vehicles and roadside edge resource nodes, the method comprising:
step S1, defining a vehicle time slot
Figure DEST_PATH_IMAGE001
Internal use service
Figure DEST_PATH_IMAGE002
The migration scheme of (2) generates a cost of
Figure DEST_PATH_IMAGE003
；
For the continuity service, the calculation formula is as follows:
Figure DEST_PATH_IMAGE004
for the instant service, the calculation formula is as follows:
Figure DEST_PATH_IMAGE005
wherein, the first and the second end of the pipe are connected with each other,
Figure DEST_PATH_IMAGE006
Figure DEST_PATH_IMAGE007
representing services on a vehicle
Figure DEST_PATH_IMAGE008
And connecting resource nodes
Figure DEST_PATH_IMAGE009
A wireless transmission cost generated by transmitting service data between, wherein the resource node is connected with the clothesAffairs
Figure 685864DEST_PATH_IMAGE008
The roadside edge resource nodes are connected with the vehicle;
Figure DEST_PATH_IMAGE010
setting adjusting parameters for presetting;
Figure DEST_PATH_IMAGE011
for connecting resource nodes
Figure 181434DEST_PATH_IMAGE009
To serve
Figure DEST_PATH_IMAGE012
The amount of network resources provided;
Figure DEST_PATH_IMAGE013
to serve
Figure 85805DEST_PATH_IMAGE012
Located vehicle and connection resource node
Figure 481014DEST_PATH_IMAGE009
The distance between them;
wherein, the first and the second end of the pipe are connected with each other,
Figure DEST_PATH_IMAGE014
Figure DEST_PATH_IMAGE015
presentation to service
Figure 357704DEST_PATH_IMAGE012
Adopting the wired transmission cost generated by a transit node mode;
Figure DEST_PATH_IMAGE016
setting adjusting parameters for presetting;
Figure DEST_PATH_IMAGE017
to serve
Figure 806265DEST_PATH_IMAGE012
In that
Figure DEST_PATH_IMAGE018
Deployment and operation resource node of time slot
Figure DEST_PATH_IMAGE019
And service
Figure 135615DEST_PATH_IMAGE012
In that
Figure DEST_PATH_IMAGE020
Connection resource node of time slot
Figure 396832DEST_PATH_IMAGE009
Network hop count therebetween, wherein the deployment run resource node is a deployment run service
Figure DEST_PATH_IMAGE021
Roadside edge resource nodes of (1); the coefficient 2 represents the transmission process of the forwarding data and the result;
wherein the content of the first and second substances,
Figure DEST_PATH_IMAGE022
Figure DEST_PATH_IMAGE023
presentation to service
Figure 688880DEST_PATH_IMAGE012
Migration cost generated by adopting a migration mode;
Figure DEST_PATH_IMAGE024
presetting adjustment parameters;
Figure DEST_PATH_IMAGE025
to serve
Figure 806877DEST_PATH_IMAGE012
In that
Figure 124988DEST_PATH_IMAGE018
Deployment and operation resource node of time slot
Figure 862000DEST_PATH_IMAGE019
And service
Figure 447702DEST_PATH_IMAGE012
In that
Figure 877547DEST_PATH_IMAGE020
Deployment and operation resource node of time slot
Figure DEST_PATH_IMAGE026
Network hop count in between;
Figure DEST_PATH_IMAGE027
cost for restarting the service instance after the preset migration to the target node;
wherein the content of the first and second substances,
Figure DEST_PATH_IMAGE028
Figure DEST_PATH_IMAGE029
representing vehicle and resource nodes
Figure 243806DEST_PATH_IMAGE009
Connection ofAnd rebuild the cost generated when the example through the application mirror image;
Figure DEST_PATH_IMAGE030
creating an instance cost for a preset;
Figure DEST_PATH_IMAGE031
as a resource node
Figure 147958DEST_PATH_IMAGE009
A set of offered service types;
Figure DEST_PATH_IMAGE032
presentation service
Figure DEST_PATH_IMAGE033
Is of the type of a resource node
Figure 853746DEST_PATH_IMAGE009
A set of offered service types;
Figure 188912DEST_PATH_IMAGE024
setting adjusting parameters for presetting;
Figure DEST_PATH_IMAGE034
as a resource node
Figure DEST_PATH_IMAGE035
And resource node
Figure 543932DEST_PATH_IMAGE009
Network hop count therebetween;
Figure DEST_PATH_IMAGE036
as a resource node
Figure DEST_PATH_IMAGE037
A set of offered service types;
Figure DEST_PATH_IMAGE038
presentation service
Figure 747380DEST_PATH_IMAGE012
Is not of a resource node type
Figure 245358DEST_PATH_IMAGE009
Set of offered service types, but belonging to resource nodes
Figure 79322DEST_PATH_IMAGE035
A set of offered service types;
wherein the content of the first and second substances,
Figure DEST_PATH_IMAGE039
presentation service
Figure 29960DEST_PATH_IMAGE002
In that
Figure DEST_PATH_IMAGE040
The mode selection of the time slot is performed,
Figure DEST_PATH_IMAGE041
presentation service
Figure 535635DEST_PATH_IMAGE002
In that
Figure 888118DEST_PATH_IMAGE040
The time slot adopts a migration mode;
Figure DEST_PATH_IMAGE042
presentation service
Figure 892984DEST_PATH_IMAGE002
In that
Figure 330918DEST_PATH_IMAGE001
The time slot adopts a transit node mode;
Figure DEST_PATH_IMAGE043
presentation service
Figure 813852DEST_PATH_IMAGE002
In that
Figure 850203DEST_PATH_IMAGE001
The time slot adopts an application mirror image reconstruction instance mode;
step S2, setting constraint conditions; the method comprises the following steps:
Figure DEST_PATH_IMAGE044
Figure DEST_PATH_IMAGE045
Figure DEST_PATH_IMAGE046
Figure DEST_PATH_IMAGE047
wherein, the first and the second end of the pipe are connected with each other,
Figure DEST_PATH_IMAGE048
represents a collection of all services; binary variable
Figure DEST_PATH_IMAGE049
Is shown in
Figure 150604DEST_PATH_IMAGE001
Time slot service
Figure 75834DEST_PATH_IMAGE008
Whether to deploy and run in resource node
Figure DEST_PATH_IMAGE050
In (1),
Figure DEST_PATH_IMAGE051
presentation service
Figure 855135DEST_PATH_IMAGE008
In that
Figure 978949DEST_PATH_IMAGE001
Time slot deployment running on resource node
Figure 263300DEST_PATH_IMAGE050
In (1),
Figure DEST_PATH_IMAGE052
then represents the service
Figure 738143DEST_PATH_IMAGE008
In that
Figure 828459DEST_PATH_IMAGE001
The time slot is not deployed and operated on the resource node
Figure 10042DEST_PATH_IMAGE050
The preparation method comprises the following steps of (1) performing; binary variable
Figure DEST_PATH_IMAGE053
Is shown in
Figure 763496DEST_PATH_IMAGE020
Time slot service
Figure 663319DEST_PATH_IMAGE008
Whether the located vehicle is connected with the resource node
Figure 291747DEST_PATH_IMAGE050
The connection is carried out by connecting the two parts,
Figure DEST_PATH_IMAGE054
is shown in
Figure 655732DEST_PATH_IMAGE020
Time slot service
Figure 16306DEST_PATH_IMAGE012
Vehicle and resource node
Figure 465742DEST_PATH_IMAGE050
The connection is carried out by connecting the two parts,
Figure DEST_PATH_IMAGE055
then it is indicated at
Figure 835543DEST_PATH_IMAGE020
Time slot service
Figure 286991DEST_PATH_IMAGE012
The vehicle is not connected with the resource node
Figure DEST_PATH_IMAGE056
Connecting;
Figure DEST_PATH_IMAGE057
and
Figure 208680DEST_PATH_IMAGE011
respectively representing services
Figure 817515DEST_PATH_IMAGE012
The amount of computing, storage, and network resources required;
Figure DEST_PATH_IMAGE058
and
Figure DEST_PATH_IMAGE059
respectively representing resource nodes
Figure 617106DEST_PATH_IMAGE050
In time slot
Figure 627788DEST_PATH_IMAGE020
The amount of available computing, storage, and network resources;
Figure DEST_PATH_IMAGE060
，
Figure DEST_PATH_IMAGE061
represents a collection of all resource nodes;
Figure DEST_PATH_IMAGE062
to serve
Figure 720378DEST_PATH_IMAGE012
In that
Figure 816510DEST_PATH_IMAGE020
Deployment and operation resource node of time slot
Figure DEST_PATH_IMAGE063
And service
Figure 590430DEST_PATH_IMAGE012
In that
Figure 22330DEST_PATH_IMAGE020
Connection resource node of time slot
Figure 161187DEST_PATH_IMAGE009
Network hop count in between;
Figure DEST_PATH_IMAGE064
to serve
Figure 806932DEST_PATH_IMAGE012
The preset maximum connection distance between the connection resource node and the deployment operation resource node;
step S3, according to the time slot of vehicle
Figure 56648DEST_PATH_IMAGE020
Internal use service
Figure 104238DEST_PATH_IMAGE012
Cost of migration scheme
Figure 413997DEST_PATH_IMAGE003
The calculation formula and the constraint condition of (2), the calculation is in the time slot
Figure 547038DEST_PATH_IMAGE020
Migration policy that minimizes the total cost of migration of all services within.
2. The method for service migration in a vehicle network according to claim 1, wherein step S3 includes:
according to time slot
Figure 600445DEST_PATH_IMAGE020
Calculating candidate connection resource nodes of each service according to the position of each vehicle and the coverage range of each resource node and constructing a candidate connection resource node set;
determining a candidate migration scheme of each service according to the candidate connection resource node set;
and obtaining a plurality of candidate migration strategies according to the candidate migration scheme of each service, wherein each candidate migration strategy comprises one migration scheme of each service, and the migration strategy with the minimum total migration cost of all the services is selected from the candidate migration strategies.
3. The method for service migration in a vehicle network according to claim 2, wherein a plurality of candidate migration strategies are obtained according to the candidate migration scheme of each service and the correlation between different services, each candidate migration strategy comprises one migration scheme of each service, and the migration strategy with the minimum total migration cost of all the services is selected from the plurality of candidate migration strategies, and comprises:
setting chromosomes, each chromosome corresponding to one migration strategy and each chromosome comprising
Figure DEST_PATH_IMAGE065
The gene segments of the gene are divided into a plurality of gene segments,
Figure 4006DEST_PATH_IMAGE065
for the total number of all services, each gene fragment corresponds to one migration scheme of one service; each gene segment comprises a first part and a second part, wherein the first part represents the sequence of the connection resource nodes of the service in the candidate connection resource node set, and the second part represents whether the deployment operation resource nodes of the service are consistent with the connection resource nodes of the service;
setting a fitness function related to the cost, wherein the cost is smaller if the fitness function value is larger, and the cost is larger if the fitness function value is smaller;
initializing a preset number of chromosomes to form a population, continuously carrying out iterative evolution on the population by using a genetic algorithm, and finally determining a migration strategy corresponding to the optimal chromosomes in the population as a migration strategy with the minimum total migration cost of all services.
4. The method for service migration in a vehicle network of claim 3, wherein said setting a fitness function comprises:
setting a penalty function: penalty function when constraint condition is satisfied
Figure DEST_PATH_IMAGE066
And
Figure DEST_PATH_IMAGE067
the function value of (1) is 0, and when the constraint condition is violated, the penalty function is given
Figure DEST_PATH_IMAGE068
And
Figure 609300DEST_PATH_IMAGE067
has a function value of
Figure DEST_PATH_IMAGE069
Wherein
Figure 964058DEST_PATH_IMAGE069
A fixed constant greater than 0;
Figure DEST_PATH_IMAGE070
setting fitness function
Figure DEST_PATH_IMAGE071
：
Figure DEST_PATH_IMAGE072
Wherein the content of the first and second substances,
Figure DEST_PATH_IMAGE073
in order to set the constant value in advance,
Figure 444324DEST_PATH_IMAGE003
presentation service
Figure 138611DEST_PATH_IMAGE012
In a time slot
Figure 852489DEST_PATH_IMAGE020
The migration cost of (2).
5. The method for service migration in a vehicular network according to claim 4, wherein initializing a preset number of chromosomes to form a population, continuously performing iterative evolution on the population by using a genetic algorithm, and finally determining a migration strategy corresponding to an optimal chromosome in the population as a migration strategy with a minimum total migration cost of all services comprises:
calculating the fitness of each chromosome;
selecting at least two chromosomes from the population of all chromosomes according to fitness to perform cross operation and mutation operation of gene segments to obtain updated chromosomes;
calculating the fitness of the updated chromosome;
if the difference value between the maximum fitness of the chromosome after updating and the maximum fitness of the chromosome before updating is within a preset range, determining the time slot according to the chromosome after updating corresponding to the maximum fitness
Figure DEST_PATH_IMAGE074
A migration strategy with the minimum total migration cost of all the services;
and if the difference value between the maximum fitness of the updated chromosome and the maximum fitness of the chromosome before updating is not in the preset range, replacing the chromosome before updating with the updated chromosome, selecting the chromosome again to perform the crossover operation and mutation operation of the gene segments, and calculating the fitness of the chromosome again until the difference value between the maximum fitness of the chromosome and the last maximum fitness is in the preset range.
6. An apparatus for service migration in a vehicle network, applied to a scenario including a vehicle and roadside edge resource nodes, the apparatus comprising a processing module configured to:
defining a vehicle time slot
Figure 897806DEST_PATH_IMAGE020
Internally used services
Figure 355332DEST_PATH_IMAGE012
The migration scheme of (2) generates a cost of
Figure DEST_PATH_IMAGE075
；
For the continuity service, the calculation formula is as follows:
Figure DEST_PATH_IMAGE076
for the instant service, the calculation formula is as follows:
Figure DEST_PATH_IMAGE077
wherein the content of the first and second substances,
Figure DEST_PATH_IMAGE078
Figure 530223DEST_PATH_IMAGE007
representing services on a vehicle
Figure 618265DEST_PATH_IMAGE002
And connecting resource nodes
Figure 712996DEST_PATH_IMAGE009
A wireless transmission cost generated by transmitting service data between the resource nodes and the service
Figure 911896DEST_PATH_IMAGE002
The roadside edge resource nodes are connected with the vehicle;
Figure 377513DEST_PATH_IMAGE010
setting adjusting parameters for presetting;
Figure 636456DEST_PATH_IMAGE011
for connecting resource nodes
Figure 16884DEST_PATH_IMAGE009
To serve
Figure 753896DEST_PATH_IMAGE008
The amount of network resources provided;
Figure DEST_PATH_IMAGE079
to serve
Figure 339598DEST_PATH_IMAGE008
Located vehicle and connection resource node
Figure 831759DEST_PATH_IMAGE009
The distance between them;
wherein the content of the first and second substances,
Figure DEST_PATH_IMAGE080
Figure 368657DEST_PATH_IMAGE015
presentation to service
Figure 909360DEST_PATH_IMAGE008
Adopting the wired transmission cost generated by a transit node mode;
Figure 615148DEST_PATH_IMAGE016
presetting adjustment parameters;
Figure DEST_PATH_IMAGE081
to serve
Figure 12631DEST_PATH_IMAGE008
In that
Figure 803870DEST_PATH_IMAGE018
Deployment and operation resource node of time slot
Figure 882684DEST_PATH_IMAGE019
And service
Figure 944443DEST_PATH_IMAGE008
In that
Figure 450511DEST_PATH_IMAGE001
Connection resource node of time slot
Figure 729045DEST_PATH_IMAGE009
Network hop count therebetween, wherein the deployment run resource node is a deployment run service
Figure 611551DEST_PATH_IMAGE021
Roadside edge resource nodes of (1); the coefficient 2 represents the transmission process of the forwarding data and the result;
wherein the content of the first and second substances,
Figure DEST_PATH_IMAGE082
Figure 26352DEST_PATH_IMAGE023
presentation to service
Figure 968900DEST_PATH_IMAGE012
Migration cost generated by adopting a migration mode;
Figure 469151DEST_PATH_IMAGE024
setting adjusting parameters for presetting;
Figure 889768DEST_PATH_IMAGE025
to serve
Figure 929049DEST_PATH_IMAGE012
In that
Figure 776920DEST_PATH_IMAGE018
Deployment and operation resource node of time slot
Figure 702150DEST_PATH_IMAGE019
And service
Figure 988775DEST_PATH_IMAGE012
In that
Figure 315851DEST_PATH_IMAGE020
Deployment and operation resource node of time slot
Figure 662519DEST_PATH_IMAGE026
Network hop count in between;
Figure 75046DEST_PATH_IMAGE027
cost for restarting the service instance after the preset migration to the target node;
wherein the content of the first and second substances,
Figure DEST_PATH_IMAGE083
Figure 899782DEST_PATH_IMAGE029
representing vehicle and resource nodes
Figure 81365DEST_PATH_IMAGE009
Costs incurred in connecting and rebuilding instances by applying mirroring;
Figure 100399DEST_PATH_IMAGE030
creating an instance cost for a preset;
Figure DEST_PATH_IMAGE084
as a resource node
Figure 62539DEST_PATH_IMAGE009
A set of offered service types;
Figure DEST_PATH_IMAGE085
presentation service
Figure 690966DEST_PATH_IMAGE012
Is of the type of a resource node
Figure 727055DEST_PATH_IMAGE009
A set of offered service types;
Figure 415526DEST_PATH_IMAGE024
setting adjusting parameters for presetting;
Figure DEST_PATH_IMAGE086
as a resource node
Figure 363497DEST_PATH_IMAGE035
And resource node
Figure 467719DEST_PATH_IMAGE009
Network hop count in between;
Figure DEST_PATH_IMAGE087
as a resource node
Figure 686211DEST_PATH_IMAGE037
A set of offered service types;
Figure DEST_PATH_IMAGE088
presentation service
Figure 545582DEST_PATH_IMAGE012
Is not of a resource node type
Figure 154418DEST_PATH_IMAGE009
Set of offered service types, but belonging to resource nodes
Figure DEST_PATH_IMAGE089
A set of offered service types;
wherein the content of the first and second substances,
Figure 390227DEST_PATH_IMAGE039
presentation service
Figure 964690DEST_PATH_IMAGE012
In that
Figure 932646DEST_PATH_IMAGE020
The mode selection of the time slot is performed,
Figure DEST_PATH_IMAGE090
presentation service
Figure 91095DEST_PATH_IMAGE012
In that
Figure 537120DEST_PATH_IMAGE020
The time slot adopts a migration mode;
Figure DEST_PATH_IMAGE091
presentation service
Figure 730204DEST_PATH_IMAGE012
In that
Figure 931378DEST_PATH_IMAGE020
The time slot adopts a transit node mode;
Figure DEST_PATH_IMAGE092
presentation service
Figure 69799DEST_PATH_IMAGE012
In that
Figure 319515DEST_PATH_IMAGE020
The time slot adopts an application mirror image reconstruction instance mode;
setting constraint conditions; the method comprises the following steps:
Figure DEST_PATH_IMAGE093
Figure DEST_PATH_IMAGE094
Figure DEST_PATH_IMAGE095
Figure DEST_PATH_IMAGE096
wherein the content of the first and second substances,
Figure 429422DEST_PATH_IMAGE048
represents a collection of all services; binary variable
Figure DEST_PATH_IMAGE097
Is shown in
Figure 801498DEST_PATH_IMAGE040
Time slot service
Figure 436004DEST_PATH_IMAGE012
Whether to deploy and run in resource node
Figure 489410DEST_PATH_IMAGE050
In (1),
Figure DEST_PATH_IMAGE098
presentation service
Figure 391507DEST_PATH_IMAGE012
In that
Figure 872167DEST_PATH_IMAGE001
Time slot deployment running on resource node
Figure 226925DEST_PATH_IMAGE050
In (1),
Figure DEST_PATH_IMAGE099
then represents the service
Figure 146339DEST_PATH_IMAGE012
In that
Figure 840626DEST_PATH_IMAGE001
The time slot is not deployed and operated on the resource node
Figure 53039DEST_PATH_IMAGE050
Performing the following steps; binary variable
Figure DEST_PATH_IMAGE100
Is shown in
Figure 98356DEST_PATH_IMAGE001
Time slot service
Figure 555882DEST_PATH_IMAGE012
Whether the vehicle is in contact with the resource node
Figure 166992DEST_PATH_IMAGE050
The connection is carried out by connecting the two parts,
Figure DEST_PATH_IMAGE101
is shown in
Figure 317350DEST_PATH_IMAGE001
Time slot service
Figure 584384DEST_PATH_IMAGE008
Vehicle and resource node
Figure 81486DEST_PATH_IMAGE050
The connection is carried out by connecting the two parts,
Figure DEST_PATH_IMAGE102
then it is indicated at
Figure 812682DEST_PATH_IMAGE001
Time slot service
Figure 71625DEST_PATH_IMAGE008
The vehicle is not connected with the resource node
Figure 622692DEST_PATH_IMAGE050
Connecting;
Figure DEST_PATH_IMAGE103
and
Figure 687600DEST_PATH_IMAGE011
respectively representing services
Figure 210985DEST_PATH_IMAGE008
The amount of computing, storage, and network resources required;
Figure DEST_PATH_IMAGE104
and
Figure DEST_PATH_IMAGE105
respectively representing resource nodes
Figure 941962DEST_PATH_IMAGE050
In a time slot
Figure 245904DEST_PATH_IMAGE001
The amount of available computing, storage, and network resources;
Figure 786607DEST_PATH_IMAGE060
，
Figure 226815DEST_PATH_IMAGE061
represents a collection of all resource nodes;
Figure 827561DEST_PATH_IMAGE062
to serve
Figure 353220DEST_PATH_IMAGE008
In that
Figure 697614DEST_PATH_IMAGE001
Deploying and operating resource nodes of time slots
Figure 759373DEST_PATH_IMAGE026
And service
Figure 265441DEST_PATH_IMAGE008
In that
Figure 543975DEST_PATH_IMAGE001
Connection resource node of time slot
Figure 426481DEST_PATH_IMAGE009
Network hop count therebetween;
Figure 841282DEST_PATH_IMAGE064
to serve
Figure 518251DEST_PATH_IMAGE008
The preset maximum connection distance between the connection resource node and the deployment operation resource node;
according to time slot of vehicle
Figure 956185DEST_PATH_IMAGE020
Internally used services
Figure 704698DEST_PATH_IMAGE012
Cost of migration scheme
Figure 911689DEST_PATH_IMAGE003
The calculation formula and the constraint condition of (2), the calculation is in the time slot
Figure 585990DEST_PATH_IMAGE074
Migration policy that minimizes the total cost of migration of all services within.
7. The apparatus for service migration in a vehicle network of claim 6, wherein the processing module is further configured to:
according to time slot
Figure 511221DEST_PATH_IMAGE020
Calculating candidate connection resource nodes of each service according to the position of each vehicle and the coverage range of each resource node and constructing a candidate connection resource node set;
obtaining a candidate migration scheme of each service according to the candidate connection resource node set;
and obtaining a plurality of candidate migration strategies according to the candidate migration scheme of each service, wherein each candidate migration strategy comprises one migration scheme of each service, and the migration strategy with the minimum total migration cost of all the services is selected from the candidate migration strategies.
8. The apparatus for service migration in a vehicle network of claim 7, wherein the processing module is further configured to:
setting chromosomes, each chromosome corresponding to one migration strategy and each chromosome comprising
Figure 797846DEST_PATH_IMAGE065
The gene segments of the gene are divided into a plurality of gene segments,
Figure 124922DEST_PATH_IMAGE065
for the total number of all services, each gene fragment corresponds to one migration scheme of one service; each gene segment comprises a first part and a second part, wherein the first part represents the sequence of the connection resource node of the service in the candidate connection resource node set, and the second part represents whether the deployment operation resource node of the service is consistent with the connection resource node of the service;
setting a fitness function related to the cost, wherein the cost is smaller if the fitness function value is larger, and the cost is larger if the fitness function value is smaller;
initializing a preset number of chromosomes to form a population, continuously carrying out iterative evolution on the population by using a genetic algorithm, and finally determining a migration strategy corresponding to the optimal chromosomes in the population as the migration strategy with the minimum total migration cost of all services.
9. The apparatus for service migration in a vehicle network of claim 8, wherein the processing module is further configured to:
setting a penalty function: penalty function when constraint condition is met
Figure DEST_PATH_IMAGE106
And
Figure DEST_PATH_IMAGE107
the function value of (1) is 0, and when the constraint condition is violated, the penalty function is given
Figure DEST_PATH_IMAGE108
And
Figure 533907DEST_PATH_IMAGE107
has a function value of
Figure 680854DEST_PATH_IMAGE069
Wherein
Figure 272635DEST_PATH_IMAGE069
A fixed constant greater than 0;
Figure DEST_PATH_IMAGE109
setting fitness function
Figure 516534DEST_PATH_IMAGE071
：
Figure DEST_PATH_IMAGE110
Wherein, the first and the second end of the pipe are connected with each other,
Figure 34103DEST_PATH_IMAGE073
is a constant value which is preset by the user,
Figure 933926DEST_PATH_IMAGE003
presentation service
Figure 500037DEST_PATH_IMAGE008
In a time slot
Figure 598443DEST_PATH_IMAGE001
The migration cost of (2).
10. A system for service migration in a vehicle network, comprising vehicles, roadside edge resource nodes, and the apparatus of any of claims 6-9.
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