CN107317700A - Vehicle-mounted edge calculations node selects system and method - Google Patents
Vehicle-mounted edge calculations node selects system and method Download PDFInfo
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- H—ELECTRICITY
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- H04L41/00—Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks
- H04L41/14—Network analysis or design
- H04L41/145—Network analysis or design involving simulating, designing, planning or modelling of a network
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L41/00—Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks
- H04L41/50—Network service management, e.g. ensuring proper service fulfilment according to agreements
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L67/00—Network arrangements or protocols for supporting network services or applications
- H04L67/01—Protocols
- H04L67/12—Protocols specially adapted for proprietary or special-purpose networking environments, e.g. medical networks, sensor networks, networks in vehicles or remote metering networks
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- H—ELECTRICITY
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- H04W—WIRELESS COMMUNICATION NETWORKS
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- H04W16/02—Resource partitioning among network components, e.g. reuse partitioning
- H04W16/10—Dynamic resource partitioning
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- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W40/00—Communication routing or communication path finding
- H04W40/02—Communication route or path selection, e.g. power-based or shortest path routing
- H04W40/04—Communication route or path selection, e.g. power-based or shortest path routing based on wireless node resources
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Abstract
The invention discloses a kind of vehicle-mounted edge calculations node selection system and method, system includes：Multiple users, task requests are sent to WAP, and itself task uninstall process is completed according to the matching information of vehicles of return；Multiple vehicles, each vehicle as vehicle-mounted edge calculations node, sends status information to WAP at regular intervals；Wait and user's successful match, perform corresponding task, and assist user to complete task unloading；WAP, receives data and processing that user and vehicle edge node are sent, performs node selecting method and matched user and vehicle-mounted edge calculations node；Radio access node specifically includes communication constraint module, calculates constraints module, preliminary matches module and resource distribution module.The present invention can cause Consumer's Experience total in certain area to reach maximum by the vehicle-mounted edge calculations node of optimizing decision and the pairing scheme of user, while ensureing the limited frequency spectrum resource of use of the user node to energy maximal efficiency.
Description
Technical field
The invention belongs to wireless communication field, it is related to edge calculations therein (Edge Computing, EC) framework, especially
It is related to vehicle-mounted edge calculations node selection system and method.
Background technology
Edge calculations (Edge Computing, EC) were proposed that the purpose is to effectively profit by Cisco System Co. in 2014 first
With local idle calculating and storage resource.Nearest edge calculations are considered the low service time delay of acquirement and high Information Security, hidden
The example of private security.It can be assisted it is worth noting that, edge calculations and traditional cloud computing can be compatible, between them
Make.Particularly, edge calculations can carry out pre-processing and then sending it to again distal end using limited local resource to data
Cloud be further processed.On the other hand, edge calculations can also handle some alone to delay sensitive or and geographical position
The application of pass is equipped with, it can ensure lower time delay and energy consumption.Recently, as augmented reality and virtual reality etc. calculate tight type
The appearance of Mobile solution, user is more likely to offload tasks to calculating and storage resource of the edge calculations node using them,
To lift Consumer's Experience (Quality of Experience, QoE).
Recently, the unloading of task to edge calculations node has also obtained the concern of some researchers.Two classes can be divided into：One
Class is to use logic edge calculations node, is not illustrated with instantiation, but with this concept generation of edge calculations node
Refer to；It is another kind of, edge calculations node is embodied as small base station (small cell), unmanned plane (unmanned aerial
Vehicle), vehicle (vehicle) etc., with reference to the analysis of its specific nature.For the different research mode of edge calculations node, no
Same unloading strategy is suggested.
(1) logic edge calculations node is used.By the resource joint in scattered equipment so as to be supplied to Mobile solution
Strategy, is shown in document Z.M.Zhang N, Yang X and S.Y, " Crowd-funding:a new
resourcecooperation mode for mobile cloud computing,”PLoS ONE,Dec.2016.This method
It is edge calculations node by scattered device abstract, QoE values is obtained with the prestige of node, availability, service time delay weighting, so that
Unloading node is selected.But the above method does not specify specific edge calculations node, without actual operability.
(2) use specific edge calculations node, it has been suggested that scheme have：
(2.1) S.Barbarossa, S.Sardellitti, and are seen in small base station as edge calculations node
P.D.Lorenzo,“Joint allocation of computation and communication resources in
multiuser mobile cloud computing,”in IEEE Workshop on Signal Processing
Advances in Wireless Communications(SPAWC),Darmstadt,Jun.2013,pp.26–30.This method
The communication of the small base station of co-allocation and computing resource so that can be with the smaller more requests of energy consumption processing.But the above method
It is required that adding extra computing function in small base station, which increase cost.
(2.2) unmanned plane is shown in document N.H.Motlagh, M.Bagaa and T.Taleb as edge calculations node, "
UAV Selection for a UAV-Based Integrative IoT Platform,"IEEE Global
Communications Conference(GLOBECOM),Washington,DC,2016,pp.1-6.This method is by solving line
Property integer programming problem optimize the energy consumption and run time of unmanned plane, it is desirable to energy consumption is more under the premise of same task is completed
Low, run time is less.But the unmanned plane in above method energy itself also needs to support its flight, leaves the energy consumption of calculating for
May be very limited.
(2.3) vehicle is used as edge calculations node.Current vehicle can serve as node in EC by being connected into network.Vehicle
We term it car networking (Internet of Vehicle, IoV) for the network that interconnection is formed.Some nearest researchers regard IoV
Make one kind and have very much potential EC platforms, reason is as follows：First, the huge amount of vehicle and widely distributed, user can be so as to
Vehicle around prompt access；Secondly, the vehicle computing unit (On Board Unit, OBU) on vehicle can be terminal user
The calculating enriched and storage resource are provided；Finally, vehicle and without the concern for quantity problem, because its own can just regard one as
Individual small generator.
See document H.Zhang, Q.Zhang, and X.Du, " Toward vehicle-assisted cloud
computingfor smartphones,”IEEE Transactions on Vehicular Technology,vol.64,
no.12,pp.5610–5618,Dec.2015.It this method propose and assist smart mobile phone to carry out using the idling-resource in vehicle
Task is unloaded, and selects suitable vehicle calculate node to meet and task is completed within the time limit.But this method does not account for user
The guarantee of experience, and it is only capable of supporting the calculating task unloading of mobile phone.
The content of the invention
It is an object of the invention to provide a kind of vehicle-mounted edge calculations node selecting method, this method passes through optimizing decision car
Edge calculations node and the pairing scheme of user are carried, Consumer's Experience total in certain area can be caused to reach maximum, is protected simultaneously
Demonstrate,prove the limited frequency spectrum resource of use of the user-node to energy maximal efficiency.
For up to above-mentioned purpose, the technical scheme used is：
A kind of vehicle-mounted edge calculations node selection system, including multiple users, radio access node and multiple vehicles are provided；
Multiple users, task requests are sent to WAP, and itself task is completed according to the matching information of vehicles of return
Uninstall process；
Multiple vehicles, each vehicle as vehicle-mounted edge calculations node, is sent to WAP at regular intervals
The status information of oneself；And wait and user's successful match, corresponding task is performed, and assist user to complete task unloading；
WAP, receives data and processing that user and vehicle edge node are sent, performs node selecting method, will
User and vehicle-mounted edge calculations node are matched；
Radio access node specifically includes communication constraint module, calculates constraints module, preliminary matches module and resource allocation
Module；
Communication constraint module, according to the mobility of vehicle, calculates time constraint condition, determines occur between user and vehicle
Number of sub-channels required for pairing；Channel is divided into by the equal subchannel of some bandwidth by OFDM, for
The average data transfer rate of each sub-channels of identical link is equal；Led to according to the maximum that car status information calculates vehicle
Believe duration, take the smaller of the communication time of task time-constrain in itself and vehicle, as the actual total duration of task, this is total
Duration includes the time of task transmission and processing procedure；According to each task size, calculating is gone out on missions processing time, and is calculated
The transmission time of task, and the message transmission rate of demand is calculated, then according to shannon formula, noise power and user and car
Channel gain matrix between calculates actual data transfer rate；Make the message transmission rate and actual data transfer speed of demand
Rate is equal, then obtains the subchannel number distributed between every a pair of users and vehicle；
Constraints module is calculated, processing task institute consumed energy is modeled, according to whether carrying out unloading is divided into two kinds of feelings
Condition is modeled：If 1) do not unloaded, task is locally handled；Assuming that task execution time is exactly the time-constrain of task
Under conditions of, the cpu frequency of user equipment is taken between peak frequency and mission requirements frequency according to dynamic voltage scaling technology
Smaller value；Then local consumed energy is calculated；If 2) unloaded, task is handled in vehicle-mounted fringe node；Calculate
User equipment is sent with receiving the energy that data and static power are consumed；If task result data amount very little, the energy consumed
Amount and time ignore；With reference to send Time Calculation go out on missions unloading when user equipment consume energy；
Subchannel number, calculating constraint mould needed for preliminary matches module, the user-vehicle exported according to communication constraint module
The processing required by task consumed energy and Consumer's Experience evaluation model of block output, user-car is carried out based on Double Auction theory
Carry edge calculations node preliminary matches；User is weighed by node availability, three aspects of node prestige and communication overhead
Consumer's Experience, and based on Double Auction theory user and vehicle-mounted edge calculations node are matched；
Resource distribution module, the user exported according to preliminary matches module-vehicle matches scheme, is carried out based on linear programming
Sub-channel resource is distributed, the final matching of output and frequency spectrum resource allocation result.
Above-mentioned technical proposal is connect, the task requests that user sends include task size, the QoE values that should be reached, time about
Beam, transmit power, static power, maximum cpu frequency and user coordinates.
Connect above-mentioned technical proposal, the status information of vehicle include the coordinate of car, speed, the direction of motion, maximum cpu frequency,
Prestige and availability.
Above-mentioned technical proposal is connect, the node availability finger joint point can provide the probability of service after receiving an assignment, saved
Point prestige finger joint point can be provided the probability of service after receiving an assignment by quality, and communication overhead represents that user sends and receives data
The energy of consumption.
Above-mentioned technical proposal is connect, task requests are sent to WAP by WiFi network respectively between user and vehicle
And status information, pass through the short haul connection based on OFDMA technology between user and vehicle-mounted edge calculations node.
Present invention also offers a kind of vehicle-mounted edge calculations node selecting method, comprise the following steps：
Multiple users send task requests to WAP, and completing itself task according to the matching information of vehicles of return unloads
Load process；
Each vehicle is as vehicle-mounted edge calculations node, and multiple vehicles are sent certainly to WAP at regular intervals
Oneself status information；And wait and user's successful match, corresponding task is performed, and assist user to complete task unloading；
WAP receives data and the processing that user and vehicle edge node are sent, and performs node selecting method, will
User and vehicle-mounted edge calculations node are matched, and are specially：
According to the mobility of vehicle, time constraint condition is calculated, is determined required for being matched between user and vehicle
Number of sub-channels；Channel is divided into by the equal subchannel of some bandwidth by OFDM, it is each for identical link
The average data transfer rate of sub-channels is equal；The maximum communication duration of vehicle is calculated according to car status information, takes and appoints
The smaller of the time-constrain of business itself and the communication time of vehicle, as the actual total duration of task, the total duration includes appointing
Business sends the time with processing procedure；According to each task size, calculating is gone out on missions processing time, and calculates the transmission of task
Time, and the message transmission rate of demand is calculated, then according to the letter between shannon formula, noise power and user and vehicle
Road gain matrix calculates actual data transfer rate；Make the message transmission rate and actual data transfer rate of demand equal, then
Obtain the subchannel number distributed between every a pair of users and vehicle；
Processing task institute consumed energy is modeled, according to whether carrying out unloading is divided into two kinds of situation modelings：If 1)
Do not unload, then task is locally handled；Under conditions of assuming that task execution time is exactly the time-constrain of task, user
The cpu frequency of equipment takes the smaller value between peak frequency and mission requirements frequency according to dynamic voltage scaling technology；Then count
Calculate local consumed energy；If 2) unloaded, task is handled in vehicle-mounted fringe node；Calculate user equipment send with
Receive the energy that data and static power are consumed；If task result data amount very little, the energy and time consumed is ignored not
Meter；With reference to send Time Calculation go out on missions unloading when user equipment consume energy；
The processing that subchannel number, calculating constraints module needed for the user-vehicle exported according to communication constraint module are exported
The Consumer's Experience evaluation model of required by task consumed energy and structure simultaneously carries out user-vehicle-mounted edge based on Double Auction theory
Calculate node preliminary matches；The user of user is weighed by node availability, three aspects of node prestige and communication overhead
Experience, and user and vehicle-mounted edge calculations node are matched based on Double Auction theory；
The user exported according to preliminary matches module-vehicle pairing scheme, sub-channel resource point is carried out based on linear programming
Match somebody with somebody, the final matching of output and frequency spectrum resource allocation result.
Above-mentioned technical proposal is connect, the task requests that user sends include task size, the QoE values that should be reached, time about
Beam, transmit power, static power, maximum cpu frequency and user coordinates.
Connect above-mentioned technical proposal, the status information of vehicle include the coordinate of car, speed, the direction of motion, maximum cpu frequency,
Prestige and availability.
Above-mentioned technical proposal is connect, the node availability finger joint point can provide the probability of service after receiving an assignment, saved
Point prestige finger joint point can be provided the probability of service after receiving an assignment by quality, and communication overhead represents that user sends and receives data
The energy of consumption.
Above-mentioned technical proposal is connect, task requests are sent to WAP by WiFi network respectively between user and vehicle
And status information, pass through the short haul connection based on OFDMA technology between user and vehicle-mounted edge calculations node.
The beneficial effect comprise that：The vehicle-mounted edge calculations node selecting method of the present invention is considered edge calculations
Node is set to vehicle, and is accounted for reference to its mobility.The Consumer's Experience of user is modeled, by this system of selection
So that the Consumer's Experience summation that all users obtain is tried one's best greatly.Meanwhile, frequency spectrum money is carried out to every a pair of users of matching and node
Source is distributed so that maximum resource utilization.Present invention can apply in future car networking arenas, effectively utilize the free time of vehicle
Resource, wide application.
Brief description of the drawings
Below in conjunction with drawings and Examples, the invention will be further described, in accompanying drawing：
Fig. 1 is the system block diagram for the task uninstall process that the present invention is provided；
Fig. 2 is WAP internal module system block diagram.
Fig. 3 is the flow chart of vehicle-mounted edge calculations.
Embodiment
In order to make the purpose , technical scheme and advantage of the present invention be clearer, it is right below in conjunction with drawings and Examples
The present invention is further elaborated.It should be appreciated that specific embodiment described herein is only to explain the present invention, not
For limiting the present invention.
As shown in figure 1, it is related to multiple users in the present invention, multiple vehicle-mounted edge calculations nodes and WAP.
Multiple users (user 1, user 2) can send task requests to WAP 3, and (it is big that request content includes task
QoE values, time-constrain, transmit power, static power, maximum cpu frequency and user coordinates small, should reach), matched
The information of vehicles arrived, so as to continue to complete task uninstall process.
Multiple vehicle-mounted edge calculations nodes (vehicle-mounted edge calculations node 4, vehicle-mounted edge calculations node 5) are at regular intervals
Sending the status information of oneself to WAP, (status information includes coordinate, speed, the direction of motion, the maximum CPU frequencies of car
Rate, prestige, availability).Wait and user's successful match, so as to assist completion task to unload.
WAP 3 is task distribution end, handles the user received and vehicle edge node data, performs node selection
Method, will be matched between multi-user and how vehicle-mounted edge calculations node.
Fig. 2 is the internal module system block diagram of WAP, including communication constraint module 31, calculate constraints module 32,
Preliminary matches module 33 and resource distribution module 34.Communication constraint module and calculate constraints module to be collected into user, car
Fringe node information is pre-processed, respectively output result to preliminary matches module, afterwards preliminary matches module output knot
Fruit enters resource distribution module, exports final user-vehicle-mounted fringe node and matches and frequency spectrum resource allocative decision.
The cycle (such as 100ms) receives the status information that neighbouring vehicle is sent to WAP at regular intervals.When with
When family has task to need to be unloaded, their solicited message is equally sent to WAP.WAP can cache this
A little information, then in conjunction with user and the information of vehicle, every the fixed cycle (such as 100ms) perform node selecting method to user and
Node match and output matching result.
Communication constraint module 31 considers the mobility of vehicle, its time constraint condition is calculated, so that it is determined that user and node
Between communication bandwidth.Assuming that user's collection is combined into U, number of users is M, and vehicle-mounted edge calculations node set is V, vehicle-mounted edge meter
Operator node quantity is N.It is contemplated that OFDM (Orthogonal Frequency Division Multiple,
), OFDMA it (is W that channel is divided into some bandwidth equal0) subchannel, its average data transfer rate is equal.L is channel
Sum, lijRepresent the subchannel number (i ∈ U, j ∈ V) distributed between user i and vehicle j.According to vehicle and AP coordinate, AP
Communication radius, the direction of motion of speed and car, we can calculate the maximum communication duration of car.Take task in itself when
Between constraint and the smaller of the communication time of car, the as actual total duration of task, including task send and processing procedure when
Between.Due to each task data amount, it is known that we can calculate task processing time, then can further calculate the hair of task
The time is sent, such as user i transmission time is expressed asWith reference to task size, (user i task size is expressed as Di) can count
The message transmission rate of calculation demand, then according to shannon formula, noise power N0And the channel gain between user and vehicle
(channel gain matrix between user i and vehicle j is H to the actual data transfer rate that matrix H is calculatedij).Both orders are equal can
To obtain the subchannel number distributed between every a pair of users and node；
Calculate 32 pairs of processing task institute consumed energies of constraints module to be modeled, be divided into two kinds of situation considerations：
If 1) do not unloaded, task is locally handled.Assuming that task execution time is exactly the time of task about
Under conditions of beam, the cpu frequency of user equipment is according to dynamic voltage scaling (Dynamic Voltage Scaling, DVS) skill
Art, takes the smaller value between peak frequency and mission requirements frequency.Local consumed energy (user is calculated then in conjunction with correlation formula
I local consumed energy is expressed as)。
If 2) unloaded, task is handled in fringe node.Calculative is that user equipment is sent with connecing
(user i task unloads consumed energy to the energy that receipts data and static power are consumedTransmit power is).By
In task result data amount very little, so the energy and time of consumption can be ignored, M.Halpern, Y.Zhu, and are referred to
V.J.Reddi,“Mobile cpu’s rise to power:Quantifying the impact of generational
mobile cpu design trends on performance,energy,and user satisfaction,”in IEEE
International Symposium on High Performance Computer Architecture(HPCA),
Barcelona,Mar.2016,pp.64–76.The energy of user equipment consumption when going out on missions unloading can be calculated with reference to the transmission time.
Unloading can not still be decided whether by calculating constraints module, and calculating constraints module handle is unloaded, do not unloaded either way
Take in, the result of last resource distribution module have decided on whether unloading (be not paired to vehicle be taken as do not unload
Carry).
Preliminary matches module 33 is based on Consumer's Experience evaluation model and carries out user-vehicle-mounted edge based on Double Auction theory
Calculate node preliminary matches.Consumer's Experience evaluation model is by node availability, node prestige and communication overhead three
Come the Consumer's Experience of weighing user, (node availability finger joint point can provide the probability of service, node to aspect after receiving an assignment
Prestige finger joint point can be provided the probability of service after receiving an assignment by quality, and communication overhead represents that user sends and receives data
The energy of consumption).User has a preference coefficient for each index, uses rxRepresent, (x ∈ { 1,2,3 }), between (0,1)
Value, three adds up to 1.The numerical value of this three aspect (is usedRepresent the numerical value in terms of vehicle j xth) arrived by standardizing (0,
1) it is weighted after according to preference coefficient and can obtain corresponding Consumer's Experience (vehicle j is for the user i Consumer's Experiences provided
QoEij).Use αijRepresent whether user i is matched with vehicle j.
According to above communication constraint, constraint and frequency spectrum resource constraint limitation are calculated, in order to improve Consumer's Experience, is established
Following optimization problem.The optimization problem can export the user-node matching result for improving overall customer experience.The optimization of foundation
Problem is as follows：
It is confined to：s.t.
Wherein M is number of users, generally can use 1-50, N is vehicle fleet size, generally can use 10-100.
This problem is segmented into two sub- problem solvings, and first is based on the theoretical user of Double Auction and vehicle-mounted side
Edge calculate node marriage problem, second is limited spectrum resources assignment problem.Preliminary matches module solves first problem.It is double
Side Game Theory refers to A.L.Jin, W.Song, P.Wang, D.Niyato, and P.Ju, " Auction mechanisms
toward efficient resource sharing for cloudlets in mobile cloud computing,”
IEEE Transactions on Services Computing,vol.9,no.6,pp.895–909,Nov.2016.Solve and calculate
Method is as follows：
The QNS preliminary matches stage
_____________________________________
1. a couple set Q is ranked up, user i serial number i=1 is made；
2. for user i ∈ U, following steps are performed if i≤M：
3. define Q-iFor set Q removed users i QiThe set formed.Find set Q-iIntermediate value, and be defined as
If matched 4. node j is successful with user i, then we leave out node j from set V；
5. C is defined to meet QoE in set Vij≥QiNumber of nodes；
If 6. C==0, then haveUser i mismatches simultaneously perform i=i+1, return to Step2；
If 7. C==1, performs following steps：
If 8. node x is to meet QoEix≥QiNode, then corresponding QoE is defined as Qselect；
9. find set V0In meet QoEij≤QselectNode, if it does, selection possesses highest QoE node y,
Its QoE provided is QoEiy；
10. definition balance QoE is
11. ifAndUser i and node x into
Work(is matched, wherein,And j ≠ x,I=i+1 is performed, Step2 is returned；
If 12. C >=2, perform following steps：
13. QoE will be met in set Vij≥QiNode composition set be defined as I.Find in set I and possess highest
QoE node x, its QoE provided is defined as Qselect；
14. find set V0In meet QoEij≤QselectNode, selection possess highest QoEijNode y；
15. definition balance QoE is
16. ifAndUser i and node x successful match, wherein,And j ≠ x,I=i+1 is performed, Step2 is returned；
17. otherwise leaving out node x from set I, and highest QoE in I is selected againijNode, define its offer QoE
For QselectAnd return to Step14；
The solution Second Problem of resource distribution module 34, the communication resource allocation issues based on linear programming, referring to
A.Schrijver, Theory of Linear and Integer Programming.John Wiley and Sons,
1998.And export last matching result.The optimization problem that the process is solved is as follows：
It is confined to：
Solved using the existing solution of 0-1 knapsack problems.
As shown in figure 3, based on said system, present invention also offers a kind of vehicle-mounted edge calculations node selecting method, bag
Include following steps：
Multiple users send task requests to WAP, and completing itself task according to the matching information of vehicles of return unloads
Load process；
Each vehicle is as vehicle-mounted edge calculations node, and multiple vehicles are sent certainly to WAP at regular intervals
Oneself status information；And wait and user's successful match, corresponding task is performed, and assist user to complete task unloading；
WAP receives data and the processing that user and vehicle edge node are sent, and performs node selecting method, will
User and vehicle-mounted edge calculations node are matched, and are specially：
According to the mobility of vehicle, time constraint condition is calculated, is determined required for being matched between user and vehicle
Number of sub-channels；Channel is divided into by the equal subchannel of some bandwidth by OFDM, it is each for identical link
The average data transfer rate of sub-channels is equal；The maximum communication duration of vehicle is calculated according to car status information, takes and appoints
The smaller of the time-constrain of business itself and the communication time of vehicle, as the actual total duration of task, the total duration includes appointing
Business sends the time with processing procedure；According to each task size, calculating is gone out on missions processing time, and calculates the transmission of task
Time, and the message transmission rate of demand is calculated, then according to the letter between shannon formula, noise power and user and vehicle
Road gain matrix calculates actual data transfer rate；Make the message transmission rate and actual data transfer rate of demand equal, then
Obtain the subchannel number distributed between every a pair of users and vehicle；
Processing task institute consumed energy is modeled, according to whether carrying out unloading is divided into two kinds of situation modelings：If 1)
Do not unload, then task is locally handled；Under conditions of assuming that task execution time is exactly the time-constrain of task, user
The cpu frequency of equipment takes the smaller value between peak frequency and mission requirements frequency according to dynamic voltage scaling technology；Then count
Calculate local consumed energy；If 2) unloaded, task is handled in vehicle-mounted fringe node；Calculate user equipment send with
Receive the energy that data and static power are consumed；If task result data amount very little, the energy and time consumed is ignored not
Meter；With reference to send Time Calculation go out on missions unloading when user equipment consume energy；
The processing that subchannel number, calculating constraints module needed for the user-vehicle exported according to communication constraint module are exported
The Consumer's Experience evaluation model of required by task consumed energy and structure simultaneously carries out user-vehicle-mounted edge based on Double Auction theory
Calculate node preliminary matches；The user of user is weighed by node availability, three aspects of node prestige and communication overhead
Experience, and user and vehicle-mounted edge calculations node are matched based on Double Auction theory；
The user exported according to preliminary matches module-vehicle pairing scheme, sub-channel resource point is carried out based on linear programming
Match somebody with somebody, the final matching of output and frequency spectrum resource allocation result.
Above-mentioned technical proposal is connect, the task requests that user sends include task size, the QoE values that should be reached, time about
Beam, transmit power, static power, maximum cpu frequency and user coordinates.
Connect above-mentioned technical proposal, the status information of vehicle include the coordinate of car, speed, the direction of motion, maximum cpu frequency,
Prestige and availability.
Above-mentioned technical proposal is connect, the node availability finger joint point can provide the probability of service after receiving an assignment, saved
Point prestige finger joint point can be provided the probability of service after receiving an assignment by quality, and communication overhead represents that user sends and receives data
The energy of consumption.
Above-mentioned technical proposal is connect, task requests are sent to WAP by WiFi network respectively between user and vehicle
And status information, pass through the short haul connection based on OFDMA technology between user and vehicle-mounted edge calculations node.
In the specific embodiment of the present invention, it is assumed that WAP communication radius is 100m, and number of users is 10, car
Quantity is 10.User and vehicle are using AP as the center of circle, and radius is to be uniformly distributed in 100m circle.User emission power is
100mW, static power is 10mW.User's maximum cpu frequency is 0.5GHz, and vehicle cpu frequency is 1.2GHz.Total bandwidth is 5Mb/
S, subchannel number is 500.The coordinate of user be (- 21.67,47.54), (72.77,67.66), (20.32, -8.07), (-
6.45, -8.38), (- 10.87,1.41), (- 4.07, -4.88), (- 38.87, -11.21), (- 26.96, -35.82), (-
35.19, -9.95), (- 13.81, -75.09) (unit：m).The QoE threshold values of user are respectively 0.6255,0.6543,0.6865,
0.6945、0.5384、0.5277、0.6392、0.5187、0.6050、0.6060.The time-constrain of user be 145.55,
74.50th, 125.72,105.75,81.22,114.07,76.36,110.52,81.65,79.59 (unit：ms).The coordinate of vehicle
For (16.89,64.00), (- 10.53, -40.26), (7.27,83.87), (60.93,56.78), (- 20.03, -16.00), (-
58.35,18.90), (- 56.27,14.93), (- 28.41, -46.00), (11.05, -86.28), (- 15.59,21.39) are (single
Position：m).The credit value of vehicle is respectively 0.9345,0.8452,0.9440,0.9312,0.8405,0.8018,0.9396,
0.9778、0.8286、0.9111.The availability of vehicle is respectively 0.8561,0.7546,0.8294,0.8518,0.81486,
0.7972、0.9472、0.8531、0.9630、0.8438。
The user of final output and vehicle mapping relations are σ={ 8,3,0,0,0,0,0,0,2,4 }.σ (1)=8 represents sequence
Number the vehicle-mounted edge calculations node of serial number 8 is matched for 1 user, σ (3)=0 represents that the user of serial number 3 does not succeed
Vehicle-mounted edge calculations node is matched, similarly hereinafter.It is 3.0453 finally to calculate total Consumer's Experience.When total bandwidth is 5Mb/s, respectively
The band of distribution is a width of：User 1 --- 1.46Mb/s, user 2 --- 0.6Mb/s, user 9 --- 1.3Mb/s, user 10 ---
1.52Mb/s.Total occupied bandwidth is 4.88Mb/s, less than 5Mb/s.
It should be appreciated that for those of ordinary skills, can according to the above description be improved or converted,
And all these modifications and variations should all belong to the protection domain of appended claims of the present invention.
Claims (10)
1. a kind of vehicle-mounted edge calculations node selection system, it is characterised in that including multiple users, radio access node and multiple
Vehicle；
Multiple users, task requests are sent to WAP, and the unloading of itself task is completed according to the matching information of vehicles of return
Process；
Multiple vehicles, each vehicle as vehicle-mounted edge calculations node, sends oneself to WAP at regular intervals
Status information；And wait and user's successful match, corresponding task is performed, and assist user to complete task unloading；
WAP, receives data and processing that user and vehicle edge node are sent, node selecting method is performed, by user
Matched with vehicle-mounted edge calculations node；
Radio access node specifically includes communication constraint module, calculates constraints module, preliminary matches module and resource distribution module；
Communication constraint module, according to the mobility of vehicle, calculates time constraint condition, determines to match between user and vehicle
Required number of sub-channels；Channel is divided into by the equal subchannel of some bandwidth by OFDM, for identical
Each sub-channels of link average data transfer rate it is equal；When the maximum communication of vehicle is calculated according to car status information
It is long, take the smaller of the communication time of task time-constrain in itself and vehicle, the total duration for being used as task actual, the total duration
The time with processing procedure is sent including task；According to each task size, calculating is gone out on missions processing time, and calculates task
The transmission time, and calculate the message transmission rate of demand, then according to shannon formula, noise power and user and vehicle it
Between channel gain matrix calculate actual data transfer rate；Make the message transmission rate and actual data transfer rate phase of demand
Deng then obtaining the subchannel number distributed between every a pair of users and vehicle；
Constraints module is calculated, processing task institute consumed energy is modeled, is built according to whether carrying out unloading and being divided into two kinds of situations
Mould：1）If do not unloaded, task is locally handled；Assuming that task execution time is exactly the bar of the time-constrain of task
Under part, the cpu frequency of user equipment takes smaller between peak frequency and mission requirements frequency according to dynamic voltage scaling technology
Value；Then local consumed energy is calculated；2）If unloaded, task is handled in vehicle-mounted fringe node；Calculate user
Equipment is sent with receiving the energy that data and static power are consumed；If task result data amount very little, the energy consumed and
Time ignores；With reference to send Time Calculation go out on missions unloading when user equipment consume energy；
Subchannel number, calculating constraints module are defeated needed for preliminary matches module, the user-vehicle exported according to communication constraint module
The processing required by task consumed energy and Consumer's Experience evaluation model gone out, user-vehicle-mounted side is carried out based on Double Auction theory
Edge calculate node preliminary matches；The use of user is weighed by node availability, three aspects of node prestige and communication overhead
Family is experienced, and user and vehicle-mounted edge calculations node are matched based on Double Auction theory；
Resource distribution module, the user exported according to preliminary matches module-vehicle matches scheme, and sub- letter is carried out based on linear programming
Road resource allocation, the final matching of output and frequency spectrum resource allocation result.
2. system according to claim 1, it is characterised in that the task requests that user sends include task size, should
QoE values, time-constrain, transmit power, static power, maximum cpu frequency and the user coordinates reached.
3. system according to claim 1, it is characterised in that coordinate of the status information of vehicle including car, speed, motion
Direction, maximum cpu frequency, prestige and availability.
4. system according to claim 1, it is characterised in that the node availability finger joint point can after receiving an assignment
The probability of service is provided, node prestige finger joint point can be provided the probability of service after receiving an assignment by quality, and communication overhead is represented
User sends and receives the energy of data consumption.
5. system according to claim 1, it is characterised in that by WiFi network respectively to wireless between user and vehicle
Access point sends task requests and status information, by based on OFDM skill between user and vehicle-mounted edge calculations node
The short haul connection of art.
6. a kind of vehicle-mounted edge calculations node selecting method, it is characterised in that comprise the following steps：
Multiple users send task requests to WAP, and completing itself task according to the matching information of vehicles of return unloaded
Journey；
Each vehicle is as vehicle-mounted edge calculations node, and multiple vehicles send oneself to WAP at regular intervals
Status information；And wait and user's successful match, corresponding task is performed, and assist user to complete task unloading；
WAP receives data and the processing that user and vehicle edge node are sent, and node selecting method is performed, by user
Matched with vehicle-mounted edge calculations node, be specially：
According to the mobility of vehicle, time constraint condition is calculated, the son letter required for being matched between user and vehicle is determined
Road quantity；Channel is divided into by the equal subchannel of some bandwidth by OFDM, for each height of identical link
The average data transfer rate of channel is equal；The maximum communication duration of vehicle is calculated according to car status information, task sheet is taken
The smaller of the time-constrain of body and the communication time of vehicle, as the actual total duration of task, the total duration is sent out including task
Send the time with processing procedure；According to each task size, calculating is gone out on missions processing time, and when calculating the transmission of task
Between, and the message transmission rate of demand is calculated, then according to the channel between shannon formula, noise power and user and vehicle
Gain matrix calculates actual data transfer rate；Make the message transmission rate and actual data transfer rate of demand equal, then
To the subchannel number distributed between every a pair of users and vehicle；
Processing task institute consumed energy is modeled, according to whether carrying out unloading is divided into two kinds of situation modelings：1）If do not unloaded
Carry, then task is locally handled；Under conditions of assuming that task execution time is exactly the time-constrain of task, user equipment
Cpu frequency according to dynamic voltage scaling technology, take the smaller value between peak frequency and mission requirements frequency；Then this is calculated
Ground consumed energy；2）If unloaded, task is handled in vehicle-mounted fringe node；User equipment is calculated to send with receiving
The energy that data and static power are consumed；If task result data amount very little, the energy and time consumed is ignored；Knot
Close send Time Calculation go out on missions unloading when user equipment consumption energy；
The processing task that subchannel number, calculating constraints module needed for the user-vehicle exported according to communication constraint module are exported
The Consumer's Experience evaluation model of required consumed energy and structure simultaneously carries out user-vehicle-mounted edge calculations based on Double Auction theory
Node preliminary matches；The Consumer's Experience of user is weighed by node availability, three aspects of node prestige and communication overhead,
And user and vehicle-mounted edge calculations node are matched based on Double Auction theory；
The user exported according to preliminary matches module-vehicle pairing scheme, sub-channel resource distribution is carried out based on linear programming, defeated
Go out final matching and frequency spectrum resource allocation result.
7. method according to claim 6, it is characterised in that the task requests that user sends include task size, should
QoE values, time-constrain, transmit power, static power, maximum cpu frequency and the user coordinates reached.
8. method according to claim 6, it is characterised in that coordinate of the status information of vehicle including car, speed, motion
Direction, maximum cpu frequency, prestige and availability.
9. system according to claim 6, it is characterised in that the node availability finger joint point can after receiving an assignment
The probability of service is provided, node prestige finger joint point can be provided the probability of service after receiving an assignment by quality, and communication overhead is represented
User sends and receives the energy of data consumption.
10. method according to claim 6, it is characterised in that by WiFi network respectively to nothing between user and vehicle
Line access point sends task requests and status information, by based on OFDM between user and vehicle-mounted edge calculations node
The short haul connection of technology.
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Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104509090A (en) * | 2012-07-27 | 2015-04-08 | 歌乐牌株式会社 | Vehicle-mounted image recognition device |
| CN106470449A (en) * | 2015-08-14 | 2017-03-01 | 电信科学技术研究院 | A kind of data transmit-receive, trunking method, device and communication system |
| WO2017088905A1 (en) * | 2015-11-24 | 2017-06-01 | Nec Europe Ltd. | A method and network for managing and orchestrating virtual network functions and network applications |
-
2017
- 2017-06-09 CN CN201710434272.6A patent/CN107317700B/en active Active
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104509090A (en) * | 2012-07-27 | 2015-04-08 | 歌乐牌株式会社 | Vehicle-mounted image recognition device |
| CN106470449A (en) * | 2015-08-14 | 2017-03-01 | 电信科学技术研究院 | A kind of data transmit-receive, trunking method, device and communication system |
| WO2017088905A1 (en) * | 2015-11-24 | 2017-06-01 | Nec Europe Ltd. | A method and network for managing and orchestrating virtual network functions and network applications |
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