CN113613210A - Internet of vehicles task unloading method based on multivariate joint optimization - Google Patents
Internet of vehicles task unloading method based on multivariate joint optimization Download PDFInfo
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- CN113613210A CN113613210A CN202110750002.2A CN202110750002A CN113613210A CN 113613210 A CN113613210 A CN 113613210A CN 202110750002 A CN202110750002 A CN 202110750002A CN 113613210 A CN113613210 A CN 113613210A
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
- H04W4/30—Services specially adapted for particular environments, situations or purposes
- H04W4/40—Services specially adapted for particular environments, situations or purposes for vehicles, e.g. vehicle-to-pedestrians [V2P]
- H04W4/44—Services specially adapted for particular environments, situations or purposes for vehicles, e.g. vehicle-to-pedestrians [V2P] for communication between vehicles and infrastructures, e.g. vehicle-to-cloud [V2C] or vehicle-to-home [V2H]
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W24/00—Supervisory, monitoring or testing arrangements
- H04W24/02—Arrangements for optimising operational condition
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W52/00—Power management, e.g. TPC [Transmission Power Control], power saving or power classes
- H04W52/02—Power saving arrangements
- H04W52/0209—Power saving arrangements in terminal devices
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W52/00—Power management, e.g. TPC [Transmission Power Control], power saving or power classes
- H04W52/04—TPC
- H04W52/18—TPC being performed according to specific parameters
- H04W52/28—TPC being performed according to specific parameters using user profile, e.g. mobile speed, priority or network state, e.g. standby, idle or non transmission
- H04W52/282—TPC being performed according to specific parameters using user profile, e.g. mobile speed, priority or network state, e.g. standby, idle or non transmission taking into account the speed of the mobile
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W52/00—Power management, e.g. TPC [Transmission Power Control], power saving or power classes
- H04W52/04—TPC
- H04W52/18—TPC being performed according to specific parameters
- H04W52/28—TPC being performed according to specific parameters using user profile, e.g. mobile speed, priority or network state, e.g. standby, idle or non transmission
- H04W52/285—TPC being performed according to specific parameters using user profile, e.g. mobile speed, priority or network state, e.g. standby, idle or non transmission taking into account the mobility of the user
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W52/00—Power management, e.g. TPC [Transmission Power Control], power saving or power classes
- H04W52/04—TPC
- H04W52/30—TPC using constraints in the total amount of available transmission power
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W52/00—Power management, e.g. TPC [Transmission Power Control], power saving or power classes
- H04W52/04—TPC
- H04W52/38—TPC being performed in particular situations
- H04W52/46—TPC being performed in particular situations in multi hop networks, e.g. wireless relay networks
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- 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
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Abstract
The invention discloses a vehicle networking task unloading method based on multivariate joint optimization, and belongs to the field of vehicle communication. The in-vehicle user equipment sends the total calculation task amount required to be processed to a vehicle edge calculation server through a vehicle; receiving a calculation task from vehicle user equipment through a vehicle relay, and calculating transmission energy consumption of the user equipment in the vehicle; determining the task unloading proportion of the user equipment according to the transmission energy consumption and the local calculation energy consumption of the user equipment in the vehicle; determining the sending power and subcarrier selection factors of the user equipment according to the transmission energy consumption; sending the determined sending power of the user equipment, the subcarrier selection factor and the task unloading proportion to the user equipment; the user equipment receives the parameter setting from the vehicle edge calculation server, and configures corresponding parameters; and the user equipment completes the unloading of the corresponding task through the corresponding sending power and the subcarrier factor. The invention minimizes the energy consumption of the user equipment for unloading tasks.
Description
Technical Field
The invention belongs to the field of vehicle communication, and particularly relates to a multivariate joint optimization task unloading method based on Internet of vehicles.
Background
The rapid development of vehicle networks will stimulate a range of applications in the areas of travel assistance, autopilot, video streaming and online gaming, require significant computing resources to process large amounts of workload data, and have strict time-critical requirements. To support delay-sensitive and multimedia-rich services for user equipment in a vehicle network, Vehicle Edge Computing (VEC) has been proposed, where the workload is processed at the network edge to eliminate excessive network hops. The VEC not only reduces computational response time, but also alleviates traffic congestion problems in capacity-limited backhaul links. VECs allow for opportunistic energy conservation for vehicle user devices with limited battery capacity, such as smart phones and wearable devices. Traditionally, all workloads had to be handled locally on the user equipment, which greatly shortened battery life and hampered reliability of service delivery. With the help of the VEC, high energy consumption workloads can be offloaded from user devices over vehicle-to-infrastructure (V2I) links to nearby VEC nodes with higher computing power and rich energy supply. Therefore, it is a necessary development result to design a multivariate joint optimization task unloading method based on the internet of vehicles.
However, the current research focuses mainly on the problem of unloading of vehicle computing tasks and the like, and the research on the in-vehicle user equipment is less. The in-vehicle user equipment has poor user experience due to the limitation of computing resources, the battery power efficiency, the signal shielding of the vehicle to the user equipment and other problems, so that reasonable utilization of battery energy can be realized by jointly optimizing the frequency spectrum and the computing resources of the user equipment, and tasks are timely unloaded, so that the application experience of the in-vehicle user is improved.
Disclosure of Invention
The present invention is directed to solving the above problems of the prior art. The vehicle networking task unloading method based on the multivariate joint optimization is provided, and the vehicle networking task unloading method is capable of reducing energy consumption of user equipment, improving spectrum efficiency, enhancing information transmission reliability and prolonging user equipment. The technical scheme of the invention is as follows:
a vehicle networking task unloading method based on multivariate joint optimization comprises the following steps:
s1: user equipment will need to process the total task computation amount through vehicle relay { Dk,m,Ck,m,τk,mSending to the vehicle edge calculation server, where Dk,mIndicating the size of the task data volume, Ck,mIndicating the size of the computational task, τk,mRepresents the maximum tolerable delay for the completion of the task;
s2: the vehicle edge computing server receives a task request from user equipment;
s3: the vehicle edge calculation server substitutes the received task data volume, task calculation volume and time delay constraint of the user equipment into the optimization model to obtain
Wherein alpha isk,mDenotes the subcarrier selection factor, pk,mIndicating the transmission power, lambda, of the user equipment in the vehiclek,mRepresenting a proportion of the computing tasks of the user device offloaded to the vehicle edge computing server;
s4: the vehicle edge calculation server obtains 3 parameters by solving
The information is sent to the user equipment through a vehicle relay;
s5: the in-vehicle user equipment receives the task execution result from the vehicle edge computing server
S6: user equipment with transmit power
Selecting subcarrier n, offloading lambda to the vehicle edge calculation server with the assistance of vehicle relayk,mDk,mAmount of data of (1-. lambda.) remainingk,m)Dk,mIs processed locally, lambdak,mRepresenting the proportion of the user equipment's computational tasks offloaded to the vehicle edge computing server, Dk,mRepresenting the size of the task data volume;
further, the vehicle edge calculation server substitutes the received task data volume, task calculation volume and time delay constraint of the user equipment into the optimization model to solve to obtain
The specific optimization model is as follows:
k represents that K vehicles exist and also represents the number of user equipment in the vehicles; k represents a kth vehicle or a kth user equipment; n represents the nth subcarrier, and N represents the number of subcarriers into which the total system bandwidth is divided; m denotes the m-th vehicle edge calculation server, λk,mRepresenting a proportion of the computing tasks of the user device offloaded to the vehicle edge computing server; ck,mRepresenting the size of the computing task; tau isk,mRepresents the maximum tolerable delay for task completion, delta represents the coefficient of the CPU chip architecture,
the transmission rate when the user equipment k selects the subcarrier n to unload the calculation task to the vehicle edge calculation server m is shown, and the transmission rate can be obtained by the above parameters and formula
The invention has the following advantages and beneficial effects:
the invention designs a multivariate joint optimization task unloading method based on the internet of vehicles on the basis of considering the battery energy efficiency of users, the limitation of computing resources and the adverse effect of vehicles on the shielding of user equipment. At present, most of research on vehicle networks is the unloading of tasks of vehicles or tasks of vehicle-mounted equipment, while research on users in vehicles is less, and with the continuous development of vehicle networks and internet of things, more and more available devices of the users in vehicles are provided, such as wearable devices, video streaming playing videos, mobile phone online games and the like, requirements of applications on time delay and computing resources are higher and higher, vehicles are more and more prone to intelligent driving, a large number of emergency computing tasks need to be processed, and insufficient computing resources are not provided for the users in vehicles to use, so that the users need to unload the computing tasks to edge servers with richer computing resources around. The model provided by the invention fully analyzes the existing problems, firstly, in order to improve the battery efficiency of the user equipment, the calculation task is unloaded to the vehicle edge calculation server, so that the opportunity of saving the battery electric quantity of the user equipment can be saved, and the battery endurance time of the user equipment is improved; secondly, due to the shielding effect of the sealing property of the vehicle on the user equipment in the vehicle, the transmission signal of the user equipment is weakened, and the processing of a calculation task is not facilitated, so that the vehicle where the user equipment is located serves as a full-duplex relay, the synchronous receiving-sending of the task is realized, the unloading of the calculation task is realized through two hops, the first hop is that the user equipment firstly sends the calculation task to the vehicle where the user equipment is located, and the task transmission efficiency is improved; the second hop vehicle sends the calculation task to a vehicle edge calculation node to realize the unloading of the task; meanwhile, the connection between the vehicle and the edge computing server is frequently interrupted in the task unloading process due to the high-speed movement of the vehicle, a partial unloading mode is adopted, and when the driving speed of the vehicle is too high, the unloading proportion of the task is reduced so as to avoid unloading failure; the vehicle needs to successfully receive the task processing result when driving out of the RSU coverage range of the unloading task, and the user equipment can successfully receive the task return result by ensuring that the driving time of the vehicle is less than the sum of the transmission time of the task and the calculation time of the vehicle edge calculation server; in the task transmission process, when each user equipment task is unloaded, the corresponding subcarrier needs to be selected for transmission, and the spectrum utilization rate is improved. Finally, the user equipment in the vehicle obtains the optimal sending power of the user equipment, the unloading proportion of the task and the subcarrier selected by the user to realize the task unloading energy consumption minimization of the user equipment by jointly considering the mobility of the vehicle, the time constraint of task transmission and the transmission power constraint of the task.
Drawings
FIG. 1 is a diagram of a task transmission scenario in accordance with a preferred embodiment of the present invention;
FIG. 2 is a flow chart of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be described in detail and clearly with reference to the accompanying drawings. The described embodiments are only some of the embodiments of the present invention.
The technical scheme for solving the technical problems is as follows:
a method for allocating spectrum resources and computing resources of user equipment in a vehicle comprises the following steps:
s1: user equipment will need to process the total task computation amount through vehicle relay { Dk,m,Ck,m,τk,mSending the data to a vehicle edge calculation server;
s2: the vehicle edge computing server receives a task request from user equipment;
s3: the vehicle edge calculation server substitutes the received task data volume, task calculation volume and time delay constraint of the user equipment into the optimization model to obtain
S4: the vehicle edge calculation server obtains 3 parameters by solving
The information is sent to the user equipment through a vehicle relay;
s5: the in-vehicle user equipment receives the task execution result from the vehicle edge computing server
S6: user equipment with transmit power
Subcarrier n, unloading lambda to the vehicle edge calculation server by vehicle relayk,mDk,mAmount of data of (1-. lambda.) remainingk,m)Dk,mProcessing is carried out locally;
as shown in the invention flow 2, the user equipment calculates the total task calculation amount { D ] needing to be processed through vehicle relayk,m,Ck,m,τk,mAnd sending the data to a vehicle edge calculation server.
The vehicle edge computing server receives a task request from a user device.
The vehicle edge calculation server substitutes the received task data volume, task calculation volume and time delay constraint of the user equipment into the optimization model to obtain
The method specifically comprises the following steps:
the transmission power can be obtained by solving the above parameters and formulas
The vehicle edge calculation server obtains 3 parameters by solving
And transmitting the data to the user equipment through the vehicle relay.
The in-vehicle user equipment receives the task execution result from the vehicle edge computing server
User equipment with transmit power
Subcarrier n, unloading lambda to the vehicle edge calculation server by vehicle relayk, mDk,mAmount of data of (1-. lambda.) remainingk,m)Dk,mThe processing is done locally.
It should also be noted that the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises the element.
The above examples are to be construed as merely illustrative and not limitative of the remainder of the disclosure. After reading the description of the invention, the skilled person can make various changes or modifications to the invention, and these equivalent changes and modifications also fall into the scope of the invention defined by the claims.
Claims (2)
1. A vehicle networking task unloading method based on multivariate joint optimization is characterized by comprising the following steps:
s1: user equipment will need to process the total task computation amount through vehicle relay { Dk,m,Ck,m,τk,mSending to the vehicle edge calculation server, where Dk,mIndicating the size of the task data volume, Ck,mIndicating the size of the computational task, τk,mIndicating completion of a taskLarge tolerable delay;
s2: the vehicle edge computing server receives a task request from user equipment;
s3: the vehicle edge calculation server substitutes the received task data volume, task calculation volume and time delay constraint of the user equipment into the optimization model to obtain
Wherein alpha isk,mDenotes the subcarrier selection factor, pk,mIndicating the transmission power, lambda, of the user equipment in the vehiclek,mRepresenting a proportion of the computing tasks of the user device offloaded to the vehicle edge computing server;
s4: the vehicle edge calculation server obtains 3 parameters by solving
The information is sent to the user equipment through a vehicle relay;
s5: the in-vehicle user equipment receives the task execution result from the vehicle edge computing server
S6: in-vehicle user equipment to transmit power
Selecting subcarrier n, offloading lambda to the vehicle edge calculation server with the assistance of vehicle relayk,mDk,mAmount of data of (1-. lambda.) remainingk,m)Dk,mThe processing is done locally.
2. The method as claimed in claim 1, wherein the vehicle edge computing server substitutes the task data volume, task calculation volume and time delay constraint of the received user equipment into the optimization model to obtain the task data volume, task calculation volume and time delay constraint of the received user equipment
The specific optimization model is as follows:
k represents that K vehicles exist and also represents the number of user equipment in the vehicles; k represents a kth vehicle or a kth user equipment; n represents the nth subcarrier, and N represents the number of subcarriers into which the total system bandwidth is divided; m denotes the m-th vehicle edge calculation server, λk,mRepresenting a proportion of the computing tasks of the user device offloaded to the vehicle edge computing server; ck,mRepresenting the size of the computing task; tau isk,mRepresents the maximum tolerable delay for task completion, delta represents the coefficient of the CPU chip architecture,
the transmission rate when the user equipment k selects the subcarrier n to unload the calculation task to the vehicle edge calculation server m is shown, and the transmission rate can be obtained by the above parameters and formula
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