CN113613210B - Internet of vehicles task unloading method based on multi-variable joint optimization - Google Patents
Internet of vehicles task unloading method based on multi-variable joint optimization Download PDFInfo
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- CN113613210B CN113613210B CN202110750002.2A CN202110750002A CN113613210B CN 113613210 B CN113613210 B CN 113613210B CN 202110750002 A CN202110750002 A CN 202110750002A CN 113613210 B CN113613210 B CN 113613210B
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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
Abstract
The invention discloses a vehicle networking task unloading method based on multi-variable joint optimization, and belongs to the field of vehicle communication. The user equipment in the vehicle sends the total calculation task quantity to be processed to a vehicle edge calculation server through a vehicle relay; 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 transmission power and subcarrier selection factor of the user equipment according to the transmission energy consumption; transmitting the determined transmitting power of the user equipment, subcarrier selection factors and task unloading proportion to the user equipment; the user equipment receives parameter setting from a vehicle edge computing server, and configures corresponding parameters; and the user equipment finishes the task unloading of the corresponding task through the corresponding transmitting power and the subcarrier factor. The invention minimizes the energy consumption of the user equipment for offloading tasks.
Description
Technical Field
The invention belongs to the field of vehicle communication, and particularly relates to a multivariable joint optimization task unloading method based on the 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, requiring significant computing resources to handle large amounts of workload data, and having stringent time-frame requirements. In order to support delay sensitive and multimedia rich services of user devices in a vehicle network, vehicle Edge Computing (VEC) has been proposed in which the workload is handled 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. The VEC allows for opportunity power conservation for vehicle-mounted user devices such as smartphones and wearable devices that have limited battery capacity. Traditionally, all workloads have had to be handled locally on the user device, which greatly shortens battery life and hampers reliability of service delivery. With the aid of the VEC, high-energy-consumption workloads can be offloaded from user equipment to nearby VEC nodes with higher computing power and rich energy supply over vehicle-to-infrastructure (V2I) links. Therefore, designing a multivariable joint optimization task unloading method based on the Internet of vehicles is a necessary development result.
However, the present research focus is mainly focused on the problems of unloading the calculation tasks of the vehicle, and the like, and the research on user equipment in the vehicle is less. The in-car user equipment has relatively poor user experience due to the problems of limitation of computing resources, battery electric quantity efficiency, signal shielding of the vehicle to the user equipment and the like, so that reasonable utilization of battery energy can be realized by jointly optimizing the frequency spectrum and computing resources of the user equipment, tasks are unloaded in time, and the application experience of in-car users is improved.
Disclosure of Invention
The present invention is directed to solving the above problems of the prior art. The Internet of vehicles task unloading method based on the multi-variable joint optimization reduces the energy consumption of the user equipment, improves the frequency spectrum efficiency, enhances the information transmission reliability and prolongs the user equipment. The technical scheme of the invention is as follows:
a vehicle networking task unloading method based on multi-variable joint optimization comprises the following steps:
s1: the user equipment calculates the total task calculation amount { D ] which needs to be processed through vehicle relay k,m ,C k,m ,τ k,m Send to the vehicle edge calculation server, where D k,m Representing the size of the task data volume, C k,m Representing the size of the computational task, τ k,m Representing the maximum tolerable delay for task completion;
s2: the vehicle edge computing server receives a task request from user equipment;
s3: the vehicle edge calculation server substitutes the task data volume, the task calculation volume and the time delay constraint of the received user equipment into the optimization model to obtain the vehicle edge calculation server
Wherein alpha is k,m Representing subcarrier selection factors, p k,m Representing the transmit power, lambda, of user equipment in a vehicle k,m Representing a proportion of computing tasks of the user device offloaded to the vehicle edge computing server;
s4: 3 parameters obtained by solving by vehicle edge calculation server
The method comprises the steps of sending the message to user equipment through vehicle relay;
s5: in-vehicle user equipment receives task execution results from vehicle edge computing server
/>
S6: user equipment to transmit power
Selecting subcarrier n, offloading λ to vehicle edge calculation server with assistance of vehicle relay k,m D k,m Is the data volume of (1-lambda) k,m )D k,m Is processed locally lambda k,m Representing the ratio of the user device's computing tasks offloaded to the vehicle edge computing server, D k,m Representing the task data size;
further, the vehicle edge calculation server substitutes the task data volume of the received user equipment, the task calculation volume and the time delay constraint into the optimization model to obtain the vehicle edge calculation server
The specific optimization model is as follows:
wherein K represents K vehicles and also represents the number of user equipment in the vehicle; k represents a kth vehicle or a kth user equipment; n represents an nth subcarrier, and N represents the number of subcarriers into which the total bandwidth of the system is divided; m represents an mth vehicle edge calculation server, lambda k,m Representing a proportion of computing tasks of the user device offloaded to the vehicle edge computing server; c (C) k,m Representing the size of the computing task; τ k,m Represents the maximum tolerable delay for task completion, delta represents the coefficients of the CPU chip architecture,
representing the transmission rate of the user equipment k when selecting the subcarrier n to offload the calculation task to the vehicle edge calculation server m, the +.>
The invention has the advantages and beneficial effects as follows:
the invention designs a multivariable 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 adverse effects caused by the shielding of vehicles to user equipment. At present, most of research on a vehicle network is unloading of a vehicle self task or a vehicle-mounted equipment task, while less research is conducted on in-vehicle users, with the continuous development of the vehicle network and the Internet of things, the available equipment of the in-vehicle users is more and more, such as wearable equipment, video streaming video playing, mobile phone online games and the like, the requirements of the applications on time delay and computing resources are higher and higher, the vehicle is also more and more biased to intelligent driving, a large number of emergency computing tasks need to be processed, and insufficient computing resources are available for the in-vehicle user equipment, so that the user equipment needs to unload the computing tasks to an edge server with more abundant computing resources. The model provided by the method fully analyzes the existing problems, firstly, in order to improve the battery efficiency of the user equipment, a calculation task is unloaded to a vehicle edge calculation server, so that the opportunity saving of the battery electric quantity of the user equipment can be realized, and the battery endurance time of the user equipment is improved; secondly, because the sealing performance of the vehicle shields the user equipment in the vehicle, the emission signal of the user equipment is weakened, which is unfavorable for processing the calculation task, therefore, the vehicle where the user equipment is positioned is used as a full duplex relay to realize synchronous receiving-transmitting of the task, the unloading of the calculation task is realized through two hops, and the first hop is that the user equipment firstly transmits the calculation task to the vehicle where the user equipment is positioned, so that the task transmission efficiency is improved; the second jump vehicle sends the calculation task to a vehicle edge calculation node to realize task unloading; meanwhile, as the high-speed movement of the vehicle can cause frequent interruption of connection between the vehicle and the edge computing server in the task unloading process, a partial unloading mode is adopted, and when the running 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 running out of the RSU coverage area of the unloading task, and the user equipment can successfully receive the task feedback result by ensuring that the running 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 is required to be selected for transmission, so that the spectrum utilization rate is improved. Finally, the user equipment in the vehicle obtains the optimal transmitting power of the user equipment by jointly considering the mobility of the vehicle, the time constraint of task transmission and the transmitting power constraint of the task, and the task unloading proportion and the sub-carrier selected by the user realize the task unloading energy consumption minimization of the user equipment.
Drawings
FIG. 1 is a task transmission scenario diagram of a preferred embodiment provided by 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 clearly and specifically described below with reference to the drawings in the embodiments of the present invention. The described embodiments are only a few embodiments of the present invention.
The technical scheme for solving the technical problems is as follows:
an in-vehicle user equipment spectrum resource and a computing resource allocation method, which comprises the following steps:
s1: the user equipment calculates the total task calculation amount { D ] which needs to be processed through vehicle relay k,m ,C k,m ,τ k,m Transmitting 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 task data volume, the task calculation volume and the time delay constraint of the received user equipment into the optimization model to obtain the vehicle edge calculation server
S4: 3 parameters obtained by solving by vehicle edge calculation server
The method comprises the steps of sending the message to user equipment through vehicle relay;
s5: in-vehicle user equipment receives task execution node from vehicle edge computing serverFruit set
S6: user equipment to transmit power
Subcarrier n, offloading λ to vehicle edge calculation server by vehicle relay k,m D k,m Is the data volume of (1-lambda) k,m )D k,m Processing is carried out locally;
as shown in the flow 2 of the present invention, the user equipment calculates the total task calculation amount { D ] to be processed through the vehicle relay k,m ,C k,m ,τ k,m And transmitted to the vehicle edge calculation server.
The vehicle edge computing server receives a task request from the user device.
The vehicle edge calculation server substitutes the task data volume, the task calculation volume and the time delay constraint of the received user equipment into the optimization model to obtain the vehicle edge calculation server
The method comprises the following steps:
the transmission power can be obtained by solving the above parameters and formulas
3 parameters obtained by solving by vehicle edge calculation server
And the data is transmitted to the user equipment through the vehicle relay.
In-vehicle user equipment receives task execution results from vehicle edge computing server
User equipment to transmit power
Subcarrier n, offloading λ to vehicle edge calculation server by vehicle relay k, m D k,m Is the data volume of (1-lambda) k,m )D k,m The processing is performed 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 one … …" does not exclude the presence of other like elements in a process, method, article or apparatus that comprises the element.
The above examples should be understood as illustrative only and not limiting the scope of the invention. Various changes and modifications to the present invention may be made by one skilled in the art after reading the teachings herein, and such equivalent changes and modifications are intended to fall within the scope of the invention as defined in the appended claims.
Claims (1)
1. The internet of vehicles task unloading method based on the multi-variable joint optimization is characterized by comprising the following steps of:
s1: the user equipment calculates the total task calculation amount { D ] which needs to be processed through vehicle relay k,m ,C k,m ,τ k,m Send to the vehicle edge calculation server, where D k,m Representing the size of the task data volume, C k,m Representing the size of the computational task, τ k,m Representing the maximum tolerable delay for task completion;
s2: the vehicle edge computing server receives a task request from user equipment;
s3: vehicle sideThe edge computing server substitutes the task data volume, the task computation volume and the time delay constraint of the received user equipment into an optimization model to obtain
Wherein alpha is k,m Representing subcarrier selection factors, p k,m Representing the transmit power, lambda, of user equipment in a vehicle k,m Representing a proportion of computing tasks of the user device offloaded to the vehicle edge computing server;
s4: 3 parameters obtained by solving by vehicle edge calculation server
The method comprises the steps of sending the message to user equipment through vehicle relay;
s5: in-vehicle user equipment receives task execution results from vehicle edge computing server
S6: in-vehicle user equipment to transmit power
Selecting subcarrier n, offloading λ to vehicle edge calculation server with assistance of vehicle relay k,m D k,m Is the data volume of (1-lambda) k,m )D k,m Processing is carried out locally;
the vehicle edge calculation server substitutes the task data volume, the task calculation volume and the time delay constraint of the received user equipment into the optimization model to obtain the vehicle edge calculation server
The specific optimization model is as follows:
wherein K represents K vehicles, also denoted byShowing the number of user devices in the vehicle; k represents a kth vehicle or a kth user equipment; n represents an nth subcarrier, and N represents the number of subcarriers into which the total bandwidth of the system is divided; m represents an mth vehicle edge calculation server, lambda k,m Representing a proportion of computing tasks of the user device offloaded to the vehicle edge computing server; c (C) k,m Representing the size of the computing task; τ k,m Represents the maximum tolerable delay for task completion, delta represents the coefficients of the CPU chip architecture,
representing the transmission rate of the user equipment k when selecting the subcarrier n to offload the calculation task to the vehicle edge calculation server m, the +.>
/>
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