CN113938394A - Monitoring service bandwidth allocation method and device, electronic equipment and storage medium - Google Patents
Monitoring service bandwidth allocation method and device, electronic equipment and storage medium Download PDFInfo
- Publication number
- CN113938394A CN113938394A CN202111525074.3A CN202111525074A CN113938394A CN 113938394 A CN113938394 A CN 113938394A CN 202111525074 A CN202111525074 A CN 202111525074A CN 113938394 A CN113938394 A CN 113938394A
- Authority
- CN
- China
- Prior art keywords
- base station
- user
- bandwidth allocation
- game
- strategy
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
- 230000004044 response Effects 0.000 claims description 36
- 238000005457 optimization Methods 0.000 claims description 32
- 230000000875 corresponding Effects 0.000 claims description 10
- 238000004590 computer program Methods 0.000 claims description 5
- 230000002349 favourable Effects 0.000 claims description 5
- 238000004891 communication Methods 0.000 abstract description 11
- 230000003993 interaction Effects 0.000 abstract description 5
- 238000010586 diagram Methods 0.000 description 5
- 238000000034 method Methods 0.000 description 3
- 238000005516 engineering process Methods 0.000 description 2
- 239000000463 material Substances 0.000 description 2
- 230000003287 optical Effects 0.000 description 2
- 230000004075 alteration Effects 0.000 description 1
- 230000006399 behavior Effects 0.000 description 1
- 230000005540 biological transmission Effects 0.000 description 1
- 230000000903 blocking Effects 0.000 description 1
- 238000011030 bottleneck Methods 0.000 description 1
- 230000004069 differentiation Effects 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 239000003365 glass fiber Substances 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000006011 modification reaction Methods 0.000 description 1
- 230000002093 peripheral Effects 0.000 description 1
- 239000000126 substance Substances 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
Classifications
-
- 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
- H04L41/08—Configuration management of networks or network elements
- H04L41/0896—Bandwidth or capacity management, i.e. automatically increasing or decreasing capacities
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04B—TRANSMISSION
- H04B17/00—Monitoring; Testing
- H04B17/30—Monitoring; Testing of propagation channels
- H04B17/391—Modelling the propagation channel
-
- 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
- H04L41/08—Configuration management of networks or network elements
- H04L41/0803—Configuration setting
- H04L41/0823—Configuration setting characterised by the purposes of a change of settings, e.g. optimising configuration for enhancing reliability
- H04L41/0836—Configuration setting characterised by the purposes of a change of settings, e.g. optimising configuration for enhancing reliability to enhance reliability, e.g. reduce downtime
-
- 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
- H04L41/08—Configuration management of networks or network elements
- H04L41/0893—Assignment of logical groups to network elements
Abstract
The application relates to the technical field of wireless communication networks, in particular to a monitoring service bandwidth allocation method, a monitoring service bandwidth allocation device, electronic equipment and a storage medium, wherein the method comprises the following steps: constructing a channel model for acquiring linear gain between users and base stations based on total path loss between the users and the base stations in a network, and determining a bandwidth allocation strategy; generating a base station service request according to the requirements of each user, and determining a pricing strategy by combining channel information and network congestion conditions; and constructing a two-stage Stackelberg game by taking the bandwidth allocation strategy and the pricing strategy as constraint conditions, and determining a bandwidth allocation result. The method and the device are based on a multi-base-station and multi-user interaction scene, the path loss influence between each user and each base station is considered, a two-stage Stackelberg game taking a dynamic bandwidth allocation strategy and a pricing strategy as constraint conditions is constructed, the experience quality of the users and the income of the base stations are effectively guaranteed, and the effectiveness of bandwidth allocation is realized.
Description
Technical Field
The present application relates to the field of wireless communication network technologies, and in particular, to a method and an apparatus for allocating a monitoring service bandwidth, an electronic device, and a storage medium.
Background
With the development of the technology, people have higher and higher requirements on the definition of security monitoring videos. The ultra-high-definition video is a new great technical innovation following video digitization and high-definition, and although the ultra-high-definition monitoring data is provided for a cloud at a higher speed due to the characteristics of 5G low delay and high bandwidth, a lot of obstacles still exist from shooting to terminal playing of the ultra-high-definition video at present, especially the problem of transmission bandwidth. The huge data volume generated by the ultra-high-definition monitoring service makes the bandwidth a serious bottleneck, which directly affects the experience quality of the mobile user, and meanwhile, the huge data volume also brings high service price, which also affects the income of the base station. Therefore, the base station needs to flexibly make a reasonable charging scheme according to the characteristics of differentiation of different user requirements and the like.
Disclosure of Invention
The application provides a monitoring service bandwidth allocation method, a monitoring service bandwidth allocation device, electronic equipment and a storage medium, so that the user experience quality and the base station income are guaranteed, the bandwidth allocation effectiveness is realized, and the technical problem that the bandwidth cannot be allocated according to different user requirements in the related technology is solved.
An embodiment of a first aspect of the present application provides a method for allocating a monitoring service bandwidth, including the following steps: constructing a channel model for acquiring linear gain between users and base stations based on total path loss between the users and the base stations in a network, and determining a bandwidth allocation strategy; generating a base station service request according to the requirements of each user, and determining a pricing strategy by combining channel information and network congestion conditions; and constructing a two-stage Stackelberg game by taking the bandwidth allocation strategy and the pricing strategy as constraint conditions, and determining a bandwidth allocation result.
Optionally, in an embodiment of the present application, the constructing a two-stage Stackelberg game by using the bandwidth allocation policy and the pricing policy as constraints, and determining a bandwidth allocation result includes: based on the property of each benefit of the user and the base station, two optimization problems for maximizing the utility of the user and the base station are formulated; generating a two-stage Stackelberg game by using the two optimization problems, and solving the optimal response of the sub-game of the user by using the given price of the base station; and solving the best response of the base station sub-game according to the best response of the user sub-game, so that the benefits of the user and the base station are relatively maximized.
Optionally, in an embodiment of the present application, the formulating two optimization problems for maximizing the utility of the user and the base station based on the respective favorable properties of the user and the base station includes: respectively acquiring targets of the users and the base stations, and generating corresponding utility functions by the targets of the users and the base stations; and formulating the two optimization problems by maximizing the utility of the user and the base station according to the utility function.
Optionally, in an embodiment of the present application, the generating a two-stage Stackelberg game by using the two optimization problems, and solving the best response of the sub-game of the user by using the base station given price includes: giving unit bandwidth price by taking the base station as a leader, and respectively enabling the utility function of the user to calculate a first order reciprocal and a second order derivative for the requested bandwidth resource of the service request of the base station to obtain the optimal requirement of the user to be solved; and substituting the user optimal demand solution into the utility function of the base station, and obtaining the optimal response of the base station according to the user optimal demand solution.
Optionally, in an embodiment of the present application, the determining a pricing policy includes: and acquiring the corresponding dynamic pricing strategy according to the total bandwidth request quantity of each user to the base station.
An embodiment of a second aspect of the present application provides a monitoring service bandwidth allocation apparatus, including: the system comprises a building module, a bandwidth allocation module and a control module, wherein the building module is used for building a channel model for acquiring linear gain between users and base stations and determining a bandwidth allocation strategy based on total path loss between each user and each base station in a network; the determining module is used for generating a base station service request according to the requirements of each user and determining a pricing strategy by combining channel information and network congestion conditions; and the allocation module is used for constructing a two-stage Stackelberg game by taking the bandwidth allocation strategy and the pricing strategy as constraint conditions and determining a bandwidth allocation result.
Optionally, in an embodiment of the present application, the allocating module is further configured to formulate two optimization problems maximizing the utility of the user and the base station based on the property of respective benefits of the user and the base station, generate a two-stage Stackelberg game by using the two optimization problems, solve the best response of the sub-game of the user by using a given price of the base station, and solve the best response of the sub-game of the base station according to the best response of the sub-game of the user, so that the benefits of the user and the base station are relatively maximized.
Optionally, in an embodiment of the present application, the formulating two optimization problems for maximizing the utility of the user and the base station based on the respective favorable properties of the user and the base station includes: respectively acquiring targets of the users and the base stations, and generating corresponding utility functions by the targets of the users and the base stations; and formulating the two optimization problems by maximizing the utility of the user and the base station according to the utility function.
An embodiment of a third aspect of the present application provides an electronic device, including: the system comprises a memory, a processor and a computer program stored on the memory and capable of running on the processor, wherein the processor executes the program to realize the monitoring service bandwidth allocation method according to the embodiment.
A fourth aspect of the present application provides a computer-readable storage medium, which stores computer instructions for causing the computer to execute the monitoring traffic bandwidth allocation method according to the foregoing embodiment.
The monitoring service bandwidth allocation method and device provided by the embodiment of the application have the following beneficial effects:
1) service reliability: based on a multi-base station and multi-user interaction scene, the influence of path loss between each user and each base station is considered, and a dynamic bandwidth allocation strategy is adopted as a constraint condition to ensure the reliability of the base station, so that the experience quality of the user is ensured.
2) Bandwidth allocation availability: on the basis of ensuring that the base station is reliable, a dynamic pricing strategy is constructed based on the bandwidth resource utilization rate, so that price change can keep up with demand change. The more efficient the allocation of bandwidth resources as price changes can keep up with demand changes.
3) The maximum number of user accesses is as follows: the bandwidth allocation method for the ultra-high-definition monitoring service enables the user access number to be maximum on the premise of ensuring that the base station is reliable.
Additional aspects and advantages of the present application will be set forth in part in the description which follows and, in part, will be obvious from the description, or may be learned by practice of the present application.
Drawings
The foregoing and/or additional aspects and advantages of the present application will become apparent and readily appreciated from the following description of the embodiments, taken in conjunction with the accompanying drawings of which:
fig. 1 is a schematic view of a scene provided according to an embodiment of the present application;
fig. 2 is a flowchart of a method for monitoring service bandwidth allocation according to an embodiment of the present application;
fig. 3 is a schematic diagram illustrating a user requesting a bandwidth resource from a base station according to an embodiment of the present application;
fig. 4 is a diagram illustrating an example of a monitoring service bandwidth allocation apparatus according to an embodiment of the present application;
fig. 5 is a schematic diagram of an electronic device according to an embodiment of the present application.
Detailed Description
Reference will now be made in detail to embodiments of the present application, examples of which are illustrated in the accompanying drawings, wherein like or similar reference numerals refer to the same or similar elements or elements having the same or similar function throughout. The embodiments described below with reference to the drawings are exemplary and intended to be used for explaining the present application and should not be construed as limiting the present application.
In order to effectively improve user satisfaction and base station revenue, the application introduces a game theory (game theory) model. The game theory model has been proposed in the past for non-cooperative wireless communication, which is a powerful framework for analyzing interactions between multiple participants acting on their own interests. The main idea of the game is that after the leader makes a decision, the follower makes a decision according to the decision of the leader, and then the leader adjusts the decision of the follower according to the decision of the follower, and the steps are repeated until Nash equilibrium is reached. At this time, both the leader and the follower select their own optimal strategies to maximize profits. The game theory is recognized as the best mathematical tool for researching the mutual influence and behavior interaction of different main body decisions.
Assuming that both the base station and the user are selfish and rational, it is clear that both parties explicitly want to get higher profits. The base station wants to sell more bandwidth resources at a higher price, while the user wants to buy as much bandwidth resources as possible at a lower price. In the game, the base station is used as a leader to carry out pricing game, and the user is used as a follower to carry out demand game.
The following describes a monitoring service bandwidth allocation method, apparatus, electronic device, and storage medium according to an embodiment of the present application with reference to the drawings. In the method, based on a multi-base station and multi-user interaction scene, the influence of path loss between each user and each base station is considered, and a two-stage Stackelberg game taking a dynamic bandwidth allocation strategy and a pricing strategy as constraint conditions is constructed. Firstly, the reliability of the base station is ensured through a bandwidth allocation strategy, then a dynamic pricing strategy with cost effectiveness is constructed on the basis, and an optimization problem is made by maximizing the utility of users and the base station. The method effectively guarantees the experience quality of the user and the income of the base station, and realizes the effectiveness of bandwidth allocation. Therefore, the problem that bandwidth cannot be allocated according to different user requirements in a differentiated mode is solved.
In the embodiment of the present application, as shown in fig. 1, it is assumed that all edge base stations deployed by the operator are aggregated intoN={1,2,...,n,...,NAt the same time, a group of mobile users is represented asM={1,2,...,m,...,M}. By a base stationn∈NThe price per unit bandwidth is made as a time-varying functionWherein, in the step (A),called charging time zone, the price of the unit bandwidth resource is not changed in one charging time zone.
Specifically, fig. 2 is a flowchart of a method for monitoring service bandwidth allocation according to an embodiment of the present application.
As shown in fig. 1, the monitoring service bandwidth allocation method includes the following steps:
in step S101, a channel model for obtaining linear gain between each user and each base station is constructed based on total path loss between each user and each base station in the network, and a bandwidth allocation policy is determined.
Specifically, a channel model is first constructed, taking into account the total path loss between each user and each base station in the 5G network, to obtain linear gain between themφ(n,m)。
In step S102, a base station service request is generated according to the requirement of each user, and a pricing strategy is determined by combining the channel information and the network congestion condition.
In one embodiment of the present application, determining a pricing strategy includes: and acquiring a corresponding dynamic pricing strategy according to the total bandwidth request quantity of each user to the base station.
It can be understood that, according to the channel information, the user requests the base station for service on demand, as shown in fig. 3, specifically including:
1) user' smTo be provided withIn the charging time zone deltat kInward base stationnRequest bandwidth resources。And
respectively represent base stationsnIn a charging time zone deltat kThe minimum bandwidth resource and the maximum bandwidth resource that can be provided. If the bandwidth resource requested by the user is lower thanThe user can only followPurchase if requested bandwidth resources are higher thanIf the service requirement of the user is not satisfied, the user will quit the request of the current base station and request the service from other base stations.
2) According to each user to base stationnThe dynamic pricing strategy is established according to the total bandwidth request quantity:
（2）
wherein the content of the first and second substances,。
according toJudging the network blocking degree ifYIf > 1, it means that the user is to the base stationnThe total bandwidth request amount is larger than the total bandwidth amount which can be provided by the base stationIn this case, the base station cannot satisfy the service requests of all users. To address this situation, the base station will rely on the usage of bandwidth resourcesYBase price per bandwidthReasonable increase to negotiated priceTo enable part of users to pay according to willingnessQuitting the current resource competition until
The allocation strategy ensures the reliability of the base station. When the resources of the base station remain, the new user can also continue to request service from it, which can ensure the maximum number of user accesses. In addition, in this case, the service cost of the base station is also determined by
Is increased toIt involves a delay to the user and the cost of discarding.
In step S103, a two-stage Stackelberg game is constructed by using the bandwidth allocation policy and the pricing policy as constraint conditions, and a bandwidth allocation result is determined.
In an embodiment of the present application, a two-stage Stackelberg game is constructed by using a bandwidth allocation policy and a pricing policy as constraint conditions, and determining a bandwidth allocation result includes: based on the property of each benefit of the user and the base station, two optimization problems for maximizing the utility of the user and the base station are formulated; generating a two-stage Stackelberg game by using two optimization problems, and solving the optimal response of the sub-game of the user by using the given price of the base station; and solving the best response of the base station sub-game according to the best response of the user sub-game, so that the benefits of the user and the base station are relatively maximized.
In one embodiment of the present application, two optimization problems are formulated to maximize the utility of the user and the base station based on the respective favorable properties of the user and the base station, including: respectively acquiring targets of each user and each base station, and generating a corresponding utility function by the targets of each user and each base station; two optimization problems are formulated according to the utility function and with maximized user and base station utility.
In one embodiment of the present application, a two-stage Stackelberg game is generated by using two optimization problems, and the best response of the sub-game of the user is solved by using the given price of the base station, including: giving unit bandwidth price by taking the base station as a leader, and respectively enabling the utility function of the user to calculate a first reciprocal and a second derivative for the bandwidth request resource of the service request of the base station to obtain the optimal requirement of the user to be solved; and substituting the optimal needs of the user into the utility function of the base station, and obtaining the optimal response of the base station according to the optimal needs of the user.
Specifically, the base stationnHope to sell more bandwidth resources at a higher price, usermIt is desirable to purchase as much bandwidth resource as possible at a lower price. According to the targets of both parties, the utility function of both parties is formulatedAndand to maximize use ofHouseholdmAnd base stationnThe utility of (1) and (2) of (base station sub-game-pricing game) optimization problem.
Problem 1 and problem 2 together form a two-stage Stackelberg game that aims to find Stackelberg balances that maximize the relative benefits of both the user and the base station. Typically, the Stackelberg equalization is obtained by solving the Nash equalization of the sub-game.
Price setting by base stationSolving problem 2 to obtain the user's optimal responseThen it is used to solve problem 1 to get the best response of the base station. And according to the nonnegativity, monotonicity and expandability of the optimal response, the base station and the user reach Nash balance, so that the game is proved to have Stackelberg balance, and the benefits of the user and the base station are relatively maximized.
Specifically, first, the base station gives a price per bandwidth as a leader
Then respectively ordering the user utility functions
To pairFirst derivative ofAnd second derivative. From the second derivative being less than zero, the userUtility functionIs a strictly concave function, bySolving the optimal solution of the user. Will be provided withSubstituting base station utility functionIn the method, the problem 1 is solved, and the optimal response of the base station is further obtained
. And obtaining that the base station and the user reach Nash equilibrium according to the nonnegativity, monotonicity and expandability of the optimal response, thereby proving that the game has Stackelberg equilibrium to enable the benefits of the user and the base station to be relatively maximized.
According to the monitoring service bandwidth allocation method provided by the embodiment of the application, a two-stage Stackelberg (Stackelberg) game taking a dynamic bandwidth allocation strategy and a pricing strategy as constraint conditions is constructed. The optimization problem is formulated by maximizing the utility of the user and the base station, the optimal response of the sub game of the user is solved according to the given price of the base station, and the optimal response of the sub game of the base station is solved according to the optimal response of the user, so that the game is proved to have Stackelberg balance, and the benefit of the user and the base station is relatively maximized.
Next, a monitoring traffic bandwidth allocation apparatus according to an embodiment of the present application will be described with reference to the drawings.
Fig. 4 is a diagram illustrating an example of a monitoring service bandwidth allocation apparatus according to an embodiment of the present application.
As shown in fig. 4, the monitoring traffic bandwidth allocating apparatus 10 includes: a building module 100, a determining module 200 and an assigning module 300.
The building module 100 is configured to build a channel model for obtaining linear gains between users and base stations based on total path losses between the users and the base stations in the network, and determine a bandwidth allocation policy. A determining module 200, configured to generate a base station service request according to the requirement of each user, and determine a pricing policy by combining channel information and a network congestion condition. And the allocating module 300 is configured to construct a two-stage Stackelberg game by using the bandwidth allocation policy and the pricing policy as constraint conditions, and determine a bandwidth allocation result.
In an embodiment of the present application, the allocating module 300 is further configured to formulate two optimization problems maximizing the utility of the user and the base station based on the respective benefits of the user and the base station, generate a two-stage Stackelberg game by using the two optimization problems, solve the best response of the sub-game of the user by using the given price of the base station, and solve the best response of the sub-game of the base station according to the best response of the sub-game of the user, so that the benefits of the user and the base station are relatively maximized.
In one embodiment of the present application, two optimization problems are formulated to maximize the utility of the user and the base station based on the respective favorable properties of the user and the base station, including: respectively acquiring targets of each user and each base station, and generating a corresponding utility function by the targets of each user and each base station; two optimization problems are formulated according to the utility function and with maximized user and base station utility.
In one embodiment of the present application, a two-stage Stackelberg game is generated by using two optimization problems, and the best response of the sub-game of the user is solved by using the given price of the base station, including: giving unit bandwidth price by taking the base station as a leader, and respectively enabling the utility function of the user to calculate a first reciprocal and a second derivative for the bandwidth request resource of the service request of the base station to obtain the optimal requirement of the user to be solved; and substituting the optimal needs of the user into the utility function of the base station, and obtaining the optimal response of the base station according to the optimal needs of the user.
In one embodiment of the present application, determining a pricing strategy includes: and acquiring a corresponding dynamic pricing strategy according to the total bandwidth request quantity of each user to the base station.
It should be noted that the foregoing explanation on the embodiment of the monitoring service bandwidth allocation method is also applicable to the monitoring service bandwidth allocation apparatus of this embodiment, and details are not described here again.
According to the monitoring service bandwidth allocation device provided by the embodiment of the application, a two-stage Stackelberg (Stackelberg) game taking a dynamic bandwidth allocation strategy and a pricing strategy as constraint conditions is constructed. The optimization problem is formulated by maximizing the utility of the user and the base station, the optimal response of the sub game of the user is solved according to the given price of the base station, and the optimal response of the sub game of the base station is solved according to the optimal response of the user, so that the game is proved to have Stackelberg balance, and the benefit of the user and the base station is relatively maximized. The scheme effectively ensures the user experience quality and the base station income, and realizes the effectiveness of bandwidth allocation.
Fig. 5 is a schematic structural diagram of an electronic device according to an embodiment of the present application. The electronic device may include:
a memory 501, a processor 502, and a computer program stored on the memory 501 and executable on the processor 502.
The processor 502 executes the program to implement the monitoring service bandwidth allocation method provided in the above embodiments.
Further, the electronic device further includes:
a communication interface 503 for communication between the memory 501 and the processor 502.
A memory 501 for storing computer programs that can be run on the processor 502.
The memory 501 may comprise high-speed RAM memory, and may also include non-volatile memory (non-volatile memory), such as at least one disk memory.
If the memory 501, the processor 502 and the communication interface 503 are implemented independently, the communication interface 503, the memory 501 and the processor 502 may be connected to each other through a bus and perform communication with each other. The bus may be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, an Extended ISA (EISA) bus, or the like. The bus may be divided into an address bus, a data bus, a control bus, etc. For ease of illustration, only one thick line is shown in FIG. 5, but this is not intended to represent only one bus or type of bus.
Alternatively, in practical implementation, if the memory 501, the processor 502 and the communication interface 503 are integrated on a chip, the memory 501, the processor 502 and the communication interface 503 may complete communication with each other through an internal interface.
The processor 502 may be a Central Processing Unit (CPU), an Application Specific Integrated Circuit (ASIC), or one or more Integrated circuits configured to implement embodiments of the present Application.
The present embodiment also provides a computer-readable storage medium, on which a computer program is stored, which when executed by a processor implements the monitoring traffic bandwidth allocation method as above.
In the description herein, reference to the description of the term "one embodiment," "some embodiments," "an example," "a specific example," or "some examples," etc., means that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the application. In this specification, the schematic representations of the terms used above are not necessarily intended to refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or N embodiments or examples. Furthermore, various embodiments or examples and features of different embodiments or examples described in this specification can be combined and combined by one skilled in the art without contradiction.
Furthermore, the terms "first", "second" and "first" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one such feature. In the description of the present application, "N" means at least two, e.g., two, three, etc., unless specifically limited otherwise.
Any process or method descriptions in flow charts or otherwise described herein may be understood as representing modules, segments, or portions of code which include one or more N executable instructions for implementing steps of a custom logic function or process, and alternate implementations are included within the scope of the preferred embodiment of the present application in which functions may be executed out of order from that shown or discussed, including substantially concurrently or in reverse order, depending on the functionality involved, as would be understood by those reasonably skilled in the art of implementing the embodiments of the present application.
The logic and/or steps represented in the flowcharts or otherwise described herein, e.g., an ordered listing of executable instructions that can be considered to implement logical functions, can be embodied in any computer-readable medium for use by or in connection with an instruction execution system, apparatus, or device, such as a computer-based system, processor-containing system, or other system that can fetch the instructions from the instruction execution system, apparatus, or device and execute the instructions. For the purposes of this description, a "computer-readable medium" can be any means that can contain, store, communicate, propagate, or transport the program for use by or in connection with the instruction execution system, apparatus, or device. More specific examples (a non-exhaustive list) of the computer-readable medium would include the following: an electrical connection (electronic device) having one or N wires, a portable computer diskette (magnetic device), a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disc read-only memory (CDROM). Additionally, the computer-readable medium could even be paper or another suitable medium upon which the program is printed, as the program can be electronically captured, via for instance optical scanning of the paper or other medium, then compiled, interpreted or otherwise processed in a suitable manner if necessary, and then stored in a computer memory.
It should be understood that portions of the present application may be implemented in hardware, software, firmware, or a combination thereof. In the above embodiments, the N steps or methods may be implemented in software or firmware stored in a memory and executed by a suitable instruction execution system. If implemented in hardware, as in another embodiment, any one or combination of the following techniques, which are known in the art, may be used: a discrete logic circuit having a logic gate circuit for implementing a logic function on a data signal, an application specific integrated circuit having an appropriate combinational logic gate circuit, a Programmable Gate Array (PGA), a Field Programmable Gate Array (FPGA), or the like.
It will be understood by those skilled in the art that all or part of the steps carried by the method for implementing the above embodiments may be implemented by hardware related to instructions of a program, which may be stored in a computer readable storage medium, and when the program is executed, the program includes one or a combination of the steps of the method embodiments.
In addition, functional units in the embodiments of the present application may be integrated into one processing module, or each unit may exist alone physically, or two or more units are integrated into one module. The integrated module can be realized in a hardware mode, and can also be realized in a software functional module mode. The integrated module, if implemented in the form of a software functional module and sold or used as a stand-alone product, may also be stored in a computer readable storage medium.
The storage medium mentioned above may be a read-only memory, a magnetic or optical disk, etc. Although embodiments of the present application have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting the present application, and that variations, modifications, substitutions and alterations may be made to the above embodiments by those of ordinary skill in the art within the scope of the present application.
Claims (10)
1. A method for allocating monitoring service bandwidth is characterized by comprising the following steps:
constructing a channel model for acquiring linear gain between users and base stations based on total path loss between the users and the base stations in a network, and determining a bandwidth allocation strategy;
generating a base station service request according to the requirements of each user, and determining a pricing strategy by combining channel information and network congestion conditions;
and constructing a two-stage Stackelberg game by taking the bandwidth allocation strategy and the pricing strategy as constraint conditions, and determining a bandwidth allocation result.
2. The method according to claim 1, wherein the constructing a two-stage Stackelberg game using the bandwidth allocation policy and the pricing policy as constraints and determining the bandwidth allocation result comprises:
based on the property of each benefit of the user and the base station, two optimization problems for maximizing the utility of the user and the base station are formulated;
generating a two-stage Stackelberg game by using the two optimization problems, and solving the optimal response of the sub-game of the user by using the given price of the base station;
and solving the best response of the base station sub-game according to the best response of the user sub-game, so that the benefits of the user and the base station are relatively maximized.
3. The method of claim 2, wherein the formulating two optimization problems that maximize the utility of the user and the base station based on the respective favorable properties of the user and the base station comprises:
respectively acquiring targets of the users and the base stations, and generating corresponding utility functions by the targets of the users and the base stations;
and formulating the two optimization problems by maximizing the utility of the user and the base station according to the utility function.
4. The method of claim 3, wherein said generating a two-stage Stackelberg game using said two optimization problems, and solving the best response of the sub-game of the users using the base station given price comprises:
giving unit bandwidth price by taking the base station as a leader, and respectively enabling the utility function of the user to calculate a first order reciprocal and a second order derivative for the requested bandwidth resource of the service request of the base station to obtain the optimal requirement of the user to be solved;
and substituting the user optimal demand solution into the utility function of the base station, and obtaining the optimal response of the base station according to the user optimal demand solution.
5. The method according to any of claims 1-4, wherein the determining a pricing strategy comprises:
and acquiring the corresponding dynamic pricing strategy according to the total bandwidth request quantity of each user to the base station.
6. A monitoring traffic bandwidth allocation apparatus, comprising:
the system comprises a building module, a bandwidth allocation module and a control module, wherein the building module is used for building a channel model for acquiring linear gain between users and base stations and determining a bandwidth allocation strategy based on total path loss between each user and each base station in a network;
the determining module is used for generating a base station service request according to the requirements of each user and determining a pricing strategy by combining channel information and network congestion conditions;
and the allocation module is used for constructing a two-stage Stackelberg game by taking the bandwidth allocation strategy and the pricing strategy as constraint conditions and determining a bandwidth allocation result.
7. The apparatus of claim 6, wherein the allocating module is further configured to formulate two optimization problems maximizing the utility of the user and the base station based on the respective benefits of the user and the base station, generate a two-stage Stackelberg game by using the two optimization problems, solve the best response of the sub-game of the user by using the given price of the base station, and solve the best response of the sub-game of the base station according to the best response of the sub-game of the user, so that the benefits of the user and the base station are relatively maximized.
8. The apparatus of claim 7, wherein two optimization problems are formulated to maximize the utility of the user and the base station based on the respective benefits of the user and the base station, comprising:
respectively acquiring targets of the users and the base stations, and generating corresponding utility functions by the targets of the users and the base stations;
and formulating the two optimization problems by maximizing the utility of the user and the base station according to the utility function.
9. An electronic device, comprising: a memory, a processor and a computer program stored on the memory and executable on the processor, the processor executing the program to implement the monitoring traffic bandwidth allocation method according to any one of claims 1 to 5.
10. A computer-readable storage medium having stored thereon a computer program, the program being executable by a processor for implementing a method for policing traffic bandwidth allocation according to any one of claims 1 to 5.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202111525074.3A CN113938394B (en) | 2021-12-14 | 2021-12-14 | Monitoring service bandwidth allocation method and device, electronic equipment and storage medium |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202111525074.3A CN113938394B (en) | 2021-12-14 | 2021-12-14 | Monitoring service bandwidth allocation method and device, electronic equipment and storage medium |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN113938394A true CN113938394A (en) | 2022-01-14 |
| CN113938394B CN113938394B (en) | 2022-03-25 |
Family
ID=79288848
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202111525074.3A Active CN113938394B (en) | 2021-12-14 | 2021-12-14 | Monitoring service bandwidth allocation method and device, electronic equipment and storage medium |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN113938394B (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114548409A (en) * | 2022-01-30 | 2022-05-27 | 清华大学 | Unmanned vehicle task allocation game method and device based on state potential field |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2008072083A2 (en) * | 2006-12-11 | 2008-06-19 | New Jersey Institute Of Technology | Method and system for decentralized power control of a multi-antenna access point using game theory |
| WO2011014647A2 (en) * | 2009-07-31 | 2011-02-03 | Ntt Docomo, Inc. | A method for wireless network virtualization through sequential auctions and conjectural pricing |
| CN105848274A (en) * | 2016-03-25 | 2016-08-10 | 山东大学 | Non-uniform pricing power control method based on Steinberg game theory in bi-layer heterogeneous network |
| CN108600014A (en) * | 2018-04-27 | 2018-09-28 | 哈尔滨工业大学深圳研究生院 | A kind of storage resource distribution method based on Stackelberg games |
| CN112543498A (en) * | 2020-11-24 | 2021-03-23 | 山东科技大学 | Power self-adaptive distribution method based on layered game model |
-
2021
- 2021-12-14 CN CN202111525074.3A patent/CN113938394B/en active Active
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2008072083A2 (en) * | 2006-12-11 | 2008-06-19 | New Jersey Institute Of Technology | Method and system for decentralized power control of a multi-antenna access point using game theory |
| WO2011014647A2 (en) * | 2009-07-31 | 2011-02-03 | Ntt Docomo, Inc. | A method for wireless network virtualization through sequential auctions and conjectural pricing |
| CN105848274A (en) * | 2016-03-25 | 2016-08-10 | 山东大学 | Non-uniform pricing power control method based on Steinberg game theory in bi-layer heterogeneous network |
| CN108600014A (en) * | 2018-04-27 | 2018-09-28 | 哈尔滨工业大学深圳研究生院 | A kind of storage resource distribution method based on Stackelberg games |
| CN112543498A (en) * | 2020-11-24 | 2021-03-23 | 山东科技大学 | Power self-adaptive distribution method based on layered game model |
Non-Patent Citations (3)
| Title |
|---|
| 仲崇显等: "基于非合作博弈论的多小区OFDMA系统动态资源分配算法研究", 《电子与信息学报》 * |
| 危泽华等: "基于Stackelberg博弈论的边缘计算卸载决策方法", 《数学的实践与认识》 * |
| 王慧等: "移动广播融合网络中的资源分配和定价模型", 《北京邮电大学学报》 * |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114548409A (en) * | 2022-01-30 | 2022-05-27 | 清华大学 | Unmanned vehicle task allocation game method and device based on state potential field |
Also Published As
| Publication number | Publication date |
|---|---|
| CN113938394B (en) | 2022-03-25 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Ndikumana et al. | Collaborative cache allocation and computation offloading in mobile edge computing | |
| US9350624B2 (en) | Dynamic assignment of connection priorities for applications operating on a client device | |
| US7930403B2 (en) | Allocation of network resources | |
| CN109802998B (en) | Game-based fog network cooperative scheduling excitation method and system | |
| US8996723B2 (en) | ISP-aware peer-to-peer content exchange | |
| EP1993231A1 (en) | Allocation method, system and device for network resource in communication network | |
| US20090178058A1 (en) | Application Aware Networking | |
| CN109831796B (en) | Resource allocation method in wireless network virtualization | |
| WO2015176496A1 (en) | Radio channel control method, traffic package transaction and recommendation methods and related devices | |
| US20200136926A1 (en) | Dynamic adaptive network | |
| WO2022222755A1 (en) | Service processing method and apparatus, and storage medium | |
| CN113938394B (en) | Monitoring service bandwidth allocation method and device, electronic equipment and storage medium | |
| CN112615730B (en) | Resource allocation method and device based on block chain network slice proxy | |
| Wang et al. | Multi-leader multi-follower Stackelberg game based dynamic resource allocation for mobile cloud computing environment | |
| CN111400001A (en) | Online computing task unloading scheduling method facing edge computing environment | |
| Tang et al. | MOMD: A multi-object multi-dimensional auction for crowdsourced mobile video streaming | |
| Rahman et al. | Edge computing assisted joint quality adaptation for mobile video streaming | |
| CN107920108A (en) | A kind of method for pushing of media resource, client and server | |
| CN110035128B (en) | Live broadcast scheduling method and device, live broadcast system and storage medium | |
| Guan et al. | The value of cooperation: Minimizing user costs in multi-broker mobile cloud computing networks | |
| Alioua et al. | Incentive edge caching in software‐defined internet of vehicles: A Stackelberg game approach | |
| US20130290124A1 (en) | Data delivery optimization via an auction system | |
| Aazam et al. | Framework of resource management for intercloud computing | |
| Dubin et al. | A fair server adaptation algorithm for HTTP adaptive streaming using video complexity | |
| US10142184B2 (en) | Centralized architecture for establishing federations of content distributors |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |