CN115209555A - Game theory-based network slicing and computing resource allocation method and system - Google Patents

Game theory-based network slicing and computing resource allocation method and system Download PDF

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CN115209555A
CN115209555A CN202210652835.XA CN202210652835A CN115209555A CN 115209555 A CN115209555 A CN 115209555A CN 202210652835 A CN202210652835 A CN 202210652835A CN 115209555 A CN115209555 A CN 115209555A
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bandwidth
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CN115209555B (en
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唐东红
潘博
赵芸
李进盛
韦肖斌
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Technical Service Branch Of Guangxi Zhuang Autonomous Region Communication Industry Service Co ltd
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    • G06F9/00—Arrangements for program control, e.g. control units
    • G06F9/06—Arrangements for program control, e.g. control units using stored programs, i.e. using an internal store of processing equipment to receive or retain programs
    • G06F9/46—Multiprogramming arrangements
    • G06F9/50—Allocation of resources, e.g. of the central processing unit [CPU]
    • G06F9/5005—Allocation of resources, e.g. of the central processing unit [CPU] to service a request
    • G06F9/5011—Allocation of resources, e.g. of the central processing unit [CPU] to service a request the resources being hardware resources other than CPUs, Servers and Terminals
    • G06F9/5016—Allocation of resources, e.g. of the central processing unit [CPU] to service a request the resources being hardware resources other than CPUs, Servers and Terminals the resource being the memory
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F9/00—Arrangements for program control, e.g. control units
    • G06F9/06—Arrangements for program control, e.g. control units using stored programs, i.e. using an internal store of processing equipment to receive or retain programs
    • G06F9/46—Multiprogramming arrangements
    • G06F9/50—Allocation of resources, e.g. of the central processing unit [CPU]
    • G06F9/5005—Allocation of resources, e.g. of the central processing unit [CPU] to service a request
    • G06F9/5027—Allocation of resources, e.g. of the central processing unit [CPU] to service a request the resource being a machine, e.g. CPUs, Servers, Terminals
    • G06F9/5038—Allocation of resources, e.g. of the central processing unit [CPU] to service a request the resource being a machine, e.g. CPUs, Servers, Terminals considering the execution order of a plurality of tasks, e.g. taking priority or time dependency constraints into consideration
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    • G06F9/00—Arrangements for program control, e.g. control units
    • G06F9/06—Arrangements for program control, e.g. control units using stored programs, i.e. using an internal store of processing equipment to receive or retain programs
    • G06F9/46—Multiprogramming arrangements
    • G06F9/50—Allocation of resources, e.g. of the central processing unit [CPU]
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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W28/00—Network traffic management; Network resource management
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    • H04W28/09—Management thereof
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    • H04W—WIRELESS COMMUNICATION NETWORKS
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Abstract

The invention discloses a method and a system for distributing network slicing and computing power resources based on a game theory, which are used for constructing a revenue function of a terminal, a revenue function of a virtual network operator and a revenue function of a computing power resource provider, solving three revenue functions according to the game theory to obtain a game theory equilibrium solution, so that the terminal, the virtual network operator and the computing power resource provider can respectively select and purchase bandwidth amount and computing power resources, adjust the bandwidth unit price and adjust the computing power resource unit price according to the game theory. The invention relates to a game of multiple terminals, multiple virtual network operators and multiple computing power resource suppliers, and provides a game theory scheme of network slicing and computing power resources; in the process of designing the revenue function of the terminal, the service of the user is prioritized according to the service QoS requirements of different terminals, so that the service QoS requirements of different users can be fully met, resources can be allocated in a customized manner, and the resources can be allocated to busy terminals preferentially after the priorities are divided for different terminal services, thereby avoiding resource waste.

Description

Game theory-based network slicing and computing resource allocation method and system
Technical Field
The invention relates to the technical field of resource allocation, in particular to a method and a system for allocating network slicing and computing resources based on a game theory.
Background
With the coming of the 5G era, the intelligent world of everything interconnection is developing step by step. The emergence of edge computing of the internet of things inevitably brings about a technical and commercial revolution. The combination of the Internet of things and the intelligent building can meet the new era of the intelligent building with high-speed development and open an infinite possible tomorrow.
As one of the key technologies of 5G, based on Network Function Virtualization (NFV)/Software Defined Network (SDN) and other technologies, under the control and management of a Network orchestrator, resource elements of a Network information system, relationships among Network functional units, and interaction criteria among the functional units are customized and arranged through Network slice identifiers, so as to instantiate a dedicated logic Network with shared physical resources, isolated logical resources, and guaranteed quality, thereby guaranteeing differentiated service requirements of different services, and being divided by time delay, bandwidth, security, reliability, and the like, so as to flexibly deal with different Network application scenarios. For example: the video return is needed for the television entertainment business, so that a network slice with larger bandwidth is needed to improve the data throughput, and the requirements on the spectral efficiency and the bandwidth capacity of the slice are higher; the entrance guard access safety needs information quick response, and the narrow-band slice is configured to reduce the data transmission time. Due to limited resources, the broadband purchasing cost is reduced while different service requirements are met, network slice resources are reasonably arranged according to service application scenes and the energy consumption scale of the user terminal, and the resource utilization rate is improved.
At present, game theory is widely used for solving the problem of scheduling and arranging network slice resources, but the existing research has the following defects:
1) Only gaming between device providers and network operators is considered, but with the advent of management systems that integrate multiple service scenarios, existing research does not consider gaming between user terminals, network operators, and computing resource providers.
2) Under intelligent building management multi-service management, existing research does not consider the balance of bandwidth, computing resources and purchase cost required by each service.
Disclosure of Invention
The present invention is directed to solving at least one of the problems of the prior art. Therefore, the invention provides a network slicing and computing resource allocation method based on the game theory.
The invention also provides a system, an electronic device and a computer readable storage medium for executing the method for allocating the network slicing and the computing power resources based on the game theory.
The method for allocating network slices and computing resources based on game theory according to the embodiment of the first aspect of the invention is used for a resource allocation system comprising a plurality of terminals, a plurality of virtual network operators and a plurality of computing resource providers, wherein the virtual network operators are used for supplying the terminals with the bandwidth of the network slices, and the computing resource providers are used for supplying the terminals with the computing resources; the method comprises the following steps:
constructing a first revenue function of the terminal:
acquiring multiple services corresponding to each terminal, and performing priority sequencing on the multiple services of each terminal respectively to obtain a sequencing result; acquiring the required bandwidth amount of the service in the network slice, the spectrum efficiency of occupying the network slice and the bandwidth unit price of each virtual network operator for selling the network slice; acquiring the computing resources required by the service and the unit price of the computing resources for selling the computing resources by each computing resource provider;
constructing a first revenue function of the terminal according to the service, the sequencing result, the bandwidth amount of the service required in the network slice, the spectrum efficiency occupying the network slice, the bandwidth unit price, the computing resource required by the service and the computing resource unit price;
constructing a second revenue function for the virtual network operator:
acquiring the bandwidth amount of the network slice sold to the terminal by each virtual network operator and the cost of the bandwidth amount of the network slice;
constructing a second revenue function of the virtual network operator according to the bandwidth unit price, the bandwidth amount of the network slice sold to the terminal by each virtual network operator and the cost of the bandwidth amount of the network slice;
constructing a third revenue function for the computing resource provider:
acquiring the computing power resource sold by each computing power resource supplier and the cost of the computing power resource;
constructing a third revenue function of the computing resource supplier according to the unit price of the computing resource, the computing resource sold by each computing resource supplier and the cost of the computing resource;
solving the first revenue function, the second revenue function and the third revenue function according to a game theory to obtain a game theory equilibrium solution, so that the terminal selects the bandwidth amount purchased from the virtual network operator and selects the computing power resource purchased from the computing power resource provider according to the game theory equilibrium solution, so that the virtual network operator adjusts the bandwidth unit price according to the game theory equilibrium solution, and the computing power resource provider adjusts the computing power resource unit price according to the game theory equilibrium solution.
The distribution method provided by the embodiment of the invention at least has the following beneficial effects:
the method relates to the game among multiple terminals, multiple virtual network operators and multiple computing power resource providers, and provides a game theory scheme of network slicing resources and computing power resources. Compared with the traditional scheme, in order to meet the service QoS requirements of different terminals, the method prioritizes the users in the process of designing the revenue function of the terminal, so that the service QoS requirements of different users can be fully met, resources can be allocated in a customized manner, and meanwhile, after the priorities are divided for different terminal services, the resources can be allocated to busy terminals preferentially, and the waste of resources is avoided.
According to some embodiments of the present invention, the prioritizing the plurality of services for each terminal includes:
acquiring the data transmission rate and the data transmission time delay which are expected by each service of each terminal;
calculating the ratio between the data transmission rate and the data transmission delay;
and sequencing the services according to the ratio of each service.
According to some embodiments of the invention, the computing resource provider comprises a CPU provider and a memory bank provider, the computing resource comprises a CPU and a memory bank, the third revenue function comprises a revenue function of the CPU provider and a revenue function of the memory bank provider, and the computing resource unit price comprises a CPU unit price and a memory bank unit price.
According to some embodiments of the invention, the representation of the first benefit function of the terminal comprises:
Figure BDA0003688262110000031
Figure BDA0003688262110000032
Figure BDA0003688262110000033
Figure BDA0003688262110000034
Figure BDA0003688262110000035
wherein u is i A first revenue function, v, representing the terminal i Set of services, ξ, representing terminal i t Representing the ratio R of the expected data transmission rate of the service t to the data transmission delay it /D it ，ρ j Represents the bandwidth unit price, W, of the jth virtual network operator tj Representing the amount of bandwidth, S, required by the service t in the jth network slice of the virtual network operator tj Representing the spectral efficiency, gamma, of the jth network slice occupied by the service t tj Representing a constraint variable, Y tk Number of cores occupied by CPU of type k, T, representing service T k CPU Bandwidth, μ, representing the kth type number k CPU unit price, Z, representing kth type tl The memory capacity U of the service t occupied by the memory bank of the type I is represented l Memory bandwidth, τ, representing type I number l Memory bank unit price, beta, representing type I tk And alpha tl Representing a constraint variable; ζ represents a unit k Set of traffic, phi, representing the kth CPU provider l Representing a set of services of the first memory bank provider;
the representation of the second revenue function of the virtual network operator comprises:
ψ j ＝ρ j χ j -εκ j
Figure BDA0003688262110000041
wherein, χ j Represents the amount of bandwidth, ρ, sold by the network slice of the jth virtual network operator j Representing the jth virtual network operationBandwidth unit price of operator,. Epsilon.. Kappa.) j Representing a bandwidth amount cost of a network slice of a jth virtual network operator;
the representation form of the revenue function of the CPU supplier comprises the following steps:
δ k ＝μ k c k -θd k
Figure BDA0003688262110000042
wherein, c k Indicates the number of CPU cores sold by the kth CPU supplier, mu k Represents the CPU unit price, θ d, of the kth CPU supplier k Represents the CPU cost of the kth CPU supplier;
the representation form of the income function of the memory bank supplier comprises the following steps:
Figure BDA0003688262110000048
Figure BDA0003688262110000043
wherein e is l Indicates the number of memory banks sold by the first bank supplier, Z l Indicating the memory bank cost of the first memory bank provider,
Figure BDA0003688262110000049
indicating the memory bank cost of the first memory bank provider.
According to some embodiments of the invention, solving the first revenue function, the second revenue function, the revenue function of the CPU provider and the revenue function of the memory bank provider according to game theory comprises:
respectively constructing a game model of the terminal, a game model of the virtual network operator, a game model of the CPU supplier and a game model of the memory bank supplier, wherein the representation form of the game model of the terminal comprises the following steps:
Figure BDA0003688262110000044
the representation of the gaming model of the virtual network operator includes:
Figure BDA0003688262110000045
Figure BDA0003688262110000046
the representation form of the game model of the CPU supplier comprises the following steps:
Figure BDA0003688262110000047
Figure BDA0003688262110000051
the representation form of the game model of the memory bank supplier comprises the following steps:
Figure BDA0003688262110000052
Figure BDA0003688262110000053
and solving a game model of the terminal, a game model of the virtual network operator, a game model of the CPU supplier and a game model of the memory bank supplier to obtain a game theory equilibrium solution.
According to some embodiments of the invention, the balanced solution of the gaming theory of the gaming model of the terminal comprises:
Figure BDA0003688262110000054
Figure BDA0003688262110000055
Figure BDA0003688262110000056
the balanced solution of the gaming model of the virtual network operator comprises:
Figure BDA0003688262110000057
the equilibrium solution of the gaming model of the CPU supplier comprises:
Figure BDA0003688262110000058
the equilibrium solution of the gaming model of the memory bank supplier comprises:
Figure BDA0003688262110000059
wherein, W * Vector, Y, representing the bandwidth composition purchased by various services from a virtual network operator * Vector, Z, of quantities of CPUs purchased from CPU suppliers for various services * Vector, p, representing the number of memory chips purchased by various services from a chip supplier * Vector, mu, representing the optimal bandwidth unit price component of all virtual network operators * Vector, τ, representing the optimal CPU unit price component of the CPU supplier * Vector representing best selling price component of memory bank supplier
The system for distributing network slicing and force-calculating resources based on the game theory comprises the following components:
the parameter acquisition unit is used for acquiring various services corresponding to each terminal and respectively carrying out priority sequencing on the various services of each terminal to obtain a sequencing result; acquiring the required bandwidth amount of the service in the network slice, the spectrum efficiency of occupying the network slice and the bandwidth unit price of each virtual network operator for selling the network slice; acquiring the computing resources required by the service and the unit price of the computing resources for selling the computing resources by each computing resource provider; acquiring the bandwidth amount of the network slice sold by each virtual network operator to the terminal and the cost of the bandwidth amount of the network slice; acquiring the computing resources sold by each computing resource supplier and the cost of the computing resources;
a revenue function constructing unit, configured to construct a first revenue function of the terminal according to the service, the ordering result, the bandwidth amount required by the service in the network slice, the spectrum efficiency of occupying the network slice, the bandwidth unit price, the computing resource required by the service, and the computing resource unit price; constructing a second revenue function of the virtual network operator according to the bandwidth unit price, the bandwidth amount of the network slice sold to the terminal by each virtual network operator and the cost of the bandwidth amount of the network slice; constructing a third revenue function of the computing resource supplier according to the unit price of the computing resource, the computing resource sold by each computing resource supplier and the cost of the computing resource;
the game theory solving unit is used for solving the first revenue function, the second revenue function and the third revenue function according to game theory to obtain a game theory equilibrium solution, so that the terminal selects the bandwidth amount purchased from the virtual network operator and selects the computing power resource purchased from the computing power resource supplier according to the game theory equilibrium solution, the virtual network operator adjusts the bandwidth unit price according to the game theory equilibrium solution, and the computing power resource supplier adjusts the computing power resource unit price according to the game theory equilibrium solution.
The distribution system adopts all the technical schemes of the network slicing and computing resource distribution method based on the game theory in the embodiment, so that the distribution system at least has all the beneficial effects brought by the technical schemes in the embodiment.
An electronic device according to an embodiment of the third aspect of the present invention includes: at least one control processor and a memory for communicative connection with the at least one control processor; the memory stores instructions executable by the at least one control processor to enable the at least one control processor to perform a method of gaming theory based network slicing and computing resource allocation as described above.
Since the electronic device adopts all the technical solutions of the method for distributing network slicing and computing resources based on the game theory in the above embodiments, at least all the advantages brought by the technical solutions in the above embodiments are achieved.
According to a fourth aspect of the present invention, there is provided a computer-readable storage medium storing computer-executable instructions for causing a computer to perform a method for network slicing and power resource allocation based on game theory as described above
Since the electronic device adopts all the technical solutions of the method for distributing network slicing and computing resources based on the game theory in the above embodiments, at least all the advantages brought by the technical solutions in the above embodiments are achieved.
Additional features and advantages of the invention will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention.
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The above and/or additional aspects and advantages of the present invention 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 flow chart of a method for allocating network slices and computing resources based on game theory according to an embodiment of the present invention;
fig. 2 is a flowchart of a method for allocating network shards and computing resources based on a game theory according to an embodiment of the present invention;
FIG. 3 is a graph comparing the bandwidth amounts of the HUS scheme and the RSS scheme with the present method according to an embodiment of the present invention;
FIG. 4 is a comparison of the present method with the HUS scheme and the RSS scheme in terms of the number of CPU cores according to the embodiment of the present invention;
FIG. 5 is a graph of the present method versus the HUS and RSS schemes on an inventory basis according to an embodiment of the present invention;
FIG. 6 is a diagram illustrating the user's bandwidth purchase amount and data transmission rate according to the present invention;
fig. 7 is a schematic diagram of bandwidth unit price and data transmission rate in virtual network operation of the present method according to an embodiment of the present invention;
FIG. 8 is a schematic diagram of user bandwidth purchase amount and delay requirement of the method provided by the embodiment of the present invention;
fig. 9 is a schematic diagram of the bandwidth unit price and the delay requirement in the virtual network operation of the present method according to the embodiment of the present invention;
FIG. 10 is a schematic diagram of the user bandwidth purchase amount and the number of users of the method provided by the embodiment of the present invention;
fig. 11 is a schematic diagram of the bandwidth unit price and the number of users in virtual network operation according to the present invention.
Detailed Description
Reference will now be made in detail to embodiments of the present invention, 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 accompanying drawings are illustrative only for the purpose of explaining the present invention, and are not to be construed as limiting the present invention.
In the description of the present invention, if there are first, second, etc. described, it is only for the purpose of distinguishing technical features, and it is not understood that relative importance is indicated or implied or that the number of indicated technical features is implicitly indicated or that the precedence of the indicated technical features is implicitly indicated.
In the description of the present invention, it should be understood that the orientation descriptions, such as the orientation or positional relationship indicated above, below, etc., are based on the orientation or positional relationship shown in the drawings, and are only for convenience of description and simplification of the description, but do not indicate or imply that the system or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and thus should not be construed as limiting the present invention.
In the description of the present invention, it should be noted that unless otherwise explicitly defined, terms such as setup, installation, connection, etc. should be understood in a broad sense, and those skilled in the art can reasonably determine the specific meanings of the above terms in the present invention by combining the detailed contents of the technical solutions.
Referring to fig. 1, an embodiment of the present invention provides a method for allocating network slices and computing resources based on a game theory, which is used in a resource allocation system comprising a plurality of terminals, a plurality of virtual network operators and a plurality of computing resource providers, wherein a virtual network operator is used to supply bandwidth of a network slice to a terminal, and a computing resource provider is used to supply computing resources to a terminal; the method comprises the following steps:
s101, constructing a first revenue function of the terminal:
acquiring multiple services corresponding to each terminal, and performing priority sequencing on the multiple services of each terminal according to the QoS (quality of service) requirements of the services to obtain a sequencing result; acquiring the bandwidth amount of a service required in a network slice, the spectrum efficiency of the service occupying the network slice and the bandwidth unit price of each virtual network operator selling the network slice; acquiring computing resources required by the service and the unit price of the computing resources for selling the computing resources by each computing resource provider;
and constructing a first revenue function of the terminal according to the service, the sequencing result, the bandwidth amount required by the service in the network slice, the spectrum efficiency of the occupied network slice, the unit price of the bandwidth, the computing resource required by the service and the unit price of the computing resource.
In some embodiments, the priority of the service is expressed by a ratio between a data transmission rate and a data transmission delay desired by the service, and therefore, the step S101 of prioritizing the services of each terminal according to QoS requirements of the services includes the steps of:
step S1011, obtaining the data transmission rate and the data transmission delay expected by each service of each terminal.
Step S1012, calculating a ratio between the data transmission rate and the data transmission delay.
And step S1013, sequencing the services according to the ratio of each service.
Step S102, constructing a second revenue function of the virtual network operator:
acquiring the bandwidth amount of a network slice sold to a terminal by each virtual network operator and the cost of the bandwidth amount of the network slice;
and constructing a second revenue function of the virtual network operator according to the unit price of the bandwidth, the bandwidth amount of the network slice sold to the terminal by each virtual network operator and the cost of the bandwidth amount of the network slice.
Step S103, constructing a third revenue function of the computing resource provider:
acquiring computing power resources sold by each computing power resource supplier and the cost of the computing power resources;
and constructing a third revenue function of the computing resource provider according to the unit price of the computing resource, the computing resource sold by each computing resource provider and the cost of the computing resource.
In an embodiment, the computing resource provider includes a CPU provider and a memory bank provider, the computing resource includes a CPU and a memory bank, the third revenue function includes a revenue function of the CPU provider and a revenue function of the memory bank provider, and the unit price of the computing resource includes a CPU unit price and a memory bank unit price.
And step S104, solving the first profit function, the second profit function and the third profit function according to the game theory to obtain a game theory equilibrium solution, so that the terminal selects the bandwidth amount purchased from the virtual network operator and selects the computing power resource purchased from the computing power resource provider according to the game theory equilibrium solution, the virtual network operator adjusts the bandwidth unit price according to the game theory equilibrium solution, and the computing power resource provider adjusts the computing power resource unit price according to the game theory equilibrium solution.
The method relates to the game among multiple terminals (users), multiple virtual network operators and multiple computing power resource providers, and provides a game theory scheme of network slicing resources and computing power resources. Compared with the traditional game scheme, the method has the advantages that in order to meet the requirements of different terminal services QoS (Quality of Service), the priorities are divided for the services of the terminals in the process of designing the revenue function of the terminals, so that the requirements of the different users on the Service QoS can be fully met, resources can be allocated in a customized manner, and resources can be allocated for busy terminals preferentially after the priorities are divided for the different terminal services, so that resource waste is avoided.
For easy understanding, referring to fig. 2 to 11, an embodiment of the present invention provides a method for allocating network slicing and computing resources based on a game theory, where the method is used in a resource allocation system including N terminals (users), M virtual network operators, L CPU providers, and K memory bank providers, in the resource allocation system, each terminal has a respective service, each virtual network operator has a group of subscription terminals, and each terminal has different QoS requirements for the services, and the QoS requirements are measured by an expected data transmission rate and a delay requirement index.
The CPU supplier, the memory bank supplier, the virtual network operator and the terminal are used as rational individuals in the decision process for maximizing the self income, and the CPU supplier, the memory bank supplier and the virtual network operator are used as decision makers at the same level and decide before the terminal. The relationship between the CPU provider, the memory bank provider, the virtual network operator and the terminals can thus be described in a gaming model. The gaming process is as follows:
firstly, a CPU supplier, a memory bank supplier and a virtual network operator respectively set unit prices of a CPU, a memory bank and a bandwidth to sell to a terminal; then, the terminal determines the purchase amount according to the real-time service requirement, the unit price of the CPU, the memory bank and the bandwidth, so that the self income is maximized.
1.1, structureEstablishing a revenue function of the terminal: considering the diversity requirements of different terminal services, the revenue function u of the terminal i i Comprises the following steps:
Figure BDA0003688262110000091
the revenue function of the terminal consists of two parts, namely network resources and computing resources.
Network resources: v. of i Service set, ξ, representing terminal i t Ratio R of data transmission rate to data transmission delay for service t expected in service scene it /D it Used to indicate the priority of the service t, p j Represents the bandwidth unit price, W, of the jth virtual network operator tj Represents the amount of bandwidth, S, required by the service t in the jth network slice of the virtual network operator tj Representing the spectral efficiency, gamma, of the jth network slice occupied by the service t tj Representing a constraint variable, assuming that each service occupies one slice resource.
Figure BDA0003688262110000101
Figure BDA0003688262110000106
Representing the traffic of the jth network slice.
Calculating power resources: y is tk Representing the number of cores occupied by the service T in the kth type number CPU, T k CPU Bandwidth, μ, representing the kth type number k CPU unit price, Z, representing the kth model number tl The memory capacity U of the service t occupied by the memory bank of the type I is represented l Indicates the memory bandwidth of type I l Memory bank unit price, beta, representing type I tk And alpha tl Representing constraint variables, assuming that each service only occupies one model of CPU and memory bank.
Figure BDA0003688262110000102
Figure BDA0003688262110000103
ζ k Represents the set of traffic of the kth CPU provider, phi l And representing the service set of the first memory bank provider.
1.2, revenue function of virtual network operator: the revenue for the virtual network operator is derived from the difference between the profit in selling bandwidth to the terminal and the cost of purchasing bandwidth from the network equipment provider, and the revenue function is as follows:
ψ j ＝ρ j χ j -εκ j (3)
χ j represents the amount of bandwidth sold by the jth virtual network operator network slice, ε represents the network equipment provider's specified unit price of bandwidth sold to the virtual network operator, κ j Representing the amount of bandwidth bought by the jth virtual network operator. In order to maximize the income of the virtual network operator, the virtual network operator always makes the bought bandwidth sold to the terminal totally according to the market sales condition, namely:
Figure BDA0003688262110000104
1.3, revenue function of CPU supplier: the CPU supplier revenue comes from selling CPU profit to the terminal, and the revenue function is as follows:
δ k ＝μ k c k -θd k (5)
c k denotes the number of CPU cores sold by the kth CPU supplier, θ denotes the unit price cost of CPU buying by the supplier, d k Representing the purchase of the kth CPU vendor. In order to maximize the income of the CPU supplier, the CPU supplier enables the purchased CPU to be sold to the terminal according to the market sale condition, namely:
Figure BDA0003688262110000105
1.4 revenue function of the bank supplier: the revenue of the memory bank supplier comes from the profit of the memory sold to the terminal, and the revenue function is as follows:
Figure BDA0003688262110000107
e l indicating the number of memory banks sold by the first bank supplier,
Figure BDA0003688262110000108
representing a unit price cost of memory bank purchase by a supplier, f l The purchase amount of the first memory bank supplier is shown. In order to maximize the self income, the memory bank supplier enables the bought memory banks to be sold to the terminal according to the market sale condition, namely:
Figure BDA0003688262110000111
2.1, the game strategy of the terminal: based on the revenue function of the terminal, the game model (optimal decision model) can be obtained by solving the following optimization problem P1:
Figure BDA0003688262110000112
the unit price of the bandwidth established by the virtual network operator j is rho j Under the condition (2), the bandwidth purchase quantity of the problem P1 has an optimal unique solution, and the expression of the optimal solution is as follows:
Figure BDA0003688262110000113
and (3) proving that: by applying an objective function u i For variable W ij The second derivative is calculated to obtain:
Figure BDA0003688262110000114
then the problem P1 is now a convex optimization problem, which can be solved by letting the objective function U i For variable W tj The first partial derivative of (a) is equal to zero to obtain an optimal solution, i.e.:
Figure BDA0003688262110000115
the optimal solution to the problem P1 is thus derived as:
Figure BDA0003688262110000116
in summary, unit price ρ for the terminal virtual network operator j The optimal response strategy is as above.
The unit price of CPU established by CPU supplier k is mu k Under the condition (2), the CPU purchase amount of the problem P1 has an optimal unique solution, which is expressed as follows:
Figure BDA0003688262110000117
the price made by the memory bank supplier l is τ l In the case of (2), the memory purchase amount of the problem P1 has an optimal unique solution, which is expressed as follows:
Figure BDA0003688262110000118
2.2, game decision of the virtual network operator:
Figure BDA0003688262110000119
the game model (optimal decision model) of the virtual network operator j is expressed as follows (problem P2):
Figure BDA0003688262110000121
wherein the constraint conditions ensure positive revenue for the virtual network operator and comply with market trading rules.
Solving the optimization problem P2, the optimal pricing strategy for the price epsilon established by the virtual network operator for the network equipment provider (which is the provider for supplying bandwidth to the virtual network operator) is:
Figure BDA0003688262110000122
and (3) proving that: the objective function psi due to the problem P2 j The second derivative of the pair variable is less than zero, i.e.:
Figure BDA0003688262110000123
the problem P2 is a convex optimization problem, the optimal solution of which can be found by the lagrange relaxation variance method. Wherein the Lagrangian function of the convex optimization problem is:
Figure BDA0003688262110000124
wherein α is a relaxation factor. From the KKT condition, the following series of equations can be obtained:
Figure BDA0003688262110000125
ρ j ≥ε
α(ε-ρ j )＝0
it can be deduced that the relaxation factor α =0, the optimal pricing strategy of the virtual network operator can be obtained by equation (12) as shown in equation (14).
2.3, game decision of CPU supplier:
Figure BDA0003688262110000126
the game model (optimal decision model) of the CPU provider k is expressed as follows (problem P3):
Figure BDA0003688262110000127
solving the optimization problem P3 can yield: for a buy-in CPU price θ, the optimal sell pricing strategy by the CPU supplier is:
Figure BDA0003688262110000128
2.4, game decision of a memory bank supplier:
Figure BDA0003688262110000129
the gaming model (best decision model) of the memory bank supplier l is expressed as follows (problem P4):
Figure BDA0003688262110000131
solving the optimization problem P4 can yield: memory bank supplier for buying memory bank price
Figure BDA0003688262110000133
The optimal selling pricing strategy is as follows:
Figure BDA0003688262110000132
in summary, the game theory equilibrium solution proposed by the method is as follows: w is a group of * ,Y * ,Z * ,ρ * ,μ * ,τ * Wherein W is * Service representing each terminal is operated from virtual networkVector of bandwidths purchased from merchants, Y * Vector, Z, consisting of the number of CPUs purchased from CPU suppliers for each service * A vector, p, representing the number of memory chips purchased by each service from a memory chip supplier * A vector consisting of the optimum bandwidth selling price (i.e., the optimum bandwidth unit price) established by all the virtual network operators, a vector consisting of the optimum CPU selling price (i.e., the optimum CPU unit price) established by the CPU supplier to the terminal, and τ * And a vector consisting of the optimal selling price of the memory banks (i.e. the optimal unit price of the memory banks) established by the memory bank supplier to the terminal.
Compared with the traditional scheme, in order to meet the QoS requirements of different terminal services, the method takes the data throughput, the time delay requirement and the equipment usage as indexes to prioritize the different services of the terminal in the process of designing the revenue function. Compared with the traditional game scheme, the scheme can fully meet the service QoS requirements of different terminals, reasonably allocates network (bandwidth) resources, CPU (central processing unit) resources and memory resources for different user service requirements, and can preferentially allocate resources for busy terminals after the terminals are divided into priorities, so that resource waste is avoided.
In order to verify the reasonability of resource allocation brought by the method for prioritizing different services of the terminal, the method is compared with the traditional resource allocation method HUS and RSS. Assuming that there are 3 network slices, each network slice carries 4 terminal services, and the expected data transmission rate and the tolerant delay time of each service are respectively: r = [ 1.1.5.2.3.5.3.5 3.5 ] 2.5 ]/mbps; d = [50 70 100 150 80 50 250 100 50] ms. By comparing the three methods, the bandwidth allocation amount under 12 services proves the effectiveness of the priority design.
As shown in fig. 3, in the method, terminals with higher priorities, such as services 6, 7, and 12, have higher expected data transmission rates and lower tolerated delays, and more bandwidth resource allocations are obtained. The HUS allocates the same bandwidth for the terminal services, which may result in that no more resources are available for the services with high priority, or resources are allocated for the idle services with low priority but the utilization rate is not sufficient, resulting in waste. RSS randomly allocates resources for traffic also causes the same problems as HUS.
As shown in fig. 4 and 5, the resource allocation of the cpu core number and the memory amount is also the same. Fig. 6 and 7 show the expected transmission rate impact on the game, fig. 8 and 9 show the user size impact on the game, and fig. 10 and 11 show the user size impact on the game.
The invention further provides a system for distributing network slicing and computing power resources based on the game theory, which comprises a parameter acquisition unit, a revenue function construction unit and a game theory solving unit, wherein:
the parameter acquisition unit is used for acquiring various services corresponding to each terminal and respectively performing priority sequencing on the various services of each terminal to obtain a sequencing result; acquiring the bandwidth amount of a service required in a network slice, the spectrum efficiency of the service occupying the network slice and the bandwidth unit price of each virtual network operator selling the network slice; acquiring computing power resources required by the service and computing power resource unit prices for each computing power resource supplier to sell the computing power resources; acquiring the bandwidth amount of a network slice sold to a terminal by each virtual network operator and the cost of the bandwidth amount of the network slice; and acquiring the computing resources sold by each computing resource supplier and the cost of the computing resources.
The profit function building unit is used for building a first profit function of the terminal according to the service, the sequencing result, the bandwidth amount required by the service in the network slice, the spectrum efficiency of the occupied network slice, the bandwidth unit price, the calculation resource required by the service and the calculation resource unit price; constructing a second revenue function of the virtual network operator according to the bandwidth unit price, the bandwidth amount of the network slice sold to the terminal by each virtual network operator and the cost of the bandwidth amount of the network slice; and constructing a third revenue function of the computing power resource supplier according to the unit price of the computing power resource, the computing power resource sold by each computing power resource supplier and the cost of the computing power resource.
The game theory solving unit is used for solving the first revenue function, the second revenue function and the third revenue function according to the game theory to obtain a game theory equilibrium solution, so that the terminal selects the bandwidth amount purchased from the virtual network operator and selects the computing power resource purchased from the computing power resource provider according to the game theory equilibrium solution, the virtual network operator adjusts the bandwidth unit price according to the game theory equilibrium solution, and the computing power resource provider adjusts the computing power resource unit price according to the game theory equilibrium solution.
It should be noted that the embodiment of the present system and the embodiment of the method described above are based on the same inventive concept, and therefore, the related contents of the above embodiments are also applicable to the embodiment of the present system, and are not described herein again.
According to one embodiment of the invention, an electronic device is provided, and the electronic device can be any type of intelligent terminal, such as a mobile phone, a tablet computer, a personal computer and the like.
Specifically, the electronic device includes: one or more control processors and memory. The control processor and memory may be connected by a bus or other means.
The memory, which is a non-transitory computer-readable storage medium, may be used to store non-transitory software programs, non-transitory computer-executable programs, and modules, such as program instructions/modules corresponding to the electronic device in the embodiments of the present invention. The control processor executes various functional applications and data processing of the network slicing and computing power resource allocation system based on the game theory by running the non-transitory software program, the instructions and the modules stored in the memory, namely, the method for allocating the network slicing and computing power resources based on the game theory is realized.
The memory may include a storage program area and a storage data area, wherein the storage program area may store an operating system, an application program required for at least one function; the storage data area may store data created by use of the distribution system of network slices and computing resources based on game theory, and the like. Further, the memory may include high speed random access memory, and may also include non-transitory memory, such as at least one disk storage device, flash memory device, or other non-transitory solid state storage device. In some embodiments, the memory optionally includes memory located remotely from the control processor, and these remote memories may be connected to the electronic device via a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.
The one or more modules are stored in the memory and, when executed by the one or more control processors, perform a method of game theory-based network slicing and computing resource allocation in the above-described method embodiments.
Embodiments of the present invention further provide a computer-readable storage medium, where the computer-readable storage medium stores computer-executable instructions, which are executed by one or more control processors, and can cause the one or more control processors to execute a method for allocating network slices and computing resources based on game theory in the above method embodiments.
The above described system embodiments are merely illustrative, wherein the units described as separate components may or may not be physically separate, may be located in one place, or may be distributed over a plurality of network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of the present embodiment.
Through the above description of the embodiments, those skilled in the art will clearly understand that the embodiments may be implemented by software plus a general hardware platform. Those skilled in the art will appreciate that all or part of the processes of the methods of the above embodiments may be implemented by hardware related to instructions of a computer program, which may be stored in a computer readable storage medium, and when executed, may include the processes of the embodiments of the methods described above. The storage medium may be a magnetic disk, an optical disk, a Read Only Memory (ROM), a Random Access Memory (RAM), or the like.
In the description of the present specification, reference to the description of "one embodiment," "some embodiments," "an illustrative embodiment," "an example," "a specific example," or "some examples" or the like 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 present invention. In this specification, the schematic representations of the terms used above do not necessarily 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 more embodiments or examples.
The embodiments of the present invention have been described in detail with reference to the accompanying drawings, but the present invention is not limited to the above embodiments, and various changes can be made within the knowledge of those skilled in the art without departing from the gist of the present invention.

Claims (9)

1. A method for distributing network slices and computing resources based on game theory is characterized by comprising a resource distribution system consisting of a plurality of terminals, a plurality of virtual network operators and a plurality of computing resource providers, wherein the virtual network operators are used for supplying the bandwidth of the network slices to the terminals, and the computing resource providers are used for supplying the computing resources to the terminals; the method comprises the following steps:
constructing a first revenue function of the terminal:
acquiring multiple services corresponding to each terminal, and performing priority sequencing on the multiple services of each terminal according to the QoS requirements of the services to obtain a sequencing result; acquiring the required bandwidth amount of the service in the network slice, the spectrum efficiency of occupying the network slice and the bandwidth unit price of each virtual network operator for selling the network slice; acquiring the computing resources required by the service and the unit price of the computing resources for selling the computing resources by each computing resource provider;
constructing a first revenue function of the terminal according to the service, the sequencing result, the bandwidth amount required by the service in the network slice, the spectrum efficiency occupying the network slice, the bandwidth unit price, the computing resource required by the service and the computing resource unit price;
constructing a second revenue function for the virtual network operator:
acquiring the bandwidth amount of the network slice sold to the terminal by each virtual network operator and the cost of the bandwidth amount of the network slice;
constructing a second revenue function of the virtual network operator according to the bandwidth unit price, the bandwidth amount of the network slice sold to the terminal by each virtual network operator and the cost of the bandwidth amount of the network slice;
constructing a third revenue function for the computing resource provider:
acquiring the computing power resource sold by each computing power resource supplier and the cost of the computing power resource;
constructing a third revenue function of the computing resource supplier according to the unit price of the computing resource, the computing resource sold by each computing resource supplier and the cost of the computing resource;
solving the first revenue function, the second revenue function and the third revenue function according to a game theory to obtain a game theory equilibrium solution, so that the terminal selects the bandwidth amount purchased from the virtual network operator and selects the computing power resource purchased from the computing power resource provider according to the game theory equilibrium solution, so that the virtual network operator adjusts the bandwidth unit price according to the game theory equilibrium solution, and the computing power resource provider adjusts the computing power resource unit price according to the game theory equilibrium solution.
2. A method for network slicing and force resource allocation based on game theory as claimed in claim 1, wherein the prioritizing of the services for each of the terminals according to the QoS requirements of the services comprises:
acquiring the data transmission rate and the data transmission time delay which are expected by each service of each terminal;
calculating the ratio between the data transmission rate and the data transmission delay;
and sequencing the services according to the ratio of each service.
3. The method for distributing network slicing and computing power resources based on game theory according to claim 2, wherein the computing power resource suppliers comprise a CPU supplier and a memory bank supplier, the computing power resources comprise a CPU and a memory bank, the third revenue function comprises a revenue function of the CPU supplier and a revenue function of the memory bank supplier, and the computing power resource unit price comprises a CUP unit price and a memory bank unit price.
4. A method for network slicing and power resource allocation based on the game theory as claimed in claim 3, wherein the representation of the first benefit function of the terminal comprises:
Figure FDA0003688262100000021
Figure FDA0003688262100000022
Figure FDA0003688262100000023
Figure FDA0003688262100000024
wherein u is i A first gain function, v, representing a terminal i Set of services, ξ, representing terminal i t A ratio R of data transmission rate to data transmission delay representing the expectation of a service t it /D it ，ρ j Represents the bandwidth unit price, W, of the jth virtual network operator tj Representing the amount of bandwidth, S, required by the service t in the jth network slice of the virtual network operator tj Frequency of j-th network slice representing occupation of service tSpectral efficiency, gamma tj Representing a constraint variable, Y tk Number of cores occupied by CPU of type k, T, representing service T k CPU Bandwidth, μ, representing the kth type number k CPU unit price, Z, representing the kth model number tl The memory capacity U of the service t occupied by the memory bank of the type I is represented l Indicates the memory bandwidth of type I l Unit price of memory bank, beta, representing type I tk And alpha tl Representing a constraint variable;
Figure FDA0003688262100000026
set of traffic, phi, representing the kth CPU provider l Representing the set of the service of the first memory bank provider;
the representation of the second revenue function of the virtual network operator comprises:
ψ j ＝ρ j χ j -εκ j
Figure FDA0003688262100000025
wherein, χ j Represents the amount of bandwidth sold by the network slice of the jth virtual network operator, ρ j Denotes the bandwidth unit price of the jth virtual network operator, ε κ j Representing a bandwidth amount cost of a network slice of a jth virtual network operator;
the representation form of the revenue function of the CPU supplier comprises the following steps:
δ k ＝μ k c k -θd k
Figure FDA0003688262100000031
wherein, c k Indicates the number of CPU cores sold by the kth CPU vendor, μ k Represents the CPU unit price, θ d, of the kth CPU supplier k Represents the CPU cost of the kth CPU supplier;
the representation form of the income function of the memory bank supplier comprises the following steps:
Figure FDA0003688262100000032
Figure FDA0003688262100000033
wherein e is l Indicates the number of memory banks sold by the first bank supplier, Z l Indicating the memory bank cost of the first memory bank provider,
Figure FDA0003688262100000034
indicating the memory bank cost of the first memory bank provider.
5. The method for network slicing and computing power resource allocation based on game theory as claimed in claim 4, wherein solving the first revenue function, the second revenue function, the revenue function of the CPU supplier and the revenue function of the memory bank supplier according to game theory comprises:
respectively constructing a game model of the terminal, a game model of the virtual network operator, a game model of the CPU supplier and a game model of the memory bank supplier, wherein the representation form of the game model of the terminal comprises the following steps:
Figure FDA0003688262100000035
the representation of the gaming model of the virtual network operator includes:
Figure FDA0003688262100000036
Figure FDA0003688262100000037
the representation form of the game model of the CPU supplier comprises the following steps:
Figure FDA0003688262100000038
Figure FDA0003688262100000039
the representation form of the game model of the memory bank supplier comprises the following steps:
Figure FDA0003688262100000041
Figure FDA0003688262100000042
and solving a game model of the terminal, a game model of the virtual network operator, a game model of the CPU supplier and a game model of the memory bank supplier to obtain a game theory equilibrium solution.
6. The method for network slicing and force resource allocation based on game theory as claimed in claim 5, wherein the equilibrium solution of the game theory of the game model of the terminal comprises:
Figure FDA0003688262100000043
Figure FDA0003688262100000044
Figure FDA0003688262100000045
the equilibrium solution for the gaming model of the virtual network operator includes:
Figure FDA0003688262100000046
the equilibrium solution of the gaming model of the CPU supplier comprises:
Figure FDA0003688262100000047
the equilibrium solution of the gaming model of the memory bank supplier comprises:
Figure FDA0003688262100000048
wherein, W * Vector, Y, representing the bandwidth composition purchased by various services from the virtual network operator * Vector, Z, of quantities of CPUs purchased from CPU suppliers for various services * A vector, p, representing the number of memory chips purchased by each service from a memory chip provider * Vector, mu, representing the optimal bandwidth unit price component of all virtual network operators * Vector, τ, representing the optimal CPU unit price component of the CPU supplier * A vector representing the best selling unit price component of the memory bank supplier.
7. A network slicing and computing power resource distribution system based on game theory is characterized by comprising:
the parameter obtaining unit is used for obtaining various services corresponding to each terminal and carrying out priority sequencing on the various services of each terminal according to the QoS requirements of the services to obtain a sequencing result; acquiring the required bandwidth amount of the service in the network slice, the spectrum efficiency of occupying the network slice and the bandwidth unit price of each virtual network operator for selling the network slice; acquiring the computing resources required by the service and the unit price of the computing resources for selling the computing resources by each computing resource provider; acquiring the bandwidth amount of the network slice sold to the terminal by each virtual network operator and the cost of the bandwidth amount of the network slice; and obtaining the computing resources sold by each computing resource supplier and the cost of the computing resources;
a revenue function constructing unit, configured to construct a first revenue function of the terminal according to the service, the sorting result, the bandwidth amount required by the service in the network slice, the spectrum efficiency of occupying the network slice, the bandwidth unit price, and the computing power resource unit price required by the service; constructing a second revenue function of the virtual network operator according to the bandwidth unit price, the bandwidth amount of the network slice sold to the terminal by each virtual network operator and the cost of the bandwidth amount of the network slice; constructing a third profit function of the computing resource supplier according to the unit price of the computing resource, the computing resource sold by each computing resource supplier and the cost of the computing resource;
the game theory solving unit is used for solving the first revenue function, the second revenue function and the third revenue function according to game theory to obtain a game theory equilibrium solution, so that the terminal selects the bandwidth amount purchased from the virtual network operator and selects the computing power resource purchased from the computing power resource supplier according to the game theory equilibrium solution, the virtual network operator adjusts the bandwidth unit price according to the game theory equilibrium solution, and the computing power resource supplier adjusts the computing power resource unit price according to the game theory equilibrium solution.
8. An electronic device, comprising: at least one control processor and a memory for communicative connection with the at least one control processor; the memory stores instructions executable by the at least one control processor to enable the at least one control processor to perform a method of game theory based network slicing and computing resource allocation according to any one of claims 1 to 6.
9. A computer-readable storage medium having stored thereon computer-executable instructions for causing a computer to perform a method for gaming theory based network slicing and computing power resource allocation according to any of claims 1 to 6.
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