CN111031344A - Edge video cache excitation optimization method in passive optical network under double-layer game driving - Google Patents

Edge video cache excitation optimization method in passive optical network under double-layer game driving Download PDF

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CN111031344A
CN111031344A CN201911271688.6A CN201911271688A CN111031344A CN 111031344 A CN111031344 A CN 111031344A CN 201911271688 A CN201911271688 A CN 201911271688A CN 111031344 A CN111031344 A CN 111031344A
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optical network
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CN111031344B (en
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李燕
曹杰
张震
刘金良
代仕芳
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Nanjing University of Finance and Economics
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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N21/00—Selective content distribution, e.g. interactive television or video on demand [VOD]
    • H04N21/20—Servers specifically adapted for the distribution of content, e.g. VOD servers; Operations thereof
    • H04N21/23—Processing of content or additional data; Elementary server operations; Server middleware
    • H04N21/231—Content storage operation, e.g. caching movies for short term storage, replicating data over plural servers, prioritizing data for deletion
    • H04N21/23103—Content storage operation, e.g. caching movies for short term storage, replicating data over plural servers, prioritizing data for deletion using load balancing strategies, e.g. by placing or distributing content on different disks, different memories or different servers
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N21/00—Selective content distribution, e.g. interactive television or video on demand [VOD]
    • H04N21/60—Network structure or processes for video distribution between server and client or between remote clients; Control signalling between clients, server and network components; Transmission of management data between server and client, e.g. sending from server to client commands for recording incoming content stream; Communication details between server and client 
    • H04N21/61—Network physical structure; Signal processing
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04Q—SELECTING
    • H04Q11/00—Selecting arrangements for multiplex systems
    • H04Q11/0001—Selecting arrangements for multiplex systems using optical switching
    • H04Q11/0062—Network aspects
    • H04Q11/0067—Provisions for optical access or distribution networks, e.g. Gigabit Ethernet Passive Optical Network (GE-PON), ATM-based Passive Optical Network (A-PON), PON-Ring

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Abstract

The invention discloses an edge video cache excitation optimization method in a passive optical network under double-layer game driving, which comprises three stages: the first stage, a double-layer Stackelberg game model is constructed for a video cache system; in the second stage, the optimal decision of the optical network unit in the double-layer game is given by adopting a recurrence method; and in the third stage, based on the optimal decision of the optical network unit, an iterative method is utilized to reversely solve the optimal strategy of the video provider. Based on the invention, the video data can be buffered in the storage space provided by the optical network unit, thereby effectively improving the video service quality and the video service benefit in the passive optical network supporting the edge buffer.

Description

Edge video cache excitation optimization method in passive optical network under double-layer game driving
Technical Field
The invention belongs to the field of optical fiber access networks, and particularly relates to an edge video cache excitation optimization method in a passive optical network.
Background
With the increasing of mobile data traffic, passive optical networks with high speed and stable bandwidth are widely researched and used as a back end for constructing a mobile access sub-network to support broadband services in the mobile access sub-network more efficiently. However, transmitting increasingly high bandwidth demands and delay sensitive mobile video data over passive optical networks still faces significant challenges. Considering that video data is conventionally stored on a server in the core network, in order to satisfy a video request generated by a mobile terminal user, a video provider first needs to send the video data requested by the user to an optical line terminal where the passive optical network is connected to the core network, and then forwards the video data to the final user through an optical network unit to which the video requester is attached. Such a transmission (as indicated by the black dashed arrow in fig. 1) not only results in a high video transmission delay, but also results in excessive consumption of network bandwidth and energy.
Edge caching, a video caching technique that utilizes network edge storage to speed up content retrieval, has become an ideal solution to reduce core bandwidth pressure. In current practical deployment, the most common method for passive optical network to implement edge caching is to deploy storage facilities on the optical network units, and these storage facilities are generally managed by a unified network operator. In such passive optical networks supporting edge caching, video providers want to meet the video demands of users by caching the video on optical network units near the mobile terminals, thereby improving video quality of service while conserving network bandwidth and energy consumption (as indicated by the solid black arrows in fig. 1). In practice, however, the optical network unit generally does not actively provide a storage space for buffering the video, because additional cost consumption is inevitably caused by the storage space, and therefore, a video provider needs to design a specific incentive mechanism for the optical network unit to make a profit in providing the buffer space for the optical network unit, so that the optical network unit actively contributes the storage space for buffering the video.
When designing an edge video caching incentive mechanism, since both a video provider and an optical network unit inherently want to obtain higher benefits, there is a competitive relationship between the two, and meanwhile, since storage devices of the optical network unit are generally managed by a unified network operator, the optical network units need to cooperate with each other to maximize the overall benefits. Therefore, the design of the incentive mechanism needs to comprehensively consider the competition relationship between the video provider and the optical network units and the cooperation relationship between the optical network units, so that the optical network units actively and reasonably provide the storage space for caching the video.
Disclosure of Invention
In order to solve the technical problems mentioned in the background art, the invention provides an edge video cache excitation optimization method in a passive optical network under double-layer game driving, so that video data is cached in a storage space provided by an optical network unit, and the video service quality and the video service benefit in the passive optical network supporting edge cache are effectively improved.
In order to achieve the technical purpose, the technical scheme of the invention is as follows:
the method for optimizing the edge video cache excitation in the passive optical network under the double-layer game drive comprises three stages: the method comprises the following steps that in the first stage, a double-layer Stackelberg game model of a competition relationship between a video provider and optical network units and a cooperation relationship between the optical network units is established for a video cache system; and in the second stage, the optimal decision of the optical network unit in the double-layer game is given by adopting a recurrence method: firstly, the first layer in the double-layer game is supposed to be finished and the unit cache space price paid to the optical network unit by the video provider is determined, and then on the basis, the optical network unit determines the optimal video cache space providing scheme of each optical network unit in mutual cooperation; and in the third stage, based on the optimal decision of the optical network unit, an iterative method is utilized to reversely solve the optimal strategy of the video provider, namely the video cache space pricing of the net profit can be maximized.
Further, in the first stage, consider a video buffering system consisting of a video provider and a passive optical network supporting edge buffering, assuming that a total of N optical network units in the passive optical network can be used for buffering video, wherein each optical network unit ONUiMaximum video memory that can be providedStorage capacity of SiBy xiIndicating an ONUiThe actually provided video cache space size is that i is more than or equal to 1 and less than or equal to N and Si＞0，0≤xi≤Si(ii) a Providing total buffer space in optical network unit
Figure BDA0002314376580000031
The profit obtained by the video provider is defined as RCPDefining the price of the unit buffer space paid by the video provider to the optical network unit for obtaining the profit as PCPPublishing P at video providerCPThen, each optical network unit determines the net profit U obtained by providing the cache space for the video provider according to the self conditioni(ii) a On the basis, the video provider is regarded as a leader, the optical network unit is regarded as a follower, and a double-layer Stackelberg game model describing the competition relationship between the video provider and the optical network unit and the cooperation relationship between the optical network units in the edge video cache excitation mechanism is further obtained.
Further characterized by revenue R obtained by the video providerCPThe definition is as follows:
RCP＝Aln(1+X)
in the above formula, the parameter A > 0 determines RCPThe rate of increase of;
unit video buffer space price P paid by video provider to optical network unitCPThe definition is as follows:
Figure BDA0002314376580000032
in the above equation, the variable ψ represents the basic unit video buffer space price decided by the video provider;
benefits U of video providerCPThe definition is as follows:
UCP＝RCP-XPCP
optical network unit ONUiNet earnings U due to providing buffer space to video providersiThe definition is as follows:
Ui＝xiPCP-xici
in the above formula, ciIndicating an ONUiOverhead per unit paid for providing video buffer space, ci＞0,1≤i≤N。
Further, in the constructed two-tier Stackelberg game model, in the first tier, the video provider decides the psi value to maximize its own profit, and thus the video provider's best decision psi*：
Figure BDA0002314376580000041
In the second layer, the interaction between the optical network units is described by a cooperative sub-game in which all the optical network units cooperatively determine the size of the video buffer space provided by each optical network unit to maximize the overall efficiency of the optical network units, and this optimization problem is described as follows:
Figure BDA0002314376580000042
in the above formula, Ui(xiψ) represents xiCorresponding U under psi decisioniThe value is obtained.
Further, in the second phase, it is first assumed that the video provider has determined RCPAnd issues P to optical network unitCPAnd then analyzing the cooperative sub game on the basis to obtain an optimal video cache space providing scheme of each optical network unit, wherein in the cooperative sub game, based on the decision of a video provider, the optical network units determine respective video cache space providing decisions of the optical network units by taking the maximized overall benefit as the target, and the process is defined as solving the following optimization problem:
Figure BDA0002314376580000043
constraint conditions are as follows:
Figure BDA0002314376580000044
Figure BDA0002314376580000045
further, the optimization problem is divided into two sub-problems: (a) problem of minimum buffer cost, i.e. at SiUnder the limitation of (2), how to provide a video cache space with the size of X for a video provider by using the minimum total overhead of the optical network unit; (b) the optimal cache space problem, namely how to determine the optimal X value so as to maximize the overall benefit of the optical network unit;
first, consider the minimum cache cost problem, which is expressed as follows:
Figure BDA0002314376580000046
constraint conditions are as follows:
Figure BDA0002314376580000051
Figure BDA0002314376580000052
aiming at the problem, a sequencing iterative method is provided for solving, firstly, N optical network units are subjected to non-decreasing sequencing according to unit overhead paid when the optical network units provide video cache space and are used
Figure BDA0002314376580000053
Representing the ordered set of optical network units, j being greater than or equal to 11,j2,...,jNIs less than or equal to N, and
Figure BDA0002314376580000054
then, obtaining the optimal solution of the problem of the minimum cache cost through the iteration of at most N times, wherein in the ith iteration, i is more than or equal to 1 and less than or equal to N, if the iteration value X of the ith time is XiIf it is greater than zero, then order
Figure BDA0002314376580000055
And update
Figure BDA0002314376580000056
Otherwise, the iteration is ended; based on the ordering iteration method, the optical network unit provides the video provider with the minimum total cost mc (X) paid by the video cache space with the size of X as follows:
Figure BDA0002314376580000057
according to the above formula, an optimal cache space problem is defined:
Figure BDA0002314376580000058
constraint conditions are as follows:
Figure BDA0002314376580000059
in the above formula, USU(X) is a piecewise function comprising N segments with respect to X;
then the optimal solution X to the optimal cache space problem*：
Figure BDA00023143765800000510
In the above formula, the first and second carbon atoms are,
Figure BDA00023143765800000511
and q isi≥qi+1，
Figure BDA00023143765800000512
Further, based on the solution of the minimum cache cost problem and the optimal cache space problem, firstly, according to the optimal solution X of the optimal cache space problem*Calculating video cache space provided by optical network unit to video provider by formulaAnd then obtaining an optimal video cache space providing scheme of each optical network unit according to a sequencing iteration method provided for solving the problem of minimum cache cost.
Further, in the third stage, a basic value is first set for psi, and then the decision of the ONU is obtained according to the second stage and the benefit U of the video provider is calculated according to the decisionCPIn each iteration psi is set a small increment delta, i.e. psi + delta, and as psi increases, the benefit U of the video provider is increased because the onu will contribute more video buffer space under larger excitationCPFirst of all, it will increase, but then the benefit U of the video provider will exceed the benefit it receives because the incentive costs it paysCPWill be lowered accordingly, so that when U is loweredCPThe iteration is stopped when the decrease is started, and ψ is the optimal decision of the video provider.
Adopt the beneficial effect that above-mentioned technical scheme brought:
the invention plans the competition relationship between the video provider and the optical network units and the cooperation relationship between the optical network units into a double-layer Stackelberg game model, and obtains the optimal decision of the video provider and each optical network unit through model analysis, so that the optical network units actively provide a storage space for caching videos after obtaining a certain return, and the video provider realizes edge video caching on the basis of the storage space provided by the optical network units and benefits the video provider.
Compared with the existing video cache excitation work based on the game theory, the invention fully exploits the structural characteristics of the passive optical network supporting the edge cache and takes the two types of interaction relations appearing when the video cache excitation method is designed into consideration, namely the competition relation between a video provider and an optical network unit and the cooperation relation between the optical network units, and further designs the edge video cache excitation mechanism in the passive optical network for maximizing the net income of the video provider and the whole net income of the optical network unit on the basis of constructing a double-layer Stackelberg game model, and the mechanism can greatly promote the improvement of the video service quality and the improvement of the video service benefit in the passive optical network under the edge cache environment.
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Fig. 1 is a schematic diagram of a mobile video streaming approach in a passive optical network;
FIG. 2 is a flow chart of three phases of the present invention;
FIG. 3 is a graph of the effectiveness of a video provider as a function of its determined base unit cache space price ψ in the present invention;
fig. 4 is a comparison chart of the overall benefits of the onu obtained by the cooperative onu-based excitation mechanism and the competitive onu-based excitation mechanism proposed in the present invention.
Detailed Description
The technical scheme of the invention is explained in detail in the following with the accompanying drawings.
The invention designs an edge video cache excitation optimization method in a passive optical network under the drive of a double-layer game, and an excitation mechanism describes a competition relationship between a video provider and an optical network unit and a cooperation relationship between the optical network units by establishing a double-layer Stackelberg game model and analyzes interaction between the video provider and the optical network unit by adopting a recursion method so as to obtain an optimal return strategy of the video provider and an optimal video cache space supply decision of the optical network unit. As shown in fig. 2, the method is divided into three implementation stages, namely a first stage of constructing a double-layer Stackelberg game model; and obtaining a second stage of optimal decision of each optical network unit in the constructed double-layer Stackelberg game and a third stage of reverse reasoning of the optimal strategy of the video provider in the first-layer game on the basis of the second stage by utilizing a recurrence method. The specific process is as follows:
in the first stage, it is assumed that a total of N optical network units in the passive optical network are available for buffering video, wherein each optical network unit ONUi(1 is more than or equal to i is less than or equal to N) can provide the maximum video storage capacity Si(Si> 0) with xi(0≤xi≤Si) Indicating an ONUiThe size of the video buffer space actually provided. Then, the total amount of video buffer space contributed to the system by all the optical network units is defined as X, where
Figure BDA0002314376580000071
Obviously, the video provider can obtain the profit when X > 0, and the larger the value of X, the higher the profit the video provider obtains, but the marginal profit of the video provider will decrease instead as the value of X increases. Thus, the profit R of the video providerCPDefined as a function of the total amount of video buffer space X provided by the onu as follows:
RCP＝Aln(1+X) (1)
wherein the parameter A > 0 determines RCPThe rate of increase of. It can be seen that RCPIs an increasing concave function of X and reaches a maximum as X approaches infinity. Of course, the revenue of the video provider is obtained by paying a certain return to encourage the optical network unit to actively provide the video buffer space, so the price P of the unit video buffer space paid by the video provider to the optical network unitCPThe definition is as follows:
Figure BDA0002314376580000081
wherein the variable ψ represents the basic unit video buffer space price decided by the video provider. As can be seen from equation (2), the video provider is due to ONUi(1 ≦ i ≦ N) providing video cache space and paying a total of xiPCP. Therefore, the benefit U of the video providerCPI.e. the net gain, can be expressed as:
UCP＝RCP-XPCP(3)
while for each ONU it may be rewarded for providing video buffer space to the video provider, they need to pay additional overhead for such provision of video buffer space at the same time, and hence the ONUi(1 ≦ i ≦ N) benefit U obtained from providing video buffer spaceiI.e. the net gain, can be expressed as:
Ui＝xiPCP-xici(4)
wherein, ci(ciI is more than 0 and more than or equal to 1 and less than or equal to N) represents ONUiThe unit overhead due to providing video buffer space.
Based on the definition of the benefits of the video provider and the optical network units, in the edge video caching system, the video provider is regarded as a leader, and the N optical network units are regarded as followers, so that the following double-layer Stackelberg game model is obtained:
the participants: a video provider and N optical network units;
strategy: the video provider first issues its reward scheme and then determines its specific policy, i.e. the value of ψ; the optical network unit further gives a specific video cache space providing decision according to the policy of the video provider, namely { x }i}1≤i≤N；
The benefits are as follows: the benefit of the video provider is UCPEach optical network unit ONUi(1. ltoreq. i. ltoreq.N) has the benefit of Ui。
In the defined stackable game, the video provider decides the value of ψ in the first layer to maximize its own profit, so the video provider's best decision is:
Figure BDA0002314376580000091
in the second layer, the interaction between the optical network units can be described by a cooperative sub-game in which all the optical network units cooperatively determine the size of the video buffer space provided by each optical network unit to maximize the overall efficiency of the optical network units, and this optimization problem can be described as follows:
Figure BDA0002314376580000092
and in the second stage, the optimal decision of each optical network unit in the constructed double-layer Stackelberg game is obtained by using a recurrence method. First assume that the video provider has determined RCPAnd issues P to optical network unitCPThen at this baseAnd analyzing the cooperative sub game on the basis to obtain the optimal video cache space providing strategy of each optical network unit. The specific process is as follows:
in cooperative sub-gaming, the optical network units determine their respective video cache space providing decisions with the goal of maximizing overall efficiency based on the video provider's decisions, so this process can be reduced to solve the following optimization problem:
Figure BDA0002314376580000093
the constraint conditions are as follows:
Figure BDA0002314376580000094
Figure BDA0002314376580000095
as can be seen from equation (7), the overall benefit of the onu is equal to the total profit obtained by all onus minus the total cost paid by all onus, so if the total amount of video buffer space provided by onus, i.e. X, can be optimally determined, the problem is transformed into the size X of the video buffer space specifically contributed by each onu with the goal of minimizing the total cost paid by onusi(i is more than or equal to 1 and less than or equal to N). Accordingly, the optimization objective in equation (7) can be rewritten as:
Figure BDA0002314376580000101
in view of this, the optimization problem constructed for determining the optimal video buffer space providing strategy of each onu can be divided into two sub-problems: (a) problem of minimum buffer cost, i.e. at SiUnder the limitation that i is more than or equal to 1 and less than or equal to N, how to provide a video cache space with the size of X for a video provider by using the minimum total overhead of the optical network unit; (b) optimal buffer space problem, i.e. how to determine the optimal X value and thus maximize lightThe overall efficiency of the network element.
First, consider the minimum cache cost problem, which can be expressed as:
Figure BDA0002314376580000102
with the proviso that formula (8) and formula (9) are given. Aiming at the problem, a sequencing iteration method is provided for solving the problem. Specifically, N optical network units are firstly sorted in a non-decreasing order according to unit overhead paid when the optical network units provide video cache space and used
Figure BDA0002314376580000103
Represents a sorted set of optical network units, here
Figure BDA0002314376580000104
Then, the optimal solution of the problem of the minimum cache cost is obtained through the maximum N times of iteration, wherein in the ith (i is more than or equal to 1 and less than or equal to N) time of iteration, if X isi(its initial value equals X) is greater than zero, then order
Figure BDA0002314376580000105
And update
Figure BDA0002314376580000106
Otherwise, the iteration is ended. Based on the ordering iteration method, the minimum total cost paid by the onu to provide the video provider with the video cache space of size X can be expressed as a function of X as follows:
Figure BDA0002314376580000107
from the conclusions given by equation (12), the optimal cache space problem can be defined as follows:
Figure BDA0002314376580000108
the constraint conditions are as follows:
Figure BDA0002314376580000109
u as defined aboveSU(X) is a piecewise function including N segments with respect to X, wherein the ith (1 ≦ i ≦ N) segment is labeled
Figure BDA0002314376580000111
The left and right endpoints are respectively
Figure BDA0002314376580000112
And
Figure BDA0002314376580000113
here, the
Figure BDA0002314376580000114
The lower limit of X is shown. It is clear that,
Figure BDA0002314376580000115
is a continuously derivable function, so that its first derivative is equal to 0, i.e. it is
Figure BDA0002314376580000116
Can obtain the product
Figure BDA0002314376580000117
In view of
Figure BDA0002314376580000118
That is to say
Figure BDA0002314376580000119
Is a concave function, so that it can be further obtained
Figure BDA00023143765800001110
The maximum points of (a) are:
Figure BDA00023143765800001111
based on this, let
Figure BDA00023143765800001112
Knowing qiIs USUThe stagnation point of (X) is only q is more than or equal to 0i≤d1(i ═ 1) or di-1＜qi≤di(1 < i.ltoreq.N), where qi≥qi+1Because of the fact that
Figure BDA00023143765800001113
In practice, if q is presentlIs USU(X) stagnation point, then all qh(1 is not equal to h not equal to l is not equal to N) is not USU(X) stagnation point, because:
Figure BDA00023143765800001114
this indicates USU(X) at most one stagnation point. In view of this, the optimal solution of the optimal cache space problem can be discussed and obtained in two cases, marked as X*. The first case is USU(X) has a stagnation point, assumed to be qlIn this case, any one can be found from the formula (15)
Figure BDA00023143765800001115
The maximum points of (a) are:
Figure BDA00023143765800001116
while taking into account USU(X) is a continuous function, and further, U is known from the formula (17)SU(X) the maximum point of (X) is X*＝ql. The second case is USU(X) has no stagnation point, which indicates that q is1< 0 or q1＞d1. If q is1If < 0, then there is qi≤q1< 0(1 < i.ltoreq.N), and in this case, any value can be found from the formula (15)
Figure BDA00023143765800001117
Is Xi *＝di-1Considering USU(X) is a continuous function of the number of pixels,further derive USU(X) the maximum point of (X) is X*＝d00; if q is1＞d1I is not more than 1*＝max{i|qi＞diI is more than or equal to 1 and less than or equal to N, and q isi＞di(1≤i≤i*) And q isi≤di-1(i*i.ltoreq.N), in which case the formula (15) can be arbitrarily set
Figure BDA00023143765800001118
The maximum points of (a) are:
Figure BDA0002314376580000121
while taking into account USU(X) is a continuous function, further yielding USUThe maximum value point of (X) is
Figure BDA0002314376580000122
In summary, USUThe maximum point of (X), i.e. the optimal solution to the optimal cache space problem, can be expressed as follows:
Figure BDA0002314376580000123
based on the solution of the minimum cache cost problem and the optimal cache space problem, the total amount of the video cache space provided by the optical network unit to the video provider can be calculated according to the formula (19), and then a decision is provided for obtaining the optimal video cache space of each optical network unit according to a sequencing iteration method provided for solving the minimum cache cost problem.
In the third stage, according to the second stage, given the decision psi of the video provider, the optimal video cache space providing decision of the optical network unit can be obtained always so as to maximize the overall benefit of the optical network unit, therefore, the dual-layer Stackelberg game constructed by the invention has Stackelberg balance, that is, if psi is used*Represents the optimal decision made by the video provider at the first layer, and
Figure BDA0002314376580000124
the optimal decision made by the optical network unit in the second layer cooperation sub game is represented, and then:
Figure BDA0002314376580000125
wherein
Figure BDA0002314376580000126
Although it is difficult to obtain a solution in the form of a closed decision optimal for the video provider, psi can still be obtained by an iterative method*. Specifically, a base value is set for psi, and the decision of the ONU is obtained according to the method set forth in the second stage, and U is calculated based on the decisionCPIn each iteration psi is set to a small increment, i.e. psi + δ, and as psi increases, the benefit of the video provider increases first because the onu will contribute more video buffer space under greater excitation, but then decreases because the excitation overhead it pays will exceed the gain it receives, so when U is going to do soCPThe iteration is stopped when the decrease is started, and ψ is the optimal decision of the video provider.
Fig. 3 is a graph showing the variation of the benefit of the video provider in the incentive scheme according to the present invention, as a function of the price ψ of the basic unit video buffer space determined by the video provider. It can be clearly seen from the figure that the benefit of the video provider increases with the increase of the psi value, then decreases with the increase of the psi value and reaches the maximum value when the psi value is 0.3, which proves that the constructed dual-layer Stackelberg game has game equilibrium points and can be approximated by an iterative method.
Fig. 4 is a comparison diagram of the overall benefits of the optical network units obtained by the incentive mechanism based on the cooperative optical network units and the incentive mechanism based on the competing optical network units, in the incentive mechanism based on the competing optical network units, each optical network unit competitively provides a video buffer space to maximize the respective benefits. In fig. 4, although the overall benefits of the optical network unit obtained by the two excitation mechanisms are both reduced with the increase of the overhead of the optical network unit providing the video buffer space, the excitation mechanism provided by the present invention is always significantly better than the excitation mechanism based on the competing optical network units, so as to obtain greater overall benefits of the optical network unit.
The video cache space providing incentive mechanism provided by the invention plans the competition relationship between the video provider and the optical network units and the cooperation relationship between the optical network units into a double-layer Stackelberg game model, and provides the optimal return strategy of the video provider and the optimal video cache space providing decision of the optical network units under the model by using a recursion method. This will have a positive push to effectively provide high quality video services to subscribers in passive optical networks that support edge caching.
The embodiments are only for illustrating the technical idea of the present invention, and the technical idea of the present invention is not limited thereto, and any modifications made on the basis of the technical scheme according to the technical idea of the present invention fall within the scope of the present invention.

Claims (8)

1. The method for optimizing the edge video cache excitation in the passive optical network under the drive of the double-layer game is characterized by comprising three stages: the method comprises the following steps that in the first stage, a double-layer Stackelberg game model of a competition relationship between a video provider and optical network units and a cooperation relationship between the optical network units is established for a video cache system; and in the second stage, the optimal decision of the optical network unit in the double-layer game is given by adopting a recurrence method: firstly, the first layer in the double-layer game is supposed to be finished and the unit cache space price paid to the optical network unit by the video provider is determined, and then on the basis, the optical network unit determines the optimal video cache space providing scheme of each optical network unit in mutual cooperation; and in the third stage, based on the optimal decision of the optical network unit, an iterative method is utilized to reversely solve the optimal strategy of the video provider, namely the video cache space pricing of the net profit can be maximized.
2. The passive optical network edge vision under the double-layer game driving of claim 1A frequency buffer excitation optimization method is characterized in that in the first stage, a video buffer system composed of a video provider and a passive optical network supporting edge buffer is considered, and N optical network units are assumed to be used for buffering video in the passive optical network, wherein each optical network unit ONU can be used for buffering videoiThe maximum video storage capacity provided is SiBy xiIndicating an ONUiThe actually provided video cache space size is that i is more than or equal to 1 and less than or equal to N and Si＞0，0≤xi≤Si(ii) a Providing total buffer space in optical network unit
Figure FDA0002314376570000011
The profit obtained by the video provider is defined as RCPDefining the price of the unit buffer space paid by the video provider to the optical network unit for obtaining the profit as PCPPublishing P at video providerCPThen, each optical network unit determines the net profit U obtained by providing the cache space for the video provider according to the self conditioni(ii) a On the basis, the video provider is regarded as a leader, the optical network unit is regarded as a follower, and a double-layer Stackelberg game model describing the competition relationship between the video provider and the optical network unit and the cooperation relationship between the optical network units in the edge video cache excitation mechanism is further obtained.
3. The method for optimizing the caching incentive of the edge video in the passive optical network under the driving of the double-layer game as claimed in claim 2, wherein the profit R obtained by the video providerCPThe definition is as follows:
RCP＝Aln(1+X)
in the above formula, the parameter A > 0 determines RCPThe rate of increase of;
unit video buffer space price P paid by video provider to optical network unitCPThe definition is as follows:
Figure FDA0002314376570000021
in the above equation, the variable ψ represents the basic unit video buffer space price decided by the video provider;
benefits U of video providerCPThe definition is as follows:
UCP＝RCP-XPCP
optical network unit ONUiNet earnings U due to providing buffer space to video providersiThe definition is as follows:
Ui＝xiPCP-xici
in the above formula, ciIndicating an ONUiOverhead per unit paid for providing video buffer space, ci＞0,1≤i≤N。
4. The method for optimizing edge video cache excitation in the passive optical network under the dual-layer game drive of claim 3, wherein in the constructed dual-layer Stackelberg game model, in the first layer, a video provider decides psi value to maximize its own benefit, so that the optimal decision psi of the video provider*：
Figure FDA0002314376570000022
In the second layer, the interaction between the optical network units is described by a cooperative sub-game in which all the optical network units cooperatively determine the size of the video buffer space provided by each optical network unit to maximize the overall efficiency of the optical network units, and this optimization problem is described as follows:
Figure FDA0002314376570000023
in the above formula, Ui(xiψ) represents xiCorresponding U under psi decisioniThe value is obtained.
5. The dual-deck gaming drive of claim 4Edge video cache incentive optimization method in passive optical network, characterized in that in the second phase, it is first assumed that the video provider has determined RCPAnd issues P to optical network unitCPAnd then analyzing the cooperative sub game on the basis to obtain an optimal video cache space providing scheme of each optical network unit, wherein in the cooperative sub game, based on the decision of a video provider, the optical network units determine respective video cache space providing decisions of the optical network units by taking the maximized overall benefit as the target, and the process is defined as solving the following optimization problem:
Figure FDA0002314376570000031
constraint conditions are as follows:
0≤xi≤Si,
Figure FDA0002314376570000032
Figure FDA0002314376570000033
6. the method for optimizing edge video cache excitation in a passive optical network under the double-layer game driving according to claim 5, wherein the optimization problem in claim 5 is divided into two sub-problems: (a) problem of minimum buffer cost, i.e. at SiUnder the limitation of (2), how to provide a video cache space with the size of X for a video provider by using the minimum total overhead of the optical network unit; (b) the optimal cache space problem, namely how to determine the optimal X value so as to maximize the overall benefit of the optical network unit;
first, consider the minimum cache cost problem, which is expressed as follows:
Figure FDA0002314376570000034
constraint conditions are as follows:
0≤xi≤Si,
Figure FDA0002314376570000035
Figure FDA0002314376570000036
aiming at the problem, a sequencing iterative method is provided for solving, firstly, N optical network units are subjected to non-decreasing sequencing according to unit overhead paid when the optical network units provide video cache space and are used
Figure FDA0002314376570000037
Representing the ordered set of optical network units, j being greater than or equal to 11,j2,...,jNIs less than or equal to N, and
Figure FDA0002314376570000038
then, obtaining the optimal solution of the problem of the minimum cache cost through the iteration of at most N times, wherein in the ith iteration, i is more than or equal to 1 and less than or equal to N, if the iteration value X of the ith time is XiIf it is greater than zero, then order
Figure FDA0002314376570000039
And update
Figure FDA00023143765700000310
Otherwise, the iteration is ended; based on the ordering iteration method, the optical network unit provides the video provider with the minimum total cost mc (X) paid by the video cache space with the size of X as follows:
Figure FDA0002314376570000041
according to the above formula, an optimal cache space problem is defined:
Figure FDA0002314376570000042
constraint conditions are as follows:
Figure FDA0002314376570000043
in the above formula, USU(X) is a piecewise function comprising N segments with respect to X;
then the optimal solution X to the optimal cache space problem*：
Figure FDA0002314376570000044
In the above formula, the first and second carbon atoms are,
Figure FDA0002314376570000045
and q isi≥qi+1，
Figure FDA0002314376570000046
7. The method for optimizing the excitation of the edge video cache in the passive optical network under the double-layer game drive according to claim 6, wherein based on the solution of the minimum cache cost problem and the optimal cache space problem, the optimal solution X of the optimal cache space problem is first solved*And calculating the total amount of video cache space provided by the optical network unit to a video provider by using a formula, and then obtaining an optimal video cache space providing scheme of each optical network unit according to a sequencing iteration method provided for solving the problem of minimum cache cost.
8. The method for optimizing edge video cache excitation in the passive optical network under the dual-layer game drive according to claim 4, wherein psi is obtained by an iterative method in the third stage*(ii) a Firstly setting a basic value for psi, then obtaining the decision of the optical network unit according to the second stage and calculating the benefit U of the video provider according to the decisionCPIn each iteration psi is set a small increment delta, i.e. psi + delta, since the optical network unit increasesMore video buffer space can be contributed under larger excitation, and the benefit U of the video providerCPFirst of all, it will increase, but then the benefit U of the video provider will exceed the benefit it receives because the incentive costs it paysCPWill be lowered accordingly, so that when U is loweredCPThe iteration is stopped when the decrease is started, and ψ is the optimal decision of the video provider.
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