Satellite network two-stage cross-layer bandwidth allocation method based on game model

Abstract

The invention provides a satellite network two-stage cross-layer bandwidth allocation method based on a game model, and relates to the technical field of satellite system resource allocation. The method relates to a plurality of access nodes, a plurality of sink nodes and a virtual intermediary, the sink nodes are one party with time slots, each sink node transmits a bandwidth allocation parameter to the virtual intermediary, the virtual intermediary feeds back a time slot performance value to the sink node, and the time slot of which sink node is preferentially allocated is obtained; and the access node is one party applying for the time slot, and the virtual intermediary obtains the number of time slots allocated to each service of the access node according to bandwidth allocation parameters in each access node. According to the method, the multi-node, multi-type and self-similarity characteristics of network services are fully considered, the calculation complexity is low, the method is suitable for efficient resource management of the multi-node and multi-type services in the satellite network, the overall system utility value can be improved while the requirements of different priority nodes and services can be met, and then the bandwidth utilization rate of the satellite network is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of satellite system resource allocation, and in particular to a two-level cross-layer bandwidth allocation method for a satellite network based on a game model. Background Art

[0002] Satellite networks are widely used in the field of modern communications and technology. With their wide coverage and large communication capacity, they can break through geographical restrictions with the help of intersatellite networking and provide global users with high-speed, low-latency network access services. They have become an important part of the integrated space-ground network. However, due to the limited onboard processing capacity of satellite communication systems and the scarcity of bandwidth resources, large delays will occur when the traffic volume is large, resulting in users being unable to obtain satisfactory service quality. Therefore, in order to solve this problem, it is of great research value to seek more effective bandwidth allocation to maximize and reasonably use limited bandwidth resources.

[0003] The services included in the satellite network usually have multi-node, multi-type and self-similar characteristics. Multi-node means that there are multiple aggregation nodes with bandwidth resources and multiple access nodes with different types of services in the satellite network. Based on the bandwidth resources of the aggregation node, the system performs differentiated and reasonable bandwidth allocation for different services in different access nodes. Different types of services have different bandwidth requirements. In the process of bandwidth allocation, it is necessary to consider the priority of different types of services and meet the dynamic changes of data traffic of different services. The data traffic in the satellite network presents similar fluctuation patterns on different time scales. This self-similarity is represented by the Hurst index. The larger the Hurst index value, the greater the correlation and stronger the mutation of the business flow, and more bandwidth is required to ensure the stable transmission of the business. Due to the limited on-board processing capacity of the satellite communication system and the scarce bandwidth resources, there will be a large delay when the business volume is large, resulting in users unable to obtain satisfactory service quality. In order to solve this problem, it is very valuable to seek more effective bandwidth allocation to maximize and reasonably use limited bandwidth resources.

[0004] At present, most of the research on satellite network bandwidth allocation is based on a single node and a single type of business flow, which cannot meet the multi-node, multi-type and self-similar business characteristics in satellite networks. In view of the multi-node, multi-type and self-similar characteristics of services in satellite networks, it is an urgent problem to reasonably allocate the limited bandwidth resources in the aggregation node to effectively transmit the services of each access node and improve the utilization rate of bandwidth resources.

[0005] Regarding the allocation of bandwidth resources in satellite networks, domestic and foreign researchers have proposed some models and algorithms, including: static bandwidth allocation strategy, dynamic bandwidth allocation strategy, bandwidth allocation strategy based on neural network, and bandwidth allocation strategy based on economic principles.

[0006] Chen Donghao proposed a static bandwidth compensation strategy in the article "Static Compensation Bandwidth Allocation Scheduling Algorithm for Passive High-Frequency Voltage Meters [J]. Journal of Chifeng University (Natural Science Edition) 2019, 35(06): 39-42." Bandwidth can be allocated in order of priority, but this allocation algorithm lacks certain fairness. N. Blefari-Melazzi, M. Susanto, etc. proposed a dynamic resource allocation algorithm (Dynamic Resource Allocation Algorithm, DRAA), which can dynamically change the resource allocation of each connection. It has obvious advantages in resource utilization and can well solve the shortcomings of static allocation. However, it does not fully consider the multi-feature nature of services in satellite networks. F. Chit et al. used statistical modeling to predict the bandwidth demand of future services for allocation, but this strategy is unstable in the face of rapidly changing network environments. In recent years, some scholars have proposed a bandwidth allocation strategy based on neural networks. By searching and optimizing the objective function, neural networks are used to maximize the efficiency of allocation, but the computational complexity is high. Although the bandwidth allocation strategy based on deep learning has strong learning ability, it requires a large amount of data processing and takes a long time to process. Therefore, some scholars have proposed bandwidth allocation strategies based on economic principles. For example, D. Niyato et al. proposed to transform the bandwidth allocation problem into a Cournot game model in economics in the paper "Competitive spectrum sharing in cognitive radio networks: a dynamic game approach [J]. IEEE transactions on wireless communications, 2008, 7 (7): p. 2651-2660." In this model, each service competes with each other according to its own utility function, and finally reaches a Nash equilibrium. Each service is allocated the best bandwidth, but the difference between the services is only reflected in the signal-to-noise ratio, which lacks rationality; Q. Xu et al. proposed to transform the bandwidth allocation problem into a Stan-Kohlberg game model to simulate the dynamic interaction between services in the paper "Game Theoretical Secure Bandwidth Allocation in UAV-assisted Heterogeneous Networks" ICC 2021-IEEE International Conference on Communications, Montreal, QC, Canada, 2021, pp. 1-5." to simulate the dynamic interaction between services. Although the utility function of the service is further introduced, the multi-type characteristics of the service are not fully considered.

[0007] The above bandwidth allocation strategies can adapt to the network status and improve bandwidth utilization, but they do not fully consider the multi-node, multi-type and self-similar characteristics of services in satellite networks. Summary of the invention

[0008] The technical problem to be solved by the present invention is to provide a two-level cross-layer bandwidth allocation method for satellite networks based on a game model in view of the deficiencies of the above-mentioned prior art, so as to realize reasonable bandwidth allocation for multi-node, multi-type and self-similar services in satellite networks.

[0009] In order to solve the above technical problems, the technical solution adopted by the present invention is as follows: the present invention provides a two-level cross-layer bandwidth allocation method for a satellite network based on a game model, involving multiple access nodes, multiple aggregation nodes and a virtual intermediary, the aggregation node is the party that owns the time slot, each aggregation node transmits the bandwidth allocation parameter to the virtual intermediary, the virtual intermediary feeds back the time slot performance value to the aggregation node based on the Bertrand game model, and obtains which aggregation node's time slot is preferentially allocated; the access node is the party that applies for the time slot, and the virtual intermediary obtains the number of time slots allocated for each service of the access node based on the bandwidth allocation parameter in each access node based on the Cournot game model;

[0010] The specific steps include:

[0011] Step 1: Multiple access nodes of the satellite network apply for bandwidth from the aggregation node, i.e., in the time slot, multiple aggregation nodes pass their respective bandwidth allocation parameters to the virtual intermediary;

[0012] Step 2: The virtual intermediary constructs a Bertrand game model with the sink nodes as participants and the time slot performance value as the game strategy. The sink node with the highest time slot performance value is selected as the sink node for priority allocation of primary bandwidth, and its time slot is allocated preferentially.

[0013] Step 2.1: The virtual intermediary receives the bandwidth allocation parameters of each sink node and sets the congestion level m of the time slot of sink node i to i As a transport layer parameter, the number of time slots owned by sink node i is W i , the service rate B required for the time slot owned by the aggregation node i to establish a connection with the service of the access node i req , the signal-to-noise ratio snr of the sink node i i and the delay t of the time slot of sink node i i As a physical layer parameter, the time slot evaluation feedback value of sink node i is set to 1;

[0014] Step 2.2: Establish a connection with the access node based on the time slot owned by the aggregation node i and the service rate B required i req , the number of time slots owned by sink node i is W i, calculate the time slot utilization f of the sink node i , as shown in the following formula (1):

[0015]

[0016] Step 2.3: Combine the transport layer parameters and the physical layer parameters to establish the bandwidth allocation cross-layer utility function H(p) of the aggregation node, as shown in the following formula (2):

[0017]

[0018] Among them, p i is the time slot price of sink node i, N is the total number of sink nodes, d i is the time slot requirement of the access node to the sink node i, C(d i ) is the cost function of the sink node, as shown in the following formula (3):

[0019] C(d i )=B i req -f i (W i -d i ) (3)

[0020] The time slot requirement d of the access node to the sink node i i According to the time slot utilization f of sink node i i , congestion level m i Calculate as shown in the following formula (4):

[0021]

[0022] Among them, p i′ is the time slot price of sink node i′, f i′ is the time slot utilization rate of sink node i′, m i′ is the congestion level of the time slot of the sink node i′, η∈(0,1] represents the preference of the access node for the time slot of the sink node;

[0023] Step 2.4: Based on the Bertrand game model, according to the various parameter values ​​of the sink node and the bandwidth allocation cross-layer utility function H(p), the time slot price p of the sink node i is obtained. i , as shown in the following formula (5):

[0024]

[0025] In a round of Bertrand game, all sink nodes continuously adjust the time slot price to improve the cross-layer utility value of bandwidth allocation of the sink node until the cross-layer utility value of bandwidth allocation of the sink node reaches the maximum, that is, the equilibrium state is reached, thus obtaining the time slot price equilibrium value p of this round of game e ;

[0026] Step 2.5: Based on the equilibrium value p of the current time slot price e , calculate the time slot performance value T of the aggregation node i in this round of game i , and then calculate the time slot evaluation feedback value Y of the access node for the aggregation node i ;

[0027] Based on the equilibrium price p of this round of time slot obtained in step 2.4 e , and the time slot performance value T of the sink node i in this round of game is obtained i , as shown in the following formula (6):

[0028]

[0029] In the Bertrand game, after using the time slot, the access node gives evaluation feedback on the time slot performance value of the sink node used, that is, the evaluation feedback function is used to calculate the time slot evaluation feedback value Y of the access node to the sink node. i , the evaluation feedback function is shown in the following formula (7):

[0030] Y i =log 15 (T i +1) (7)

[0031] The virtual intermediary will evaluate the feedback value Y i Passed to the corresponding sink node to adjust the price of the next round of game time slots of each sink node;

[0032] Step 2.6: In the Bertrand game, the sink node calculates the evaluation feedback value Y i Adjust the time slot price; when the time slot price obtained by game is too high, the time slot performance value of the sink node is too low. When the time slot performance value of the sink node is lower than the set threshold, set the evaluation feedback Y i ≤1, the time slot price of the sink node will be reduced accordingly in the next round of game; on the contrary, when the time slot price is too low, the time slot performance value of the sink node is too high. When the time slot performance value is higher than the set threshold, the evaluation feedback Y is set. i >1, that is, the time slot price in the next round will be increased accordingly. The evaluation feedback value is fed back to the next round of Bertrand game to adjust the time slot price, as shown in the following formula (8):

[0033] p e ′=Y i*p e (8)

[0034] Among them, p e ′ is the adjusted time slot price equilibrium value. When the time slot performance value T i When a certain value is reached, the evaluation feedback function tends to converge, and finally the time slot performance value T based on Bertrand game is obtained. i ;

[0035] Step 2.7: Select the time slot performance value T i The highest aggregation node is used as the priority first-level bandwidth allocation node, and its time slot is allocated preferentially to complete the first-level bandwidth allocation.

[0036] Step 3: The virtual intermediary constructs a Cournot game model with access nodes as participants and the number of time slots as the game strategy. The time slots owned by the aggregation node that prioritizes the first-level bandwidth allocation in step 2 are allocated to the services of each access node. On the basis of ensuring that the cross-layer utility value of the bandwidth allocation of the access node is maximized, the number of time slots allocated to each service in each access node is determined through game.

[0037] Step 3.1: The virtual intermediary receives the bandwidth allocation parameters of each access node and assigns the node priority l of service k in access node j to the j and business priority j,k As an application layer parameter, the Hurst estimate h j,k and the number of frames to be transmitted s j,k As a link layer parameter, the signal-to-noise ratio μ of access node j j and the bit error rate BER of service k in access node j j,k As a physical layer parameter, set the revenue u obtained by service k using a unit time slot in access node j j,k , extract the time slot number of the priority first-level bandwidth allocation aggregation node in step 2 as the total number of time slots to be allocated W;

[0038] Step 3.2: Based on the service priority r of service k in access node j j,k , the benefit u obtained when using the unit time slot j,k , Number of frames to be transmitted s j,k , calculate the dynamic priority n of service k in access node j j,k , as shown in the following formula (9):

[0039] n j,k =αr j,k +βu j,k +γs j,k (9)

[0040] Among them, α, β, and γ are all weight coefficients, and α+β+γ=1;

[0041] Step 3.3: Combine the application layer parameters, link layer parameters and physical layer parameters to establish the bandwidth allocation cross-layer utility function G of the access node. j,k (b j,k ), as shown in the following formula (10):

[0042] G j,k (b j,k )=n j,k ·ln(1+h j,k )·l j ·z j,k b j,k -b j,k ·C j,k (10)

[0043] Among them, C j,k 、z j,k are the time slot pricing and time slot utilization of service k in access node j respectively. j,k The total number of time slots W and the number of time slots allocated to the service b j,k Assuming x, y, τ are non-negative integers, and τ ≥ 1 (to ensure convex function), then the time slot pricing C j,k As shown in the following formula (11):

[0044]

[0045] The time slot utilization rate z of the service k to be transmitted in access node j j,k As shown in the following formula (12):

[0046]

[0047] Step 3.4: Allocate the cross-layer utility function G according to the bandwidth of the access node j,k (b j,k ), and obtain the number of time slots b allocated to service k in access node j j,k , as shown in the following formula (13):

[0048]

[0049] Where, m = 1, ..., j, v = 1, ..., k;

[0050] In the Cournot game, the number of time slots b j,k The adjustment is continued until an equilibrium value is reached. This equilibrium value allocates time slots to each service in combination with its bandwidth allocation parameters on the basis of maximizing the cross-layer utility value of the bandwidth allocation of the access node. Finally, the number of equilibrium time slots b allocated to the services of each access node is obtained. e ;

[0051] Step 3.5: According to the number of equalization time slots b eThe total number of time slots W to be allocated is allocated to the services of each access node to complete the secondary bandwidth allocation.

[0052] The beneficial effect of adopting the above technical solution is that: the present invention provides a two-level cross-layer bandwidth allocation method for satellite networks based on a game model, establishes a two-level bandwidth allocation mechanism, uses the first-level bandwidth allocation for the aggregation node, and obtains the bandwidth of the aggregation node that is preferentially allocated. The second-level bandwidth allocation is used for the access node to obtain the number of time slots allocated to each application service of each access node. This method aims at the problem of limited bandwidth resources in satellite networks, fully considers the multi-node, multi-type, and self-similar characteristics of network services, has low computational complexity, is suitable for efficient resource management of multi-node and multi-type services in satellite networks, and can improve the overall system utility value while meeting the needs of nodes and services of different priorities, thereby improving the bandwidth utilization of satellite networks. BRIEF DESCRIPTION OF THE DRAWINGS

[0053] Figure 1 A schematic diagram of a two-level cross-layer bandwidth allocation method for a satellite network based on a game model provided by an embodiment of the present invention;

[0054] Figure 2 A schematic diagram of a method for allocating primary bandwidth of a convergence node provided by an embodiment of the present invention;

[0055] Figure 3 A schematic diagram of a method for allocating secondary bandwidth of access nodes provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0056] The specific implementation of the present invention is further described in detail below in conjunction with the accompanying drawings and examples. The following examples are used to illustrate the present invention, but are not intended to limit the scope of the present invention.

[0057] The present embodiment is a two-level cross-layer bandwidth allocation method for satellite networks based on a game model, such as Figure 1 As shown, the following steps are included:

[0058] Step 1: Multiple access nodes of the satellite network apply for bandwidth from the aggregation node, i.e., in the time slot, multiple aggregation nodes pass their respective bandwidth allocation parameters to the virtual intermediary;

[0059] Step 2: The virtual intermediary constructs a Bertrand game model with the sink nodes as participants and the time slot performance value as the game strategy. The sink node with the highest time slot performance value is selected as the sink node for priority allocation of primary bandwidth, and its time slot is allocated preferentially.

[0060] The Bertrand game model can effectively simulate the price competition among multiple sellers, and achieve price equilibrium through the mutual observation of sellers. It is often used to reflect the situation of price competition. The Bertrand game model in this embodiment uses the aggregation node as the seller and the access node as the buyer. The sellers need to compete for the number of time slots provided. In the Bertrand game process of this embodiment, different aggregation nodes (participants) adjust the time slot price according to the time slot performance value (game strategy) to attract access nodes, thereby optimizing resource allocation through competition strategy;

[0061] Step 2.1: The virtual intermediary receives the bandwidth allocation parameters of each sink node and sets the congestion level m of the time slot of sink node i to i As a transport layer parameter, the number of time slots owned by sink node i is W i , the service rate B required for the time slot owned by the aggregation node i to establish a connection with the service of the access node i req , the signal-to-noise ratio snr of the sink node i i and the delay t of the time slot of sink node i i As a physical layer parameter, the time slot evaluation feedback value of sink node i is set to 1;

[0062] Step 2.2: Establish a connection with the access node based on the time slot owned by the aggregation node i and the service rate B required i req , the number of time slots owned by sink node i is W i , calculate the time slot utilization f of the sink node i , as shown in the following formula (1):

[0063]

[0064] Step 2.3: Combine the transport layer parameters and the physical layer parameters to establish the bandwidth allocation cross-layer utility function H(p) of the aggregation node, as shown in the following formula (2):

[0065]

[0066] Among them, p i is the time slot price of sink node i, N is the total number of sink nodes; d i is the time slot requirement of the access node to the sink node i, C(d i ) is the cost function of the sink node i, as shown in the following formula (3):

[0067] C(d i )=B i req -f i (W i -d i ) (16)

[0068] The time slot requirement d of the access node to the sink node i i According to the time slot utilization f of sink node i i , congestion level m i Calculate as shown in the following formula (4):

[0069]

[0070] Among them, p i′ is the time slot price of sink node i′, f i′ is the time slot utilization rate of sink node i′, m i′ is the congestion level of the time slot of the sink node i′, η∈(0,1] represents the preference of the access node for the time slot of the sink node;

[0071] Step 2.4: Based on the Bertrand game model, according to the various parameter values ​​of the sink node and the bandwidth allocation cross-layer utility function H(p), the time slot price p of the sink node i is obtained. i , as shown in the following formula (5):

[0072]

[0073] The time slot price of the sink node is not only affected by its own parameters, but also by the time slot prices of other sink nodes, and the time slot price of the sink node will also affect the bandwidth allocation cross-layer utility value of the sink node. In a round of Bertrand game, the sink node continuously adjusts the time slot price. If the time slot price of a sink node is too high, the access node will turn to the sink node with a lower time slot price, which prompts all sink nodes to continuously adjust the time slot price to improve the bandwidth allocation cross-layer utility value of the sink node until the bandwidth allocation cross-layer utility value of the sink node reaches the maximum, that is, reaches an equilibrium state, thereby obtaining the time slot price equilibrium value p of this round of game e ;

[0074] Step 2.5: Based on the equilibrium value p of the current time slot price e , calculate the time slot performance value T of the aggregation node i in this round of game i , and then calculate the time slot evaluation feedback value Y of the access node for the aggregation node i ;

[0075] Since the equilibrium price of the time slot in this round of game is p e It cannot fully reflect the performance of the time slot. Therefore, the equilibrium price value p of the current time slot at the sink node i is e Based on this, we further consider the signal-to-noise ratio snr of the sink node i. i and the delay t of the time slot of sink node i i , and the time slot performance value T of the sink node i in this round of game is obtained i, as shown in the following formula (6):

[0076]

[0077] The Bertrand game process is as follows Figure 2 As shown in Figure 1, after using the time slot, the access node will evaluate and feedback the time slot performance value of the used aggregation node. Evaluation feedback can, to a certain extent, curb the aggregation node from arbitrarily raising the time slot price, thereby improving the quality and utilization of the time slot. The time slot evaluation feedback function of the access node to the aggregation node is shown in the following formula (7):

[0078] Y i =log 15 (T i +1) (20)

[0079] The virtual intermediary will evaluate the feedback value Y i Passed to the corresponding sink node to adjust the price of the next round of game time slots of each sink node;

[0080] Step 2.6: In the Bertrand game, the sink node calculates the evaluation feedback value Y i Adjust the time slot price. When the time slot price obtained by game is too high, the time slot performance value of the aggregation node will be too low. When the time slot performance value of the aggregation node is lower than the set threshold, set the evaluation feedback Y i ≤1, in the next round of game, the time slot price of the sink node will be reduced accordingly; on the contrary, when the game time slot price is too low, the time slot performance value of the sink node is too high. When the time slot performance value is higher than the set threshold, the evaluation feedback Y i >1, that is, the price of the next round of time slots will be increased accordingly;

[0081] In this embodiment, the threshold of the time slot performance value is set to 14. When the time slot performance value T of the sink node i is i <14:00, evaluation feedback Y i ≤1, otherwise, the evaluation feedback Y i >1, the evaluation feedback value is fed back to the time slot price obtained by the next round of Bertrand game, as shown in the following formula (8):

[0082] p e ′=Y i *p e (twenty one)

[0083] Among them, p e ′ is the adjusted price. If the time slot price is reduced, the time slot performance value T i is improved; otherwise, the time slot performance value T i Since the evaluation feedback function is a logarithmic function, it will not blindly follow the time slot performance value T iWhen the slot performance value T i When a certain value is reached, the evaluation feedback function tends to converge, and finally the time slot performance value T based on Bertrand game is obtained. i ;

[0084] Step 2.7: Select the time slot performance value T i The highest aggregation node is used as the priority first-level bandwidth allocation node, and its time slot is allocated preferentially to complete the first-level bandwidth allocation.

[0085] In this embodiment, the first-level bandwidth allocation method based on the Bertrand game model is shown in Table 1.

[0086] Table 1. Primary bandwidth allocation method based on Bertrand game model

[0087]

[0088] Step 3: The virtual intermediary constructs a Cournot game model with access nodes as participants and the number of time slots as the game strategy. The time slots owned by the aggregation node that prioritizes the first-level bandwidth allocation in step 2 are allocated to the services of each access node. On the basis of ensuring that the cross-layer utility value of the bandwidth allocation of the access node is maximized, the number of time slots allocated to each service in each access node is determined through game.

[0089] The Cournot game model is mostly used to reflect the competition for the number of goods, and is applicable to the competition for the number of time slots of the aggregation node in this embodiment. The Cournot game model in this embodiment uses the aggregation node as the seller and the access node as the buyer, and the buyers need to compete for the number of time slots. In the Cournot game process of this embodiment, by adjusting the number of time slots (game strategy) allocated to each service of different access nodes (participants), the number of time slots allocated to each service in each access node is obtained on the basis of ensuring the maximum cross-layer utility of the access node bandwidth allocation;

[0090] Step 3.1: The virtual intermediary receives the bandwidth allocation parameters of each access node and assigns the node priority l of service k in access node j to the j and business priority j,k As an application layer parameter, the Hurst estimate h j,k and the number of frames to be transmitted s j,k As a link layer parameter, the signal-to-noise ratio μ of access node j j and the bit error rate BER of service k in access node j j,k As a physical layer parameter, set the revenue u obtained by service k using a unit time slot in access node j j,k In this embodiment, different benefits are set for different access nodes, and u 1,1 =u 1,2 =u 2,1 =1,u 2,2 =u2,3 =0.5, extract the time slot number of the priority first-level bandwidth allocation aggregation node in step 2 as the total number of time slots to be allocated W;

[0091] Step 3.2: Based on the service priority r of service k in access node j j,k , the benefit u obtained when using the unit time slot j,k , Number of frames to be transmitted s j,k , calculate the dynamic priority n of service k in access node j j,k , as shown in the following formula (9):

[0092] n j,k =αr j,k +βu j,k +γs j,k (twenty two)

[0093] Among them, α, β, and γ are all weight coefficients, and α+β+γ=1;

[0094] Step 3.3: Combine the application layer parameters, link layer parameters and physical layer parameters to establish the bandwidth allocation cross-layer utility function G of the access node. j,k (b j,k ), as shown in the following formula (10):

[0095] G j,k (b j,k )=n j,k ·ln(1+h j,k )·l j ·z j,k b j,k -b j,k ·C j,k (twenty three)

[0096] Among them, C j,k 、z j,k are the time slot pricing and time slot utilization of service k in access node j respectively. j,k The total number of time slots W and the number of time slots allocated to the service b j,k Assuming x, y, τ are non-negative integers, and τ ≥ 1 (to ensure convex function), then the time slot pricing C j,k As shown in the following formula (11):

[0097]

[0098] The time slot utilization rate z of the waiting service k in the access service j j,k As shown in the following formula (12):

[0099]

[0100] Step 3.4: Allocate the cross-layer utility function G according to the bandwidth of the access node j,k (b j,k ), and obtain the number of time slots b allocated to service k in access node j j,k , as shown in the following formula (13):

[0101]

[0102] Where, m = 1, ..., j, v = 1, ..., k;

[0103] The number of time slots allocated to the services of an access node is not only related to its own parameters, but also to the number of time slots allocated to the services of other access nodes. Figure 3 As shown, the number of time slots b j,k The balance value is adjusted continuously until an equilibrium value is found. This equilibrium value is based on maximizing the cross-layer utility value of bandwidth allocation of access nodes and combining each service with its node priority l j , business priority j,k 、Hurst index h j,k , time slot utilization z j,k , the total number of time slots to be allocated by the aggregation node W is used to allocate time slots, and finally the number of balanced time slots b allocated to the services of each access node is obtained e ;

[0104] Step 3.5: According to the number of equalization time slots b e The total number of time slots W to be allocated is allocated to the services of each access node to complete the secondary bandwidth allocation.

[0105] In this embodiment, the secondary bandwidth allocation method based on the Cournot game model is shown in Table 2.

[0106] Table 2 Secondary bandwidth allocation method based on Cournot game model

[0107]

[0108] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some or all of the technical features therein. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope defined by the claims of the present invention.

Claims

1. A two-level cross-layer bandwidth allocation method for satellite networks based on a game model, characterized in that: The method involves multiple access nodes, multiple aggregation nodes and virtual intermediaries. The aggregation node is the party that owns the time slot. Each aggregation node passes the bandwidth allocation parameter to the virtual intermediary. The virtual intermediary feeds back the time slot performance value to the aggregation node based on the Bertrand game model to determine which aggregation node's time slot should be allocated first. The access node is the party that applies for the time slot. The virtual intermediary determines the number of time slots allocated to each service of the access node based on the bandwidth allocation parameters in each access node based on the Cournot game model.

2. According to the game model-based satellite network two-level cross-layer bandwidth allocation method of claim 1, it is characterized in that: The specific steps include: Step 1: Multiple access nodes of the satellite network apply for bandwidth from the aggregation node, i.e., in the time slot, multiple aggregation nodes pass their respective bandwidth allocation parameters to the virtual intermediary; Step 2: The virtual intermediary constructs a Bertrand game model with the sink nodes as participants and the time slot performance value as the game strategy. The sink node with the highest time slot performance value is selected as the sink node for priority allocation of primary bandwidth, and its time slot is allocated preferentially. Step 3: The virtual intermediary constructs a Cournot game model with access nodes as participants and the number of time slots as the game strategy. The time slots owned by the aggregation node that prioritizes the first-level bandwidth allocation in step 2 are allocated to the services of each access node. On the basis of ensuring that the cross-layer utility value of the bandwidth allocation of the access node is maximized, the number of time slots allocated to each service in each access node is determined through game.

3. According to the game model-based satellite network two-level cross-layer bandwidth allocation method of claim 2, it is characterized in that: The step 2 specifically includes: Step 2.1: The virtual intermediary receives the bandwidth allocation parameters of each sink node and sets the congestion level m of the time slot of sink node i to i As a transmission layer parameter, the number of time slots owned by sink node i is W i , the service rate B required for the time slot owned by the aggregation node i to establish a connection with the service of the access node i req , the signal-to-noise ratio snr of the sink node i i and the delay t of the time slot of sink node i i As a physical layer parameter, the time slot evaluation feedback value of sink node i is set to 1; Step 2.2: Establish a connection with the access node based on the time slot owned by the aggregation node i. i req , the number of time slots owned by sink node i is W i , calculate the time slot utilization f of the sink node i , as shown in the following formula (1): Step 2.3: Combine the transport layer parameters and the physical layer parameters to establish the bandwidth allocation cross-layer utility function H(p) of the aggregation node, as shown in the following formula (2): Among them, p i is the time slot price of sink node i, N is the total number of sink nodes, d i is the time slot requirement of the access node to the sink node i, C(d i ) is the cost function of the sink node, as shown in the following formula (3): C(d i )=B i req -f i (W i -d i ) (3) The time slot requirement d of the access node to the sink node i i According to the time slot utilization f of sink node i i , congestion level m i Calculate as shown in the following formula (4): Among them, p i′ is the time slot price of sink node i′, f i′ is the time slot utilization rate of sink node i′, m i′ is the congestion level of the time slot of the sink node i′, η∈(0,1] represents the preference of the access node for the time slot of the sink node; Step 2.4: Based on the Bertrand game model, according to the various parameter values ​​of the sink node and the bandwidth allocation cross-layer utility function H(p), the time slot price p of the sink node i is obtained. i , as shown in the following formula (5): In a round of Bertrand game, all sink nodes continuously adjust the time slot price to improve the cross-layer utility value of bandwidth allocation of the sink node until the cross-layer utility value of bandwidth allocation of the sink node reaches the maximum, that is, the equilibrium state is reached, thus obtaining the time slot price equilibrium value p of this round of game e ; Step 2.5: Based on the equilibrium value p of the current time slot price e , calculate the time slot performance value T of the aggregation node i in this round of game i , and then calculate the time slot evaluation feedback value Y of the access node for the aggregation node i ; Step 2.6: In the Bertrand game, the sink node calculates the evaluation feedback value Y i Adjust time slot prices; Step 2.7: Select the time slot performance value T i The highest aggregation node is used as the priority first-level bandwidth allocation node, and its time slot is allocated preferentially to complete the first-level bandwidth allocation.

4. The two-level cross-layer bandwidth allocation method for satellite networks based on a game model according to claim 3 is characterized in that: The step 2.5 specifically includes: Based on the equilibrium price p of this round of time slot obtained in step 2.4 e , and the time slot performance value T of the sink node i in this round of game is obtained i , as shown in the following formula (6): In the Bertrand game, after using the time slot, the access node gives evaluation feedback on the time slot performance value of the sink node used, that is, the evaluation feedback function is used to calculate the time slot evaluation feedback value Y of the access node to the sink node. i , the evaluation feedback function is shown in the following formula (7): Y i =log 15 (T i +1) (7) The virtual intermediary will evaluate the feedback value Y i It is passed to the corresponding sink node to adjust the time slot price of the next round of game at each sink node.

5. The two-level cross-layer bandwidth allocation method for satellite networks based on a game model according to claim 4 is characterized in that: The step 2.6 specifically includes: When the time slot price obtained by game is too high, the time slot performance value of the sink node is too low. When the time slot performance value of the sink node is lower than the set threshold, the evaluation feedback Y is set. i ≤1, the time slot price of the sink node will be reduced accordingly in the next round of game; on the contrary, when the time slot price is too low, the time slot performance value of the sink node is too high. When the time slot performance value is higher than the set threshold, the evaluation feedback Y is set. i >1, that is, the time slot price in the next round will be increased accordingly, and the evaluation feedback value will be fed back to the next round of Bertrand game to adjust the time slot price, as shown in the following formula (8): p e ′=Y i *p e (8) Among them, p e ′ is the adjusted time slot price equilibrium value, when the time slot performance value T i When a certain value is reached, the evaluation feedback function tends to converge, and finally the time slot performance value T based on Bertrand game is obtained. i .

6. The two-level cross-layer bandwidth allocation method for satellite networks based on a game model according to claim 5, characterized in that: The step 3 specifically includes: Step 3.1: The virtual intermediary receives the bandwidth allocation parameters of each access node and assigns the node priority l of service k in access node j to the j and business priority j,k As an application layer parameter, the Hurst estimate h j,k and the number of frames to be transmitted s j,k As a link layer parameter, the signal-to-noise ratio μ of access node j j and the bit error rate BER of service k in access node j j,k As a physical layer parameter, set the revenue u obtained by service k using a unit time slot in access node j j,k , extract the time slot number of the priority first-level bandwidth allocation aggregation node in step 2 as the total number of time slots to be allocated W; Step 3.2: Based on the service priority r of service k in access node j j,k , the benefit u obtained when using the unit time slot j,k , Number of frames to be transmitted s j,k , calculate the dynamic priority n of service k in access node j j,k , as shown in the following formula (9): n j,k =αr j,k +bu j,k +γs j,k (9) Among them, α, β, and γ are all weight coefficients, and α+β+γ=1; Step 3.3: Combine the application layer parameters, link layer parameters and physical layer parameters to establish the bandwidth allocation cross-layer utility function G of the access node. j,k (b j,k ), as shown in the following formula (10): G j,k (b j,k )=n j,k ·ln(1+h j,k )·l j ·z j,k ·b j,k -b j,k ·C j,k (10) Among them, C j,k 、z j,k are the time slot pricing and time slot utilization of service k in access node j, respectively. The time slot pricing C j,k The total number of time slots W and the number of time slots allocated to the service b j,k Assuming x, y, τ are non-negative integers, and τ ≥ 1 (to ensure convex function), then the time slot pricing C j,k As shown in the following formula (11): The time slot utilization rate z of the service k to be transmitted in access node j j,k As shown in the following formula (12): Step 3.4: Allocate the cross-layer utility function G according to the bandwidth of the access node j,k (b j,k ), and obtain the number of time slots b allocated to service k in access node j j,k , as shown in the following formula (13): Where, m = 1, ..., j, v = 1, ..., k; In the Cournot game, the number of time slots b j,k The adjustment is continued until an equilibrium value is reached. This equilibrium value allocates time slots to each service in combination with its bandwidth allocation parameters on the basis of maximizing the cross-layer utility value of bandwidth allocation of the access node. Finally, the number of equilibrium time slots b allocated to the services of each access node is obtained. e ; Step 3.5: According to the number of equalization time slots b e The total number of time slots W to be allocated is allocated to the services of each access node to complete the secondary bandwidth allocation.

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