Lunar surface communication network cache deployment scheme based on reliable transmission

Abstract

The invention provides a reliable transmission-based lunar communication network cache deployment scheme. The scheme comprises the following steps of: constructing a cache cost model of equipment nodes according to the size of content needing to be cached on each equipment node; constructing an energy consumption model of the equipment node according to energy consumption consumed by the equipment node during data caching, detection activity maintaining and data transmission; according to the data position cached by the device node, constructing a time delay cost model for the device node to obtain the request content; constructing a fault probability model of the equipment node according to the hardware state of the equipment node and the environment state of the equipment, and constructing an availability model of the equipment node based on the fault probability model of the equipment node; according to the availability model of the equipment node, the cache cost model of the equipment node, the energy consumption model of the equipment node and the time delay cost model of the equipment node, constructing a cache strategy optimization model of the equipment node; and converting the caching strategy optimization model into an unconstrained caching strategy optimization model, solving the unconstrained caching strategy optimization model by using a mayfly naiad algorithm to obtain an optimal data caching strategy, and caching the data of the device node based on the optimal data caching strategy.

Description

Technical Field

[0001] The present invention belongs to the field of communication technology, and in particular relates to a lunar communication network cache deployment solution based on reliable transmission. Background Art

[0002] As lunar exploration activities continue to deepen, the number and types of lunar exploration nodes will continue to increase in the future, and devices need to maintain persistent communication, establish a self-organizing network between lunar nodes, and ensure communication between exploration nodes. In the lunar scenario, the deployment range of wired links is limited, and it is more practical to use the lunar wireless backbone network combined with the regional wireless self-organizing network. In the lunar exploration mission, astronauts, lunar rovers, robots, etc. will form multiple exploration teams to form a lunar wireless self-organizing communication network to carry out exploration missions. The exploration team will upload the acquired exploration data to the lander. At the same time, the landing capsule will maintain real-time communication with the exploration team, monitor the location of the exploration team and the astronauts' vital signs, and issue command orders. The exploration teams can achieve multi-hop communication through the lander or communicate directly.

[0003] However, the communication scenario on the moon is completely different from that on the earth. Figure 2 and Figure 3 As shown in the figure. Compared with the mobile ad hoc network on Earth, the wireless communication environment on the moon is poor. The lunar exploration nodes have the following characteristics: (1) Affected by the lunar topography, magnetic field, radiation, charged lunar dust and temperature, the communication link between the exploration nodes is easily interrupted, making the network topology highly dynamic. At the same time, the node equipment ages faster and the failure probability is higher. (2) The high cost of launching lunar equipment adds difficulties, resulting in the limited computing power and storage capacity of the lunar communication network nodes. (3) The energy of the nodes is limited. The exploration nodes usually generate electricity through solar panels. They can work normally during the lunar day, but enter a dormant state during the lunar night. Only a small number of devices are on standby to restart the lunar rover when the lunar day arrives. (4) Since there is no atmosphere on the moon, there is no infrastructure such as aircraft to assist communication in the lunar communication network. In summary, the complex topography, magnetic field, radiation, charged lunar dust, temperature changes, and energy and resource limitations on the moon have caused many challenges for reliable communication networks, such as low link reliability, high node failure rate, and easy data loss, resulting in low data transmission reliability and high transmission delay. Summary of the invention

[0004] In order to solve the problems existing in the background technology, the present invention performs data cache backup through caching, and other nodes can obtain backup data from nearby cache nodes, and then use the mayfly algorithm to solve the optimal cache node solution to improve data transmission reliability and reduce latency.

[0005] In order to achieve the above technical objectives, the present invention provides a lunar communication network cache deployment solution based on reliable transmission, including:

[0006] S1: Build a cache cost model for device nodes based on the size of the content that needs to be cached on each device node;

[0007] S2: Building an energy consumption model of device nodes based on the energy consumed by device nodes when caching data, maintaining detection activities, and transmitting data;

[0008] S3: Based on the data location cached by the device node, a latency cost model for the device node to obtain the requested content is constructed;

[0009] S4: constructing a failure probability model of the device node according to the hardware status of the device node and the environmental status of the device, and constructing an availability model of the device node based on the failure probability model of the device node;

[0010] S5: constructing a cache strategy optimization model for the device node according to the availability model of the device node, the cache cost model of the device node, the delay cost model for the device node to obtain the request content, and the energy consumption model of the device node;

[0011] S6: Convert the cache strategy optimization model into an unconstrained cache strategy optimization model, and use the mayfly algorithm to solve the unconstrained cache strategy optimization model to obtain the optimal data cache strategy, and cache the data of the device node based on the optimal data cache strategy.

[0012] The present invention has at least the following beneficial effects

[0013] The present invention constructs a cache cost model according to the size of the content that needs to be cached on each device node, which enables accurate quantification of the cost of caching data in different device nodes. Based on the cost model, the cache content of each device node can be reasonably planned to avoid unnecessary cache overhead, thereby effectively controlling the overall cache cost and achieving optimal resource configuration. Through the constructed device node energy consumption model, the energy consumption of the device when caching data, maintaining detection activities and transmitting data is considered in detail, the energy consumption of the device under different cache strategies is estimated, and the cache scheme with lower energy consumption is preferentially selected. The delay cost model constructed by the present invention based on the data location of the device node cache is crucial to improving data access efficiency. The model can help us cache data to a location that is more conducive to reducing the delay in obtaining the request content. The fault probability model and availability model constructed by the hardware status and environmental status of the device node provide reliability considerations for cache strategy optimization. Through the availability model, when selecting cache device nodes, those nodes with good hardware status, stable environment and high availability will be given priority, thereby reducing the risk of data loss caused by device failure and enhancing the reliability and stability of the entire system. The cache strategy optimization model is constructed by combining the availability model, cache cost model and energy consumption model. This multi-dimensional comprehensive consideration can achieve global optimization of the system and avoid the problem of optimizing only a single factor and ignoring other important aspects. The system can achieve better performance in all aspects. The Mayfly algorithm is used for solving. This method can efficiently find the optimal data cache strategy. It can quickly locate the data cache method that optimizes the system performance in a complex solution space, and then cache the data of the device node based on this optimal strategy to ensure that the system can achieve the best performance in actual operation. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] Figure 1 It is a schematic diagram of the method flow of the present invention;

[0015] Figure 2 This is a schematic diagram of the lunar surface communication scenario;

[0016] Figure 3 Schematic diagram of the lunar communication environment. DETAILED DESCRIPTION

[0017] The following describes the embodiments of the present invention by specific examples, and those skilled in the art can easily understand other advantages and effects of the present invention from the contents disclosed in this specification. The present invention can also be implemented or applied through other different specific embodiments, and the details in this specification can also be modified or changed in various ways based on different viewpoints and applications without departing from the spirit of the present invention. It should be noted that the illustrations provided in the following embodiments only illustrate the basic concept of the present invention in a schematic manner, and the following embodiments and features in the embodiments can be combined with each other without conflict.

[0018] See also Figure 1 The present invention provides a lunar surface communication network cache deployment solution based on reliable transmission, including:

[0019] S1: Build a cache cost model for device nodes based on the size of the content that needs to be cached on each device node;

[0020] S2: Building an energy consumption model of device nodes based on the energy consumed by device nodes when caching data, maintaining detection activities, and transmitting data;

[0021] S3: Based on the data location cached by the device node, a latency cost model for the device node to obtain the requested content is constructed;

[0022] S4: constructing a failure probability model of the device node according to the hardware status of the device node and the environmental status of the device, and constructing an availability model of the device node based on the failure probability model of the device node;

[0023] S5: constructing a cache strategy optimization model for the device node according to the availability model of the device node, the cache cost model of the device node, the delay cost model for the device node to obtain the request content, and the energy consumption model of the device node;

[0024] S6: Convert the cache strategy optimization model into an unconstrained cache strategy optimization model, and use the mayfly algorithm to solve the unconstrained cache strategy optimization model to obtain the optimal data cache strategy, and cache the data of the device node based on the optimal data cache strategy.

[0025] In this embodiment, the lunar surface communication network can be represented as a graph G = (U, M, S, C), U = {u1, u2, ..., u n} represents the set of all mobile nodes in the network (mobile nodes), M = {u1,u2,...,u m} represents the set of all nodes m (mobile nodes + terminal nodes) in the network; Indicates the size of the content that needs to be cached on each device node; the cache capacity of the mobile node is Nodes with cache space can cache content of appropriate size, so that each node can retrieve content from local cache and adjacent cache nodes, reducing content acquisition delay and energy consumption; in the lunar communication network, when the mobile node u j When a content request is initiated, it first checks whether the content is available in its local cache; if not, it then requests the content from a cache node u within communication range. i If the requested content cannot be obtained in all cache nodes, the lunar base u o Get, the content cached by each cache node will be transmitted to the base for storage.

[0026] In the network, each node has mobility and autonomy, and the neighbor nodes of each node may change dynamically due to the mobility of the node. The detection node has a communication coverage range of radius r. If the communication distance between any two nodes is not greater than the maximum effective communication radius r, a wireless link can be established for communication. The link state between nodes is defined as a binary variable ξ i,j ∈{0,1},u i ,u j ∈U,ξ i,j =1 represents node u i and node u j A communication link can be established, otherwise i,j =0, that is:

[0027]

[0028] Among them, h i,j Represented as node u i and node u j The channel gain between th It is the channel gain threshold for establishing a wireless communication link. A link can only be established between two points if the channel gain is greater than this threshold.

[0029] In order to ensure transmission reliability, the node can cache the data to the cache node in advance, using a binary variable To represent the node u j Select cache node u i The status are:

[0030]

[0031] in, Represents node u i As node u j Cache nodes, Then it means node u i Not node u jWhen caching content, the node needs to consume storage and energy resources, so there will be a certain cache cost. i The performance is different, different u i The cache cost in is also different. i Represented as node u i The cost of caching content per unit size is then i Cache j The cost of caching data is:

[0032]

[0033] Therefore, a cache cost model of a device node is constructed, and the cache cost model of the device node includes:

[0034]

[0035]

[0036] Among them, i,j Represents device node u i Cache device node u j caching cost when consuming data; When it indicates device node u i As device node u j Cache nodes, When it indicates device node u i Not a device node u j Cache nodes; α i Represents device node u i The cost of caching a unit of content.

[0037] When performing exploration activities, each node consumes energy to cache files, maintain normal exploration activities, and transmit data. In the lunar communication network, in-network caching can reduce energy consumption to a certain extent. Although solar panels can be used to generate electricity, considering the poor lighting conditions on the lunar surface, the total energy of the equipment is limited and may be exhausted, resulting in performance impairment. Node energy consumption is mainly divided into three parts: fixed energy consumption, storage energy consumption, and transmission energy consumption.

[0038] Fixed energy consumption refers to the energy consumption used to maintain node mobile detection. This article assumes that the fixed energy consumption of nodes is the same. As a tool platform for lunar exploration, the lunar rover will carry various scientific exploration instruments to patrol and detect the lunar surface, so the walking performance of the lunar rover is related to the execution process and effect of the lunar exploration mission. The special driving environment on the lunar surface places higher requirements on the performance of the lunar rover's drive and steering system, and imposes stricter restrictions on the energy consumption of the lunar rover's driving system. Studies have shown that it is more energy-saving than an independently steering lunar rover. The total moving energy consumption of the mobile device node ui is

[0039] If the nodes are within the communication range, they can directly establish a wireless link for communication. If the nodes are not within the communication range, they can communicate through multiple hops. Therefore, node u i With node u j The transmission energy consumption is:

[0040]

[0041] Cache energy consumption: Storage energy consumption refers to the energy consumed for caching content. i Cache node u j Energy consumed by data The following formula can be used for calculation:

[0042]

[0043] in, Represents the energy consumed by caching each bit of data. Represents node u j The size of the data to be cached.

[0044] Therefore, node u i As node u j The total energy consumed by the cache nodes for:

[0045]

[0046] Node u i The energy obtained through solar energy in each time slot is Then node u i The remaining energy The calculation is as follows:

[0047]

[0048] Among them, B i represents the battery size of node i, and

[0049] Therefore, an energy consumption model of a device node is constructed, and the energy consumption model of the device node includes:

[0050]

[0051]

[0052]

[0053]

[0054]

[0055]

[0056] Among them, B i Represents device node u i The battery size; U represents the set of all mobile nodes in the lunar communication network; Represents device node u i Energy obtained through solar energy, etc.; Represents device node u i Cache device node u j The total energy consumption of the data; Represents device node u i Total energy consumption of movement; Indicates the device node u i Cache device node u j The energy consumption of data; Represents device node u j Transfer the data that needs to be cached to the device node u i The transmission energy consumption, Represents device node u i The remaining energy Represents device node u j The size of the data that needs to be cached; represents the energy consumed for caching each bit of data; J represents the device node u i To device node u j The path node set between them, v represents the elements in the set J; γ represents the device node u i The energy consumed in transmitting data per unit time; r v,v-1 Represents device node u i To device node u j The data transmission rate of each path between i,j =1 indicates device node u i and device node u j Establish a communication link; i,j =0 indicates device node u i and device node u j No communication link established; i,j Represents device node u i and device node u j The data transmission rate between i,j Represents device node u i and device node u j The channel bandwidth between; log2() represents the logarithm with base 2; p j Represents device node uj The transmission power of i′ ∈U,u i′ ≠u i Indicates that except for device node u i Other mobile nodes; h i,j Represents device node u i and device node u j The channel gain between them; N0 represents the power spectral density of Gaussian white noise; h th Indicates the channel gain threshold for establishing a wireless communication link.

[0057] In the lunar communication network, transmission delay is a key performance indicator. If the data can be found in a cache node close to the requester, it is possible to avoid obtaining data from a distant data source (such as a base), thereby greatly reducing the transmission delay. i and node u j The coordinates are (x i ,y i ) and (x j ,y j ), Represents node u i and node u i The shortest distance:

[0058]

[0059] Here are Then when the node i Get request content f from node j m , the data transmission rate is:

[0060]

[0061] Among them, the node i and the channel gain h between node j i,j , B i,j For node u i and node u j The channel bandwidth, p j is the transmission power, N0 is the power spectrum density of Gaussian white noise, u i′ ∈U,u i′ ≠u i Indicates that except for device node u i other mobile nodes. Then node u j From node u i The delay in getting the request content is:

[0062]

[0063] Therefore, a latency optimization cost model is constructed, which includes:

[0064]

[0065]

[0066] Among them, T i,j Represents node u j From node u i The latency of getting the request content, Represents device node u i and device node u v The Euclidean distance between When it indicates device node u i As device node u j Cache nodes, When it indicates device node u i Not a device node u j Cache nodes; r i,ν Represents device node u i and device node u v The data transmission rate between j Represents device node u j The delay required to obtain data from the base.

[0067] In lunar communications, on the one hand, it is necessary to consider that the hardware status of communication equipment may decline due to aging, which may lead to equipment failure. On the other hand, complex external factors such as temperature difference, lunar dust concentration, radiation intensity and light intensity on the lunar surface will cause irreversible damage to communication equipment, which may cause equipment failure and affect the normal operation of the equipment. Therefore, we introduce a failure probability model for device nodes, which includes:

[0068]

[0069]

[0070]

[0071]

[0072]

[0073]

[0074] P m =1-e -FAΔt

[0075]

[0076]

[0077] in, Represents device node u j The failure probability of the device node is 1, k1 represents the device aging factor, and t represents the usage time of the device node; T exp represents the service life of the device node, e represents the natural base, and D represents the radiation dose on the lunar surface; D th Indicates the radiation resistance threshold of the device node; P m P represents the probability of equipment on the lunar surface being hit by micrometeoroids; d|m represents the conditional probability of device node being damaged by micrometeoroid impact; F represents the micrometeoroid flux on the lunar surface; A represents the exposed area of ​​the device node; Δt represents the time interval; T min Indicates the lowest adaptable temperature of the device node; T max represents the maximum adaptable temperature of the device node; T represents the ambient temperature on the lunar surface; T ref Indicates reference temperature; T r represents the temperature sensitivity parameter of the device node; k2 represents the dust resistance parameter of the device node; C d Indicates the dust concentration on the lunar surface.

[0078] An availability model of a device node is constructed based on a failure probability model of the device node, and the availability model of the device node includes:

[0079]

[0080] Among them, L i Represents device node u i Availability, Represents device node u i The failure probability of ρ is the failure probability threshold.

[0081] If the node u j Select node u i As its cache node, the total cost required is calculated as follows:

[0082]

[0083] Among them, μ, λ, κ, γ are all constants in [0,1], and μ+λ+k+γ=1.

[0084] In the scenario of lunar communication network cache node deployment, considering that the total overhead is composed of factors such as energy consumption, delay, failure rate and cache cost, and the numerical range and dimension of these factors are different, in order to more reasonably compare the overhead of different nodes, the minimum-maximum normalization method can be used to process the total overhead. After normalization, the total overhead is:

[0085]

[0086] In this way, the total overhead of different nodes is normalized to an interval, which can more intuitively compare the advantages and disadvantages of each node as a cache node. Therefore, the cache node deployment problem in each region can be characterized as finding the most effective deployment strategy under the constraints of node energy and failure probability, so as to minimize the cache overhead under the condition of satisfying the node availability constraint, and construct a cache strategy optimization model for device nodes, which includes:

[0087]

[0088]

[0089]

[0090] in, When it indicates device node u i As device node u j Cache nodes, When it indicates device node u i Not a device node u j Cache nodes; i,j =1 indicates device node u i and device node u j Establish a communication link; i,j =0 indicates device node u i and device node u j No communication link is established; M represents the set of detection device nodes, which contains m devices in total; U represents the set of all mobile nodes, which contains n mobile devices in total; constraint C1 represents the constraint of establishing communication links between nodes and the binary cache decision variable; C i Represents device node u i The cache capacity of C2 indicates that the data cached by the node cannot exceed the cache capacity; Represents device node u i The remaining energy, Represents device node u i Total mobile energy consumption, C3 means that the remaining energy of the node should be able to support the energy required for its normal detection task; Represents device node u iEnergy obtained from solar energy, Represents device node u i Cache device node u j The total energy consumption of the data, C4 represents the node u i The total energy consumption of cached data is no greater than that of node u i Energy generated by solar panels; T i,j Represents node u j From node u i The delay in obtaining the requested content, τ j Represents device node u j The delay required to obtain data from the base, C5 represents the node u j From cache node u i The latency of getting content is much smaller than that of node u j Get the delay τ from the base j ; and They represent the minimum and maximum values ​​of node cache energy consumption, t min and t max Respectively represent the minimum and maximum values ​​of the delay, L min and L max Respectively represent the minimum and maximum values ​​of the availability of power-saving devices, Ξ min and max They represent the minimum and maximum values ​​of the cache cost of the device node respectively. μ, λ, κ and γ are weight coefficients. Their value range is between [0,1]. These coefficients are used to adjust the importance of different factors in the optimization model and μ+λ+κ+γ=1.

[0091] After modeling the system, it can be seen from the objective function and constraints that the above mathematical model has high complexity and it is difficult to find its optimal solution within polynomial time. Inspired by the life cycle and group behavior of mayflies, the mayfly algorithm has strong global search capabilities and is often used to optimize the solution of problems. Therefore, the present invention uses the mayfly algorithm to solve in order to obtain the global optimal cache set. In the lunar communication network scenario of the present invention, we regard the cache overhead function as the fitness function of the mayfly. The position of each mayfly individual represents a set of cache node selection options. For example, the position of a mayfly can be represented by a vector It represents the selection scheme of cache nodes in the network. The global optimal position is obtained through the movement and mating of mayflies. The global optimal position corresponds to the best set of cache nodes in the lunar communication network.

[0092] In order to use the Mayfly algorithm to solve the objective optimization problem, it is necessary to transform the original problem. In order to transform the constrained optimization problem into an unconstrained optimization problem, we use the concept of penalty method. The conversion process is described as follows. The penalty function is defined as:

[0093] P(x)=θ∑g(f(x))f 2 (x)+ζ∑g(h(x))h 2 (x)

[0094] Among them, θ and ζ are penalty terms, and x is the optimization variable. The equality constraint is transformed into the form of h(x) = 0. When h′(x) = 0, the constraint is satisfied, then g(h(x)) = 0, that is, the new objective function value remains unchanged. h′(x)≠0 means that the constraint is not satisfied, then g(h(x)) = 1. Due to the existence of the penalty term, the value of the new objective function is greatly improved. In this way, solutions with high overhead can be eliminated. The same principle is used to transform the inequality constraint into the form of f(x) ≤ 0, which is convenient for subsequent optimization. Therefore, the original problem can be transformed into:

[0095]

[0096] Finally, the optimization problem is given as:

[0097] minφ(x)

[0098]

[0099]

[0100]

[0101] Therefore, through the above process, the cache strategy optimization model is transformed into an unconstrained cache strategy optimization model, including:

[0102] Define the penalty function of the cache strategy optimization model:

[0103] P(x)=θ∑g(f(x))f 2 (x)+ζ∑g(h(x))h 2 (x)

[0104] Among them, θ and ζ are penalty coefficients, x is the optimization variable, the inequality constraint is transformed into the form of f(x)≤0, g() represents the control function, h(x) represents the equality constraint, and f(x) represents the inequality constraint, then the original problem is transformed into:

[0105]

[0106] Get the unconstrained cache strategy optimization model:

[0107] minφ(x)

[0108]

[0109]

[0110] Among them, φ(x) represents the unconstrained cache strategy optimization model, T i,j Represents node u j From node u i The delay in obtaining the requested content, τ j Represents device node u j The delay required to obtain data from the base.

[0111] The position of each mayfly represents a potential solution to the problem. First, there are two groups of random mayflies, representing the male population and the female population, which means that the mayflies are randomly placed in the problem space, with their positions represented by vector x, and their performance is evaluated according to the fitness function f(x). The flight direction of each mayfly is a dynamic interaction of individual and social flight experience, and each mayfly adjusts its position by dynamically updating the mayfly's speed to move toward the optimal position.

[0112] Let υ be the speed of the mayfly, and po(x) be the optimization object. The position of the mayfly in the problem space is equivalent to the potential solution of the problem. The clustering of male mayflies means that the position of each male mayfly is adjusted according to its own experience and that of its neighbors. Indicates the position of male mayfly m in the eth iteration, adding the speed to the current position The movement process of male mayflies is:

[0113]

[0114] Assume that the speed of male mayflies is not very fast and they continue to move. Then define the speed of male mayflies as:

[0115]

[0116] in, represents the moving speed of the e-th iteration, a1 is a constant measuring the cognitive contribution, a2 is a constant measuring the contribution of the social component, and pbest m represents the best position of the male mayfly m in history, gbest represents the best global position, β is a fixed visibility factor that limits the visibility of the mayfly, and r p Is the current position of Mayfly and pbest m The Cartesian distance between g is the Cartesian distance between the current position and gbest, with:

[0117]

[0118] gbest=min{φ(pbest1),φ(pbest2),...,φ(pbest M )}

[0119] Where M is the total number of male mayflies. Unlike males, female mayflies do not gather in groups. They fly to males to reproduce. The movement process of female mayflies is as follows:

[0120]

[0121] Given that the attraction process is stochastic, we decided to model it as a deterministic process. That is, the best females are attracted to the best males, and the second best females are attracted to the second best males, based on their fitness values, as follows:

[0122]

[0123] Among them, r m,f is the distance between the male and female mayflies, and fe is a random walk coefficient. According to the fitness rule, when the female mayfly is attracted to the male mayfly, it moves in the direction of the male mayfly. When the female mayfly is not attracted, it will perform a random walk and move randomly in the search space, and r∈[-1,1] is a random value.

[0124] The method of producing offspring also follows the best female mating with the best male, the second best female mating with the second best male, and so on. The result of the crossover is two offspring, generated as follows:

[0125] spring1=off*male+(1-off)*female,

[0126] spring2=off*female+(1-off)*male,

[0127] Among them, off is a random value within a certain range, the initial speed of the offspring is 0, and the iteration is repeated until the difference between the optimal fitness values ​​obtained from two consecutive iterations is less than ε (ε is a very small positive number), or the number of iterations reaches the preset maximum number of iterations so that the algorithm converges.

[0128] Therefore, based on the above process, the solution of the unconstrained cache strategy optimization model using the Mayfly algorithm includes:

[0129] S611: Initialize the mayfly population S, the offspring population F, the convergence error ε, and the maximum number of iterations I max ;

[0130] S612: using the unconstrained cache strategy optimization model as the objective function, initializing the position of each mayfly, wherein the position of the mayfly is represented as a selection scheme of the cache node;

[0131] S613: Calculate the initial fitness value φ(x) of each mayfly using the objective function according to the initial position po(x) of the mayfly;

[0132] S614: Male mayflies according to the historical best position pbest m And the global optimal position gbest update speed According to speed Update its location

[0133] S615: Male mayflies according to updated position Calculate the fitness value using the objective function And with the historical best position pbest m Compare, if Then update the historical best position pbest m ;

[0134] S616: Based on the historical best position pbest of all male mayflies m Select the position with the smallest fitness and update the global optimal position gbest;

[0135] S617: Female mayflies calculate fitness values ​​based on objective functions Update speed Update its location

[0136] S618: mate the mayfly individuals in the offspring group F and evaluate the fitness of the offspring;

[0137] S619: Create new populations, retain the best males and females, and ensure that the best individuals in the population can be retained to the next generation;

[0138] S620: Repeat the above operations until the convergence criteria are met, and output the optimal data caching strategy of the cache node corresponding to the global optimal position gbest.

[0139] The process of simulating the courtship dance of mayflies and random flight enhances the balance between exploration and exploitation properties, which are two effective ways to help the algorithm escape from the local optimum. The number of algorithm iterations is set to I max , the population size is set to S, and d is the data dimension. The complexity of the algorithm is O(I max *S*d). This scheme aims at the characteristics of lunar communication network, establishes a system model that comprehensively considers cache cost, energy consumption, latency and availability, and uses the Mayfly algorithm to solve the cache node deployment problem, providing reliable communication guarantee for future lunar exploration missions.

[0140] In summary, the present invention constructs a cache cost model according to the size of the content that needs to be cached on each device node, which enables accurate quantification of the cost of caching data on different device nodes. Based on the cost model, the cache content of each device node can be reasonably planned to avoid unnecessary cache overhead, thereby effectively controlling the overall cache cost and achieving optimal resource configuration. Through the constructed device node energy consumption model, the energy consumption of the device when caching data, maintaining detection activities and transmitting data is considered in detail, the energy consumption of the device under different cache strategies is estimated, and the cache solution with lower energy consumption is preferentially selected. The delay cost model constructed by the present invention based on the data location of the device node cache is crucial to improving data access efficiency. The model can help us cache data to a location that is more conducive to reducing the delay in obtaining the request content. The fault probability model and availability model constructed by the hardware status and environmental status of the device node provide reliability considerations for cache strategy optimization. Through the availability model, when selecting cache device nodes, those nodes with good hardware status, stable environment and high availability will be given priority, thereby reducing the risk of data loss caused by device failure and enhancing the reliability and stability of the entire system. The cache strategy optimization model is constructed by combining the availability model, cache cost model and energy consumption model. This multi-dimensional comprehensive consideration can achieve global optimization of the system and avoid the problem of optimizing only a single factor while ignoring other important aspects. The system can achieve better performance in all aspects. The Mayfly algorithm is used for solving. This method can efficiently find the optimal data cache strategy and can quickly locate the data cache method that optimizes system performance in a complex solution space. Then, based on this optimal strategy, the data of the device node is cached to ensure that the system can achieve the best performance in actual operation.

[0141] Finally, it should be noted that the above embodiments are only used to illustrate the technical solution of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solution of the present invention can be modified or replaced by equivalents without departing from the purpose and scope of the technical solution, which should be included in the scope of the claims of the present invention.

Claims

1. A lunar communication network cache deployment scheme based on reliable transmission, characterized in that: include: S1: Build a cache cost model for device nodes based on the size of the content that needs to be cached on each device node; S2: Building an energy consumption model of device nodes based on the energy consumed by device nodes when caching data, maintaining detection activities, and transmitting data; S3: Based on the data location cached by the device node, a latency cost model for the device node to obtain the requested content is constructed; S4: constructing a failure probability model of the device node according to the hardware status of the device node and the environmental status of the device, and constructing an availability model of the device node based on the failure probability model of the device node; S5: constructing a cache strategy optimization model for the device node according to the availability model of the device node, the cache cost model of the device node, the delay cost model for the device node to obtain the request content, and the energy consumption model of the device node; S6: Convert the cache strategy optimization model into an unconstrained cache strategy optimization model, and use the mayfly algorithm to solve the unconstrained cache strategy optimization model to obtain the optimal data cache strategy, and cache the data of the device node based on the optimal data cache strategy.

2. The cache deployment scheme for lunar communication network based on reliable transmission according to claim 1 is characterized in that: The cache cost model of the device node includes: Among them, i,j Represents device node u i Cache device node u j caching cost when consuming data; When it indicates device node u i As device node u j Cache nodes, When it indicates device node u i Not a device node u j Cache nodes; α i Represents device node u i The cost of caching a unit of content.

3. The cache deployment scheme for lunar communication network based on reliable transmission according to claim 1 is characterized in that: The energy consumption model of the device node includes: Among them, B i Represents device node u i The battery size; U represents the set of all mobile nodes in the lunar communication network; Represents device node u i Energy obtained through solar energy, etc.; Represents device node u i Cache device node u j The total energy consumption of the data; Represents device node u i Total energy consumption of movement; Indicates the device node u i Cache device node u j The energy consumption of data; Represents device node u j Transfer the data that needs to be cached to the device node u i The transmission energy consumption, Represents device node u i The remaining energy Represents device node u j The size of the data that needs to be cached; represents the energy consumed for caching each bit of data; J represents the device node u i To device node u j The path node set between them, v represents the elements in the set J; Υ represents the device node u i The energy consumed in transmitting data per unit time; r v,v-1 Represents device node u i To device node u j The data transmission rate of each path between i,j =1 indicates device node u i and device node u j Establish a communication link; i,j =0 indicates device node u i and device node u j No communication link established; i,j Represents device node u i and device node u j The data transmission rate between i,j Represents device node u i and device node u j The channel bandwidth between; log2() represents the logarithm with base 2; p j Represents device node u j The transmission power of i′ ∈U,u i′ ≠u i Indicates that except for device node u i Other mobile nodes; h i,j Represents device node u i and device node u j The channel gain between them; N0 represents the power spectral density of Gaussian white noise; h th Indicates the channel gain threshold for establishing a wireless communication link.

4. The lunar communication network cache deployment solution based on reliable transmission according to claim 1 is characterized in that: The delay cost model includes: Among them, T i,j Represents node u j From node u i The latency of getting the request content, Represents device node u i and device node u v The Euclidean distance between When it indicates device node u i As device node u j Cache nodes, When it indicates device node u i Not a device node u j Cache nodes; r i,v Represents device node u i and device node u v The data transmission rate between j Represents device node u j The delay required to obtain data from the base.

5. The lunar communication network cache deployment solution based on reliable transmission according to claim 1 is characterized in that: The failure probability model of the device node includes: P m =1-e -FAΔt in, Represents device node u j The failure probability of the device node is 1, k1 represents the device aging factor, and t represents the usage time of the device node; T exp represents the service life of the device node, e represents the natural base, and D represents the radiation dose on the lunar surface; D th Indicates the radiation resistance threshold of the device node; P m P represents the probability of equipment on the lunar surface being hit by micrometeoroids; d|m represents the conditional probability of device node being damaged by micrometeoroid impact; F represents the micrometeoroid flux on the lunar surface; A represents the exposed area of ​​the device node; Δt represents the time interval; T min Indicates the lowest adaptable temperature of the device node; T max represents the maximum adaptable temperature of the device node; T represents the ambient temperature on the lunar surface; T ref Indicates reference temperature; T r represents the temperature sensitivity parameter of the device node; k2 represents the dust resistance parameter of the device node; C d Indicates the dust concentration on the lunar surface.

6. The lunar communication network cache deployment solution based on reliable transmission according to claim 5 is characterized in that: The availability model of the device node includes: Among them, L i Represents device node u i Availability, Represents device node u i The failure probability of ρ is the failure probability threshold.

7. The lunar communication network cache deployment solution based on reliable transmission according to claim 1 is characterized in that: The cache strategy optimization model of the device node includes: in, When it indicates device node u i As device node u j Cache nodes, When it indicates device node u i Not a device node u j Cache nodes; i,j =1 indicates device node u i and device node u j Establish a communication link; i,j =0 indicates device node u i and device node u j No communication link is established; M represents the set of detection device nodes, which contains m devices in total; U represents the set of all mobile nodes, which contains n mobile devices in total; constraint C1 represents the constraint of establishing communication links between nodes and the binary cache decision variable; C i Represents device node u i The cache capacity of C2 indicates that the data cached by the node cannot exceed the cache capacity; Represents device node u i The remaining energy, Represents device node u i Total mobile energy consumption, C3 means that the remaining energy of the node should be able to support the energy required for its normal detection task; Represents device node u i Energy obtained from solar energy, Represents device node u i Cache device node u j The total energy consumption of the data, C4 represents the node u i The total energy consumption of cached data is no greater than that of node u i Energy generated by solar panels; T i,j Represents node u j From node u i The delay in obtaining the requested content, τ j Represents device node u j The delay required to obtain data from the base, C5 represents the node u j From cache node u i The latency of getting content is much smaller than that of node u j Get the delay τ from the base j ; and They represent the minimum and maximum values ​​of node cache energy consumption, t min and t max Respectively represent the minimum and maximum values ​​of the delay, L min and L max Respectively represent the minimum and maximum values ​​of the availability of power-saving devices, Ξ min and max They represent the minimum and maximum values ​​of the cache cost of the device node respectively. μ, λ, κ and γ are weight coefficients. Their value range is between [0,1]. These coefficients are used to adjust the importance of different factors in the optimization model and μ+λ+κ+γ=1.

8. The lunar communication network cache deployment solution based on reliable transmission according to claim 7 is characterized in that: The converting of the cache strategy optimization model into an unconstrained cache strategy optimization model comprises: Define the penalty function of the cache strategy optimization model: P(x)=θΣg(f(x))f 2 (x)+ζ∑g(h(x))h 2 (x) Among them, θ and ζ are penalty coefficients, x is the optimization variable, the inequality constraint is transformed into the form of f(x)≤0, g() represents the control function, h(x) represents the equality constraint, and f(x) represents the inequality constraint, then the original problem is transformed into: Get the unconstrained cache strategy optimization model: minφ(x) Among them, φ(x) represents the unconstrained cache strategy optimization model, T i,j Represents node u j From node u i The delay in obtaining the requested content, τ j Represents device node u j The delay required to obtain data from the base.

9. The lunar surface communication network cache deployment solution based on reliable transmission according to claim 8 is characterized in that: The method of solving the unconstrained cache strategy optimization model by using the mayfly algorithm includes: S611: Initialize the mayfly population S, the offspring population F, the convergence error ε, and the maximum number of iterations I max ; S612: using the unconstrained cache strategy optimization model as the objective function, initializing the position of each mayfly, wherein the position of the mayfly is represented as a selection scheme of the cache node; S613: Calculate the initial fitness value φ(x) of each mayfly using the objective function according to the initial position po(x) of the mayfly; S614: Male mayflies according to the historical best position pbest m And the global optimal position gbest update speed According to speed Update its location S615: Male mayflies according to updated position Calculate the fitness value using the objective function And with the historical best position pbest m Compare, if Then update the historical best position pbest m ; S616: Based on the historical best position pbest of all male mayflies m Select the position with the smallest fitness and update the global optimal position gbest; S617: Female mayflies calculate fitness values ​​based on objective functions Update speed Update its location S618: mate the mayfly individuals in the offspring group F and evaluate the fitness of the offspring; S619: Create new populations, retain the best males and females, and ensure that the best individuals in the population can be retained to the next generation; S620: Repeat the above operations until the convergence criteria are met, and output the optimal data caching strategy of the cache node corresponding to the global optimal position gbest.

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