IMA system interface resource allocation method based on hierarchical immune algorithm

Abstract

The invention discloses an IMA system interface resource allocation method based on a hierarchical immune algorithm, and the method comprises the steps: S1) determining the onboard installation position of an airborne device according to the function of the airborne device, and determining the interface type, the interface number, the interface constraint and the access cost of an IMA system network transmission and interface conversion device used by the airborne device interface; s2) determining the number of network transmission equipment and interface conversion equipment of the IMA system, networking the IMA system and airborne equipment, determining the total number of available interface types of the network transmission equipment and the interface conversion equipment, and determining a layout limitation area; and S3) carrying out system decoupling and redundancy layering on the system network equipment, the interface equipment and the access interface, and then respectively carrying out optimization for conversion interface distribution and network interface distribution on each redundancy layer. According to the method, the IMA system interface equipment can be reasonably arranged, meanwhile, the interface relation constraint and the requirement for the total quantity of different types of interface resources of all the equipment can be met, and the overall access cost is low.

Description

TECHNICAL FIELD

[0001] The application relates to a system interface resource allocation method, in particular to an IMA system interface resource allocation method based on a hierarchical immune algorithm. BACKGROUND

[0002] An avionics system is the "brain" and "nerve" of an airplane. With the high integration of avionics systems, an integrated modular avionics (IMA) architecture is used by more and more airplanes due to its low cost, easy scalability and high flexibility. An IMA system is configured according to resource requirements of an airplane system, and provides computing, network, interface and other resource services for various airborne systems, relies on network transmission equipment to provide a high-reliability airborne data bus, and relies on interface conversion equipment to provide collection, conversion and processing of thousands of interfaces from devices of different suppliers. How to reasonably arrange the network transmission equipment and the remote data conversion equipment on the airplane, how to reasonably allocate the network interface resources and the conversion interface resources while meeting the constraint conditions, and how to solve the problems of airplane system layout design and resource allocation are one of the difficulties.

[0003] The resource sharing and module performance constraint characteristics of the IMA system determine that the interfaces from devices of different suppliers need to compete for limited shared resources, and reasonable arrangement and resource allocation of the network transmission equipment and the interface conversion equipment can reduce the weight of the airplane. The arrangement and resource allocation of the equipment layout and the network interface and data conversion interface resources is an NP problem. Existing equipment layout and resource allocation methods mainly adopt manual arrangement and allocation, and rely on the experience of engineers for judgment and repeated iteration, which is low in efficiency and the allocation result is not optimized. Each round of change will bring huge change cost, and it is difficult to meet the interface allocation and optimization design of the current large airplane in a complex scene, so as to achieve the maximum weight reduction. The traditional barycenter method can be used for single device location, and the mixed integer programming can be used for interface allocation, but a static strategy is adopted, the device layout needs to be determined in advance, and the interface conversion equipment also needs to be connected to the network transmission equipment, and the mutual coupling increases the complexity of the layout and allocation. The current layout and resource allocation of the network transmission equipment and the interface conversion equipment are optimized in a split manner, which leads to a suboptimal overall cost, and lacks a systematic method.

[0004] Therefore, how to reasonably arrange the network transmission equipment and the interface conversion equipment on the airplane, meet the layout constraints on the airplane, and reasonably allocate a large number of interfaces from devices of different suppliers to each network transmission equipment and each interface conversion equipment has been a research hotspot in the field. SUMMARY

[0005] The technical problem to be solved by this invention is to provide an interface resource allocation method for an IMA system based on a hierarchical immune algorithm, which can reasonably arrange network transmission equipment and remote data conversion equipment, and reasonably allocate network interface resources and conversion interface resources while meeting constraints, so as to reduce the overall access cost of different types of interfaces accessing the IMA system.

[0006] The technical solution adopted by this invention to solve the above-mentioned technical problems is to provide an IMA system interface resource allocation method based on a hierarchical immune algorithm, including the following steps: S1) Determine the onboard installation location of the airborne equipment according to its function, and clarify the interface type, number of interfaces, interface constraints, and access cost of the network transmission and interface conversion equipment of the IMA system used by the airborne equipment interface; S2) Determine the number of network transmission equipment and interface conversion equipment in the IMA system, network the IMA system and airborne equipment, determine the total number of available interface types of each network transmission equipment and interface conversion equipment, and determine the layout restriction area; S3) Based on the interface resource requirements, the redundancy architecture design of the network transmission equipment and interface conversion equipment, first allocate the system network... The system decouples and redundancy layers network devices, interface devices, and access interfaces. Then, for each redundancy layer, the first layer optimization is performed first, followed by the second layer optimization, as follows: S4) First layer optimization: Based on the resource capabilities and constraints of the interface conversion device, a comprehensive optimization strategy for the layout of the interface conversion device and the allocation of other interfaces is formulated, and a collaborative optimization method based on immune algorithm and mixed integer programming is executed; S5) Second layer optimization: The interface conversion device is one of the access network transmission devices, and based on the resource requirements of other network interfaces, the resource capabilities of network transmission devices, and their constraints, a comprehensive optimization strategy for the layout of network transmission devices and the allocation of network interfaces is formulated, and a collaborative optimization method based on immune algorithm and mixed integer programming is executed.

[0007] Further, step S1 quantifies the access interface according to the following formula: the interface set of the access interface conversion device: IO m ={io1, io2, ..., io m There are m interfaces that need to be connected to the IMA system interface conversion device; the set of interfaces for connecting to the network transmission device: IO u ={io1, io2, ..., io u There are a total of u interfaces that need to be connected to the IMA system network transmission equipment; io i =(posi i type i ,num i cost i bind i ); posi i = (posi_x) i, posi_y i , posi_z i ); wherein, io i represents the ith access interface, posi i represents the position of the access interface, posi_x i , posi_y i , posi_z i represent the three-dimensional coordinates of the position; type i represents the type of the access interface, num i represents the number of the access interface; cost i represents the access cost coefficient of the type of access interface, bind i represents the associated requirements of the access interface; The interface of the network transmission device includes an A664 network interface and a TTE network interface, and the interface of the interface conversion device includes an A429 sending interface, an A429 receiving interface, an A825 interface, an analog quantity interface, a discrete quantity interface and a sensor interface; for the interface device without special installation position requirements, after optional installation of the shortest distance, the network interface type accesses the network transmission device, and the other type of interface accesses the interface conversion device.

[0008] Further, the step S2 quantifies the devices as follows: Interface conversion device set: IOM n ={iom1, iom2,..., iom n}, a total of n interface conversion devices; Network transmission device set: IOM v ={iom1, iom2,..., iom v}, a total of v network transmission devices; iom j = (iom_posi j , max_type_1 j , max_type_2 j ,... max_type_g j ); iom_posi j = (iom_p_x j , iom_p_y j , iom_p_z j ); Layout restriction area set: ZONE={zone1, zone2,..., zone p}, a total of p prohibited layout areas; zone s = (zone_type szone_Center s zone_par1 s zone_par2 s zone_par3 s ); zone_Center s = (zone_p_x) s zone_p_y s zone_p_z s ); Among them, iom j Represents the j-th interface device in the IMA system, iom_posi j Indicates the location of the interface device, iom_p_x j ,iom_p_y j ,iom_p_z j Indicates its three-dimensional coordinates; max_type_1 j max_type_2 j ...max_type_g j This indicates the total number of the first, second, ... g-th type interfaces of the interface device; zone s This represents the s-th layout constraint region within the layout space, represented by zone_type. s Indicates the type of the restricted area in this layout, zone_Center s This indicates the location of the restricted area of ​​the layout.

[0009] Furthermore, steps S4 and S5 employ no-distribution zone constraints and device connection constraints, ensuring that any network transmission device or interface conversion device is located outside the no-distribution zone, and that device connection constraints are implemented by controlling the sum of the interconnection distances of each interface conversion device or network transmission device.

[0010] Furthermore, the collaborative optimization method based on immune algorithm and mixed integer programming in steps S4 and S5 includes: S601: antibody encoding and population initialization; S602: affinity evaluation based on joint cost; S603: immune selection, using an elite retention and dynamic elimination mechanism, calculating the affinity of each antibody in each population update iteration, and selecting excellent antibodies to store in the memory bank; S604: clonal selection and mutation; S605: clonal suppression; S606: new antibodies and population update; S607: termination and output.

[0011] Further, the step S601 comprises: encoding rule: representing the feasible solution of the problem into a chromosome in the solution space by encoding, the chromosome representing an array with the length of the total number of devices, each gene position corresponding to an interface device and its position coordinates, the gene value n for the interface conversion device, and the gene value v for the network transmission device, representing the type device number; constraint preprocessing: generating an initial solution based on the forbidden area constraint to reduce invalid search; randomly initializing each individual in the generated population, checking whether each device position satisfies the forbidden area constraint, i.e., outside the forbidden area; parameter setting: defining the population size, mutation probability, and maximum iteration number.

[0012] Further, the step S602 comprises: evaluating the pros and cons of each individual by the affinity function, the affinity function being designed as a joint cost evaluation function, the layout optimization cost of the device position being fused with the interface access cost, the layout optimization cost including the device connection cost and the forbidden area penalty cost, the solutions not meeting the conditions being gradually eliminated in the evolution process, the solution with the highest affinity being selected to realize the device layout and interface resource allocation; the affinity function is as follows: Fitness = a - cost_dist + β - cost penalty + γ - cost Allocate ； wherein: a, b, γ optimized through experiments; cost_dist : represents the device connection cost; cost penalty : represents the number of device layouts to the forbidden area x penalty coefficient, the constraint satisfying the layout restriction; cost Allocate : represents the cost of allocating all interfaces to all interface conversion devices and network transmission devices, the interface conversion device allocation cost being calculated in its optimization level, and the interface conversion device being coupled with the network transmission device, the interface conversion device being one of the interfaces accessing the network transmission device, and its cost being included in the network transmission device optimization level interface allocation cost calculation.

[0013] Further, the step S602 calculates in the respective optimization level cost Allocate as follows: i, define the decision variables x i,j and y k,j , each interface being allocated to an interface device; x i,j =

[0014] y k,j =

[0015] i.e. one of the g interface types provided by the interface device; ii. Set the allocation constraint, allocate the interfaces with interface association requirements to the same interface device; define the allocation weight factor based on the greedy sorting allocation strategy, sort all interfaces according to the weight factor, and allocate preferentially to the interface with a larger weight factor; Set the total amount of interface type constraint, the sum of the interface resources of any one interface type type j allocated to the interface device iom i does not exceed the total amount of interface resources max_type_g of the interface device, and the sum of the interface resources of any one interface type type j does not exceed the interface resource threshold of the interface device; i iii. Set the objective function to minimize the allocation cost, and the allocation cost of a single interface is defined as cost io i , which represents the cost of accessing the interface to a certain interface device; cost io i = io_dist × num i × cost i ; io_dist represents the distance of accessing the interface to the interface device, num i represents the number of access interfaces, and cost i represents the access cost coefficient of the access interface, cost Allocate , which represents the cost of allocating all interfaces to all interface devices; cost_ Allocate = .

[0016] Further, the step S603 performs immune selection based on affinity, and retains a part of antibodies with the highest fitness as memory cells in each generation; and a similarity function between antibodies is defined, the distance between antibodies is calculated based on Hamming distance or affinity function, and if the similarity is greater than a threshold, low-affinity antibodies are randomly eliminated; the step S604 performs directional mutation on the clone by using Gaussian mutation or random mutation, randomly disturbs the clone gene, and performs boundary constraint on the mutated gene position; the step S605 performs reselection on the offspring antibodies generated after the clone mutation operation, suppresses antibodies with low affinity, and retains antibodies with high affinity to enter a new antibody population; and the step S606 introduces random new antibodies, and sorts the retained memory bank antibodies, clone mutation antibodies, and new antibodies according to affinity, selects the antibodies with high ranking to perform population recombination, and maintains the constant population size.

[0017] ​Further, the stop condition in the step S607 is that the preset iteration number and / or the change of the optimal affinity value is less than the preset threshold, and the step S607 outputs the high-affinity antibody in the memory bank satisfying the constraint condition.

[0018] The present application has the following advantages over the prior art: the IMA system interface resource allocation method based on the hierarchical immune algorithm provided by the present application relies on the installation positions and interface types and quantities of different supplier equipment, considers the total amount of interface type resources, coupling relationship and on-machine layout constraints of network transmission equipment and interface conversion equipment, adopts an optimization method based on the hierarchical immune algorithm, first distinguishes redundant equipment and redundant interfaces according to the system architecture, and then executes a hierarchical interface design strategy for each redundant layer; through hierarchical design and considering dynamic constraint processing and cost weight balance, global optimization is achieved, thereby solving the layout of network transmission and interface conversion equipment and the interface resource allocation problem of the IMA system under multiple constraint conditions. There are tens of thousands of interfaces on the machine that need to be connected to the interface conversion equipment and network transmission equipment, and using a manual method to perform equipment layout and interface allocation often takes more than a month. Using the method of the present application, an effective allocation scheme can be generated within minutes, which can ensure that the interface relationship constraints and the total amount of different types of interface resources of each equipment are met, and the overall access cost is low. BRIEF DESCRIPTION OF DRAWINGS

[0019] cost The flowchart of the IMA system interface resource allocation method based on the hierarchical immune algorithm of the present application is shown in the figure. Figure 1 The flowchart of the collaborative optimization method based on the immune algorithm and mixed integer programming of the present application is shown in the figure. DETAILED DESCRIPTION

[0020] The present application will be further described below in conjunction with the drawings and examples.

[0021] The application provides an IMA system interface resource allocation method based on a hierarchical immune algorithm, which considers installation positions of different supplier devices, interface types and quantities of the devices, total amounts of interface type resources of network transmission devices and interface conversion devices, on-machine layout constraints and system architecture redundancy relations, and adopts a hierarchical interface design strategy. The system network devices, interface devices and access interfaces are decoupled and redundantly layered, and then optimization of conversion interface allocation and network interface allocation is performed for each redundant layer. Specifically, conversion interface layout and interface allocation optimization is performed, the interface conversion devices access the network transmission devices, and then network transmission device layout and interface allocation optimization is performed. By using the method, the layout of IMA system network transmission and interface conversion devices is determined, a large number of interfaces are allocated to the interface devices, the overall cost is small, and the IMA system network transmission and interface conversion device layout and interface resource allocation problem under multiple constraints is solved. The specific implementation steps of the application are shown in Figure 2 .

[0022] Step S1: quantizing access interfaces, determining positions of each airborne device using IMA system network transmission device and interface conversion device interface resources on the aircraft according to airborne device functions, the airborne device interface types, quantities, interface constraints, access costs, and the belonging quantization formula are determined. The interface set of the access interface conversion device: IO m ={io1, io2,..., io m}, a total of m interfaces that need to access the IMA system interface conversion device; The interface set of the access network transmission device: IO u ={io1, io2,..., io u}, a total of u interfaces that need to access the IMA system network transmission device; io i =(posi i , type i , num i , cost i , bind i ); posi i =(posi_x i , posi_y i , posi_z i ); Wherein, io i represents the ith access interface, posi i represents the position of the access interface, posi_x i , posi_y i , and posi_z i represent three-dimensional coordinates of the position; typei represents the type of the access interface, network interface or other interface, network interface represents the interface accessing the onboard backbone network, such as A664 network interface, or TTE network interface, etc., other interfaces such as A429 sending interface, A429 receiving interface, A825 interface, analog interface, discrete interface, sensor interface, etc.; num i represents the number of the access interface; cost i represents the access cost coefficient of the type of access interface, different for each type of interface type, different for using cable; bind i represents the association requirement of the access interface, some interfaces come from the same device, expect to access the same, interface conversion device, or interfaces with close association between each other, need to access the same interface conversion device, network transmission device if required, the same reason.

[0023] For the interface device without special installation location requirement, after the interface allocation is completed by the algorithm in the invention, it can be optionally installed at the appropriate shortest distance, the network interface type accesses the network transmission device, and the other type of interface accesses the interface conversion device.

[0024] Step S2: quantifying device capability, determining the number of IMA system network transmission devices, interface conversion devices, layout restriction area, interface resource types and their quantities possessed by network transmission devices and interface conversion devices, the belonging quantification formula is: Interface conversion resource device set: IOM n ={iom1, iom2,..., iom n}, a total of n interface conversion devices; Network transmission resource device set: IOM v ={iom1, iom2,..., iom v}, a total of v network transmission devices; iom j = (iom_posi j , max_type_1 j , max_type_2 j ,... max_type_g j ); iom_posi j = (iom_p_x j , iom_p_y j , iom_p_z j ); Layout restriction area set: ZONE = {zone1, zone2,..., zone p}, a total of p prohibited layout areas; zones = (zone_type s , zone_Center s , zone_par1 s , zone_par2 s , zone_par3 s ) ; zone_Center s = (zone_p_x s , zone_p_y s , zone_p_z s ) ; where iom j denotes the jth interface device of the IMA system, iom_posi j denotes the position of the interface device, iom_p_x j , iom_p_y j , iom_p_z j denote its three-dimensional coordinates; max_type_1 j , max_type_2 j ,... max_type_g j denote the total amount of the 1st, 2nd,... gth type of interface provided by the interface device, i.e. the maximum number of interface resources of each type of interface that the device can provide, type_g i denotes one of the g types of interfaces provided by the interface device.

[0025] zone s denotes the s th layout restriction area in the layout space, zone_type s denotes the type of the layout restriction area, zone_Center s denotes the position of the layout restriction area, which is determined by zone_p_x s , zone_p_y s , zone_p_z s , zone_par1 s , zone_par2 s , zone_par3 s denote the parameters defining the layout restriction area.

[0026] Step S3: According to the interface resource requirements, network transmission equipment, interface conversion equipment redundancy architecture design, redundancy layering is carried out to improve the system availability, security, and through the redundancy design to ensure the stable operation of the system; distinguish the redundant equipment and the redundant interface, such as dividing the redundant A layer and the redundant B layer, and then executing the layered interface design strategy for each redundant layer, that is, the first layer optimizes the other types of interfaces except the network interface accessed through the interface conversion equipment, and the second layer optimizes the network interface accessed through the network transmission equipment to the backbone network.

[0027] Step S4: First layer optimization, according to the other interface resource requirements, interface conversion equipment resource capacity and its constraint conditions, the comprehensive optimization strategy of interface conversion equipment layout and other interface allocation is formulated, and the collaborative optimization method based on immune algorithm and mixed integer programming (step 6) is executed, that is, the improved immune algorithm is used to optimize the spatial layout of the interface conversion equipment, and the mixed integer programming is used to optimize the allocation of other interface resources.

[0028] Step S5: Second layer optimization, according to the network interface resource requirements (including the network interface of the interface conversion equipment), network transmission equipment resource capacity and its constraint conditions, the comprehensive optimization strategy of network transmission equipment layout and network interface allocation is formulated, and the collaborative optimization method based on immune algorithm and mixed integer programming (step 6) is executed, that is, the improved immune algorithm is used to optimize the spatial layout of the network transmission equipment, and the mixed integer programming is used to optimize the allocation of network interface resources.

[0029] Step S6: The collaborative optimization method based on immune algorithm and mixed integer programming, as shown in Figure 1 The mathematical model is established as follows: 1) Forbidden area constraint: iom_posi j The forbidden area ZONE should not be laid out in the forbidden area.

[0030] 2) Device connection constraint: Since the interface conversion equipment is completed after the layout, it needs to be connected with the network transmission equipment, and the network transmission equipment also needs to be interconnected, so the device needs to have a certain aggregation, which is represented by distance cost, and the model is established as follows: Minimize cost_dist= , wherein iom_posi n+1 =iom_posi1, The distance between the jth device and the j+1th device is represented by cost_dist; the device connection cost is represented by the sum of the interconnection distances of each interface conversion equipment or network transmission equipment.

[0031] Step 601: Antibody coding and population initialization 1) Coding rule: Represent the feasible solution of the problem as a chromosome (individual) in the solution space by coding, which represents an array with a length of the total number of devices, and each gene position corresponds to an interface device and its position coordinates. The gene value n for interface conversion devices and v for network transmission devices represents the device number.

[0032] 2) Constraint preprocessing: To speed up convergence and improve efficiency, generate an initial solution based on the forbidden area constraint to reduce invalid searches. Forbidden area constraint: randomly initialize each individual in the generated population, check each device position, and satisfy the forbidden area constraint, i.e., outside the forbidden area.

[0033] 3) Parameter setting Define algorithm control parameters such as population size, mutation probability, and maximum number of iterations.

[0034] Step 602: Affinity evaluation based on joint cost Calculate individual affinity based on joint cost: Evaluate the pros and cons of each individual through the affinity function, and the affinity value reflects the optimization objective of the solution. The affinity function is designed as a joint cost evaluation function, which combines the interface access cost with the device position layout optimization cost. The layout optimization cost includes device connection cost and forbidden area penalty cost. In the evolution process, eliminate solutions that do not meet the conditions, select the solution with the highest affinity, and realize device layout and interface resource allocation.

[0035] Affinity function: Figure 2 penalty Fitness = a - cost_dist + β - cost Allocate ； Where: α, β, + γ - cost Optimized through experiments; γ can : represents the device connection cost; cost_dist penalty : represents the number of device layouts to forbidden areas x penalty coefficient, which satisfies the layout restriction; cost Allocate : represents the cost of allocating all interfaces to all interface conversion devices and network transmission devices, and the cost Allocate The calculation is as follows: According to the interface resource demand and its constraint conditions, and the device resource capacity, execute the optimization method of mixed integer programming, that is, use mixed integer programming to perform dynamic allocation of access interfaces. The main model and steps are as follows: a. Define decision variables To describe the interface access to the interface device, define the following decision variables: x i,j =

[0036] A decision variable of 1 indicates that the j-th interface device provides interface resources for that interface, i.e., the I / O... i Assigned to the j-th interface device; the decision variable is 0, indicating that the I / O is... i Not assigned to this interface device IOM j .

[0037] Uniqueness of interface allocation: Each interface must be assigned to a single interface device; , cost

[0038] To describe the connection of a certain type of interface to an interface device, define the following decision variables: y k,j =

[0039] ,Right now It belongs to one of the g types of interfaces provided by the interface device.

[0040] The decision variable is 1, and the interface type is io i Assigned to the j-th interface device; the decision variable is 0, indicating that the I / O is... i Not assigned to this interface device IOM j .

[0041] b. Define assignment constraints 1) Define interface association constraints Describe the interface association requirements, interface I / O i io l Must be assigned to the same interface device: x i,j =x l,j , l m, j n; When io i When allocated to a certain IOM, io l It must be allocated to this IOM.

[0042] The greedy sorting and allocation strategy defines an allocation weight factor and sorts all interfaces according to the weight factor, prioritizing those with larger weight factors.

[0043] 2) Define the total interface type constraint The total interface type resource constraint of the interface device interface type resource is allocated to the interface device iom j The sum of the interface resources of any one interface type type i Does not exceed the total interface resource max_type_g of the interface device j .

[0044] , j = 1, 2,..., n. , j = 1, 2,..., n ... , k = 1, 2,..., g; j = 1, 2,..., n,

[0045] In order to balance the interface device margin and allocation, the sum of the interface resources of any one interface type type i Can be limited to not more than the interface resource threshold of the interface device, and the interface resource threshold can be determined by reference to the average proportion of the total amount of the interface to be allocated.

[0046] c. Objective function definition Minimize the allocation cost, and the allocation cost of a single interface is defined as k = 1, 2,..., g. io i , indicating the cost of accessing an interface to a certain interface device.

[0047] cost io i =io_dist×num i ×cost i ; io_dist indicates the distance of accessing the interface to the interface device. num i Indicates the number of access interfaces, and cost i Indicates the access cost coefficient of the access interface, which is closely related to the type of access interface.

[0048] cost Allocate Indicates the cost of allocating all interfaces to all interface devices, and the interface conversion device and the network transmission device are calculated in their respective optimization levels, cost cost Allocate = 。

[0049] According to the quantified interface, the distribution constraint, and the device of layout input, all interface distributions are completed.

[0050] The joint cost evaluation of the layout cost and the interface resource distribution cost is realized through affinity function design.

[0051] The interface quantity is m for the interface conversion device and u for the network transmission device.

[0052] The device quantity is n for the interface conversion device and v for the network transmission device.

[0053] Step 603: immune selection The elite reservation and dynamic elimination mechanism is adopted, the affinity of each antibody is calculated every time the population is updated, the excellent antibodies are selected and stored in the memory bank, and the loss of high-quality solutions is prevented.

[0054] The immune selection method is affinity-based immune selection, and part of the antibodies with the highest fitness is reserved as memory cells every generation. The similarity inhibition defines the similarity function between antibodies, calculates the distance between antibodies based on the Hamming distance or affinity function, and randomly eliminates the low-affinity antibodies if the similarity is greater than the threshold value, so as to maintain the diversity of the population and avoid premature convergence.

[0055] Step 604: clone selection and mutation Clone amplification: the excellent antibodies selected by immune selection are copied in proportion according to the antibody affinity, that is, the selected excellent antibodies are cloned and subjected to mutation operation to enhance the exploration ability and maintain the diversity of the population.

[0056] Mutation: directional mutation is performed on the clones, and random disturbance (adjusting the numerical value) is performed on the clone genes to increase the diversity of the population. The disturbance can adopt Gaussian mutation or random mutation, and boundary constraint is performed on the gene positions after mutation.

[0057] Step 605: clone inhibition After the clone mutation operation, the offspring antibodies generated by the clone mutation are reselected, the antibodies with low affinity are inhibited, and the antibodies with high affinity are reserved into the new antibody population.

[0058] Step 606: new antibody and population update New antibody: random new antibodies are introduced to maintain the diversity of the population, and the random new antibodies should meet the constraint preprocessing conditions.

[0059] Population recombination: the memory bank antibodies + clone mutation antibodies + random new antibodies are reserved, and the population size is maintained constant after being sorted according to the affinity. The excellent antibodies are reserved during the population update process, and the diversity of the population is maintained, which avoids premature convergence.

[0060] Step 607: Termination with output 1) Stopping criterion The algorithm is terminated when one or a combination of the following conditions is met: The preset number of iterations is reached. The optimal affinity value no longer improves significantly (convergence).

[0061] 2) Output result The high-affinity antibodies in the memory bank that meet the constraint conditions are output, i.e., the optimal device layout and interface resource allocation scheme.

[0062] In summary, the present application provides an IMA system network transmission and interface conversion device layout and interface resource allocation method. The optimization method based on hierarchical immune algorithm is adopted. First, the redundant devices and redundant interfaces are distinguished according to the system architecture. Then, the hierarchical interface design strategy is executed for each redundant layer. The first layer optimization accesses other types of interfaces except network interfaces through interface conversion devices. The second layer optimization accesses the network interface of the backbone network through the network transmission device, including the network interface of the interface conversion device accessing the network transmission device. For device layout and interface resource allocation, the improved immune algorithm is used to optimize the spatial layout of the device. At the same time, mixed integer programming is used for dynamic allocation of access interfaces. Then, through the joint cost evaluation of layout cost and allocation cost, the spatial layout of the device and the interface allocation are completed. Through hierarchical design, dynamic constraint processing and cost weight balance are considered to achieve global optimization, solving the problem of IMA system network transmission and interface conversion device layout and interface resource allocation under multiple constraint conditions.

[0063] Although the present application has been disclosed with the preferred embodiments as above, it is not intended to limit the present application, and any person skilled in the art can make some modifications and improvements without departing from the spirit and scope of the present application. Therefore, the protection scope of the present application shall be defined by the claims.

Claims

1. A method for allocating interface resources in an IMA system based on a hierarchical immune algorithm, characterized in that, Includes the following steps: S1) Determine the onboard installation location according to the function of the airborne equipment, and clarify the interface type, number of interfaces, interface constraints and access cost of the network transmission and interface conversion equipment of the IMA system used by the airborne equipment interface; S2) Determine the number of network transmission devices and interface conversion devices in the IMA system, network the IMA system and airborne equipment, determine the total number of available interface types for each type of network transmission device and interface conversion device, and determine the layout restriction area; S3) Based on the interface resource requirements, network transmission equipment, and interface conversion equipment redundancy architecture design, first decouple and redundancy layer the system network equipment, interface equipment, and access interfaces. Then, for each redundancy layer, perform the first layer optimization first, followed by the second layer optimization, as follows: S4) First-level optimization: Based on the resource capabilities and constraints of the interface conversion device, a comprehensive optimization strategy is formulated for the layout of the interface conversion device and the allocation of other interfaces. A collaborative optimization method based on immune algorithm and mixed integer programming is executed. S5) Second layer optimization: The interface conversion device is one of the access network transmission devices. Based on the resource requirements of other network interfaces, the resource capabilities of network transmission devices and their constraints, a comprehensive optimization strategy for the layout of network transmission devices and the allocation of network interfaces is formulated, and a collaborative optimization method based on immune algorithm and mixed integer programming is executed.

2. The IMA system interface resource allocation method based on hierarchical immune algorithm as described in claim 1, characterized in that, Step S1 quantifies the access interface according to the following formula: The interface set of the access interface conversion device: IO m ={io1, io2, ..., io m There are a total of m interfaces that need to be connected to the IMA system interface conversion device; The set of interfaces for accessing network transmission devices: IO u ={io1, io2, ..., io u There are a total of u interfaces that need to be connected to the IMA system network transmission equipment; io i =(posi i ,type i ,num i ,cost i ,bind i ); positions i =(posi_x i ,posi_y i ,posi_z i ); Among them, io i posi represents the i-th access interface. i Indicates the location of the access interface, posi_x i posi_y i posi_z i Indicates the three-dimensional coordinates of this location; type i Indicates the type of the access interface, num i Indicates the number of access interfaces; cost i This represents the access cost coefficient for this type of access interface, bind. i This indicates the associated requirements for the access interface; The interfaces of the network transmission device include an A664 network interface and a TTE network interface. The interfaces of the interface conversion device include an A429 transmitting interface, an A429 receiving interface, an A825 interface, an analog interface, a discrete interface, and a sensor interface. For interface devices without special installation location requirements, after selecting the appropriate shortest distance for installation, the network interface type is connected to the network transmission device, and other types of interfaces are connected to the interface conversion device.

3. The IMA system interface resource allocation method based on hierarchical immune algorithm as described in claim 1, characterized in that, The device is quantified in step S2 according to the following formula: Interface conversion device set: IOM n ={iom1, iom2, ..., iom n There are a total of n interface conversion devices; Network transmission device set: IOM v ={iom1, iom2, ..., iom v There are a total of v network transmission devices; iom j =(iom_posi j ,max_type_1 j ,max_type_2 j ,...max_type_g j ); iom_posi j =(iom_p_x j ,iom_p_y j ,iom_p_z j ); Layout restriction area set: ZONE = {zone1, zone2, ..., zone...} p There are a total of p prohibited layout regions; zone s =(zone_type s ,zone_Center s ,zone_par1 s ,zone_par2 s ,zone_par3 s ); zone_Center s =(zone_p_x s ,zone_p_y s ,zone_p_z s ); Among them, iom j IOM_posi represents the j-th interface device in the IMA system. j Indicates the location of the interface device, iom_p_x j ,iom_p_y j ,iom_p_z j Indicates its three-dimensional coordinates; max_type_1 j max_type_2 j ...max_type_g j This indicates the total number of the first, second, ... g-th type interfaces of this interface device; zone s This represents the s-th layout constraint region within the layout space, represented by zone_type. s Indicates the type of the restricted area in this layout, zone_Center s This indicates the location of the restricted area of ​​the layout.

4. The IMA system interface resource allocation method based on hierarchical immune algorithm as described in claim 1, characterized in that, Steps S4 and S5 employ no-distribution zone constraints and device connection constraints. Each network transmission device or interface conversion device is located outside the no-distribution zone, and device connection constraints are imposed by controlling the sum of the interconnection distances of each interface conversion device or network transmission device.

5. The IMA system interface resource allocation method based on hierarchical immune algorithm as described in claim 1, characterized in that, The collaborative optimization method based on immune algorithm and mixed integer programming in steps S4 and S5 includes: S601: Antibody encoding and population initialization; S602: Affinity assessment based on joint costs; S603: Immune selection employs an elite retention and dynamic elimination mechanism. In each population update iteration, the affinity of each antibody is calculated, and the best antibodies are selected and stored in the memory bank. S604: Clonal Selection and Mutation; S605: Clonal inhibition; S606: New Antibodies and Population Renewal; S607: Termination and Output.

6. The IMA system interface resource allocation method based on hierarchical immune algorithm as described in claim 5, characterized in that, Step S601 includes: Encoding rule: The feasible solution to the problem is represented as a chromosome in the solution space through encoding. The chromosome represents an array of length equal to the total number of devices. Each gene position corresponds to an interface device and its location coordinates. When it is an interface conversion device, the gene value is ∈n. When it is a network transmission device, the gene value is ∈v, which represents the device number of that type. Constraint preprocessing: Initial solutions are generated based on forbidden regions constraints to reduce invalid searches; each individual in the generated population is randomly initialized, and each device location is checked to ensure it satisfies the forbidden region constraint, i.e., it is outside the forbidden region; Parameter settings: Define population size, mutation probability, and maximum number of iterations.

7. The IMA system interface resource allocation method based on hierarchical immune algorithm as described in claim 5, characterized in that, Step S602 includes: evaluating the merits of each individual solution using an affinity function, which is designed as a joint cost evaluation function. This function integrates the device location layout optimization cost with the interface access cost. The layout optimization cost includes device connection cost and no-access zone penalty cost. During the evolutionary process, solutions that do not meet the conditions are gradually eliminated, and the solution with the highest affinity is selected to achieve device layout and interface resource allocation. The affinity function is as follows: Fitness=α·cost_dist+β·cost_ penalty +γ·cost_ Allocate ； Where: α, β, γ Optimize through experiments; cost_dist : Indicates the cost of device connectivity; cost_ penalty : Represents the number of devices placed in the no-layout zone multiplied by the penalty coefficient, ensuring that the layout constraints are met; cost_ Allocate This represents the cost of allocating all interfaces to all interface conversion devices and network transmission devices. The cost of interface conversion devices is included in the calculation when network transmission devices are allocated and optimized.

8. The IMA system interface resource allocation method based on hierarchical immune algorithm as described in claim 7, characterized in that, Step S602 is in its respective optimization level cost_ Allocate The calculation is as follows: i. Define decision variable x i,j and y k,j Each interface is assigned to one interface device; x i,j = y k,j = ,Right now It belongs to one of the g types of interfaces provided by the interface device; ii. Set allocation constraints to assign interfaces with interface association requirements to the same interface device; define allocation weight factors based on a greedy sorting allocation strategy, sort all interfaces according to the weight factors, and allocate interfaces with larger weight factors first. Set a total limit on the number of interface types and allocate them to the interface devices (iom). j any type of interface i The sum of the interface resources does not exceed the total number of interface resources of the interface device, max_type_g j And any type of interface i The sum of the interface resources does not exceed the interface resource threshold of the interface device; iii. Set the objective function based on minimizing the allocation cost. The allocation cost for a single interface is defined as follows: cost_ io i This indicates the cost of connecting the interface to a certain interface device; cost_ I i =io_dist×num i ×cost i ; io_dist represents the distance from the access interface to the device connected to that interface, num i Indicates the number of access interfaces, cost i This represents the access cost coefficient of the access interface. cost_ Allocate This represents the cost of allocating all interfaces to all interface devices; cost_ Allocate = 。 9. The IMA system interface resource allocation method based on hierarchical immune algorithm as described in claim 5, characterized in that, Step S603 involves immune selection based on affinity, with each generation retaining the antibodies with the highest fitness as memory cells. A similarity function between antibodies is defined, and the distance between antibodies is calculated based on Hamming distance or affinity function. If the similarity is greater than a threshold, low-affinity antibodies are randomly eliminated. In step S604, Gaussian mutation or random mutation is used to perform targeted mutation on the clone, randomly perturbing the clone genes and constraining the boundaries of the mutated gene sites. In step S605, after the clonal mutation operation, the progeny antibodies generated by the clonal mutation are reselected to suppress antibodies with low affinity and retain antibodies with high affinity to enter a new antibody population. In step S606, random new antibodies are introduced and sorted by affinity together with the retained memory library antibodies and clonal mutation antibodies. The antibodies with the highest ranking are selected for population recombination to maintain a constant population size.

10. The IMA system interface resource allocation method based on hierarchical immune algorithm as described in claim 5, characterized in that, The stopping criterion in step S607 is that the number of iterations and / or the change in the optimal affinity value is less than a preset threshold. In step S607, the high affinity antibody that meets the constraint conditions in the memory is output.

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