SDN-fused multilayer QKD constellation model and key distribution routing algorithm building method

Abstract

The invention discloses an SDN-fused multilayer QKD constellation model and a key distribution routing algorithm building method, and relates to the technical field of quantum key distribution. According to the method, orbit distribution and dynamic characteristics of a satellite in a free space are deeply analyzed, a trusted relay quantum key distribution constellation model fusing GEO / MEO / LEO three-layer orbits is provided, and a software defined networking (SDN) technology is introduced into the model, so that centralized control and efficient management are realized, and the reliability of the system is improved. A self-adaptive quantum key flow aware routing algorithm (AQKAR) is designed on the basis of a trusted relay quantum key distribution constellation model fusing GEO / MEO / LEO three-layer tracks, so that a key distribution path is dynamically optimized; a simulation result shows that compared with a traditional LEO single-layer network and a GEO / LEO double-layer network, the framework provided by the invention has the advantages that the request success rate is remarkably improved, the end-to-end network delay is lower, and meanwhile, the algorithm provided by the invention can effectively improve the flexibility of the network under the condition that the network is extremely congested.

Description

Technical Field

[0001] The present invention relates to the technical field of quantum key distribution, and specifically to a method for building a multi-layer QKD constellation model and a key distribution routing algorithm integrating SDN. Background Art

[0002] Free-space quantum key distribution is a technology that uses the principles of quantum mechanics to securely generate and share encryption keys through the transmission of photons in free space.

[0003] Quantum Key Distribution (QKD) is an information encryption technology that uses the principles of quantum state non-cloning and measurement destructiveness to achieve secure key distribution. It can provide a secure key distribution mechanism that cannot be eavesdropped or cracked for both parties in communication. [1] In the BB84 protocol, single-photon signals are usually used to implement quantum key distribution. However, since the transmission loss of single-photon signals in optical fibers increases exponentially, it is difficult to avoid high loss and depolarization in long-distance transmission, which poses a challenge to the construction of optical fiber networks for quantum key distribution for intercontinental quantum secure communication. [2-3] Free-space Quantum Key Distribution (FSO QKD) will become a more effective solution in long-distance environments, providing ultra-long-distance quantum key security services worldwide. [4] . With the increasing number of intercontinental security services, countries around the world have begun to attach great importance to the research on large-scale quantum satellite networking and quantum key distribution technology. Among them, the research on how to build a quantum satellite constellation and how to formulate an end-to-end satellite key distribution routing algorithm is the key to the future practical application of quantum satellite key distribution technology.

[0004] At present, research on free-space quantum satellite key distribution related technologies has achieved certain results. Villoresi et al., a research team from the University of Padua in Italy [5] In 2008, the quantum communication experiment of single photon signal was successfully realized through the Low Earth Orbit (LEO) satellite, proving the feasibility of quantum key distribution between LEO satellite and the ground. [6] and another Italian research institute [7]In 2017 and 2018, they successfully detected and received single-photon signals that maintained quantum states through geostationary Earth Orbit (GEO) and medium Earth orbit (MEO) satellites, further verifying the feasibility of using high, medium and low orbit satellites for quantum key distribution. Subsequently, in 2019, Vergoossen et al. from the Center for Quantum Technology at the National University of Singapore [8] A satellite QKD constellation model is proposed. By establishing a key buffer in the link and using relay satellites to transmit quantum key pairs to ground stations, this model can provide low-latency symmetric keys between any two ground stations. 2020 Beijing University of Posts and Telecommunications, China Huang et al. [9] A dual-layer QKD network architecture combining geosynchronous orbit satellites and low earth orbit satellites is proposed, and a new joint GEO / LEO routing and key distribution algorithm is proposed for the new architecture. This method can improve the success rate of key relay services and is an effective key relay solution. Milo et al. 2021

[10] Aiming at the resource allocation problem in the QKD network of GEO and LEO satellites, an optimization algorithm is proposed to maximize the minimum key exchange amount and minimize the key consumption between ground stations by modeling the QKD network as a graph and converting it into a linear programming problem. This algorithm optimizes the effective allocation of quantum key resources to a certain extent, but in some cases it will lead to waste of network resources.

[11] The satellite-to-ground link selection problem was modeled as an undirected graph solution problem, and it was proposed to transform the inter-satellite routing problem into a maximum flow problem. In the same year, He et al., a research team from Beijing University of Posts and Telecommunications, China

[12] In order to solve the problem of how to provide keys for remote multicast services, a quantum satellite network with a special node structure is designed to achieve point-to-multipoint key distribution, and a point-to-multipoint satellite relay solution is proposed. The link weight is dynamically described through auxiliary topology, and a satellite relay tree is constructed. A multicast resource routing allocation algorithm based on satellite relay is proposed to improve the success rate of long-distance multicast requests. Federico and his team from the University of Rome in 2023

[13] The orbit design of QKD satellite constellations was carried out for different ground networks, aiming to maximize the minimum key length shared by the ground station network in a fixed time by optimizing the satellite orbit.

[14] Aiming at the problem that the dynamic characteristics of satellites lead to the lack of effective scheduling schemes between GEO / LEO satellites, a routing strategy based on topological abstraction is proposed to transform the dynamic network into a quasi-static network, and three new heuristic network scheduling algorithms are proposed. This method can effectively improve the success probability of long-distance QKD.

[0005] The above research has achieved certain results in constellation design, intersatellite link optimization, and key resource allocation for quantum satellite key distribution. However, it ignores the fact that in free space, the transmission distance of tens of thousands of kilometers will cause exponential attenuation in the generation rate of quantum keys, and does not take into account that long-distance signal transmission will cause large end-to-end communication delays, and does not formulate a centralized resource management plan for the limited intersatellite quantum key resources. Specifically, the quantum key generation rate in free space quantum key distribution is currently low, and the key generation rate is also affected by the transmission distance and changes exponentially, resulting in the inability to support high-intensity security business requests. At the same time, the end-to-end communication delay between the two communicating parties is generally high.

[0006] Therefore, a new solution to the above problems needs to be proposed. Summary of the invention

[0007] The purpose of the present invention is to provide a method for building a multi-layer QKD constellation model and a key distribution routing algorithm integrating SDN to solve the technical problems raised in the background technology.

[0008] To achieve the above object, the present invention provides the following technical solution: a method for building a multi-layer QKD constellation model integrating SDN, comprising at least the following steps:

[0009] S1: Setting a trusted relay quantum key distribution constellation model, wherein the trusted relay quantum key distribution constellation model is a three-layer orbit satellite network constellation model, giving full play to the characteristics of three orbit satellites: GEO, MEO and LEO;

[0010] S2: Based on S1, a multi-layer architecture and dynamic management strategy for quantum satellite optical networks are further proposed;

[0011] S3: Setting up a key resource model, introducing a quantum key pool as a cache of quantum keys, the quantum key pool is QKP, the QKP is used to store key pairs generated between each pair of quantum nodes, the keys are stored in the corresponding QKPs of the quantum nodes that appear in pairs, the keys in the QKP are provided to the encryption and decryption modules when a security service request arrives, and the key relay function is realized;

[0012] S4: key generation and consumption;

[0013] S5: Perform link status evaluation to better describe the number and update status of quantum keys in the topology.

[0014] Furthermore, the S1 at least comprises the following steps:

[0015] In the satellite network scenario model, the LEO layer of the quantum satellite network adopts a uniformly distributed Walker constellation, which includes orbital planes, each orbit has Q satellites evenly distributed, and a total of low-orbit satellites;

[0016] Each LEO satellite is connected to four adjacent LEO orbits, two of which are in the same orbit and the other two are in different orbits. Satellites in the same orbital layer can be connected via inter-satellite links, while satellites in different orbital layers can be connected via inter-orbit links to ensure cross-orbit quantum key transmission;

[0017] LEO satellites establish quantum communication with ground stations through satellite-to-ground links. MEO satellites can establish auxiliary communication links with LEO satellites. The auxiliary communication links are used to assist the LEO layer in complex quantum key routing and forwarding, and to directly establish communication links with ground stations to enhance the redundancy and reliability of the quantum key distribution network.

[0018] The GEO satellite has a wide coverage capability and is used as a monitoring satellite, responsible for collecting and forwarding topological resources and quantum key resource information of the LEO layer and the MEO layer to the ground station, so that the ground station can update the satellite node and its link resource information in time;

[0019] The ground stations are distributed all over the world, and end-to-end secure service requests are established between the ground stations. By establishing connections with free-space relay satellites, point-to-point key distribution is carried out between the relay satellites, thereby realizing ultra-long-distance quantum key distribution services.

[0020] Furthermore, the multi-layer architecture of the quantum satellite optical network in S2 includes at least an application layer, an SDN control layer, a data layer and a QKD layer;

[0021] The application layer is composed of ground stations, and ground users can generate security service requests;

[0022] The data layer has QKD capability, and the data layer includes a LEO layer and a MEO layer, the LEO layer is used to constitute a main QKD layer, and the MEO layer is used to serve as an auxiliary forwarding layer of the LEO data layer under the condition of scarce quantum key resources;

[0023] The SDN control layer has a function of dynamic network management in the constellation model, and the SDN control layer includes a main controller and a domain controller;

[0024] The main controller is deployed on the ground and is responsible for the global management and resource scheduling of the entire quantum communication network. The tasks of the main controller include at least link optimization, path planning and load balancing.

[0025] Furthermore, the S4 at least includes the following steps:

[0026] Since the connection relationship of satellite topology is periodic, the satellite topology is divided into n static topologies {G|G l , G2, G3, ..., G n}, where G is a set of n sub-topologies, G1~G n The n sub-topologies are divided into n sub-topologies, and these n different topologies correspond to n different time periods {T|t1~t2, t1~t2, ..., t n-1 ~t n}, where T is the topological period, t1~t2, ...., t n-1 ~t n For n time slots, use L (i，j) represents the quantum link between quantum node i and quantum node j in the satellite topology;

[0027] Assuming that any two connected nodes can perform QKD, the number of keys generated and consumed is related to the duration of the link connection, and the number of keys cached in QKP is related to the initial number of keys, the number of keys generated, and the number of keys consumed in QKP. For mathematical symbols, refer to Formula 1:

[0028]

[0029] Where K (i，j) (t) is the link L at time t (i，j) The number of keys of QKP in the network, t0 is the arrival time of the current network topology, t1 is the end time of the current network topology, C (i，j) is the number of keys that need to be consumed in a single link QKD, R (i，j) (t) is the link L at time t (i，j) The key generation rate, R (i，j) (t) can be expressed by referring to Formula 2:

[0030]

[0031] Where R max Denotes the maximum key generation rate in the key generation rate set of the links in the QKD network, D (i，j) (t) represents the link L (i，j) The distance at time t, D min is the shortest link distance in the link distance set.

[0032] Furthermore, the S5 at least includes the following steps:

[0033] By establishing a link key matrix K(t), refer to Formula 3, the matrix can represent the QKP resource status of each link at time t in real time;

[0034]

[0035] When performing global QKD, due to the volume of business requests and the complexity of the network, the quantum key flow in the link may include three situations: link key supply exceeds demand, link key supply is less than demand, and link anomaly.

[20] ;

[0036] The situation where the link key supply exceeds the demand is: when there is no abnormality in the link, the number of security service requests is small, the quantum key in the QKP will be continuously updated, and its quantum key generation rate will continue to be greater than the key consumption rate, refer to Formula 4:

[0037]

[0038] Where K (ij) (t) is the link L at time t (i，j) The number of keys in QKP, K (i，j) (t0) represents the initial quantum key quantity, represents the quantum key generation amount, is the quantum key consumption.

[0039] The situation where the link key supply is less than the demand is: when there is no abnormality in the link, the number of security service requests is large, the quantum key in the QKP will be continuously updated, and its quantum key generation rate is less than the key consumption rate, and it cannot continuously support the key service, refer to Formula 5:

[0040]

[0041] The link abnormality is: when the link is abnormal, the key quantity in the QKP will not be able to be updated, its initial quantum key will become invalid, and it will no longer be able to provide encryption and decryption services for the global QKP, see formula 6:

[0042]

[0043] At the same time, the network congestion index is introduced, which can reflect the density and dispersion of requests at different time points;

[0044] The network congestion index needs to consider the total number of business requests and the number of network requests at a certain moment to determine whether the requests are evenly distributed. The network congestion index is expressed in Formula 7:

[0045] NCI=μ x σ x R peak (7)

[0046] in:

[0047] μ xIndicates the average number of requests, which represents the average number of requests at each time point. The larger the mean value, the higher the load level at each moment.

[0048] σ x Indicates the standard deviation, which reflects the volatility of the request volume distribution. The larger the standard deviation, the more uneven the load distribution at different time points.

[0049] R peak R is the peak ratio, which is used to reflect the impact of the highest peak load on the overall load. The higher the peak ratio, the more sudden peaks there are. peak Refer to formula 8:

[0050]

[0051] In formula 8, δ is the normalization adjustment factor, (x1,x1,...,x T ) represents the sequence of the number of requests occurring in time period T, and N represents the total number of requests.

[0052] A method for constructing a key distribution routing algorithm, wherein the key distribution routing algorithm is based on a multi-layer QKD constellation model integrated with SDN, and is used to ensure that the multi-layer QKD constellation model integrated with SDN achieves efficient quantum key distribution under different network loads.

[0053] Furthermore, the input of the key distribution routing algorithm is x(S i ,d i ,k i ) and G(V t ,E t ,K0,R t );

[0054] Where x(S i , d i , k i ) represents the slave service node S i To the target node d i A quantum key distribution request, where k i is the number of keys requested;

[0055] Where G(V t , E t , K0, R t ) represents a graph model, where V t is a set of vertices, E t is the edge set, i.e., the optical link, K0 is the minimum number of available keys, R t A collection of transport resources.

[0056] Furthermore, the key distribution routing algorithm comprises at least the following steps:

[0057] S1: Initialize each optical link resource and initialize each optical link resource in the graph G(V t , E t , K0, R t );

[0058] S2: Calculate the routing set, calculate the routing set P from the service node s i to the target node d i and limit the maximum number of hops;

[0059] S3: Check if a route is found. If no suitable path is found in the routing set P, stop the request and report that no suitable path can be found;

[0060] S4: Traverse each shortest-hop path. For each shortest-hop path p i in the path set P;

[0061] S5: Check if a path is found: When the path discovery flag is True, perform the quantum key relay service;

[0062] S6: Handle the case where no path is found. In the case where no suitable path is found, add the MEO layer to the graph to assist the LEO layer in QKD and re-execute the above steps;

[0063] S7: Check the number of keys on the LEO layer link, and re-evaluate whether the LEO layer link meets the requirement of the number of keys. If the number of keys on the LEO layer link and the LEO ground station link is k i < K0, perform QKD using the MEO layer alone and re-execute the above steps;

[0064] S8: Perform the final path check. If the path flag is still False, report that the key distribution fails because there is no available path.

[0065] Furthermore, the S4 at least includes the following steps:

[0066] S4.1: Obtain the passed link and obtain the optical link passed in the path p i ;

[0067] S4.2: Check the number of keys on the link. When the number of keys k i on each link in the path < K0, set the path discovery flag to True, indicating that an available path is found, and then exit the loop;

[0068] S4.3: Continue to check other paths. If no suitable number of keys is found for the current path, continue to check the next path.

[0069] Compared with the prior art, the beneficial effects of the present invention are:

[0070] 1. This paper proposes a trusted relay quantum key distribution constellation model that integrates GEO / MEO / LEO three-layer orbits by deeply analyzing the orbital distribution and dynamic characteristics of satellites in free space, and introduces software-defined networking (SDN) technology into the model to achieve centralized control and efficient management.

[0071] 2. The present invention designs an adaptive quantum key stream-aware routing algorithm (AQKAR) based on a trusted relay quantum key distribution constellation model that integrates the GEO / MEO / LEO three-layer orbits to dynamically optimize the key distribution path; simulation results show that compared with the traditional LEO single-layer network and the GEO / LEO double-layer network, the architecture proposed in the present invention has a significant improvement in request success rate and lower end-to-end network latency. At the same time, in the case of extreme network congestion, the algorithm proposed in the present invention can effectively improve the network's resilience.

[0072] 3. The present invention proposes a quantum key distribution constellation model integrating GEO / MEO / LEO three-layer orbit satellites, and combines software-defined network (SDN) technology to design an adaptive quantum key stream-aware routing algorithm. The simulation results show that under the same key consumption, the average request success rate is 17.34% higher than that of the GEO / LEO double-layer network and 32.47% higher than that of the LEO single-layer network. At the same time, its communication delay is lower than that of the GEO / LEO double-layer and LEO single-layer networks. In addition, the request success rate of the adaptive key stream-aware routing algorithm is improved by 18.46% and 26.08% compared with the benchmark algorithms SA-MFP algorithm and Dijkstra algorithm, respectively. BRIEF DESCRIPTION OF THE DRAWINGS

[0073] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for describing the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative work.

[0074] Figure 1 It is a schematic diagram of a trusted relay constellation model in a three-layer orbit satellite network of the present invention;

[0075] Figure 2 Schematic diagram of QKD architecture in software-defined network of the present invention;

[0076] Figure 3 This is a schematic diagram of the QKD process based on a trusted relay of the present invention;

[0077] Figure 4A schematic diagram of a routing selection method under a MEO-LEO data layer combination according to the present invention;

[0078] Figure 5 This is a schematic diagram comparing the request success rates of different QKD architectures;

[0079] Figure 6 It is a schematic diagram of request success rate under different forwarding numbers of the present invention;

[0080] Figure 7 It is a schematic diagram of the delay performance under different architectures of the present invention;

[0081] Figure 8 It is a schematic diagram showing the results of different routing algorithms of the present invention under the MEO / LEO architecture;

[0082] Fig. 9 A schematic diagram showing a comparison of the anti-network congestion performance of the routing algorithm of the present invention. DETAILED DESCRIPTION

[0083] The technical solutions in the embodiments of the present invention will be described clearly and completely below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all the embodiments.

[0084] Embodiment 1:

[0085] This embodiment discloses a method for building a multi-layer QKD constellation model integrating SDN. The three-layer orbit satellite network constellation model proposed in the present invention fully utilizes the characteristics of the three orbit satellites of GEO / MEO / LEO, such as Figure 1 shown.

[0086] The method for building a multi-layer QKD constellation model integrating SDN includes at least the following steps:

[0087] S1: Set up a trusted relay quantum key distribution constellation model. The trusted relay quantum key distribution constellation model is a three-layer orbit satellite network constellation model, giving full play to the characteristics of GEO, MEO and LEO orbit satellites;

[0088] In the satellite network scenario model, the LEO layer of the quantum satellite network adopts a uniformly distributed Walker constellation, which includes orbital planes, each orbit has Q satellites evenly distributed, and a total of low-orbit satellites;

[0089] Each LEO satellite is connected to four adjacent LEO orbits, two of which are in the same orbit and the other two are in different orbits. Satellites in the same orbital layer can be connected via Inter Satellite Link (ISL), while satellites in different orbital layers can be connected via Inter-Orbital Link (IOL) to ensure cross-orbit quantum key transmission;

[0090] LEO satellites establish quantum communication with ground stations through Satellite Ground Links (SGL). MEO satellites can establish auxiliary communication links (Auxiliary Satellite Links, ASL) with LEO satellites. Auxiliary communication links are used to assist the LEO layer in complex quantum key routing and forwarding, and to directly establish communication links with ground stations to enhance the redundancy and reliability of the quantum key distribution network.

[0091] GEO satellites have a wide coverage capability and are used as monitoring satellites. They are responsible for collecting and forwarding topological resources and quantum key resource information of the LEO layer and MEO layer to the ground station, so that the ground station can update the satellite node and its link resource information in time.

[0092] Ground stations are distributed all over the world, and end-to-end secure service requests are established between the ground stations. By establishing connections with free-space relay satellites, point-to-point key distribution is carried out between relay satellites, thereby realizing ultra-long-distance quantum key distribution services.

[0093] S2: Based on S1, a multi-layer architecture and dynamic management strategy for quantum satellite optical networks are further proposed;

[0094] The multi-layer architecture of the quantum satellite optical network in S2 includes at least the application layer, SDN control layer, data layer and QKD layer, see Figure 2 ;

[0095] The application layer consists of ground stations, where ground users can generate secure service requests;

[0096] The data layer has QKD capability. The data layer includes the LEO layer and the MEO layer. The LEO layer is used to form the main QKD layer, and the MEO layer is used as an auxiliary forwarding layer for the LEO data layer under the condition of scarce quantum key resources.

[0097] The SDN control layer has the function of dynamic network management in the constellation model. The SDN control layer includes the main controller and the domain controller;

[0098] The main controller is deployed on the ground and is responsible for the global management and resource scheduling of the entire quantum communication network. The tasks of the main controller include at least link optimization, path planning and load balancing.

[0099] The main controller monitors the network status in real time and dynamically adjusts the resource allocation strategy of each domain according to the communication needs and satellite link status of different regions to ensure network stability and communication efficiency;

[0100] Since GEO satellites have a wide coverage area and are stationary relative to the earth, they can continuously and reliably manage and monitor LEO and MEO satellites over a large range. As domain controllers, GEO satellites can collect link status information between quantum satellites and report this data to the main controller. They are also responsible for executing instructions issued by the main controller within their coverage area, such as switching communication paths for quantum key distribution or reconfiguring resources. Hierarchical management between the main controller and the domain controller can effectively improve the flexibility and scalability of the network, reduce dependence on ground stations, and achieve more efficient cross-regional quantum key distribution.

[0101] S3: Set the key resource model;

[0102] Due to the low key generation rate, when the number of security service requests is large and the network is busy, there will usually be a shortage of quantum keys. [15-17] Therefore, the Quantum Key Pool (QKP) is introduced as a cache of quantum keys. QKP is mainly used to store the key pairs generated between each pair of quantum nodes. The keys are stored in the corresponding QKP of the quantum nodes that appear in pairs.

[18] The key in QKP can be provided to the encryption and decryption module when a security service request arrives, realizing the key relay function.

[0103] Figure 3 For the basic process of quantum satellite QKD based on trusted relays, the quantum key required for the security request from GS1 to GS2 is stored in the QKP of the corresponding link in advance. The key K can be sent from the GS1 relay to GS2 through continuous encryption and decryption on the trusted relay.

[0104] S4: key generation and consumption;

[0105] Satellites are highly dynamic and their topology will change over time, so it is not easy to describe a real-time updated satellite network topology. Since the connection relationship of satellite topology is periodic, the satellite topology is divided into n static topologies {G|G l , G2, G3, .., G n}

[19] , where G is a set of n sub-topologies, G1~G n The n sub-topologies are divided into n sub-topologies, and these n different topologies correspond to n different time periods {T|t1~t2, t1~t2, ..., t n-1 ~tn}, where T is the topological period, t1~t2, ...., t n-1 ~t n For n time slots, use L (i，j) represents the quantum link between quantum node i and quantum node j in the satellite topology;

[0106] Assuming that any two connected nodes can perform QKD, the number of keys generated and consumed is related to the duration of the link connection, and the number of keys cached in QKP is related to the initial number of keys, the number of keys generated, and the number of keys consumed in QKP. For mathematical symbols, refer to Formula 1:

[0107]

[0108] Where K (i，j) (t) is the link L at time t (i，j) The number of keys of QKP in the network, t0 is the arrival time of the current network topology, t1 is the end time of the current network topology, C (i，j) is the number of keys that need to be consumed in a single link QKD, R (i，j) (t) is the link L at time t (i，j) The key generation rate, R (i，j) (t) can be expressed by referring to Formula 2:

[0109]

[0110] Where R max Denotes the maximum key generation rate in the key generation rate set of the links in the QKD network, D (i，j) (t) represents the link L (i，j) The distance at time t, D min is the shortest link distance in the link distance set.

[0111] S5: Perform link status evaluation to better describe the number and update status of quantum keys in the topology;

[0112] By establishing a link key matrix K(t), refer to Formula 3, the matrix can represent the QKP resource status of each link at time t in real time;

[0113]

[0114] When performing global QKD, due to the volume of business requests and the complexity of the network, the quantum key flow in the link will include three situations: link key supply exceeds demand, link key supply is less than demand, and link anomalies;

[0115] The situation where the link key supply exceeds the demand is: when there is no abnormality in the link, the number of security service requests is small, the quantum key in QKP will be continuously updated, and its quantum key generation rate will continue to be greater than the key consumption rate, refer to formula 4:

[0116]

[0117] Where K (ij) (t) is the link L at time t (i，j) The number of keys in QKP, K (i，j) (t0) represents the initial quantum key quantity, represents the quantum key generation amount, is the quantum key consumption.

[0118] The situation where the link key supply is less than the demand is: when there is no abnormality in the link, the number of security service requests is large, the quantum key in QKP will be continuously updated, and its quantum key generation rate is less than the key consumption rate, and it cannot continuously support key services. Refer to Formula 5:

[0119]

[0120] The situation of link abnormality is: when the link is abnormal, the key quantity in QKP will not be able to be updated, its initial quantum key will become invalid, and it will no longer be able to provide encryption and decryption services for the global QKP, refer to formula 6:

[0121]

[0122] At the same time, the Network Congestion Index (NCI) is introduced, which can reflect the density and dispersion of requests at different time points;

[0123] The network congestion index needs to consider the total number of business requests and the number of network requests at a certain moment to determine whether the requests are evenly distributed. The network congestion index is expressed in Formula 7:

[0124] NCI=μ x σ x R peak (7)

[0125] in:

[0126] μ x Indicates the average number of requests, which represents the average number of requests at each time point. The larger the mean value, the higher the load level at each moment.

[0127] σ x Indicates the standard deviation, which reflects the volatility of the request volume distribution. The larger the standard deviation, the more uneven the load distribution at different time points.

[0128] R peak R is the peak ratio, which is used to reflect the impact of the highest peak load on the overall load. The higher the peak ratio, the more sudden peaks there are. peak Refer to formula 8:

[0129]

[0130] In formula 8, δ is the normalized adjustment factor, (x1, x1, .., x T ) represents the sequence of the number of requests occurring in time period T, and N represents the total number of requests.

[0131] Embodiment 2:

[0132] Based on the above embodiment 1, a method for building a key distribution routing algorithm is proposed;

[0133] In large-scale quantum key distribution networks, the dynamic changes in link key resources and the fluctuations in business demand place extremely high demands on the transmission efficiency and latency of the network. Especially in the case of high communication density and low latency of low-Earth orbit satellites, traditional single-layer network architectures often find it difficult to balance load and resource allocation, and cannot effectively respond to complex business requests and dynamic link states. In order to solve this problem, the present invention proposes an adaptive quantum key stream-aware routing algorithm (AQKAR), which aims to optimize the key distribution path by flexibly mobilizing key resources in multi-layer satellite networks, and ensure efficient quantum key distribution under different network load conditions.

[0134] The key distribution routing algorithm is based on a multi-layer QKD constellation model of SDN fusion, which is used to ensure that the multi-layer QKD constellation model of SDN fusion can achieve efficient quantum key distribution under different network loads.

[0135] Propose multi-layer satellite key routing:

[0136] Since the communication delay between LEO satellites and ground stations is relatively low, when the LEO layer has sufficient quantum key resources and the service demand is not high, the ground control center will give priority to the LEO data layer as the first access layer for key relay. Figure 4 As shown in (a), when an end-to-end secure communication request is generated between ground station S1 and ground station S2, the LEO layer will find a suitable access quantum satellite through the LEO-GS link, and the key information will be uploaded to the LEO satellite layer through the link. The controller will find an available inter-satellite link (ISL) in the LEO layer and pass the key information to the satellite connected to the target ground station S2 to complete the key distribution and service request transmission.

[0137] When the service requests are busy and the key resources of the link are scarce, the relay nodes of the LEO layer alone cannot bear the high-load service traffic. At this time, the ground control center will mobilize the key resources of the MEO data layer to assist the LEO data layer in relaying, such as Figure 4 (b) Although after finding a suitable access satellite at the LEO layer, the controller cannot find a path to the destination at the LEO layer due to insufficient key resources or abnormal paths, and will include the nodes at the MEO layer in the key distribution topology. After the key information is transmitted to the LEO layer, the ASL link is used to transmit the key information to the available quantum satellites at the MEO layer, and then a suitable inter-satellite path is found, and finally the key information is returned to the LEO layer through the ASL link and delivered to the destination ground station.

[0138] If the number of keys in the LEO-GS link is insufficient and the access link cannot be established through the LEO satellite, the MEO-GS link can also be used to set the access satellite to a MEO satellite. The MEO satellite will be used directly as the access node, and the key data will be transmitted to the destination ground station through the MEO-GS link. The specific process is shown in Figure 4 (c) Although the MEO-GS link has a higher latency and lower key generation rate due to the longer communication distance, this strategy can still effectively improve the success rate of the overall quantum key distribution network under the condition of limited resources.

[0139] In order to reduce the communication delay of the end-to-end network, the maximum forwarding number of the path is set in the algorithm. In the set of available paths from ground station S1 to S2, the controller will give priority to the path with the least hops. When the key resources in this path are lower than the number of keys required for the next business, the controller will switch to a path with a larger number of hops. If there is no longer a path that meets the maximum forwarding number in the LEO layer, the MEO layer will be introduced as an auxiliary relay. When the LEO layer recovers sufficient key resources, the data layer will switch back to the single-layer QKD of LEO to ensure that the delay of the key distribution network is minimized and resource utilization is maximized.

[0140] The input of the key distribution routing algorithm is x(S i , d i , k i ) and G(V t , E t , K0, R t );

[0141] Where x(S i , d i , k i ) represents the slave service node S i To the target node d i A quantum key distribution request, where k i is the number of keys requested;

[0142] Where G(V t , E t , K0, R t ) represents a graph model, where V t is a set of vertices, E t is the edge set, i.e., the optical link, K0 is the minimum number of available keys, R t A collection of transport resources.

[0143] The key distribution routing algorithm includes at least the following steps:

[0144] S1: Initialize each optical link resource. t , E t , K0, R t ) initialize each optical link resource;

[0145] S2: Calculate the routing set and calculate the slave service node s i To the target node d i The routing set P and limit the maximum number of hops;

[0146] S3: Check whether the route is found. If no suitable path is found in the route set P, stop the request and report that no suitable path can be found.

[0147] S4: Traverse each shortest hop path, for each shortest hop path p in the path set P i ;

[0148] S5: Check whether the path is found: When the path discovery flag is True, the quantum key relay service is executed;

[0149] S6: handle the case where no path is found, add a MEO layer to the graph to assist the LEO layer in performing QKD if no suitable path is found, and re-execute the above steps;

[0150] S7: Check the number of keys of the LEO layer link and evaluate again whether the LEO layer link meets the requirement of the number of keys. If the number of keys of the LEO layer link and the LEO ground station link is k i <K0, use the MEO layer alone for QKD and repeat the above steps;

[0151] S8: Perform a final path check. If the path flag is still False, report that the key distribution failed because there is no available path.

[0152] S4 at least includes the following steps:

[0153] S4.1: Get the passed links and path p i The optical link passing through;

[0154] S4.2: Check the number of keys on the link. When the number of keys k on each link in the path i < K0, set the path discovery flag to True, indicating that an available path has been found, and then exit the loop;

[0155] S4.3: Continue to check other paths. If the appropriate number of keys is not found for the current path, continue to check the next path.

[0156] To elaborate on the implementation mechanism of the Adaptive Quantum Key Flow Aware Routing Algorithm (AQKAR), the present invention provides the pseudocode of this algorithm. The pseudocode demonstrates the process of AQKAR dynamically adjusting key resources and optimizing route selection in a multi-layer satellite network. The pseudocode of this algorithm is as follows:

[0157]

[0158] The time complexity analysis of the AQKAR algorithm shows that in the worst case, the complexity of the algorithm is O(E + V + h|P|), where E and V are the number of edges and nodes in the graph G(V t , E t , K0, R t ), h represents the maximum number of hops of the path, and |P| represents the number of calculated paths. In the worst case, the algorithm needs to traverse all nodes and edges to determine the available path set P, which leads to an increase in complexity. On the other hand, in general cases, although the formal complexity of the algorithm is still O(E + V + h|P|), in practical applications, the number of paths |P| and the maximum number of hops h are usually small, and the actual running time of the algorithm is often better than the worst case.

[0159] Based on the above two embodiments, the following experimental verification is further proposed:

[0160] 1. Experimental environment and parameter settings

[0161] To verify the effectiveness of the quantum key distribution model and its AQKAR algorithm proposed by the present invention, a satellite architecture of orbital satellites was constructed in the STK software, and 6 ground stations were set up globally. The specific simulation parameters are shown in Table 1. Through the API provided by STK, the visibility adjacency matrix of satellites and ground facilities was exported, and simulation tests were carried out in the SDN professional network simulation software. In the experiment, it was set that the arrival times of 20,000 service requests follow a Poisson distribution within a certain time, and all experimental data are the averages taken after multiple experiments.

[0162] Table 1 Experimental parameter settings

[0163]

[0164] 2. Experimental results analysis

[0165] Figure 5 The performance of the success probability of quantum satellite network topology relay service under different service request volumes under different key consumption conditions is shown. The results show that as the number of requests increases, the success probability of each request gradually decreases, and the increase in key consumption further leads to a decrease in the overall success probability of each request. Further observations show that under the same key consumption, especially when the number of requests is large, the performance of the MEO / LEO network is significantly better than that of the GEO / MEO network. When the key consumption is 3 to 5 and the number of requests is 9,000, the success probability of the GEO / LEO network begins to be lower than that of the MEO / LEO network. As the key consumption increases to 4 to 6 and the number of requests drops to 6,000, the success probability of the GEO / LEO network is lower than that of the MEO / LEO network again. When the key consumption is 5 to 7, this difference becomes obvious when the number of requests reaches 5,000. This situation mainly occurs because of the difference in communication distance between the GEO / LEO link and the MEO / LEO link. Since the generation rate of quantum keys is inversely proportional to the communication distance between the two quantum nodes, the longer the communication distance, the lower the key generation rate. The communication distance between high-orbit satellites and low-orbit satellites is tens of thousands of kilometers, so as the service key consumption increases, its performance degradation will accelerate. And under higher key consumption, the time point when performance degradation occurs is also correspondingly advanced. Simulation results show that under the same key consumption, the average request success rate of the MEO / LEO double-layer network is 17.34% higher than that of the GEO / LEO double-layer network, and 32.47% higher than that of the LEO single-layer network.

[0166] Flexible scheduling of key resources between quantum satellite nodes is a key factor affecting the success rate of quantum key relay services. The number of routing jumps will directly affect the number of key resources in the routing path between Alice and Bob. If a lower value is set for the maximum number of hops of the path, the number of shared routing paths that can be found between Alice and Bob will also be reduced. As the number of relay requests between Alice and Bob continues to increase, and when the link key generation rate between quantum satellite nodes is less than the link key consumption, the link QKP resources between quantum satellite nodes will decrease rapidly, which will in turn affect the request success rate between Alice and Bob. On the contrary, gradually relaxing the limit on the maximum number of hops of the path will enable Alice and Bob to find more shared routing paths, thereby dispersing the network load on the path with fewer hops and improving the overall success rate of the relay service.

[0167] Figure 6The performance of the LEO single-layer network and the MEO / LEO double-layer network under different maximum number of routing hops is shown. The results show that, whether it is a single-layer or double-layer network, as the load increases, the relay service success rate gradually decreases. And the relay service success rate of the two topological architectures will be greatly improved when the maximum number of hops increases. For the double-layer network, when the maximum number of hops increases to 6, the relay service success rate is still close to 1 when the load is 5000. However, in the single-layer network architecture, when the maximum number of hops is 6, the service success rate can only reach 1 when the number of visits is less than 1000. Under the same maximum number of hops, the relay service success rate of the double-layer network is always higher than that of the single-layer network. This is because the double-layer QKD network has higher key resource reserves and key generation rate per unit time in the physical layer than the single-layer network, resulting in its superior performance. When the maximum number of hops of the single-layer network increases from 4 to 5, the relay service success rate increases by 29.1%; when it increases from 5 to 6, the success rate increases by 13.1%. Correspondingly, the success rate of the two-layer network increased by 32.4% when the maximum number of hops increased from 4 to 5, and further increased by 20.7% when it increased from 5 to 6. It can be seen that increasing the maximum number of hops has a significantly higher gain on the two-layer network than on the single-layer network.

[0168] The purpose of limiting the maximum number of forwarding is to control the service delay between Alice and Bob. Figure 7 (a) shows the average delay performance between Alice and Bob in the MEO / LEO dual-layer network under different maximum forwarding numbers. Experimental data show that even under the same maximum number of hops, as the number of requests increases, the cumulative effect of network congestion and satellite processing delay will cause the average delay of a single service to increase, thereby increasing the overall service delay. In addition, increasing the maximum forwarding number does not lead to a linear increase in service delay. When the maximum forwarding number increases from 4 to 5, the span of the average delay increase is the largest, and then the span of the average delay increase gradually decreases as the maximum forwarding number increases. This shows that when performing global quantum key distribution services, the path with a routing forwarding number of 5 is the most. On this basis, increasing the forwarding number can further increase the success probability of QKD at the cost of a smaller delay, thereby improving the elasticity and stability of the network.

[0169] Figure 7(b) is a delay comparison of the LEO single-layer network, MEO / LEO, and GEO / LEO double-layer network under the routing algorithm with a fixed maximum forwarding number of 6. The service delay of the MEO / LEO double-layer network is smaller than that of the GEO / LEO double-layer network under all loads. This is the result of the GEO / LEO two-layer network having a longer communication distance than the MEO / LEO double-layer network. On the other hand, the MEO / LEO double-layer network has a MEO network layer farther away from the ground station than the LEO single-layer network, and the delay over the communication distance will be higher than the LEO single-layer key distribution network. However, the single-layer network has low overload resistance and network elasticity. When the number of visits increases dramatically, the network is more prone to congestion, and the processing delay of the quantum node will be greater than that of the double-layer network. From the figure, we can see that when the number of visits is 1,000, the average latency of the LEO single-layer network and the MEO / LEO double-layer network is close, but as the number of network requests increases, the latency difference between the two gradually increases. When the number of requests reaches 10,000, the average latency difference between the LEO single-layer network and the MEO / LEO double-layer network reaches about 30ms. By comparing the GEO / LEO and LEO networks, when the number of requests reaches 5,000, the latency of the LEO single-layer network even gradually exceeds that of the GEO / LEO network.

[0170] In the experiment, the shortest path algorithm (Dijkstra) and the maximum flow algorithm (SA-MFP) were selected as benchmark algorithms. Figure 8 (a) shows the performance of the three algorithms under different loads. The results show that the AQKAR algorithm performs best, followed by the SA-MFP algorithm, while the Dijkstra algorithm performs worst under high load conditions, especially in the early stages, where there is a significant performance degradation. The AQKAR algorithm can flexibly call the key resources of the intersatellite QKD data layer and can flexibly change under the highly dynamic satellite topology. The SA-MFP algorithm is a maximum flow algorithm. It is difficult for the algorithm to achieve real-time updates under the highly dynamic satellite topology. When the network load is high or congested, the path update lag will further reduce the utilization of quantum key resources. The experimental results show that the AQKAR algorithm has an average request success rate that is 18.46% higher than the SA-MFP algorithm and 26.08% higher than the Dijkstra algorithm.

[0171] Figure 8(b) shows the average communication delay of the AQKAR algorithm, SA-MFP algorithm and Dijkstra algorithm under different business request volumes. It can be found that the average delay of the AQKAR algorithm is significantly lower than that of the other two algorithms, and the delay effect of the Dijkstra algorithm is the worst. This is because the AQKAR algorithm calls quantum key resources in layers and gives priority to calling data layers with lower orbit heights. The other two algorithms did not take this into consideration, and their own routing mechanisms still have their own shortcomings. From the analysis of the figure, it is found that when the network request volume is large, the delay of the other two algorithms (especially the Dijkstra algorithm) increases significantly faster than the AQKAR algorithm, and their overall delay performance is not as good as the AQKAR algorithm.

[0172] In order to verify the stability of the AQKAR algorithm under QKD network congestion, the performance of the AQKAR algorithm, SA-MFP algorithm and Dijkstra algorithm in the NCI range of [0.2, 0.5] were compared. Fig. 9 (a) shows the results of the three algorithms when the number of visits is 4000. The success probability of the AQKAR algorithm in the [0.2, 0.5] NCI range remains at around 0.87 without showing significant changes. In contrast, the success probability of the SA-MFP algorithm decreases as the network congestion increases. The initial performance of the Dijkstra algorithm is not as good as the previous two algorithms, and it shows a greater decay rate after the congestion value increases. When the number of visits increases to 10,000, as shown in Fig. 9 As shown in (b), the success probability of the AQKAR algorithm begins to slowly decrease, indicating that it still maintains a certain stability under network congestion. Compared with the SA-MFP algorithm, when NCI = 0.2, the success rate of the AQKAR algorithm is about 0.05 higher than that of the SA-MFP algorithm, and when NCI = 0.5, it is about 0.1 higher. These results show that the stability of the AQKAR algorithm in a network congestion environment is better than that of the SA-MFP and Dijkstra algorithms.

[0173] In summary:

[0174] The present invention proposes a trusted relay constellation model based on the GEO / MEO / LEO three-layer orbit for free-space quantum key distribution, and combines it with software-defined network technology. In order to ensure that the model achieves efficient quantum key distribution under different network loads, an adaptive key stream-aware routing algorithm (AQKAR algorithm) is designed. The simulation results show that under the same key consumption, the average request success rate of the MEO / LEO double-layer network is 17.34% higher than that of the GEO / LEO double-layer network and 32.47% higher than that of the LEO single-layer network; at the same time, under the same routing algorithm, the average delay of the MEO / LEO double-layer network is lower than that of the GEO / LEO double-layer and LEO single-layer networks. In addition, the request success rate of the AQKAR algorithm is improved by 18.46% compared with the SA-MFP algorithm, and by 26.08% compared with the Dijkstra algorithm, and it can flexibly call key resources at different layers and between layers, effectively reducing network overhead.

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[0196] It will be apparent to those skilled in the art that the invention is not limited to the details of the exemplary embodiments described above and that the invention can be implemented in other specific forms without departing from the spirit or essential features of the invention. Therefore, the embodiments should be considered exemplary and non-limiting in all respects, and the scope of the invention is defined by the appended claims rather than the foregoing description, and it is intended that all variations falling within the meaning and scope of the equivalent elements of the claims be included in the invention. Any reference numeral in a claim should not be considered as limiting the claim to which it relates.

Claims

1. A method for building a multi-layer QKD constellation model integrating SDN, characterized by: At least the following steps are included: S1: Setting a trusted relay quantum key distribution constellation model, wherein the trusted relay quantum key distribution constellation model is a three-layer orbit satellite network constellation model, giving full play to the characteristics of three orbit satellites: GEO, MEO and LEO; S2: Based on S1, a multi-layer architecture and dynamic management strategy for quantum satellite optical networks are further proposed; S3: Setting up a key resource model, introducing a quantum key pool as a cache of quantum keys, the quantum key pool is QKP, the QKP is used to store key pairs generated between each pair of quantum nodes, the keys are stored in the corresponding QKPs of the quantum nodes that appear in pairs, the keys in the QKP are provided to the encryption and decryption modules when a security service request arrives, and the key relay function is realized; S4: key generation and consumption; S5: Perform link status evaluation to better describe the number and update status of quantum keys in the topology.

2. The method for building a multi-layer QKD constellation model integrating SDN according to claim 1, characterized in that: The S1 at least comprises the following steps: In the satellite network scenario model, the LEO layer of the quantum satellite network adopts a uniformly distributed Walker constellation, which includes orbital planes, each orbit has Q satellites evenly distributed, and a total of low-orbit satellites; Each LEO satellite is connected to four adjacent LEO orbits, two of which are in the same orbit and the other two are in different orbits. Satellites in the same orbital layer can be connected via inter-satellite links, while satellites in different orbital layers can be connected via inter-orbit links to ensure cross-orbit quantum key transmission; LEO satellites establish quantum communication with ground stations through satellite-to-ground links. MEO satellites can establish auxiliary communication links with LEO satellites. The auxiliary communication links are used to assist the LEO layer in complex quantum key routing and forwarding, and to directly establish communication links with ground stations to enhance the redundancy and reliability of the quantum key distribution network. The GEO satellite has a wide coverage capability and is used as a monitoring satellite, responsible for collecting and forwarding topological resources and quantum key resource information of the LEO layer and the MEO layer to the ground station, so that the ground station can update the satellite node and its link resource information in time; The ground stations are distributed all over the world, and end-to-end secure service requests are established between the ground stations. By establishing connections with free-space relay satellites, point-to-point key distribution is carried out between the relay satellites, thereby realizing ultra-long-distance quantum key distribution services.

3. The method for building a multi-layer QKD constellation model integrating SDN according to claim 2, characterized in that: The multi-layer architecture of the quantum satellite optical network in S2 includes at least an application layer, an SDN control layer, a data layer and a QKD layer; The application layer is composed of ground stations, and ground users can generate security service requests; The data layer has QKD capability, and the data layer includes a LEO layer and a MEO layer, the LEO layer is used to constitute a main QKD layer, and the MEO layer is used to serve as an auxiliary forwarding layer of the LEO data layer under the condition of scarce quantum key resources; The SDN control layer has a function of dynamic network management in the constellation model, and the SDN control layer includes a main controller and a domain controller; The main controller is deployed on the ground and is responsible for the global management and resource scheduling of the entire quantum communication network. The tasks of the main controller include at least link optimization, path planning and load balancing.

4. The method for building a multi-layer QKD constellation model integrating SDN according to claim 3 is characterized in that: The S4 at least comprises the following steps: Since the connection relationship of satellite topology is periodic, the satellite topology is divided into n static topologies {G|G1,G2,G3,...,G n }, where G is a set of n sub-topologies, G1~G n The n sub-topologies are divided into n sub-topologies, and these n different topologies correspond to n different time periods {T|t1~t2,t1~t2,...,t n-1 ~t n }, where T is the topological period, t1~t2,....,t n-1 ~t n For n time slots, use L (i,j) represents the quantum link between quantum node i and quantum node j in the satellite topology; Assuming that any two connected nodes can perform QKD, the number of keys generated and consumed is related to the duration of the link connection, and the number of keys cached in QKP is related to the initial number of keys, the number of keys generated, and the number of keys consumed in QKP. For mathematical symbols, refer to Formula 1: Where K (i,j) (t) is the link L at time t (i,j) The number of keys of QKP in the network, t0 is the arrival time of the current network topology, t1 is the end time of the current network topology, C (i,j) is the number of keys that need to be consumed in a single link QKD, R (i,j) (t) is the link L at time t (i,j) The key generation rate, R (i,j) (t) can be expressed by referring to Formula 2: Where R max Denotes the maximum key generation rate in the key generation rate set of the links in the QKD network, D (i,j) (t) represents the link L (i,j) The distance at time t, D min is the shortest link distance in the link distance set.

5. The method for building a multi-layer QKD constellation model integrating SDN according to claim 4, characterized in that: The S5 at least comprises the following steps: By establishing a link key matrix K(t), refer to Formula 3, the matrix can represent the QKP resource status of each link at time t in real time; When performing global QKD, due to the volume of business requests and the complexity of the network, the quantum key flow in the link will include three situations: link key supply exceeds demand, link key supply is less than demand, and link anomalies; The situation where the link key supply exceeds the demand is: when there is no abnormality in the link, the number of security service requests is small, the quantum key in the QKP will be continuously updated, and its quantum key generation rate will continue to be greater than the key consumption rate, refer to Formula 4: Where: K (ij) (k) is the link L at time t (i,j) The number of keys in QKP, K (i,j) (t0) represents the initial quantum key quantity, represents the quantum key generation amount, is the quantum key consumption; The situation where the link key supply is less than the demand is: when there is no abnormality in the link, the number of security service requests is large, the quantum key in the QKP will be continuously updated, and its quantum key generation rate is less than the key consumption rate, and it cannot continuously support the key service, refer to Formula 5: The link abnormality is: when the link is abnormal, the key quantity in the QKP will not be able to be updated, its initial quantum key will become invalid, and it will no longer be able to provide encryption and decryption services for the global QKP, see formula 6: At the same time, the network congestion index is introduced, which can reflect the density and dispersion of requests at different time points; The network congestion index needs to consider the total number of business requests and the number of network requests at a certain moment to determine whether the requests are evenly distributed. The network congestion index is expressed in Formula 7: NCI=μ x σ x R peak (7) in: μ x Indicates the average number of requests, which represents the average number of requests at each time point. The larger the mean value, the higher the load level at each moment. σ x Indicates the standard deviation, which reflects the volatility of the request volume distribution. The larger the standard deviation, the more uneven the load distribution at different time points. R peak R is the peak ratio, which is used to reflect the impact of the highest peak load on the overall load. The higher the peak ratio, the more sudden peaks there are. peak Refer to formula 8: In formula 8, δ is the normalization adjustment factor, (x1,x1,...,x T ) represents the sequence of the number of requests occurring in time period T, and N represents the total number of requests.

6. A method for constructing a key distribution routing algorithm, for constructing a multi-layer QKD constellation model of an SDN-integrated system as described in any one of claims 1 to 5, characterized in that: The key distribution routing algorithm is based on a multi-layer QKD constellation model of integrated SDN, and is used to ensure that the multi-layer QKD constellation model of integrated SDN achieves efficient quantum key distribution under different network loads.

7. The method for constructing a key distribution routing algorithm according to claim 6, characterized in that: The input of the key distribution routing algorithm is x(S i ,d i ,k i ) and G(V t ,E t ,K0,R t ); Where x(S i ,d i ,k i ) represents the slave service node S i To the target node d i A quantum key distribution request, where k i is the number of keys requested; Where G(V t ,E t ,K0,R t ) represents a graph model, where V t is a set of vertices, E t is the edge set, i.e., the optical link, K0 is the minimum number of available keys, R t A collection of transport resources.

8. The method for constructing a key distribution routing algorithm according to claim 7, characterized in that: The key distribution routing algorithm comprises at least the following steps: S1: Initialize each optical link resource. t ,E t ,K0,R t ) initialize each optical link resource; S2: Calculate the routing set and calculate the slave service node s i To the target node d i The routing set P and limit the maximum number of hops; S3: Check whether the route is found. If no suitable path is found in the route set P, stop the request and report that no suitable path can be found. S4: Traverse each shortest hop path, for each shortest hop path p in the path set P i ; S5: Check whether the path is found: When the path discovery flag is True, the quantum key relay service is executed; S6: handle the case where no path is found, add a MEO layer to the graph to assist the LEO layer in performing QKD if no suitable path is found, and re-execute the above steps; S7: Check the number of keys of the LEO layer link, and re-evaluate whether the LEO layer link meets the requirement of the number of keys. If the number of keys of the LEO layer link and the LEO ground station link is k i < K0, use the MEO layer alone for QKD, and re-execute the above steps; S8: Perform a final path check. If the path flag is still False, report that the key distribution failed because there is no available path.

9. The method for building a multi-layer QKD constellation model and a key distribution routing algorithm for integrating SDN according to claim 8, characterized in that: The S4 at least comprises the following steps: S4.1: Get the passed links and path p i The optical link passing through; S4.2: Check the number of keys on the link. When the number of keys k on each link in the path i < K0, set the path discovery flag to True, indicating that an available path has been found, and then exit the loop; S4.3: Continue to check other paths. If the current path does not find a suitable number of keys, continue to check the next path.

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