Inter-satellite routing method and system based on hop priority and load awareness

Abstract

This invention discloses an inter-satellite routing method and system based on hop count priority and load awareness, primarily addressing the problems of unreliable long-distance service transmission latency and unbalanced inter-satellite service load in existing technologies. The method includes: dividing satellite operating time into consecutive equal-length slices and executing tasks on a single time slice period; predicting ground traffic for the next time slice and generating a transmission demand matrix for ground traffic services in the next time slice; predicting the topology map of the next time slice based on satellite orbit ephemeris, and calculating the minimum hop count between the source and destination nodes of all services on this map; sorting the service transmission demands according to the minimum hop count and service transmission traffic to obtain a service transmission demand queue, and sequentially extracting the service with the maximum hop count to calculate its optimal path, updating the link weights of the topology map according to the traffic load of this service; and converting the calculated path set into a routing instruction set, which is then sent to the routing control layer to guide service forwarding. This invention offers low long-distance service transmission latency, balanced inter-satellite service load, and high inter-satellite service transmission reliability, making it suitable for large-scale inter-satellite network routing scenarios.

Description

Technical Field

[0001] This invention belongs to the field of satellite communication network technology, specifically relating to an inter-satellite routing method and system, which can be used for the construction of large-scale, highly dynamic low-Earth orbit satellite constellation networks and load balancing paths. Background Technology

[0002] With the continued growth of global communication demands and the rapid development of aerospace technology, large-scale low-Earth orbit satellite constellations, such as Starlink and OneWeb, are playing an increasingly important role in providing global broadband coverage, communication in maritime and remote areas, space-based Internet of Things (IoT), and emergency support. In these networks, a large number of satellite nodes are interconnected through inter-satellite laser or microwave links, forming a high-speed, topology-variable space-based network that carries massive amounts of data services injected from the ground.

[0003] In low-Earth orbit satellite networks, due to the limited coverage of a single satellite and the constrained distance of inter-satellite links, most cross-regional communication services must achieve end-to-end transmission through multi-hop relay forwarding. To cope with dynamic topology changes and achieve efficient routing, existing solutions typically rely on static shortest path algorithms such as Dijkstra's algorithm for routing calculation. This algorithm treats the dynamic network as a static topology within each fixed time slice and calculates the optimal path based on static metrics such as hop count or fixed propagation delay. The fundamental flaw of this algorithm is that it completely ignores real-time changes in service load. The calculated path remains fixed throughout the entire time slice, causing traffic from ground hotspots to continuously converge on a few theoretically optimal links. This easily leads to local congestion, causing queuing delay spikes and service jitter, while other parallel links in the network are under light load, resulting in severely uneven resource utilization. Furthermore, this solution treats all services equally, putting long-distance, high-hop-count services with longer paths and greater sensitivity to congestion at a natural disadvantage in resource competition with short-distance services, making it difficult to obtain guaranteed quality of service.

[0004] Patent document CN201210024919.5 discloses a constellation routing algorithm based on incremental link cost. It calculates k paths for a service to be routed, selects m critical paths prone to congestion based on constellation topology and service distribution factors, quantifies the impact of service transmission on path congestion as link cost, and designs a congestion control mechanism to redesign routes for services whose transmission paths have reached congestion thresholds. While this method can effectively optimize local link congestion caused by uneven load distribution, it suffers from high computational complexity due to calculating k shortest paths for each route to be routed, making it unsuitable for the scarce computing resources of satellite networks. Furthermore, the need to recalculate service transmission paths after a path reaches the congestion threshold leads to congestion on other available paths, lacking global planning. Additionally, the lack of protection measures for multi-hop transmission services may cause paths for multi-hop transmission services to repeatedly become congested, requiring recalculation and failing to achieve global route convergence.

[0005] In summary, existing technologies struggle to simultaneously meet the demands of large-scale, highly dynamic satellite networks for rapid route convergence, low computational complexity, and high reliability. Traditional routing algorithms rely on static shortest paths, making it difficult to adjust transmission paths based on terrestrial services. The reuse of a single link by multiple paths significantly increases the probability of network congestion. Furthermore, the lack of differentiation between long-distance and short-distance transmission services results in short-distance transmission services enjoying sufficiently short transmission delays while long-distance transmission services endure longer delays, ultimately failing to guarantee the transmission performance of service packets within the satellite network. Summary of the Invention

[0006] The purpose of this invention is to address the shortcomings of the prior art by proposing an inter-satellite routing calculation method based on hop count priority and load awareness, so as to ensure the latency requirements of long-distance transmission services, reduce the probability of communication link congestion, and improve the reliability of inter-satellite service transmission.

[0007] The technical approach to achieving the objective of this invention is as follows: by prioritizing route calculation for long-distance, high-hop-count services, the latency requirements of long-distance transmission services are guaranteed; by dynamically mapping ground traffic load to inter-satellite links, the latency cost caused by planned path service transmission is added to the topology map, and service routing calculation is performed on the dynamic topology map to reduce the probability of communication link congestion; and by planning and load balancing route calculation for each transmission service, the reliability of inter-satellite service transmission is improved.

[0008] Based on the above ideas, the technical solution of the present invention includes the following:

[0009] 1. An inter-satellite routing method based on hop count priority and load awareness, characterized in that it includes:

[0010] (1) Based on the minimum event response time required for satellite motion, link establishment / interruption and service transmission failure recovery in the satellite network, the system running time is divided into a series of continuous equal-length slices;

[0011] (2) Divide the ground service area into regular geographic grids, predict the total inbound and outbound traffic of each grid in the next time slice for the current time slice, and generate the service transmission demand matrix of inter-satellite services in the next time slice by combining the mapping relationship between grids and satellites. ;

[0012] (3) Based on the satellite's orbital ephemeris, predict the static topology G of the inter-satellite network in the next time slice, and then analyze the service transmission demand matrix. Each non-zero element in The defined service transmission requirements are used to calculate the source node on the topology graph. to the destination node Minimum number of hops between ;

[0013] (4) Minimum number of jumps Using the primary sorting key and the secondary sorting key, the service transmission traffic size is used to categorize the service transmission demand matrix. All service transmission requirements are sorted in descending order to obtain the service transmission requirement queue. ;

[0014] (5) From the service transmission demand queue Extract the service with the maximum hop count to be calculated from the current data, and calculate the optimal path for this service in the static network topology graph of the next time slice. And update the link weights in the topology graph based on the traffic load of the service;

[0015] (6) Repeat (5) until the queue is complete. Once the path planning for all service transmission requirements is completed, the set of end-to-end transmission paths for all service transmission requirements in the next time slice is obtained, and this set is converted into a routing instruction set and sent to the routing control layer to guide the services in transmission.

[0016] Furthermore, in step (4), the service transmission requirements are sorted to obtain a service transmission requirement queue. It includes:

[0017] 4a) For the traffic matrix In The service transmission requirements defined by the non-zero elements are based on the minimum number of hops from the source node to the destination node. All service transmission requirements are sorted in descending order;

[0018] 4b) When the minimum hop counts of two service transmission requirements are the same, the service transmission requirement index shall be used. Sort the data in descending order, prioritizing the calculation of the optimal transmission path for high-volume services;

[0019] 4c) After sequentially performing the sorting steps described in 4a) and 4b), an ordered queue of service transmission requirements is obtained. :

[0020] Furthermore, in (5), the service transmission demand queue Extract the service with the maximum hop count to be calculated from the current data, and calculate the optimal path for this service in the static network topology graph of the next time slice. Its implementation includes:

[0021] 5a) Based on propagation delay Processing delay Transmission delay and queuing delay Calculate the weight of each link L in the static network topology graph. ;

[0022] 5b) Weights for each link The network is updated to obtain a static weighted topology graph.

[0023] 5c) From the service transmission demand queue Extract the first service transmission request with the highest hop count from the header. ;

[0024] 5d) For the first service transmission requirement The single-source shortest path algorithm is used to calculate the shortest path from the source node on the static weighted topology graph of the network. to the destination node Optimal path .

[0025] Furthermore, the update of the link weights in the topology graph based on the traffic load of the service in step (5) includes the following implementation:

[0026] 5e) For the optimal path Each link The cumulative traffic it currently carries Add current business based on the existing business Traffic Update the link The traffic load is ;

[0027] 5f) According to the link Updated traffic load ,business Traffic and links nominal flux Calculate links based on queuing theory model Increment of queuing delay ;

[0028] 5G) will update the above increments to the link Current weight Up, obtain the link Updated weights .

[0029] 2. An inter-satellite routing system based on hop count priority and load awareness, characterized in that it includes:

[0030] The time slicing module is used to divide the system runtime into equal-length slices and to plan and schedule the execution of tasks within a single time slice.

[0031] The load prediction and sensing module is used to integrate historical data and business models to predict the inbound and outbound traffic of each ground grid in the next time slice, and combine it with satellite coverage relationships to generate an inter-satellite service transmission demand matrix with satellites as nodes.

[0032] The topology generation module is used to predict all stable inter-satellite link connections in the next time slice based on the satellite's orbital ephemeris data, and to construct a static inter-satellite network topology map.

[0033] The service transmission requirement module is used to calculate the minimum number of hops between the source node and the destination node for each service transmission requirement in the requirement matrix on the static topology graph, and sort all requirements according to the minimum number of hops to generate an ordered service transmission requirement queue.

[0034] The routing iteration calculation module is used to retrieve tasks sequentially from the service transmission demand queue, calculate the optimal path based on the current static topology graph using the shortest path algorithm, update the relevant link weights in the optimal path according to the service traffic of the allocated path, and obtain the latest static topology graph.

[0035] The service routing instruction set distribution module is used to convert all end-to-end paths output by the routing iteration calculation module into executable deterministic routing instruction sets, and distribute these instructions to the corresponding source satellite nodes in the entire network before the next time slice begins.

[0036] Compared with the prior art, the present invention has the following advantages:

[0037] Firstly, because the present invention sorts the hop count of services before allocating transmission paths and allocates the optimal transmission path across the entire network for long-distance services, it can guarantee the transmission latency of such services and avoid the defects of excessive accumulated transmission latency and difficulty in guaranteeing service quality in traditional routing methods for long-distance services.

[0038] Secondly, this invention dynamically and in real time maps the ground load to the inter-satellite links during routing calculations and updates the link weights on the topology map accordingly. This enables the routing calculations to perceive the overall network load status in real time and proactively avoid congested nodes or links, rather than relying on static topology information. This solves the problem of decision bias caused by message lag in existing methods.

[0039] Thirdly, this invention adopts a routing mode of service-by-service planning and global load balancing when calculating service transmission paths. When calculating paths for new services, it comprehensively considers the resource usage of already planned services, avoiding the hotspot aggregation effect that may be caused by traditional hop-by-hop or locally optimal routing. This makes the service flow more evenly distributed in space and time, improves the stability of service transmission, and enhances the robustness of the network in the face of sudden traffic or local failures. Attached Figure Description

[0040] Figure 1 This is a flowchart of the inter-satellite routing method based on hop count priority and load awareness of the present invention.

[0041] Figure 2 This is a schematic diagram of time slice division in the method of the present invention;

[0042] Figure 3 This is a schematic diagram of geographic grid division in the method of the present invention;

[0043] Figure 4 This is a schematic diagram of the satellite orbit ephemeris in the method of this invention;

[0044] Figure 5 This is a schematic diagram illustrating link disconnection caused by predictable factors in the method of this invention;

[0045] Figure 6 This is a block diagram of the inter-satellite routing system module based on hop count priority and load awareness of the present invention. Detailed Implementation

[0046] To enable those skilled in the art to better understand the present invention, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the present invention and not all of the embodiments. Based on the embodiments of the present invention, other embodiments obtained by those skilled in the art without creative effort should all fall within the protection scope of the present invention.

[0047] It should be noted that the step numbers in the specification and claims of this invention are only for the purpose of clearly describing the embodiments of this invention and facilitating understanding, and their order is not limited.

[0048] Example 1: Inter-satellite routing method based on hop count priority and load awareness.

[0049] The working scenario for this example includes low-Earth orbit satellites, ground gateway stations, and user terminals.

[0050] Reference Figure 1 The implementation steps of this example include the following:

[0051] Step 1: Divide the satellite's operating time into a series of continuous slices of equal length, and execute the mission with each slice as a period.

[0052] 1.1) Determine the minimum duration of time slices based on the dynamic characteristics of the satellite network, ensuring that each time slice includes at least a buffer reserve time. Information dissemination time Routing calculation time and VPN tunnel migration and reconstruction time These four time periods determine the minimum duration of a time slice. :

[0053] ;

[0054] 1.2) All satellite nodes and ground control centers within the network synchronize their time using a unified clock source, starting at a single unified time. With the origin, Step size, refer to Figure 2 Divide the timeline into an infinite number of consecutive slice intervals, the k-th time slice Defined as:

[0055] ;

[0056] 1.3) Task execution is performed periodically with a single time slice length, within the current time slice. Within the information dissemination time, the next time slice Network load information is disseminated and collected; The routing calculation time Calculate the service transmission path within the scope, VPN tunnel migration and reconstruction time The VPN tunnel used by the network is configured in advance.

[0057] Step 2: Generate the service transmission demand matrix for inter-satellite services in the next time slice. .

[0058] 2.1) Based on the method of equal division of Earth's latitude and longitude, the Earth's surface is divided into 72 non-overlapping geographic grids. Each grid corresponds to an independent business statistical unit. Based on global IoT device distribution data, the static device density in different regions is analyzed. Configure settings, such as Figure 3 As shown;

[0059] 2.2) For any pair of satellites s and d, the static equipment density index corresponding to the coverage grid of these two satellites is used. The distance d between the two satellites, and the satellite flux coefficient. and surface flow coefficient Calculate the service transmission demand index between the two satellites. :

[0060] ;

[0061] 2.3) For N satellites in the inter-satellite network, repeat step 2.2) to calculate the demand index for all satellite pairs. The inter-satellite service transmission matrix is ​​obtained. :

[0062] .

[0063] Step 3, Develop a service transmission requirement matrix. For all service transmission requirements, calculate the minimum hop count between the corresponding service source node and destination node. .

[0064] like Figure 4 As shown, the satellite's motion involves several components, including its semi-major axis. eccentricity Track inclination Right ascension of ascending node Perigeal argument True near point angle The implementation of this step includes the following parameters, such as the distance r between Earth and Mars, and the instantaneous velocity v of the satellite:

[0065] 3.1) From Figure 4 Extract the six orbital elements of the satellite from its orbital ephemeris. That is, the semi-major axis of the satellite orbit eccentricity Track inclination Right ascension of ascending node Perigeal argument True near point angle ;

[0066] 3.2) Based on the six orbital roots, the three-dimensional position coordinates and velocity vectors of each satellite are calculated using a celestial mechanical model. Combined with the visibility relationship between satellites and the constellation connection criteria, the set of inter-satellite connectivity links in the next time slice is generated.

[0067] 3.3) According to Figure 5 The link disconnection predictable factors shown are used to predict and calculate the affected links in the network, and generate the set of inter-satellite disconnected links in the next time slice.

[0068] 3.4) Combine the set of inter-satellite connected links generated in step 3.2) and the set of inter-satellite disconnected links generated in step 3.3). For any potential inter-satellite link in the network... Perform logical state determination:

[0069] If link If it appears in the connected set but not in the disconnected set, then proceed to step 3.5).

[0070] If link If a link appears in the disconnected set or does not appear in the connected set, then the link is unavailable.

[0071] 3.5) Connect the satellite nodes at both ends of the available link. and As a vertex and and Connect and construct a static topology graph G to represent the link connectivity of the network in the next time slice;

[0072] 3.6) Regarding the service transmission matrix Each business requirement Starting from the source node s and ending at the destination node d, the breadth-first search algorithm is used to calculate the minimum number of hops from s to d:

[0073] 3.6.1) Using s as the starting point of the search, mark it as the 0th jump;

[0074] 3.6.2) Search all adjacent access points of the current node in sequence and mark them as the current hop count + 1;

[0075] 3.6.3) Continuing from step 3.6.2), when node d is found for the first time, the search is terminated. At this point, the hop count of d is marked, which is the business value. Minimum number of hops from source node s to destination node d ;

[0076] 3.7) For inter-satellite service transmission matrix For each non-zero element, define the service transmission requirement, repeat step 3.6), calculate the minimum hop count for each service transmission requirement, use the calculated minimum hop count as the key attribute, and correlate it with the matrix. The corresponding service transmission requirements Associate and store.

[0077] Step 4, perform a service transmission demand matrix All service transmission requirements are arranged to obtain a service transmission requirement queue. .

[0078] 4.1) Regarding the service transmission requirement matrix In The service transmission requirements defined by the non-zero elements are sorted in descending order according to their minimum hop count H, and the service transmission requirement with the most hop count is placed at the front of the queue.

[0079] 4.2) Based on the sorting results obtained in 4.1), for all service demand groups with the same number of hops, within each group, the service transmission demand index is used to determine the order of service demand groups. Sort the data in descending order, placing the services with higher demand and the most likely to cause congestion at the front of the group;

[0080] 4.3) After sequentially executing the sorting steps described in 4.1) and 4.2), an ordered queue of service transmission requirements is obtained. :

[0081] ;

[0082] in Each element It is a service transmission requirement unit, which contains the service transmission source node. , destination node Service transmission demand index Minimum number of hops ,Right now For any satisfy: ,or and .

[0083] Step 5, queue the service transmission demand. All service transmission requirements are iteratively calculated for the service transmission path in sequence.

[0084] 5.1) Based on the static topology graph generated in step 3.5), assign dynamic weights to each edge in the graph, according to the propagation delay. Processing delay Transmission delay and queuing delay Calculate the weight of each link L in the static network topology graph: This yields a static weighted topology diagram of the network.

[0085] 5.3) The service transmission demand queue generated in step 4 Starting from the head of the queue, extract the first service transmission request with the highest number of hops that is currently pending. ,for Calculate the optimal path:

[0086] 5.3.1) Service transmission requirements In the current dynamically weighted topology, the business source node Starting point, destination node Using the destination as the endpoint, run the weighted single-source shortest path algorithm to find the optimal path from the origin to the destination on the static weighted topology of the network. ;

[0087] 5.3.2) Regarding the optimal path Each link The cumulative traffic it currently carries Add current business based on the existing business Traffic Update the link The traffic load is ;

[0088] 5.3.3) According to the link Updated traffic load ,business Traffic and links nominal flux Calculate links based on queuing theory model Increment of queuing delay :

[0089] ;

[0090] 5.3.4) Update the above increments to the link. Current weight Up, obtain the link Updated weights :

[0091] ;

[0092] 5.3.5) For the optimal path The weights of all links are updated to obtain the routing results for the next service.

[0093] The weighted topology graph of the calculation;

[0094] 5.4) Repeat step 5.3) until all N services in the service transmission demand queue Q have been processed, obtaining the transmission path for each service, forming a set of transmission paths for all services:

[0095] .

[0096] Step 6: Convert the set of end-to-end transmission paths for the service transmission requirements in the next time slice into a set of routing instructions and send it to the routing control layer to guide the service in transmission.

[0097] 6.1) The end-to-end transmission path set calculated in step 5 Perform data structure transformation:

[0098] 6.1.1) In the end-to-end transmission path set Each path in Above, except for the destination node

[0099] For each hop satellite node, extract its segment route identifier (SID) value;

[0100] 6.1.2) Based on the extracted satellite node SID values, the path... Convert into a SID list ;

[0101] 6.2) Encapsulate the forwarding instruction tables corresponding to all paths in the end-to-end transmission path set into a complete, structured network-wide routing instruction set;

[0102] 6.3) Within the current time slice, the instruction set is sent to the routing control layer of all satellites in the network, and the routing control layer guides the transmission of services.

[0103] Example 2: Inter-satellite routing system based on hop count priority and load awareness.

[0104] Reference Figure 6 This example includes a time slicing module 1, a load prediction and perception module 2, a topology generation module 3, a service transmission requirement module 4, a service route calculation module 5, and a service route instruction set distribution module 6. The service transmission requirement module 4 includes: a service transmission requirement hop count calculation submodule 41, a service transmission requirement primary sorting submodule 42, and a service transmission requirement secondary sorting submodule 43. The service route calculation module 5 includes: a service transmission requirement acquisition submodule 51, an optimal path calculation submodule 52, and a topology update submodule 53.

[0105] The working principle of the entire system is as follows:

[0106] The time slicing module 1 is used to divide the system running time into equal-step long-time slices, while planning and scheduling the execution of tasks within a single time slice, and outputting the slice division scheme to the load prediction and perception module 2 and the topology generation module 3.

[0107] The load prediction sensing module 2 is used to integrate historical data and service models to predict the inbound and outbound traffic of each ground grid in the next time slice, and combine the satellite coverage relationship to generate an inter-satellite service transmission demand matrix with satellites as nodes, and output the matrix to the service transmission demand module 4.

[0108] The topology generation module 3 is used to predict all continuous and stable inter-satellite link connections in the next time slice based on the satellite's orbital ephemeris data, construct a static inter-satellite network topology map, and output the topology map to the service transmission requirement module 4.

[0109] The service transmission demand module 4 is used to calculate the minimum hop count between the source node and the destination node for each service transmission demand in the demand matrix on the static topology graph, and sort all demands according to the minimum hop count to generate an ordered service transmission demand queue. Specifically, the service transmission demand hop count calculation submodule 41 is used to calculate the minimum hop count from the source satellite node to the destination satellite node for each non-zero element in the inter-satellite service transmission demand matrix on the next time slice static topology graph provided by the topology generation module, and output the minimum hop count of all inter-satellite service transmission demands in the matrix to the transmission demand master module. The sorting submodule 42 is used to sort all service transmission requirements in descending order using the calculated minimum hop count as the first sorting key, and output the sorting result to the secondary sorting submodule 43. The secondary sorting submodule 43 is used to sort service transmission requirements with the same minimum hop count in descending order using their corresponding service requirement index as the secondary sorting key, based on the primary sorting submodule, and finally generate a globally ordered service transmission requirement queue, and output the finally generated ordered queue to the service routing calculation module 5.

[0110] The service routing calculation module 5 is used to sequentially retrieve tasks from the service transmission demand queue, calculate the optimal path using the shortest path algorithm based on the current static topology graph, and update the relevant link weights in the optimal path according to the service traffic of the allocated path to obtain the latest static topology graph. Specifically: the service transmission demand acquisition submodule 51 is used to sequentially retrieve the currently pending service transmission demand calculation tasks from the ordered service transmission demand queue. If a service transmission demand calculation task is retrieved, the optimal path calculation submodule 52 is called; otherwise, the service routing instruction set distribution module 6 is called. The optimal path calculation submodule 52 is used to run the shortest path algorithm on the newly generated static topology graph to calculate the optimal path from the source node to the destination node, and transmit the calculated optimal path to the topology update submodule 53. The topology update submodule 53, after calculating the optimal path, immediately updates the weights of all links on the path dynamically according to the traffic demand of the service, that is, it feeds back the impact of this routing calculation on the network load to the global topology state for the routing calculation of the next service demand, and calls the service transmission demand acquisition submodule 51.

[0111] The service routing instruction set distribution module 6 is used to convert all end-to-end paths output by the routing iteration calculation module into executable deterministic routing instruction sets, and distribute these instructions to the corresponding source satellite nodes in the entire network before the next time slice begins.

[0112] It should be noted that the above functional modules can be implemented, in whole or in part, through software, hardware, firmware, or any combination thereof. When implemented in software, they can be implemented, in whole or in part, as program instruction products. A program instruction product includes one or a set of program instructions. When the program instructions are loaded and executed on a computer, all or part of the above-mentioned clustered processes or functions will be implemented. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The program instructions can be stored in a computer-readable and writable storage medium, or transferred from one computer's readable and writable storage medium to another.

[0113] In this embodiment, the direct coupling or communication connection between the modules can be achieved through indirect coupling or communication connection via interfaces, devices, or modules. The functional modules and sub-modules in this embodiment can dynamically reside within a single processing unit, or each module can exist physically independently, or two or more modules can dynamically reside within a single processing unit. When these dynamic components are implemented as software functional modules and sold or used as independent products, they can also be stored in a computer-readable and writable storage medium. This storage medium can be a memory, disk, or optical disc, etc.

[0114] The above descriptions are merely two specific examples of the present invention and do not constitute any limitation on the present invention. Obviously, those skilled in the art, after understanding the content and principles of the present invention, may make various modifications and changes in form and detail without departing from the principles and structure of the present invention. For example, in step one and time slicing module 1, in addition to buffer time, information collection time, route calculation time, and VPN tunnel migration and reconstruction time, other tasks such as route verification and clock synchronization can be added to improve or supplement the task time planning within the time slice. In step 2 and load prediction perception module 2, the load of the entire network is calculated. In addition to calculating the inter-satellite service transmission demand matrix based on the geographic grid, the inter-satellite service transmission demand matrix can also be constructed by flooding inter-satellite load information. In step 5 and service route calculation module 5, the links in the topology map are weighted. In addition to using latency as the link weight, other attributes such as throughput and packet loss rate or multiple attributes can also be used as the link weight. In step 6 and service route instruction set distribution module 6, the transmission path set is converted into a routing instruction table. In addition to using the SID of satellite nodes for conversion, network protocols such as Multi-Protocol Label Routing (MPLS) can also be used for conversion. However, these modifications and alterations based on the ideas of this invention are still within the scope of protection of the claims of this invention.

Claims

1. An inter-satellite routing method based on hop count priority and load awareness, characterized in that, include: (1) Based on the minimum event response time required for satellite motion, link establishment / interruption and service transmission failure recovery in the satellite network, the system running time is divided into a series of continuous equal-length slices; (2) Divide the ground service area into regular geographic grids, predict the total inbound and outbound traffic of each grid in the next time slice for the current time slice, and generate the service transmission demand matrix of inter-satellite services in the next time slice by combining the mapping relationship between grids and satellites. ; (3) Based on the satellite's orbital ephemeris, predict the static topology G of the inter-satellite network in the next time slice, and then analyze the service transmission demand matrix. Each non-zero element in The defined service transmission requirements are used to calculate the source node on the topology graph. to the destination node Minimum number of hops between ; (4) Minimum number of jumps Using the primary sorting key and the secondary sorting key, the service transmission traffic size is used to categorize the service transmission demand matrix. All service transmission requirements are sorted in descending order to obtain the service transmission requirement queue. ; (5) From the service transmission demand queue Extract the service with the maximum hop count to be calculated from the current data, and calculate the optimal path for this service in the static network topology graph of the next time slice. And update the link weights in the topology graph based on the traffic load of the service; (6) Repeat (5) until the queue is complete. Once the path planning for all service transmission requirements is completed, the set of end-to-end transmission paths for all service transmission requirements in the next time slice is obtained, and this set is converted into a routing instruction set and sent to the routing control layer to guide the services in transmission.

2. The method according to claim 1, characterized in that, The division of system runtime into a series of consecutive equal-length slices in (1) is implemented as follows: 1a) Within a single time slice, in combination with the needs of satellite network control and service scheduling, the tasks within the slice are scheduled in a fine-grained manner, including buffer reservation, information propagation, route calculation and VPN tunnel migration and reconstruction. 1b) The minimum duration of a time slice is determined based on the internal task planning analysis of a single time slice. ,by The system runtime is divided into equal-length slices using the step size.

3. The method according to claim 1, characterized in that, In (2), the inter-satellite service transmission demand matrix is ​​generated based on the predicted information. Its implementation includes: 2a) Based on the equal division of Earth's latitude and longitude, the Earth's surface is divided into several non-overlapping geographic grids. Each grid corresponds to an independent business statistical unit. Based on global IoT device distribution data, the static device density in different regions is analyzed. Configure settings; 2b) For satellites s and d, according to the static equipment density index The distance d between the two satellites, and the satellite flux coefficient. and surface flow coefficient Calculate the service transmission demand index : ; 2c) For N satellites in an inter-satellite network, calculate the demand index for all satellite pairs. The inter-satellite service transmission matrix is ​​obtained. : 。 4. The method according to claim 1, characterized in that, The step (3) involves predicting the static topology of the inter-satellite network within the next time slice based on the satellite's orbital ephemeris. Its implementation includes: 3a) Obtain the six orbital elements of the satellite based on its orbital ephemeris. That is, the semi-major axis of the satellite orbit eccentricity Track inclination Right ascension of ascending node Perigeal argument True near point angle ; 3b) Calculate the satellite's position and velocity vectors based on the six orbital elements of the satellite, and combine the visibility relationships between satellites with the constellation connection criteria to obtain the connectivity plan for all links in the network in the next time slice; 3c) Based on the predictable factors of link disconnection, predict and calculate the disconnection plan of all affected links in the network in the next time slice; 3d) Determine each link in the network On / off state: If link If the link appears in the connectivity plan but not in the disconnection plan, then the link is connected, and step 3e is executed. If link If the link appears in the disconnection plan or does not appear in the connectivity plan, the link is disconnected. 3e) Connect the satellite nodes at both ends of the link and Connecting the dots in the graph yields a static topology graph G that characterizes the connectivity of inter-satellite links.

5. The method according to claim 1, characterized in that, In step (3), the source node is calculated on the topology graph. to the destination node Minimum number of hops between Its implementation includes; 3f) On the static topology graph G, for the source node s and the destination node d, run the breadth-first search algorithm, starting from the source node s, traversing the network hop by hop until the destination node d is visited for the first time. The number of expansion layers traversed is the minimum number of hops. ; 3G) for inter-satellite service transmission matrix For each non-zero element that defines a service transmission requirement, repeat step 3f) to calculate the minimum number of hops for each service transmission requirement task.

6. The method according to claim 1, characterized in that, In step (4), the service transmission requirements are sorted to obtain the service transmission requirement queue. Its implementation includes: 4a) For the traffic matrix In The service transmission requirements defined by the non-zero elements are based on the minimum number of hops from the source node to the destination node. All service transmission requirements are sorted in descending order; 4b) When the minimum hop counts of two service transmission requirements are the same, the service transmission requirement index shall be used. Sort the data in descending order, prioritizing the calculation of the optimal transmission path for high-volume services; 4c) After sequentially performing the sorting steps described in 4a) and 4b), an ordered queue of service transmission requirements is obtained. : ; in Each element It is a service transmission requirement unit, which contains the service transmission source node. , destination node Service transmission demand index Minimum number of hops ,Right now .

7. The method according to claim 1, characterized in that, The (5) mentioned above refers to the service transmission demand queue. Extract the service with the maximum hop count to be calculated from the current data, and calculate the optimal path for this service in the static network topology graph of the next time slice. Its implementation includes: 5a) Based on propagation delay Processing delay Transmission delay and queuing delay Calculate the weight of each link L in the static network topology graph. : ； 5b) Weights for each link The network is updated to obtain a static weighted topology graph. 5c) From the service transmission demand queue Extract the first service transmission request with the highest hop count from the header. ; 5d) For the first service transmission requirement The single-source shortest path algorithm is used to calculate the shortest path from the source node on the static weighted topology graph of the network. to the destination node Optimal path .

8. The method according to claim 1, characterized in that, The update of link weights in the topology graph based on the traffic load of the service in step (5) includes the following implementation: 5e) For the optimal path Each link The cumulative traffic it currently carries Add current business based on the existing business Traffic Update the link The traffic load is ; 5f) According to the link Updated traffic load ,business Traffic and links nominal flux Calculate links based on queuing theory model Increment of queuing delay : ； 5G) will update the above increments to the link Current weight Up, obtain the link Updated weights : 。 9. The method according to claim 1, characterized in that, In step (6), converting the end-to-end transmission path set into a routing instruction set involves converting the end-to-end transmission path set into a routing instruction set. Each path in Perform parsing and extract the path. Passing by The SID information corresponding to each node constitutes a SID list. : ; in Representing a path The SID information of the j-th node.

10. An inter-satellite routing system based on hop count priority and load awareness, characterized in that, include: The time slicing module is used to divide the system runtime into equal-length slices and to plan and schedule the execution of tasks within a single time slice. The load prediction and sensing module is used to integrate historical data and business models to predict the inbound and outbound traffic of each ground grid in the next time slice, and combine it with satellite coverage relationships to generate an inter-satellite service transmission demand matrix with satellites as nodes. The topology generation module is used to predict all stable inter-satellite link connections in the next time slice based on the satellite's orbital ephemeris data, and to construct a static inter-satellite network topology map. The service transmission requirement module is used to calculate the minimum number of hops between the source node and the destination node for each service transmission requirement in the requirement matrix on the static topology graph, and sort all requirements according to the minimum number of hops to generate an ordered service transmission requirement queue. The routing iteration calculation module is used to retrieve tasks sequentially from the service transmission demand queue, calculate the optimal path based on the current static topology graph using the shortest path algorithm, update the relevant link weights in the optimal path according to the service traffic of the allocated path, and obtain the latest static topology graph. The service routing instruction set distribution module is used to convert all end-to-end paths output by the routing iteration calculation module into executable deterministic routing instruction sets, and distribute these instructions to the corresponding source satellite nodes in the entire network before the next time slice begins.

11. The system according to claim 9, characterized in that: The service transmission requirement module includes: The service transmission requirement hop count calculation submodule is used to calculate the minimum hop count from the source satellite node to the destination satellite node on the next time slice static topology map provided by the topology generation module for each non-zero element in the inter-satellite service transmission requirement matrix. The main sorting submodule for service transmission requirements is used to sort all service transmission requirements in descending order using the calculated minimum number of hops as the first sorting key. The secondary sorting submodule for service transmission requirements is used, based on the primary sorting submodule for service transmission requirements, to sort the sets of service transmission requirements with the same minimum hop count in descending order using their corresponding service requirement index as the secondary sorting key, and finally generate a globally ordered service transmission requirement queue. The service routing calculation module includes: The service transmission requirement acquisition submodule is used to sequentially acquire the currently pending service transmission requirement tasks from the ordered service transmission requirement queue. The optimal path calculation submodule is used to run the shortest path algorithm on the newly generated static topology graph to calculate the optimal path from the source node to the destination node. The topology update submodule is used to dynamically update the weights of all links on the path immediately after the optimal path is calculated, based on the traffic requirements of the service. In other words, it feeds back the impact of this routing calculation on the network load to the global topology state for routing calculation of the next service requirement.

Images