Large-scale unmanned aerial vehicle group network communication method and device, medium and program product

Abstract

The invention provides a large-scale unmanned aerial vehicle group network communication method and device, a medium and a program product, and the method comprises the steps: delimiting a region with a two-hop range as a radius by taking the node as a center after the node accesses the network; the area within the radius is an internal area, and the area outside the radius is an external area; selecting different routing algorithms to establish a route according to the difference between the internal area and the external area; when the node receives the service, path finding judgment is carried out according to a destination address to determine whether the service is an internal area service or an external area service; if it is judged that the service is the internal area service, the node carries out service forwarding according to a pre-established route; and if the service is judged to be the external area service, the node triggers a route established according to the demand through a virtual gateway mechanism, and performs service forwarding according to the route established according to the demand. Under the large-scale and high-maneuverability conditions, the routing maintenance overhead can be effectively reduced, the large-scale network topology can be quickly converged, the resource utilization efficiency can be improved, and meanwhile, the method is easy to deploy and convenient to use.

Description

Technical Field

[0001] The present invention relates to the field of communication technology, and in particular to a large-scale drone swarm network communication method, equipment, medium and program product. Background Art

[0002] With the extensive application of drone systems, the scale of drone swarm communication networks has also increased. However, the increase in network scale will bring many problems to the entire network system. First, the path maintenance overhead will increase at a faster rate. Second, the high dynamic changes in network topology put higher requirements on routing overhead and convergence speed. In addition, network control messages or control information in messages will also increase exponentially, while the network resources actually used for business transmission will be sharply reduced. Therefore, it is particularly important to design suitable routing and forwarding methods for large-scale drone swarm communication networks.

[0003] Routing protocols are generally divided into a priori, on-demand and hybrid.

[0004] A priori routing establishes paths to all nodes in the entire network in advance through periodic broadcast signaling. When a node needs to send a service, it can directly search the existing routing table, which requires less delay. However, the path maintenance overhead is large, and it is suitable for small and medium-sized networks with small service delays.

[0005] On-demand routing does not pre-establish paths to other nodes, and only searches on demand when there is business. Therefore, periodic signaling broadcasts are not required, saving certain network resources. However, if there is no route to the destination node, service forwarding will have a certain first packet delay. It is suitable for medium and large-scale networks with small network service concurrency and undemanding service first packet delay requirements.

[0006] Hybrid routing is a combination of a priori routing and on-demand routing. There are many different forms of hybrid routing and different applicable scenarios. For example, the pulse protocol actively maintains the paths from other nodes in the network to the pulse source, and establishes the paths from the pulse source to other nodes on demand. This is suitable for network business models where data is focused unidirectionally on the center point. For example, the hwmp protocol actively maintains the bidirectional paths between other nodes in the network and the root node, and optimizes the paths between other nodes on demand. This is suitable for network business models that interact with the center point in both directions.

[0007] Different routing protocols are applicable to different scenarios. It is meaningful to compare the performance of routing protocols only under limited scenarios and network parameter conditions. Therefore, it is necessary to design routing methods based on the application characteristics of drone swarm communication networks.

[0008] The data forwarding methods of drone swarm networks are generally divided into layer 2 forwarding and layer 3 forwarding.

[0009] Layer 2 forwarding relies on MAC addresses to determine the forwarding direction of data packets. The loads under all communication devices are equivalent to those under the same switch. The MAC addresses of all loads in the entire network can be learned through the ARP protocol. The network system with Layer 2 forwarding is simple to operate and plug-and-play, but a large number of broadcast messages in the network will occupy a large amount of bandwidth resources, thereby reducing network performance and limiting the network scale.

[0010] Layer 3 forwarding relies on IP addresses to determine the forwarding direction of data packets. Each communication device is equivalent to a separate Layer 2 network, and devices forward Layer 3 messages through IP addressing. The network system with Layer 3 forwarding reduces the overhead of a large number of broadcast messages, which is conducive to the expansion of network scale. However, when the network runs on-demand routing or hybrid routing, the communication device relies on the Layer 2 message of the load device to find the destination route. If the gateway service is not deployed, the on-demand routing cannot be discovered, and plug-and-play cannot be achieved.

[0011] Therefore, it is necessary to design a high-efficiency, low-overhead and easy-to-use communication method based on the characteristics of the drone swarm communication network. Summary of the invention

[0012] Aiming at the application scenarios where the drone swarm network is large in scale, the network topology has few hops and the mobile speed is fast, the present invention provides a large-scale drone swarm network communication method, equipment, medium and program product, which can effectively reduce routing maintenance overhead, quickly converge large-scale network topology, and improve resource utilization efficiency under large-scale and high-mobility conditions, while being easy to deploy and convenient to use.

[0013] The present invention provides a large-scale drone swarm network communication method, comprising the following steps:

[0014] S1: After a node joins the network, it defines an area with a radius of two hops with itself as the center; the area within the radius is the internal area, and the area outside the radius is the external area;

[0015] S2: According to the difference between the internal area and the external area, different routing algorithms are selected to establish routing:

[0016] Establish routing directly in the internal area;

[0017] Establish routing on demand in external areas based on business needs;

[0018] S3: When a node receives a service, it performs routing judgment according to the destination address to determine whether the service is an internal area service or an external area service;

[0019] If it is determined to be an internal area service, the node forwards the service according to the pre-established route;

[0020] If it is determined to be an external area service, the node triggers the on-demand routing through the virtual gateway mechanism and forwards the service according to the on-demand routing.

[0021] In some embodiments, the step S2 of directly establishing a route in the internal area includes the following sub-steps:

[0022] S211: The node completes the establishment of a one-hop route according to the one-hop networking neighbor information base carried by the MAC layer control time slot;

[0023] S212: The node calculates the two-hop neighbor information of the node according to the neighbor information base of the neighbor carried by the MAC layer control time slot, and completes the establishment of the two-hop routing according to the two-hop neighbor information.

[0024] In some embodiments, the method for establishing the two-hop route in step S212 is: first calculate and select the next hop according to the comprehensive link MCS algorithm, and if no selection is possible, complete the establishment of the two-hop route according to the load balancing link selection algorithm.

[0025] In some embodiments, the integrated link MCS algorithm includes the following sub-steps:

[0026] S2121: Calculate the mcs values ​​involved in all paths from the current node to a two-hop neighbor;

[0027] S2122: compare the smallest mcs values ​​among all the paths, and select the path corresponding to the largest mcs value as the path to the two-hop neighbor;

[0028] S2123: If there are multiple maximum mcs values ​​in step S2122, select the remaining path with the largest mcs value among these paths;

[0029] S2124: If there are multiple paths with completely identical mcs values ​​to reach the two-hop neighbor, then enter the load balancing link selection algorithm; otherwise, directly complete the establishment of the two-hop route.

[0030] In some embodiments, the load balancing link selection algorithm includes the following sub-steps:

[0031] S2125: Calculate the one-hop neighbor set of the node and the two-hop neighbor coverage of the node;

[0032] S2126: adding the only node in the one-hop neighbor set of the node that reaches a certain node in the two-hop neighbor set of the node to the next-hop neighbor set, and removing the nodes in the two-hop neighbor set that are covered by the selected next-hop neighbor set;

[0033] S2127: When there is a node in the two-hop neighbor set of the node that is not covered by any node in the next-hop neighbor set, execute step S2128; if there is no node, the algorithm ends;

[0034] S2128: Calculate the two-hop neighbor reachability of the node in the one-hop neighbor set of the node;

[0035] S2129: Select a node as the next hop from the nodes whose two-hop neighbor reachability is not 0 in the one-hop neighbor set of the node. If there are multiple choices, select the one with the lowest two-hop neighbor reachability. If there are still multiple choices, select the one with low two-hop neighbor coverage. Remove the nodes in the two-hop neighbor set that are already covered by the next hop set, and return to step S2127.

[0036] S21210: Establish a set of all next-hop neighbors of the node, that is, the next-hop nodes of the two-hop route; at this point, the two-hop route is established.

[0037] In some embodiments, the step S2 of establishing a route in an external area on demand according to business needs includes the following sub-steps:

[0038] S221: The source node broadcasts a routing request signaling Req carrying a link weight;

[0039] S222: other nodes receive the route request signaling Req, establish a route to the source node according to the link weight, determine whether the destination node is the local node or there is a route to the destination node, if so, unicast reply route response message Rep, otherwise update the link weight and broadcast the route request signaling Req as needed;

[0040] S223: The source node receives the route request signaling Rep and establishes a route to the destination node according to the link weight.

[0041] In some embodiments, in step 3, the node triggers the on-demand established route through the virtual gateway mechanism, and performs service forwarding according to the on-demand established route, including the following sub-steps:

[0042] S31: When the load device under this node sends an ARP request to obtain the MAC address corresponding to the IP of the load device under other nodes, this node will intercept the ARP request;

[0043] S32: After receiving the ARP request, the node assembles an ARP response message with the virtual gateway MAC address and replies to the downstream load device;

[0044] S33: After receiving the ARP response message including the MAC address of the virtual gateway, the downstream load device sends the service message to the virtual gateway;

[0045] S34: After receiving the service message, the node searches for the next hop route according to the destination IP address, removes the ETH message header in the service message, and sends it through the wireless link;

[0046] S35: After receiving the service message, the destination node assembles the ETH message header according to the destination node, and sends the service message to the downstream load device corresponding to the destination node IP, thereby completing the entire communication process.

[0047] The present invention also provides an electronic device, comprising:

[0048] at least one processor; and a memory communicatively coupled to the at least one processor;

[0049] The memory stores instructions that can be executed by the at least one processor, and the at least one processor executes the above method by executing the instructions stored in the memory.

[0050] The present invention also provides a computer-readable storage medium, wherein the computer-readable storage medium is used to store instructions, and when the instructions are executed, the above method is implemented.

[0051] The present invention also provides a computer program product, characterized in that when the computer program product is called by a computer, the computer is caused to execute the above method.

[0052] In summary, due to the adoption of the above technical solution, the beneficial effects of the present invention are:

[0053] The present invention cleverly utilizes the characteristics of the drone swarm network topology with fewer hops and frequent local business interactions, designs a zero-overhead vector routing mechanism with cross-layer fusion within two hops, and uses a virtual gateway strategy to make the three-layer forwarding network plug-and-play. At the same time, due to the restriction of the transmission of control messages and control information in the messages, the resource utilization and scale scalability are improved. Under large-scale and high-mobility conditions, it can effectively reduce routing maintenance overhead, quickly converge large-scale network topology, and improve resource utilization efficiency. At the same time, it is easy to deploy and convenient to use. BRIEF DESCRIPTION OF THE DRAWINGS

[0054] Figure 1 This is a flow chart of a large-scale drone swarm network communication method proposed in an embodiment of the present invention.

[0055] Figure 2 It is a flow chart of the comprehensive link MCS algorithm in an embodiment of the present invention.

[0056] Figure 3 It is an implementation topology diagram of the comprehensive link MCS algorithm in the embodiment of the present invention.

[0057] Figure 4 It is a flow chart of a load balancing link selection algorithm in an embodiment of the present invention.

[0058] Figure 5It is an implementation topology diagram of the load balancing link selection algorithm in the embodiment of the present invention.

[0059] Figure 6 This is process 1 of the load balancing link selection algorithm implementation in the embodiment of the present invention.

[0060] Figure 7 This is process 2 of the load balancing link selection algorithm implementation in the embodiment of the present invention.

[0061] Figure 8 This is process three of the load balancing link selection algorithm implementation in the embodiment of the present invention.

[0062] Fig. 9 This is process four of the load balancing link selection algorithm implementation in the embodiment of the present invention.

[0063] Fig.10 The routing topology diagram is established on demand in the embodiment of the present invention.

[0064] Fig.11 It is a schematic diagram of using a virtual gateway of a communication device in an embodiment of the present invention.

[0065] Fig.12 This is a simulation diagram of communication of a 200-node drone group in an embodiment of the present invention.

[0066] Fig.13 It is a comparison chart of the simulation results of the average end-to-end delay of the entire network in an embodiment of the present invention.

[0067] Fig.14 It is a comparison chart of simulation results of route establishment time in an embodiment of the present invention.

[0068] Fig.15 It is a comparison diagram of routing overhead simulation results in an embodiment of the present invention.

[0069] Fig.16 This is a schematic diagram of the structure of an electronic device proposed in an embodiment of the present invention. DETAILED DESCRIPTION

[0070] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Generally, the components of the embodiments of the present invention described and shown in the drawings here can be arranged and designed in various different configurations.

[0071] Therefore, the following detailed description of the embodiments of the present invention provided in the accompanying drawings is not intended to limit the scope of the invention claimed for protection, but merely represents selected embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0072] like Figure 1 As shown, an embodiment of the present invention proposes a large-scale drone swarm network communication method, comprising the following steps:

[0073] S1: After a node joins the network, it defines an area with a radius of two hops with itself as the center; the area within the radius is the internal area, and the area outside the radius is the external area. It should be noted that the area is defined based on each node, not for a fixed part of the nodes in the network.

[0074] S2: Select different routing algorithms to establish routing according to the difference between the internal area and the external area; the internal area uses an active cross-layer fusion routing algorithm, and the external area uses an on-demand vector routing algorithm.

[0075] In some embodiments, step S2 includes the following sub-steps:

[0076] S21: In the internal area, an active cross-layer fusion routing algorithm is used to establish routing. Specifically, through cross-layer fusion design, one-hop networking neighbor information of the MAC layer is used to establish routing without additional routing signaling overhead.

[0077] S22: In the external area, routes are established using an on-demand vector routing algorithm, that is, routes are established on demand according to business needs.

[0078] Specifically, step S21 includes the following sub-steps:

[0079] S211: The node completes the establishment of a one-hop route according to the one-hop networking neighbor information base carried by the MAC layer control time slot, without performing neighbor detection through Hello information.

[0080] S212: The node calculates the two-hop neighbor information of the node according to the neighbor information base of the neighbor carried by the MAC layer control time slot, and completes the establishment of the two-hop routing according to the two-hop neighbor information.

[0081] In some embodiments, the method for establishing the two-hop route in step S212 is: first calculate and select the next hop according to the comprehensive link MCS algorithm, and if it cannot be selected, then select the next hop according to the load balancing link selection algorithm. The specific steps are:

[0082] S2121: Calculate the mcs values ​​involved in all paths from the current node to a two-hop neighbor;

[0083] S2122: compare the smallest mcs values ​​among all the paths, and select the path corresponding to the largest mcs value as the path to the two-hop neighbor;

[0084] S2123: If there are multiple maximum mcs values ​​in step S2122, select the remaining path with the largest mcs value from these paths;

[0085] S2124: If there are multiple paths with completely identical mcs values ​​to reach the two-hop neighbor, proceed to step S2125 to start the load balancing link selection algorithm to complete the establishment of the two-hop route; otherwise, the establishment of the two-hop route is directly completed.

[0086] The comprehensive link MCS algorithm process is as follows Figure 2 For further understanding, the following examples are used for illustration. Figure 3 In the network topology shown, the process of node 1 establishing a route to node 5 is as follows:

[0087] 1) Among the three paths leading to node 5 (1-2-5, 1-3-5, 1-4-5), the mcs value of each path is 1, 2, and 2. Select the two paths with larger mcs values ​​(1-3-5, 1-4-5) and then make a selection.

[0088] 2) Compare the MCS values ​​of the remaining paths 1-3-5 and 1-4-5 (the MCS value of 3-5 is 3, and the MCS value of 4-5 is 2), and select the larger one as the final path (1-3-5).

[0089] S2125: Calculate the one-hop neighbor set NBR_HOP_1 of the node and the two-hop neighbor coverage C(i) of node i; wherein the two-hop neighbor coverage C(i) of node i refers to the number of two-hop neighbors covered by the one-hop neighbor i, excluding the nodes in the one-hop neighbor set NBR_HOP_1 and the current node.

[0090] S2126: add the only node in the one-hop neighbor set NBR_HOP_1 of the node that reaches a node in the two-hop neighbor set NBR_HOP_2 of the node to the next-hop neighbor set, and remove the nodes in the two-hop neighbor set NBR_HOP_2 that are covered by the selected next-hop neighbor set. The two-hop neighbor set NBR_HOP_2 of the node does not include the current node and nodes that can be reached in one hop.

[0091] S2127: When there is a node in the two-hop neighbor set NBR_HOP_2 of the node that is not covered by any node in the next-hop neighbor set, execute step S2128; if there is no node, the algorithm ends;

[0092] S2128: Calculate the two-hop neighbor reachability R(i) of node i in the node's one-hop neighbor set NBR_HOP_1; wherein the two-hop neighbor reachability R(i) of node i refers to the number of two-hop neighbors that can be reached after excluding the two-hop neighbors that have been reached by other one-hop neighbors, excluding members of the one-hop neighbor set NBR_HOP_1 and the current node.

[0093] S2129: Select a node as the next hop from the nodes whose two-hop neighbor reachability R(i) is not 0 in the node's one-hop neighbor set NBR_HOP_1. If there are multiple choices, select the one with the lowest two-hop neighbor reachability R(i). If there are still multiple choices, select the one with low two-hop neighbor coverage C(i). Remove the nodes in the two-hop neighbor set NBR_HOP_2 that have been covered by the next hop set, and return to step S2127.

[0094] S21210: Establish all next-hop neighbor sets of the node, that is, the next-hop nodes of the two-hop route. At this point, the two-hop route is established.

[0095] The load balancing link selection algorithm process is as follows Figure 4 For further understanding, the following examples are used for illustration. Figure 5 In the network topology shown, the process of node 0 establishing a route to nodes a, b, c, d, e, and f is as follows:

[0096] 1) Node 0 selects node 1 and node 6 as its next hop, such as Figure 6 As shown, since node 1 is the only node that can reach node a, node 6 is the only node that can reach node f;

[0097] 2) Select node 2 as the next hop to reach node b, such as Figure 7 As shown, since node 2 covers the uncovered node b;

[0098] 3) Traverse the neighbors to select, node 3 covers node c, node 4 covers node d, node 5 covers node e. Figure 8 As shown, all two-hop nodes are eventually covered.

[0099] 4) The newly added node g is a neighbor of nodes 2 and 3, and is also a two-hop neighbor of node 0. Node 0 needs to establish a route to node g. Fig. 9 As shown, since the reachability R(2) and R(3) of node 2 and node 3 are both 0, comparing the coverage C(i) of node 2 and node 3, C(2) is 4 and C(3) is 3, node 3 is selected as the next hop to reach node g.

[0100] Specifically, step S22 includes the following sub-steps:

[0101] S221: The source node broadcasts a routing request signaling Req carrying a link weight;

[0102] The link weight is an evaluation value after normalization of the link quality parameters, ranging from 0 to 1. The larger the link weight, the better the link quality. The initial link weight is 1. The node that receives the routing request signaling Req multiplies the link weight in the routing request signaling Req by the corresponding link weight calculated locally as the comprehensive link weight of the path passed by the routing request signaling Req. The larger the comprehensive link weight, the better the quality of the entire path.

[0103] S222: other nodes receive the route request signaling Req, and establish a route to the source node according to the link weight. Determine whether the destination node is the current node or there is a route to the destination node. If so, unicast a reply route response message Rep. Otherwise, update the link weight and broadcast the route request signaling Req as needed.

[0104] Among them, since the active route within the range of two hops has been established, when Req reaches the range of two hops from the destination node, a routing response message Rep will be replied.

[0105] S223: The source node receives the route request signaling Rep and establishes a route to the destination node according to the link weight.

[0106] For further understanding, the following examples are used for illustration. Fig.10 In the network topology shown, the process of node 1 establishing a route to node 8 on demand is as follows:

[0107] 1) Node 1 broadcasts a routing request signal Req, where the source node is 1, the requested destination node is 7, and the link weight is 1;

[0108] 2) Node 5 receives the route request signaling Req from three paths (path 1: 1-2-5; path 2: 1-5; path 3: 1-4-5), calculates the corresponding comprehensive link weights (path 1: 0.48; path 2: 0.3; path 3: 0.45), selects path 1 with the largest comprehensive link weight, establishes a reverse route to the source node, and updates the comprehensive link weight (0.48) to the route request signaling Req before forwarding;

[0109] 3) After receiving the routing request signaling Req forwarded by node 5, node 6 updates the corresponding link weight. Since node 6 already has a route to node 8, it directly unicasts a routing response message Rep.

[0110] 4) The routing response message Rep reaches node 1 via path 6-5-2-1, and node 1 establishes a route to node 8.

[0111] S3: When a node receives a service, it performs routing judgment according to the destination address to determine whether the service is an internal area service or an external area service.

[0112] If it is determined to be an internal area service, the node forwards the service according to the pre-established route without the need for additional route search or establishment process.

[0113] If it is determined to be an external area service, the node triggers the on-demand routing through the virtual gateway mechanism and forwards the service according to the on-demand routing. Fig.11 As shown, the details are as follows:

[0114] S31: When the load device under this node sends an ARP request to obtain the MAC address corresponding to the IP of the load device under other nodes, this node will intercept the ARP request;

[0115] S32: After receiving the ARP request, the node assembles an ARP response message with the virtual gateway MAC address and replies to the downstream load device;

[0116] S33: After receiving the ARP response message including the MAC address of the virtual gateway, the downstream load device sends the service message to the virtual gateway;

[0117] S34: After receiving the service message, the node searches for the next hop route according to the destination IP address, removes the ETH message header in the service message, and sends it through the wireless link;

[0118] S35: After receiving the service message, the destination node assembles the ETH message header according to the destination node, and sends the service message to the downstream load device corresponding to the destination node IP, thereby completing the entire communication process.

[0119] Compared with other typical routing protocols, the present invention has lower network overhead and lower network latency in the UAV swarm communication scenario. Fig.12 As shown, a 200-node networking simulation environment is built, where the network has a maximum of 8 hops, and about 80% of the nodes are reachable within two hops. The simulation is run for 30 minutes and the results are analyzed. The three performance indicators of service end-to-end delay, route establishment time, and total number of bits of route overhead of OLSR, AODV, and the routing scheme of the present invention are compared through simulation results.

[0120] The simulation results are as follows Figures 13-15 Combined with the service end-to-end delay, route establishment time and route overhead indicators, the solution of the present invention is more suitable for application scenarios with a small number of overall hops in large-scale drone swarm networks. This solution can achieve lower delay, route overhead and route establishment time.

[0121] Based on the same technical concept, an embodiment of the present invention also provides an electronic device, which can implement the large-scale drone swarm network communication method process provided by the above embodiment of the present invention. In one embodiment, the electronic device can be a server, or a terminal device or other electronic device. Fig.16 As shown, the electronic device may include:

[0122] At least one processor, and a memory connected to the at least one processor. The specific connection medium between the processor and the memory is not limited in the embodiment of the present invention. Fig.16 The example in this article is that the processor and memory are connected through a bus. Fig.16 The connections between other components are shown in bold lines, which are only for illustration and are not intended to be limiting. The bus can be divided into address bus, data bus, control bus, etc. Fig.16 In the diagram, only one thick line is used, but this does not mean that there is only one bus or only one type of bus. Alternatively, a processor can also be called a controller, and there is no limitation on the name.

[0123] In an embodiment of the present invention, the memory stores instructions that can be executed by at least one processor, and the at least one processor can execute the large-scale drone swarm network communication method discussed above by executing the instructions stored in the memory. The processor can implement Fig.16 The functions of each module in the device shown.

[0124] Among them, the processor is the control center of the device, which can use various interfaces and lines to connect the various parts of the entire control device, and monitor the device as a whole by running or executing instructions stored in the memory and calling data stored in the memory, various functions of the device and processing data.

[0125] In an optional design, the processor may include one or more processing units, and the processor may integrate an application processor and a modem processor, wherein the application processor mainly processes an operating system, a user interface, and application programs, and the modem processor mainly processes wireless communications. It is understandable that the modem processor may not be integrated into the processor. In some embodiments, the processor and the memory may be implemented on the same chip, and in some embodiments, they may also be implemented separately on separate chips.

[0126] The processor may be a general-purpose processor, such as a CPU, a digital signal processor, an application-specific integrated circuit, a field programmable gate array or other programmable logic device, a discrete gate or transistor logic device, or a discrete hardware component, and may implement or execute the methods, steps, and logic block diagrams disclosed in the embodiments of the present invention. A general-purpose processor may be a microprocessor or any conventional processor, etc. The steps of a large-scale drone swarm network communication method disclosed in the embodiments of the present invention may be directly embodied as being executed by a hardware processor, or may be executed by a combination of hardware and software modules in the processor.

[0127] As a non-volatile computer-readable storage medium, the memory can be used to store non-volatile software programs, non-volatile computer executable programs and modules. The memory may include at least one type of storage medium, such as flash memory, hard disk, multimedia card, card-type memory, random access memory (Random Access Memory, RAM), static random access memory (Static Random Access Memory, SRAM), programmable read-only memory (Programmable Read Only Memory, PROM), read-only memory (Read Only Memory, ROM), electrically erasable programmable read-only memory (Electrically Erasable Programmable Read-Only Memory, EEPROM), magnetic memory, disk, optical disk, etc. The memory is any other medium that can be used to carry or store the desired program code in the form of instructions or data structures and can be accessed by a computer, but is not limited thereto. The memory in the embodiment of the present invention can also be a circuit or any other device that can realize a storage function, used to store program instructions and / or data.

[0128] By designing and programming the processor, the code corresponding to the large-scale drone swarm network communication method introduced in the above embodiment can be fixed into the chip, so that the chip can execute Figure 1 The steps of the method of the embodiment shown. How to design and program a processor is a technique known to those skilled in the art and will not be described in detail here.

[0129] Based on the same inventive concept, an embodiment of the present invention also provides a storage medium, which stores computer instructions. When the computer instructions are executed on a computer, the computer executes a large-scale drone swarm network communication method discussed above.

[0130] In some optional embodiments, the present invention also provides various aspects of a large-scale drone swarm network communication method, which can also be implemented in the form of a program product, which includes a program code. When the program product is run on an apparatus, the program code is used to enable the control device to execute the steps of a large-scale drone swarm network communication method according to various exemplary embodiments of the present invention described above in this specification.

[0131] It should be noted that, although several units or subunits of the device are mentioned in the above detailed description, this division is merely exemplary and not mandatory. In fact, according to an embodiment of the present invention, the features and functions of two or more units described above can be embodied in one unit. Conversely, the features and functions of a unit described above can be further divided into multiple units to be embodied. In addition, although the operation of the method of the present invention is described in a specific order in the accompanying drawings, this does not require or imply that these operations must be performed in this specific order, or that all the operations shown must be performed to achieve the desired results. Additionally or alternatively, some steps can be omitted, multiple steps can be combined into one step for execution, and / or one step can be decomposed into multiple steps for execution.

[0132] Those skilled in the art will appreciate that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0133] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a server, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0134] Program code for performing the operations of the present invention may be written using any combination of one or more programming languages, including object-oriented programming languages ​​such as Java, C++, etc., and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on the user computing device, partially on the user equipment, as a stand-alone software package, partially on the user computing device and partially on a remote computing device, or entirely on a remote computing device or server.

[0135] Where a remote computing device is involved, the remote computing device may be connected to the user computing device through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computing device (e.g., via the Internet using an Internet service provider).

[0136] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0137] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0138] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. For those skilled in the art, the present invention may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A large-scale drone swarm network communication method, characterized in that: The steps include: S1: After a node joins the network, it defines an area with a radius of two hops with itself as the center; the area within the radius is the internal area, and the area outside the radius is the external area; S2: According to the difference between the internal area and the external area, different routing algorithms are selected to establish routing: Establish routing directly in the internal area; Establish routing on demand in external areas based on business needs; S3: When a node receives a service, it performs routing judgment according to the destination address to determine whether the service is an internal area service or an external area service; If it is determined to be an internal area service, the node forwards the service according to the pre-established route; If it is determined to be an external area service, the node triggers the on-demand routing through the virtual gateway mechanism and forwards the service according to the on-demand routing.

2. The large-scale drone swarm network communication method according to claim 1, characterized in that: The step S2 of directly establishing a route in the internal area includes the following sub-steps: S211: The node completes the establishment of a one-hop route according to the one-hop networking neighbor information base carried by the MAC layer control time slot; S212: The node calculates the two-hop neighbor information of the node according to the neighbor information base of the neighbor carried by the MAC layer control time slot, and completes the establishment of the two-hop routing according to the two-hop neighbor information.

3. The large-scale drone swarm network communication method according to claim 2, characterized in that: The method for establishing the two-hop route in step S212 is: firstly calculate and select the next hop according to the comprehensive link MCS algorithm, and if no next hop can be selected, then complete the establishment of the two-hop route according to the load balancing link selection algorithm.

4. The large-scale drone swarm network communication method according to claim 3 is characterized in that: The comprehensive link MCS algorithm includes the following sub-steps: S2121: Calculate the mcs values ​​involved in all paths from the current node to a two-hop neighbor; S2122: compare the smallest mcs values ​​among all the paths, and select the path corresponding to the largest mcs value as the path to the two-hop neighbor; S2123: If there are multiple maximum mcs values ​​in step S2122, select the remaining path with the largest mcs value among these paths; S2124: If there are multiple paths with completely identical mcs values ​​to reach the two-hop neighbor, then enter the load balancing link selection algorithm; Otherwise, the two-hop route is established directly.

5. The large-scale drone swarm network communication method according to claim 4, characterized in that: The load balancing link selection algorithm includes the following sub-steps: S2125: Calculate the one-hop neighbor set of the node and the two-hop neighbor coverage of the node; S2126: adding the only node in the one-hop neighbor set of the node that reaches a certain node in the two-hop neighbor set of the node to the next-hop neighbor set, and removing the nodes in the two-hop neighbor set that are covered by the selected next-hop neighbor set; S2127: When there is a node in the two-hop neighbor set of the node that is not covered by any node in the next-hop neighbor set, execute step S2128; if there is no node, the algorithm ends; S2128: Calculate the two-hop neighbor reachability of the node in the one-hop neighbor set of the node; S2129: Select a node as the next hop from the nodes whose two-hop neighbor reachability is not 0 in the one-hop neighbor set of the node. If there are multiple choices, select the one with the lowest two-hop neighbor reachability. If there are still multiple choices, select the one with low two-hop neighbor coverage. Remove the nodes in the two-hop neighbor set that are already covered by the next hop set, and return to step S2127. S21210: Establish a set of all next-hop neighbors of the node, that is, the next-hop nodes of the two-hop route; at this point, the two-hop route is established.

6. The large-scale drone swarm network communication method according to claim 1, characterized in that: The step S2 of establishing a route in the external area according to business needs includes the following sub-steps: S221: The source node broadcasts a routing request signaling Req carrying a link weight; S222: other nodes receive the route request signaling Req and establish a route to the source node according to the link weight; Determine whether the destination node is the local node or there is a route to the destination node. If so, unicast reply route response message Rep; otherwise, update the link weight and broadcast route request signaling Req as needed; S223: The source node receives the route request signaling Rep and establishes a route to the destination node according to the link weight.

7. The large-scale drone swarm network communication method according to claim 1, characterized in that: In step 3, the node triggers the on-demand established route through the virtual gateway mechanism, and performs service forwarding according to the on-demand established route, including the following sub-steps: S31: When the load device under this node sends an ARP request to obtain the MAC address corresponding to the IP of the load device under other nodes, this node will intercept the ARP request; S32: After receiving the ARP request, the node assembles an ARP response message with the virtual gateway MAC address and replies to the downstream load device; S33: After receiving the ARP response message including the MAC address of the virtual gateway, the downstream load device sends the service message to the virtual gateway; S34: After receiving the service message, the node searches for the next hop route according to the destination IP address, removes the ETH message header in the service message, and sends it through the wireless link; S35: After receiving the service message, the destination node assembles the ETH message header according to the destination node, and sends the service message to the downstream load device corresponding to the destination node IP, thereby completing the entire communication process.

8. An electronic device, characterized in that: include: at least one processor; and a memory communicatively coupled to the at least one processor; The memory stores instructions that can be executed by the at least one processor, and the at least one processor executes the method as described in any one of claims 1 to 7 by executing the instructions stored in the memory.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium is used to store instructions, and when the instructions are executed, the method according to any one of claims 1 to 7 is implemented.

10. A computer program product, characterized in that When the computer program product is called by a computer, the computer is caused to execute the method according to any one of claims 1 to 7.

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