Load balancing routing method and device, equipment and storage medium

Abstract

The invention relates to the technical field of network communication, and discloses a load balancing routing method, device and equipment and a storage medium, and the method comprises the steps: obtaining target network situation information corresponding to other nodes in a mobile ad hoc network according to a preset sensing period; determining a comprehensive load index based on the target network situation information; determining a target routing path through the target network situation information and the comprehensive load index; and sending the service data to the destination node according to the target routing path. In the mobile ad hoc network, each node senses the target network situation information of the surrounding nodes in a distributed manner, the target routing path is determined according to the target network situation information and the comprehensive load index, and the data packet is sent to the target node according to the target routing path, so that load balancing of each node on the target routing path is realized; unbalanced service distribution is avoided, and the system packet loss rate is reduced, so that the end-to-end time delay of the system is reduced; and through effective balancing of each node, the throughput of the whole system is improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of network communication, and particularly relates to a load balancing routing method and device, equipment and a storage medium. BACKGROUND

[0002] Mobile Ad Hoc Network (Mobile Ad Hoc Network) is a kind of infrastructure-free mobile communication network, and the whole network is composed of a large number of peer nodes in a distributed manner, has the characteristics of quick and flexible networking, strong invulnerability, no base station support, etc., and has become an important part of modern military and civilian communication systems. Mobility, potential large number of network nodes and limited resources make the routing technology in self-organizing network extremely challenging.

[0003] The routing protocol in the mobile ad hoc network must quickly adapt to frequent and unpredictable topology changes under limited resources, while quickly and accurately delivering service packets. However, the existing mobile ad hoc network has the problem of uneven distribution of services, and the existing mobile ad hoc network routing method has the problems of large queue delay and large packet loss rate, resulting in large end-to-end delay and poor system throughput.

[0004] The above content is only used to assist in understanding the technical solutions of the present application, and does not represent the acknowledgement of the above content as prior art. SUMMARY

[0005] The main purpose of the present application is to provide a load balancing routing method, device, equipment and storage medium, which aims to solve the technical problems of large packet loss rate of each node, large end-to-end delay and poor system throughput of the existing mobile ad hoc network routing method.

[0006] To achieve the above purpose, the present application provides a load balancing routing method, which is applied to a mobile ad hoc network comprising a plurality of nodes, the method is executed by any node, and the method comprises:

[0007] Obtaining target network situation information corresponding to other nodes in the mobile ad hoc network according to a preset sensing period;

[0008] Determining a comprehensive load index based on the target network situation information;

[0009] Determining a target routing path through the target network situation information and the comprehensive load index;

[0010] According to the target routing path, service data is sent to a destination node.

[0011] In an embodiment, the step of determining a comprehensive load index based on the target network situation information comprises:

[0012] Obtain local load based on current network situation information;

[0013] Based on the target network situation information, determine the adjacent loads corresponding to the target neighbor nodes in the mobile ad hoc network;

[0014] The overall load metric is determined by the local load and the adjacent loads.

[0015] In one embodiment, the step of determining the target routing path using the target network situation information and the comprehensive load index includes:

[0016] Determine channel quality indicators based on the target network situation information;

[0017] The target routing path is determined using the channel quality metric and the comprehensive load metric.

[0018] In one embodiment, the step of determining the channel quality index based on the target network situation information includes:

[0019] Based on the target network situation information, obtain the target transmission information corresponding to the other nodes;

[0020] The current transmission rate is determined based on the target transmission information and preset modulation parameters;

[0021] The channel quality index is determined by the current transmission rate and the preset transmission rate.

[0022] In one embodiment, the step of determining the target routing path using the channel quality metric and the comprehensive load metric includes:

[0023] The channel quality index and the comprehensive load index are pre-weighted to determine the target link cost with the destination node;

[0024] The target routing path is determined by the target link cost.

[0025] In one embodiment, the step of determining the target routing path using the target link cost includes:

[0026] Obtain the current transmission link criteria input by the user;

[0027] The target routing path is determined based on the current transmission link criteria and the target link cost.

[0028] In one embodiment, the step of determining the target routing path based on the current transmission link criterion and the target link cost includes:

[0029] Determine the target load balancing routing algorithm based on the current transmission link criteria;

[0030] The target routing path is determined using the target balanced routing algorithm and the target link cost.

[0031] Furthermore, to achieve the above objectives, this application also proposes a load balancing routing device, which is applied to a mobile ad hoc network containing several nodes. The load balancing routing device includes:

[0032] The information acquisition module is used to acquire target network situation information corresponding to other nodes in the mobile ad hoc network according to a preset sensing period;

[0033] The indicator calculation module is used to determine the comprehensive load indicator based on the target network situation information;

[0034] The path selection module is used to determine the target routing path based on the target network situation information and the comprehensive load index;

[0035] The data transmission module is used to send service data to the destination node according to the target routing path.

[0036] In addition, to achieve the above objectives, this application also proposes a load balancing routing device, which includes: a memory, a processor, and a load balancing routing program stored in the memory and executable on the processor, the load balancing routing program being configured to implement the steps of the load balancing routing method described above.

[0037] In addition, to achieve the above objectives, this application also proposes a storage medium storing a load balancing routing program, which, when executed by a processor, implements the steps of the load balancing routing method described above.

[0038] This application discloses a load balancing routing method, apparatus, device, and storage medium. The method includes: acquiring target network situation information corresponding to other nodes in a mobile ad hoc network according to a preset sensing period; determining a comprehensive load index based on the target network situation information; determining a target routing path through the target network situation information and the comprehensive load index; and sending service data to the destination node according to the target routing path. In this application, each node in the mobile ad hoc network distributes its perception of the target network situation information of surrounding nodes, determines the target routing path based on the target network situation information and the comprehensive load index, and then sends data packets to the destination node using source routing or hop-by-hop routing according to the determined target routing path. This effectively achieves load balancing among nodes on the target routing path, avoids unbalanced service distribution, reduces system packet loss rate, and thus reduces system end-to-end latency; and improves the overall system throughput through effective balancing of each node. Attached Figure Description

[0039] Figure 1This is a first flowchart illustrating the first embodiment of the load balancing routing method of this application;

[0040] Figure 2 This is a schematic diagram of network situation awareness for the first embodiment of the load balancing routing method of this application;

[0041] Figure 3 This is a second flowchart illustrating the first embodiment of the load balancing routing method of this application;

[0042] Figure 4 This is a first flowchart illustrating the second embodiment of the load balancing routing method of this application;

[0043] Figure 5 This is a second flowchart illustrating the second embodiment of the load balancing routing method of this application;

[0044] Figure 6 This is a simulated network topology diagram of the second embodiment of the load balancing routing method of this application;

[0045] Figure 7 This is a simulation delay curve of the second embodiment of the load balancing routing method of this application;

[0046] Figure 8 This is a schematic diagram of the throughput of a simulation system for the second embodiment of the load balancing routing method of this application;

[0047] Figure 9 This is a schematic diagram of the simulated node load in the second embodiment of the load balancing routing method of this application;

[0048] Figure 10 This is a schematic diagram of the module structure of the load balancing routing device according to an embodiment of this application;

[0049] Figure 11 This is a schematic diagram of the device structure of the hardware operating environment involved in the load balancing routing method in this application embodiment.

[0050] The realization of the purpose, functional features and advantages of this application will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0051] It should be understood that the specific embodiments described herein are merely illustrative of the technical solutions of this application and are not intended to limit this application.

[0052] To better understand the technical solution of this application, a detailed description will be provided below in conjunction with the accompanying drawings and specific implementation methods.

[0053] The main solution of this application is: to obtain target network situation information corresponding to other nodes in the mobile ad hoc network according to a preset sensing period; to determine the comprehensive load index based on the target network situation information; to determine the target routing path through the target network situation information and the comprehensive load index; and to send service data to the destination node according to the target routing path.

[0054] Due to limitations in power and bandwidth of mobile ad hoc network (MAV) equipment, routing protocols in MAVs should be able to distribute routing traffic evenly across nodes. However, existing MAVs suffer from unbalanced traffic distribution, with nodes heavily loaded with traffic consuming power too quickly. As more and more nodes run out of power, network connectivity decreases, leading to network fragmentation. Furthermore, nodes with high traffic loads result in significant queuing latency and packet loss rates, causing existing routing methods to suffer from substantial end-to-end latency and packet loss when routing through these nodes.

[0055] To address the shortcomings of the existing technologies, this application provides a load balancing routing algorithm for mobile ad hoc networks. In this mobile ad hoc network, each node is distributed to perceive the target network situation information of surrounding nodes. Based on the target network situation information and comprehensive load indicators, the target routing path is determined. Then, data packets are sent to the destination node using source routing or hop-by-hop routing according to the determined target routing path. This effectively achieves load balancing among nodes on the target routing path, avoids unbalanced service distribution, reduces end-to-end system latency, and improves the overall system throughput through effective balancing of nodes.

[0056] It should be noted that the execution subject in this embodiment can be a computing service device with data processing, data transmission, program execution, and mobile routing functions, such as a tablet computer, personal computer, or mobile phone, or a data-intensive application capable of performing the above functions. This embodiment does not specifically limit it. The following uses a load routing device (hereinafter referred to as a routing device) as the execution subject to describe this embodiment and the following embodiments.

[0057] Based on this, embodiments of this application provide a load balancing routing method, referring to... Figure 1 , Figure 1 This is a first flowchart illustrating the first embodiment of the load balancing routing method of this application.

[0058] In this embodiment, the load balancing routing method is applied to a mobile ad hoc network containing several nodes. The method is executed by any node, and the load balancing routing method includes steps S10 to S40:

[0059] Step S10: Obtain target network situation information corresponding to other nodes in the mobile ad hoc network according to a preset sensing period;

[0060] It should be understood that the load balancing routing method proposed in this embodiment can be determined by the routing device corresponding to any node in the mobile ad hoc network. That is, in this embodiment, each node in the mobile ad hoc network can use the load balancing routing method proposed in this embodiment to perform distributed computing locally.

[0061] Accordingly, the information acquisition method of this application is node-distributed situational awareness, that is, all nodes in the entire network can periodically perceive the remaining nodes in the network, that is, the target network situational information corresponding to the other nodes mentioned above, using a distributed method. The network situational information can refer to the state and trend of the entire network at a certain moment, which is composed of various network hardware and software operating conditions, network events or behaviors, and network user behaviors. In this embodiment, the target network situational information may include network node identifiers, the amount of data waiting to be sent by nodes, the remaining power of nodes, the link status between nodes, and other information.

[0062] It is easy to understand that in this embodiment, each node can broadcast its own situational information and propagate it through flooding, or it can merge all the situational information it possesses and send it to its neighboring nodes. Meanwhile, the load balancing method proposed in this embodiment can be an active routing system maintained according to a preset period.

[0063] Specifically, the period at which each node sends situational information can be fixed, or it can be distributed hierarchically according to the topology of the mobile ad hoc network. That is, in this embodiment, the aforementioned preset sensing period can be a fixed value, in which case each node can directly distribute its corresponding current network situational information to other nodes according to the set preset sensing period; or, the aforementioned preset sensing period can also be a variable value set according to the network topology, in which case each node can set different preset sensing periods according to the proximity of other nodes in the mobile ad hoc network to distribute the current network situational information.

[0064] For ease of understanding, combined with Figure 2 The network situation information perception process in this embodiment will be illustrated with an example. Figure 2 This is a network situation awareness diagram illustrating the first embodiment of the load balancing routing method of this application. Figure 2 As shown, assuming the mobile ad hoc network contains 15 nodes, namely Node1 to Node15, the status of each node and link is represented by different colors. Specifically, green indicates a signal-to-noise ratio (SNR) greater than 20dB, orange indicates an SNR between 10-20dB, and red indicates an SNR less than 10dB. Similarly, green indicates that there are fewer than 10 data packets in the current task queue, orange indicates that there are between 10 and 100 data packets in the current task queue, and red indicates that there are more than 100 data packets in the current task queue. Figure 2Each node in the network can perform distributed sensing to obtain target network situation information corresponding to other nodes in the network, and then determine the route to other nodes based on the target network situation information.

[0065] Step S20: Determine the comprehensive load index based on the target network situation information;

[0066] It is important to understand that, addressing the issue of uneven service distribution in existing mobile ad hoc networks, the load information in this application considers not only the local load of each node (the latency factors that the receiver may experience) but also the load of neighboring nodes. Because mobile ad hoc networks utilize wireless channels for transmission, channel access between neighboring nodes is mutually exclusive. Therefore, when calculating routes, if the path selection for each hop simultaneously considers the impact on the transmission of surrounding neighboring nodes, the routing rate can be effectively improved. Thus, this embodiment can not only combine the local load of each node for routing but also analyze the load of each node's neighboring nodes. This allows the routing device to perform overall load balancing control across all nodes in the entire network, thereby reducing network latency.

[0067] In one feasible implementation, refer to Figure 3 , Figure 3 This is a second flowchart illustrating the first embodiment of the load balancing routing method of this application. Step S20 may include steps A1 to A3:

[0068] Step A1: Obtain local load based on current network status information;

[0069] Step A2: Determine the adjacent loads corresponding to the target neighbor nodes in the mobile ad hoc network based on the target network situation information;

[0070] Step A3: Determine the comprehensive load index based on the local load and the adjacent load.

[0071] It is understood that the aforementioned target neighbor node can be a neighbor node in the network topology that shares a wireless channel with the current node. In this embodiment, the routing device can directly determine the queuing amount of data packets to be sent by the current node based on its own corresponding current network situation information, i.e., the aforementioned local load. At the same time, the routing device can also determine the adjacent load based on the target network situation information obtained from the target neighbor node, thereby determining the total load of the current node based on the local load and the adjacent load, i.e., the load characterization of the current node.

[0072] It should be noted that the aforementioned comprehensive load index may include the sum of the loads corresponding to all nodes in the mobile ad hoc network. To achieve load balancing among nodes in the mobile ad hoc network during routing, in this embodiment, the routing device can not only determine the sum of the loads corresponding to the current node based on the current network situation information and the target network situation information, but also determine the sum of the loads corresponding to other nodes in the mobile ad hoc network based on the target network situation information. Therefore, it determines the routing load index, i.e., the aforementioned comprehensive load index, based on the sum of the loads of the current node and the sum of the loads corresponding to other nodes.

[0073] For ease of understanding, Figure 2 The calculation process of the comprehensive load index will be illustrated with an example, assuming... Figure 2 The local loads (LL) of nodes 1-15 are 28, 73, 67, 97, 106, 113, 41, 102, 98, 24, 18, 75, 144, 51 and 88 respectively, and all adjacent nodes can communicate wirelessly.

[0074] Based on the aforementioned distributed situational awareness process, it is assumed that all nodes can grasp the overall network situational information, thus having a clear understanding of the total load of each node. Therefore, based on the local load values ​​of nodes 1-15 and... Figure 2 In the network topology, the total traffic load (TL) of each node can be calculated as follows:

[0075]

[0076] Among them, S i = {node k | node k is a one-hop neighbor of node i}, i = 1, 2, ..., 15; LL k This represents the local load corresponding to node k.

[0077] As can be seen from the above formula, in this embodiment, the load representation method for each node can be the sum of the local load corresponding to each node and the loads of all one-hop neighbor nodes (i.e., adjacent loads). Therefore, for node 1 ( Figure 2 For Node1 in the example, its adjacent target neighbor nodes can be Node3 and Node2, and correspondingly, their total load can be: 28 + 73 + 67 = 168. Based on the principle of similarity, Figure 2 The TL values ​​of nodes 1-15 can be 168, 304, 355, 476, 578, 403, 183, 297, 571, 642, 318, 335, 317, 307, and 256 respectively. The sum of the 15 loads obtained at this time can constitute the above-mentioned comprehensive load index.

[0078] Step S30: Determine the target routing path using the target network situation information and the comprehensive load index;

[0079] Step S40: Send the service data to the destination node according to the target routing path.

[0080] It should be noted that, after determining the comprehensive load index corresponding to each node in the mobile ad hoc network, the routing devices of each node in this embodiment can perform distributed routing calculations based on the target network situation information and the comprehensive load index to determine a feasible target routing path between the node and the destination node. Then, the routing devices can send service data packets to the destination node according to the target routing path, using source routing or hop-by-hop routing.

[0081] Specifically, if the routing device uses source routing, the data packets sent by the node can include the identifier of the path to the destination node calculated locally, and then the service data is transmitted to the destination node in sequence according to the node identifier;

[0082] If the routing device uses hop-by-hop routing, the data packets sent by the nodes may only contain the identifier of the destination node. The relay nodes corresponding to the subsequent target routing path will then forward the data packets to the next node according to their local routing tables, until the service data is transmitted to the destination node.

[0083] In this embodiment, the routing devices corresponding to each node distribute and perceive the situational information of surrounding nodes. Based on the target network situational information and comprehensive load indicators, they determine the target routing path and then send data packets to the destination node using source routing or hop-by-hop routing based on the determined route. Therefore, this embodiment not only perceives the network topology but also has a clear understanding of the network status (node ​​service load, inter-node link status, etc.), which is beneficial for routing decisions.

[0084] Meanwhile, in this embodiment, the load representation of each node is the sum of its loads. That is, the load representation of each node in this embodiment considers not only the local load (the latency factors that the receiver may experience) but also the load of neighboring nodes. Therefore, based on a routing load index that includes the sum of the loads of all nodes, the path selection for each hop is analyzed using a comprehensive load index, taking into account the impact on the transmission of surrounding neighboring nodes. Thus, this embodiment uses the local load of a node and the load of its target neighboring nodes sharing the wireless channel to jointly determine the route, effectively achieving load balancing among nodes on the target routing path, avoiding unbalanced service distribution, reducing system packet loss rate, and thereby reducing system end-to-end latency; and by effectively balancing the sum of the loads of all nodes, it improves the overall system throughput.

[0085] Therefore, compared with existing routing methods that only consider the shortest hop count or the local service load of nodes, each node in this embodiment uses the above-mentioned load balancing routing method to perform distributed computing locally, reducing node processing latency and packet loss rate of each node in the system, thereby effectively increasing the overall system throughput, reducing end-to-end latency, and achieving the effect of load balancing of nodes on the path.

[0086] This embodiment discloses a load balancing routing method, which includes: acquiring target network situation information corresponding to other nodes in a mobile ad hoc network according to a preset sensing period; acquiring local load based on the current network situation information; determining the adjacent load corresponding to the target neighbor node in the mobile ad hoc network according to the target network situation information; determining a comprehensive load index through the local load and the adjacent load; determining a target routing path through the target network situation information and the comprehensive load index; and sending service data to the destination node according to the target routing path. In this embodiment, the routing devices corresponding to each node in the mobile ad hoc network distributedly sense the target network situation information of surrounding nodes, determine the target routing path based on the target network situation information and the comprehensive load index, and then send data packets to the destination node according to the determined target routing path using source routing or hop-by-hop routing. This effectively achieves load balancing among nodes on the target routing path, avoids unbalanced service distribution, reduces system packet loss rate, and thus reduces system end-to-end latency; and improves the overall system throughput through effective balancing of each node.

[0087] Based on the first embodiment of this application, in the second embodiment of this application, the same or similar content as the first embodiment can be referred to the above description, and will not be repeated hereafter.

[0088] Reference Figure 4 , Figure 4 This is a first flowchart illustrating the second embodiment of the load balancing routing method of this application. In this embodiment, step S30 includes steps B1 to B2:

[0089] Step B1: Determine the channel quality indicators based on the target network situation information;

[0090] It is easy to understand that, based on the first embodiment, this embodiment can consider the communication channel quality of each link in the mobile ad hoc network, determine the corresponding channel quality index, and further determine the routing method with less latency from the current node to the destination node.

[0091] In one feasible implementation, in this embodiment, reference is made to Figure 5 , Figure 5 This is a second flowchart illustrating the second embodiment of the load balancing routing method of this application. Step B1 includes steps C1 to C3:

[0092] Step C1: Obtain the target transmission information corresponding to the other nodes based on the target network situation information;

[0093] Step C2: Determine the current transmission rate based on the target transmission information and preset modulation parameters;

[0094] Step C3: Determine the channel quality index using the current transmission rate and the preset transmission rate.

[0095] It is understood that the aforementioned target transmission information can be link state information between the current node and other nodes in the mobile ad hoc network, such as information transmission rate or signal-to-noise ratio (SNR), which can be directly obtained from the target network situational information. The aforementioned preset modulation parameters can be pre-set modulation and coding scheme (MCS) parameters for the mobile ad hoc network. MCS parameters are a set of parameters describing the signal modulation method and channel coding scheme; they define the modulation method and coding strategy of the wireless signal and can affect the rate and quality of communication in the mobile ad hoc network. In this embodiment, the modulation method and data rate of the mobile ad hoc network can be estimated based on the MCS parameters.

[0096] Therefore, in this embodiment, each node, based on the target network situation information it possesses, utilizes the link state information between nodes (which may be SNR information between nodes) to estimate the modulation scheme and data rate according to the MCS parameters, and determines the channel quality characterization between the current node and other nodes in the mobile ad hoc network. Specifically, this embodiment can combine the physical layer adaptive modulation scheme during actual transmission, and determine the channel quality characterization of the links between nodes in the mobile ad hoc network by the ratio of the actual transmission rate to the maximum achievable rate.

[0097] In a practical implementation, assuming the current ad hoc network operates at 20MHz, the MCS parameters of a single spatial stream (i.e., transmission path) are as shown in Table 1 below:

[0098] Table 1. MCS parameters for a single spatial flow at 20MHz

[0099] MCS Label Modulation Code Rate Data Rate (Mbps) 0 BPSK 1 / 2 6.5 1 QPSK 1 / 2 13 2 QPSK 3 / 4 19.5 3 16-QAM 1 / 2 26 4 16-QAM 3 / 4 39 5 64-QAM 2 / 3 52 6 64-QAM 3 / 4 58.5 7 64-QAM 5 / 6 65

[0100] In Table 1, BPSK (Binary Phase Shift Keying) is binary phase shift keying, QPSK (Quadrature Phase Shift Keying) is quadrature phase shift keying, 16-QAM (16-Quadrature Amplitude Modulation) is 16th-order quadrature amplitude modulation, and 64-QAM (64-Quadrature Amplitude Modulation) is 64th-order quadrature amplitude modulation.

[0101] At the same time, according to Figure 2 It can be seen that the SNR between node 4 and node 9 can be 4dB, and according to Shannon's theorem, the corresponding channel capacity between node 4 and node 9 is 31.65 Mbps (megabits per second). Therefore, referring to Table 1, the corresponding MCS number is 3. Therefore, combining... Figure 2 Based on the MCS parameters shown in Table 1 above, the current transmission rate between node 4 and node 9 is 26 Mbps.

[0102] Based on the above principles, in this embodiment, the channel quality characterization between node i and node j in a mobile ad hoc network can be defined as follows:

[0103]

[0104] Among them, R ij R represents the data rate represented by the MCS parameter corresponding to the SNR of the link between node i and node j. max This represents the data rate corresponding to the current maximum MCS parameter.

[0105] Therefore, based on the above formula, the channel quality characterization between node 4 and node 9 can be determined as 26 / 65 = 0.4. Similarly, each node can estimate the channel quality characterization of all inter-node links in the entire mobile ad hoc network.

[0106] It is easy to understand that the aforementioned channel quality index can include the channel quality representation between all nodes in the mobile ad hoc network. That is, in this embodiment, the current node can not only determine the channel quality representation between itself and other nodes based on the target network situation information, but also determine the channel quality representation between each pair of other nodes based on the target network situation information. Finally, a channel quality index containing the channel quality representation between each pair of all nodes in the entire mobile ad hoc network is obtained, thereby performing routing based on the channel conditions of the entire network to reduce routing latency.

[0107] In summary, in this embodiment, each node, based on the target network situation information it possesses, utilizes the link status information between each node (which may be the SNR information between nodes), and estimates the modulation scheme and data rate based on the MCS parameters to determine the channel quality characteristics corresponding to the links between all nodes in the entire mobile ad hoc network, namely the aforementioned channel quality index.

[0108] Step B2: Determine the target routing path using the channel quality index and the comprehensive load index.

[0109] It is easy to understand that after further determining the channel quality indicators corresponding to all links between nodes in the mobile ad hoc network, this embodiment can combine the analysis of channel quality and comprehensive load to select a route path with good channel quality and balanced load for transmission, thereby effectively reducing latency and improving information transmission rate.

[0110] In one feasible implementation, in this embodiment, step B2 includes steps D1 to D2:

[0111] Step D1: Perform a preset weighting on the channel quality index and the comprehensive load index to determine the target link cost with the destination node;

[0112] Step D2: Determine the target routing path using the target link cost.

[0113] It should be noted that during the data routing process in this embodiment, the entries in the routing table may include the destination node address, the next-hop node, and the link cost, which can be determined based on a weighted average of channel quality indicators and comprehensive load indicators.

[0114] It should be understood that in this embodiment, the routing device can determine the link cost of each link between nodes by weighting the load characterization of the nodes and the channel quality characterization of each link between the nodes.

[0115] Specifically, in this embodiment, the link cost from node i to node j can be represented as TL. j and Q ij The function, denoted as f(TL). j Q ij If so, it can be as follows:

[0116]

[0117] Where α is the channel quality characterization Q ij Weight in link cost.

[0118] Therefore, based on the above formula, each node can determine the link cost corresponding to all feasible routing paths between itself and the destination node, i.e., the target link cost. After calculating the link cost corresponding to each routing path, this embodiment can summarize and judge the target link cost according to different criteria to determine the most suitable routing path between itself and the destination node, i.e., the target routing path.

[0119] In one feasible implementation, in this embodiment, step D2 includes steps D21 to D22:

[0120] Step D21: Obtain the current transmission link criteria input by the user;

[0121] Step D22: Determine the target routing path based on the current transmission link criteria and the target link cost.

[0122] It is easy to understand that, in order to improve the user experience, this embodiment can summarize and judge the link cost based on the current transmission link criteria input by the user. The aforementioned current transmission link criteria can be an additivity metric (which corresponds to the minimum system latency requirement) or a minimum metric (which corresponds to the minimum system load requirement).

[0123] The additivity metric can be expressed as follows: For a path from node 1 to node N, assuming the path nodes include node 1, node 2, ..., node N-1, node N, choose a path that minimizes the link cost of that path, i.e., obtain f(TL2,Q) 12 )+f(TL2,Q 12 )+...+f(TL N Q (N-1)N (Minimum)

[0124] The minimum metric can be expressed as follows: For a path from node 1 to node N, assuming the path contains nodes from node 1 to node N, select a path that minimizes the maximum link cost among all links on that path, i.e., obtain max{f(TL2,Q 12 ),f(TL2,Q 12 ),...,f(TL N Q (N-1)N The smallest.

[0125] In one feasible implementation, in this embodiment, step D22 includes steps D221 to D222:

[0126] Step D221: Determine the target load balancing routing algorithm based on the current transmission link criteria;

[0127] Step D222: Determine the target routing path using the target balanced routing algorithm and the target link cost.

[0128] It is important to understand that in this embodiment, the routing device can select algorithms such as Dijkstra's algorithm, Bellman-Ford algorithm, and depth-first search to determine the path from the local node to other nodes based on the criterion characteristics of the current transmission link criterion input by the user. Both Dijkstra's algorithm and Bellman-Ford algorithm are based on relaxation operations, meaning the estimated shortest path value is gradually replaced by a more accurate value until the optimal solution is obtained. In both algorithms, the estimated distance between each edge is larger than the actual value during calculation and is replaced by the minimum length of the newly found path. Specifically, Dijkstra's algorithm greedily selects the unprocessed node with the minimum weight and then relaxes its outgoing edges; while Bellman-Ford's algorithm simply relaxes all edges. Therefore, these two algorithms are suitable for additive metrics. Depth-first search starts from the unvisited neighbors of the current node and performs a depth-first traversal of the graph until all vertices in the graph connected to the current node by a path have been visited. Therefore, it can be used for both additive metrics and minimum metric criteria.

[0129] In summary, when the current transmission link criterion is an additivity metric, Dijkstra's algorithm, Bellman-Ford algorithm, or depth-first search algorithm can be selected as the target balanced routing algorithm; while when the current transmission link criterion is a minimum metric, depth-first search algorithm can be selected as the target balanced routing algorithm.

[0130] Therefore, in this embodiment, after determining the current transmission link criteria, a corresponding feasible balanced routing algorithm can be determined to obtain the target routing path that conforms to the current transmission link criteria among the various routing paths from the current node to the destination node.

[0131] In this embodiment, each node can calculate its load profile and the channel quality profile of the inter-node links based on the target network situation information it possesses. By weighting these values, the target link cost between nodes is determined, and the optimal routing path from the local node to the destination node, i.e., the aforementioned target routing path, is determined using methods such as additivity metrics or minimum metrics. Compared with traditional routing methods, the distributed routing method proposed in this embodiment can achieve load balancing among nodes along the path while selecting the routing path with the best channel quality that meets user needs, further improving the user experience.

[0132] Furthermore, to verify the beneficial effects of the load balancing method proposed in this embodiment, this embodiment can compare and verify the existing routing methods and the load balancing routing method proposed in this embodiment in a simulation environment. It is assumed that the simulation uses link additivity measurement, and the link cost only considers the load characterization of nodes, and the structural diagram of the mobile ad hoc network during the simulation process is as follows... Figure 6 As shown, Figure 6This is a simulated network topology diagram of the second embodiment of the load balancing routing method of this application.

[0133] exist Figure 6 In the network topology shown, initially none of the nodes are sending any traffic. Starting from the 10th second, nodes 1 and 8 generate traffic packets every 25ms and send them to node 14. The size of each traffic packet is 1500 bytes. Simultaneously, the entire network senses the target network situational information at a period of 0.2s. The simulation results are as follows: Figure 7 and Figure 8 As shown, Figure 7 This is a simulation delay curve of the second embodiment of the load balancing routing method of this application. Figure 8 This is a schematic diagram of the throughput of a simulation system for the second embodiment of the load balancing routing method of this application.

[0134] Understandable Figure 7 and Figure 8 The three curves in the simulation results show three different routing criteria: ① shortest path (hop count) routing; ② minimum local load routing, which selects a path that minimizes the link cost of the path, where the cost of each link segment is the local load of the node; ③ the load balancing routing method proposed in this application.

[0135] It is easy to understand that, from Figure 7 and Figure 8 As can be seen, by adopting the minimum comprehensive load criterion proposed in this application, the latency is significantly reduced and the system throughput is greatly increased compared with existing routing methods. Therefore, the load balancing routing method proposed in this application has significant advantages over traditional routing methods in terms of system throughput and end-to-end latency.

[0136] Furthermore, this embodiment can also be based on Figure 6 Another simulation experiment was conducted using the proposed simulated network topology diagram. Starting from the 10th second, all nodes generated traffic packets every 15ms and sent them to any specific node. The size of each traffic packet was 1500 bytes. Simultaneously, the entire network sensed the target network situational information at a period of 0.2s. The simulation results are as follows: Figure 9 As shown, Figure 9 This is a schematic diagram of the simulated node load in the second embodiment of the load balancing routing method of this application.

[0137] at this time, Figure 9 The three curves also correspond to three different routing criteria: ① shortest path (hop count) routing; ② minimum local load routing; ③ the load balancing routing method proposed in this application. Figure 9 The vertical axis represents the remaining amount of the MAC layer buffer in each node (i.e., MAC buffer rest), with different colors corresponding to the remaining load of different nodes.Figure 9 In the `Object:mobile_node_i of Office Network`, it represents the remaining load of node i. It's important to understand that... Figure 9 The larger the remaining buffer amount corresponding to a node, the smaller the node's data cache size, and the faster the data transmission speed. That is, before 10 seconds, the buffer has no data packets (100). As the number of data packets generated by the service increases, the buffer size begins to increase. Therefore, from... Figure 9 As can be seen, under the same business load, the minimum comprehensive load routing method proposed in this embodiment can make the buffer cache size of each node similar and remain at a low level over time. Compared with traditional algorithms, it achieves the effect of traffic balancing, thus reducing node processing latency and effectively increasing the overall system throughput and reducing end-to-end latency, which has significant advantages.

[0138] This embodiment obtains target transmission information corresponding to other nodes based on target network situation information; determines the current transmission rate based on the target transmission information and preset modulation parameters; and determines the channel quality index using the current transmission rate and preset transmission rate. The channel quality index and comprehensive load index are weighted in a preset manner to determine the target link cost with the destination node; the current transmission link criterion input by the user is obtained; a target balanced routing algorithm is determined based on the current transmission link criterion; and the target routing path is determined using the target balanced routing algorithm and the target link cost. In this embodiment, each node can determine its load characterization and inter-node link channel quality characterization based on the target network situation information it possesses. By weighting these characteristics, the target link cost between nodes is determined, and the optimal routing path from the local node to the destination node, i.e., the aforementioned target routing path, is determined using additivity metrics or minimum metrics. Compared with traditional routing methods, the distributed routing method proposed in this embodiment can achieve load balancing among nodes on the path while selecting the routing path with the best channel quality and meeting user needs, thereby further reducing system latency and improving user experience.

[0139] It should be noted that the above examples are only for understanding this application and do not constitute a limitation on the load balancing routing method of this application. Any simple modifications based on this technical concept are within the protection scope of this application.

[0140] This application also provides a load balancing routing device; please refer to... Figure 10 , Figure 10 This is a schematic diagram of the module structure of the load balancing routing device in an embodiment of this application, as shown below. Figure 10 As shown, the load balancing routing device is applied to a mobile ad hoc network containing several nodes. The load balancing routing device includes:

[0141] Information acquisition module T1 is used to acquire target network situation information corresponding to other nodes in the mobile ad hoc network according to a preset sensing period;

[0142] The indicator calculation module T2 is used to determine the comprehensive load indicator based on the target network situation information;

[0143] The path selection module T3 is used to determine the target routing path based on the target network situation information and the comprehensive load index.

[0144] The data transmission module T4 is used to send service data to the destination node according to the target routing path.

[0145] In one possible implementation, in this embodiment, the index calculation module T2 is also used to obtain the local load based on the current network situation information;

[0146] The indicator calculation module T2 is also used to determine the adjacent load corresponding to the target neighbor node in the mobile ad hoc network based on the target network situation information;

[0147] The index calculation module T2 is also used to determine the comprehensive load index through the local load and the adjacent load.

[0148] In one possible implementation, in this embodiment, the path selection module T3 is further configured to determine channel quality indicators based on the target network situation information.

[0149] The path selection module T3 is also used to determine the target routing path through the channel quality index and the comprehensive load index.

[0150] In one possible implementation, in this embodiment, the path selection module T3 is further configured to obtain target transmission information corresponding to the other nodes based on the target network situation information;

[0151] The path selection module T3 is also used to determine the current transmission rate based on the target transmission information and preset modulation parameters;

[0152] The path selection module T3 is also used to determine the channel quality index based on the current transmission rate and the preset transmission rate.

[0153] In one possible implementation, in this embodiment, the path selection module T3 is further configured to perform a preset weighting on the channel quality index and the comprehensive load index to determine the target link cost between the destination node;

[0154] The path selection module T3 is also used to determine the target routing path based on the target link cost.

[0155] In one possible implementation, in this embodiment, the path selection module T3 is further used to obtain the current transmission link criteria input by the user;

[0156] The path selection module T3 is also used to determine the target routing path based on the current transmission link criteria and the target link cost.

[0157] In one possible implementation, in this embodiment, the path selection module T3 is further configured to determine the target balanced routing algorithm based on the current transmission link criteria;

[0158] The path selection module T3 is also used to determine the target routing path through the target balanced routing algorithm and the target link cost.

[0159] The load balancing routing device provided in this application, employing the load balancing routing method described in the above embodiments, can solve the technical problem of how to achieve highly reliable and low-energy information transmission between satellite and ground information source terminals in a satellite Internet of Things. Compared with the prior art, the beneficial effects of the load balancing routing device provided in this application are the same as those of the load balancing routing method provided in the above embodiments, and other technical features in the load balancing routing device are the same as those disclosed in the methods of the above embodiments, and will not be repeated here.

[0160] This application provides a load balancing routing device, which includes: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to execute the load balancing routing method in the above embodiment 1.

[0161] The following is for reference. Figure 11 This document illustrates a structural diagram of a load balancing routing device suitable for implementing embodiments of this application. The load balancing routing device in these embodiments may include, but is not limited to, mobile terminals such as mobile phones, laptops, digital broadcast receivers, PDAs (Personal Digital Assistants), PADs (Portable Application Description), PMPs (Portable Media Players), and in-vehicle terminals (e.g., in-vehicle navigation terminals), as well as fixed terminals such as digital TVs and desktop computers. Figure 11 The load balancing routing device shown is merely an example and should not impose any limitations on the functionality and scope of use of the embodiments of this application.

[0162] like Figure 11As shown, the load balancing routing device may include a processing unit 1001 (e.g., a central processing unit, a graphics processing unit, etc.), which can perform various appropriate actions and processes according to a program stored in read-only memory (ROM) 1002 or a program loaded from storage device 1003 into random access memory (RAM) 1004. The RAM 1004 also stores various programs and data required for the operation of the load balancing routing device. The processing unit 1001, ROM 1002, and RAM 1004 are interconnected via a bus 1005. An input / output (I / O) interface 1006 is also connected to the bus. Typically, the following systems can be connected to the I / O interface 1006: input devices 1007 including, for example, touchscreens, touchpads, keyboards, mice, image sensors, microphones, accelerometers, gyroscopes, etc.; output devices 1008 including, for example, liquid crystal displays (LCDs), speakers, vibrators, etc.; storage devices 1003 including, for example, magnetic tapes, hard disks, etc.; and communication devices 1009. Communication device 1009 allows the load balancing routing device to communicate wirelessly or wiredly with other devices to exchange data. While the figure shows load balancing routing devices with various systems, it should be understood that implementation or having all of the systems shown is not required. More or fewer systems may be implemented alternatively.

[0163] Specifically, according to the embodiments disclosed in this application, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments disclosed in this application include a computer program product comprising a computer program carried on a computer-readable medium, the computer program containing program code for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via a communication device, or installed from storage device 1003, or installed from ROM 1002. When the computer program is executed by processing device 1001, it performs the functions defined in the methods of the embodiments disclosed in this application.

[0164] The load balancing routing device provided in this application, employing the load balancing routing method in the above embodiments, can solve the technical problem of load balancing routing. Compared with the prior art, the beneficial effects of the load balancing routing device provided in this application are the same as those of the load balancing routing method provided in the above embodiments, and other technical features in this load balancing routing device are the same as those disclosed in the previous embodiment method, and will not be repeated here.

[0165] It should be understood that the various parts disclosed in this application can be implemented using hardware, software, firmware, or a combination thereof. In the description of the above embodiments, specific features, structures, materials, or characteristics can be combined in any suitable manner in one or more embodiments or examples.

[0166] The above are merely specific embodiments of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

[0167] This application provides a storage medium having computer-readable program instructions (i.e., a computer program) stored thereon, the computer-readable program instructions being used to execute the load balancing routing method in the above embodiments.

[0168] The storage medium provided in this application may be, for example, a USB flash drive, but is not limited to, electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices, or any combination thereof. More specific examples of storage media may include, but are not limited to: electrical connections with one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof. In this embodiment, the storage medium may be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, system, or device. The program code contained on the storage medium may be transmitted using any suitable medium, including but not limited to: wires, optical cables, RF (Radio Frequency), etc., or any suitable combination thereof.

[0169] The aforementioned storage medium may be included in the load balancing routing device; or it may exist independently and not be installed in the load balancing routing device.

[0170] The aforementioned storage medium carries one or more programs. When the aforementioned one or more programs are executed by the load balancing routing device, the load balancing routing device becomes a load balancing router.

[0171] Computer program code for performing the operations of this application can be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, and C++, and conventional procedural programming languages ​​such as the "C" language or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving remote computers, the remote computer can be connected to the user's computer via any type of network—including a Local Area Network (LAN) or a Wide Area Network (WAN)—or can be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0172] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of this application. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, can be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0173] The modules described in the embodiments of this application can be implemented in software or hardware. The names of the modules do not necessarily limit the functionality of the unit itself.

[0174] The readable storage medium provided in this application is a storage medium that stores computer-readable program instructions (i.e., a computer program) for executing the above-described load balancing routing method, and is capable of solving the technical problem of load balancing routing. Compared with the prior art, the beneficial effects of the storage medium provided in this application are the same as the beneficial effects of the load balancing routing method provided in the above embodiments, and will not be repeated here.

[0175] The above are only some embodiments of this application and do not limit the patent scope of this application. All equivalent structural transformations made under the technical concept of this application and using the contents of the specification and drawings of this application, or direct / indirect applications in other related technical fields, are included in the patent protection scope of this application.

Claims

1. A load balancing routing method, characterized in that, The method is applied to a mobile ad hoc network comprising several nodes, the method is executed by any one node, and the method includes: According to a preset sensing period, acquire the target network situation information corresponding to other nodes in the mobile ad hoc network; Determine the comprehensive load index based on the target network situation information; The target routing path is determined using the target network situation information and the comprehensive load index. The service data is sent to the destination node according to the target routing path.

2. The load balancing routing method as described in claim 1, characterized in that, The step of determining the comprehensive load index based on the target network situation information includes: Obtain local load based on current network situation information; Based on the target network situation information, determine the adjacent loads corresponding to the target neighbor nodes in the mobile ad hoc network; The overall load metric is determined by the local load and the adjacent loads.

3. The load balancing routing method as described in claim 1, characterized in that, The step of determining the target routing path using the target network situation information and the comprehensive load index includes: Determine channel quality indicators based on the target network situation information; The target routing path is determined using the channel quality metric and the comprehensive load metric.

4. The load balancing routing method as described in claim 3, characterized in that, The step of determining the channel quality index based on the target network situation information includes: Based on the target network situation information, obtain the target transmission information corresponding to the other nodes; The current transmission rate is determined based on the target transmission information and preset modulation parameters; The channel quality index is determined by the current transmission rate and the preset transmission rate.

5. The load balancing routing method as described in claim 4, characterized in that, The step of determining the target routing path using the channel quality metric and the comprehensive load metric includes: The channel quality index and the comprehensive load index are pre-weighted to determine the target link cost with the destination node; The target routing path is determined by the target link cost.

6. The load balancing routing method as described in claim 5, characterized in that, The step of determining the target routing path through the target link cost includes: Obtain the current transmission link criteria input by the user; The target routing path is determined based on the current transmission link criteria and the target link cost.

7. The load balancing routing method as described in claim 6, characterized in that, The step of determining the target routing path based on the current transmission link criterion and the target link cost includes: Determine the target load balancing routing algorithm based on the current transmission link criteria; The target routing path is determined using the target balanced routing algorithm and the target link cost.

8. A load balancing routing device, characterized in that, The load balancing routing device is applied to a mobile ad hoc network containing several nodes, and the device includes: The information acquisition module is used to acquire target network situation information corresponding to other nodes in the mobile ad hoc network according to a preset sensing period; The indicator calculation module is used to determine the comprehensive load indicator based on the target network situation information; The path selection module is used to determine the target routing path based on the target network situation information and the comprehensive load index; The data transmission module is used to send service data to the destination node according to the target routing path.

9. A load balancing routing device, characterized in that, The device includes: a memory, a processor, and a load balancing routing program stored in the memory and executable on the processor, the load balancing routing program being configured to implement the steps of the load balancing routing method as described in any one of claims 1 to 7.

10. A storage medium, characterized in that, The storage medium stores a load balancing routing program, which, when executed by a processor, implements the steps of the load balancing routing method as described in any one of claims 1 to 7.

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