Network topology determination method and device, equipment, storage medium and program product

Abstract

The embodiment of the invention provides a network topology determination method and device, equipment, a storage medium and a program product. In the process of determining a network topology structure of a to-be-generated network, a screening connection set can be screened out from a connection link based on a set constraint condition; therefore, the connection links which cannot meet the transmission requirements are eliminated, so that the target connection link which is subsequently screened out from the screening connection set has relatively good data transmission performance and stability, and the overall performance and reliability of the network topology are improved. In addition, according to the embodiment of the invention, an edge selection strategy is optimized, and the network topology data transmission performance can be further improved in a mode of considering the signal strength of a connection link in an edge selection process. According to the embodiment of the invention, the technical problems of low network performance and poorer reliability caused by difficulty in generating the optimal network topology in a complex wireless network environment in related technologies are solved.

Description

Technical Field

[0001] Embodiments of the present application relate to the field of communications, and in particular, to a method, apparatus, device, storage medium, and program product for determining a network topology. Background Art

[0002] At present, with the rapid development of network communication technology, the scale of wireless networking support is expanding, especially in outdoor multi-hop network scenarios, the number of communication nodes and connection complexity of the network have increased significantly. Therefore, in order to improve network performance, how to find the optimal path in a complex network to build the optimal topology of the network has become a hot topic in research and application. Traditional network path optimization algorithms include minimum spanning tree algorithm, genetic algorithm, annealing algorithm, ant colony algorithm and fireworks algorithm, etc. These algorithms are based on different theories and models and are configured in different network topology optimization scenarios. Among them, the minimum spanning tree algorithm aims to select a tree containing all communication nodes and with the smallest total weight value from a weighted connected graph. The Prim algorithm is a relatively classic implementation method of the minimum spanning tree algorithm. The principle of the Prim algorithm is to start from a starting communication node and select the edges with the smallest weight in turn to add the new communication node to the spanning tree.

[0003] However, when determining the network topology based on the traditional Prim algorithm, factors such as network parameters and communication parameters in the communication links in the wireless network are not fully considered. Some communication links cannot meet the data transmission requirements of the wireless network, resulting in poor reliability of the resulting wireless network. In addition, the edge selection strategy based on the traditional Prim algorithm does not consider the actual communication conditions of the connection links. The data transmission performance of the connection links determined as the edges of the spanning tree is poor, making it difficult to generate the optimal network topology in a complex wireless network environment, resulting in poor performance of the wireless network. Summary of the invention

[0004] The embodiments of the present application provide a network topology determination method, apparatus, device, storage medium and program product. In the process of determining the network topology, the embodiments of the present application can filter out a filter connection set in the connection link based on the set constraints, and determine the edges of the spanning tree based on the filter connection set, thereby improving the overall performance and reliability of the network topology. In addition, the embodiments of the present application optimize the edge selection strategy, and by considering the signal strength of the connection link during the edge selection process, the overall performance and data transmission efficiency of the network topology can be improved. The embodiments of the present application solve the technical problem in the related art that it is difficult to generate the optimal network topology in a complex wireless network environment, resulting in poor network performance and reliability.

[0005] In a first aspect, an embodiment of the present application provides a method for determining a network topology, the method comprising:

[0006] Measuring the signal strength between each communication node in the network to be generated, wherein each signal strength corresponds to a connection link;

[0007] Calculate a weight value of a corresponding connection link based on each of the signal strengths;

[0008] An initial node is selected from each of the communication nodes, and connection screening is performed in turn based on the set constraints to obtain a filtered connection set, and edge connections are added according to the filtered connection set, a spanning tree algorithm, and a weight value of each connection link in the filtered connection set to obtain a network topology structure of the network to be generated.

[0009] In a second aspect, an embodiment of the present application provides a network topology determination device, the network topology determination device comprising:

[0010] A signal strength measurement module, configured to measure the signal strength between each communication node in the network to be generated, wherein each signal strength corresponds to a connection link;

[0011] A weight value determination module, configured to calculate a weight value of a corresponding connection link based on each of the signal strengths;

[0012] A topology structure determination module is configured to select an initial node from each of the communication nodes, perform connection screening based on set constraints in turn to obtain a screened connection set, and add edge connections based on the screened connection set, a spanning tree algorithm, and a weight value of each connection link in the screened connection set to obtain a network topology structure of the network to be generated.

[0013] In a third aspect, an embodiment of the present application provides a network topology determination device, the network topology determination device comprising a processor and a memory;

[0014] The memory is configured to store a computer program and transmit the computer program to the processor;

[0015] The processor is configured to execute the network topology determination method as described in the first aspect according to the instructions in the computer program.

[0016] In a fourth aspect, an embodiment of the present application provides a storage medium storing computer executable instructions, wherein the computer executable instructions, when executed by a computer processor, are configured to execute the network topology determination method as described in the first aspect.

[0017] In a fifth aspect, an embodiment of the present application provides a computer program product, including a computer program, which, when executed by a processor, implements the network topology determination method described in the first aspect.

[0018] The embodiments of the present application provide a network topology determination method, apparatus, device, storage medium, and program product. In the process of determining the network topology structure of the network to be generated, the embodiments of the present application can filter out a filter connection set in the connection link based on the set constraints, thereby eliminating the connection links that cannot meet the transmission requirements, so that the target connection links subsequently filtered out from the filter connection set have good data transmission performance and stability, thereby improving the overall performance and reliability of the network topology. In addition, the embodiments of the present application also optimize the edge selection strategy, and by considering the signal strength of the connection link in the edge selection process, the network topology data transmission performance can be further improved. The embodiments of the present application solve the technical problem that it is difficult to generate the optimal network topology in a complex wireless network environment in the related art, resulting in poor network performance and reliability. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] Figure 1 A flowchart of a network topology determination method provided in an embodiment of the present application.

[0020] Figure 2 A flowchart of another network topology determination method provided in an embodiment of the present application.

[0021] Figure 3 A schematic diagram of a communication node provided in an embodiment of the present application.

[0022] Figure 4 A schematic diagram of a spanning tree generation process provided in an embodiment of the present application.

[0023] Figure 5 A schematic diagram of the final spanning tree provided in an embodiment of the present application.

[0024] Figure 6 A flowchart of another network topology determination method provided in an embodiment of the present application.

[0025] Figure 7 A schematic diagram of the structure of a network topology determination device provided in an embodiment of the present application.

[0026] Figure 8 A schematic diagram of the structure of a network topology determination device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0027] The following description and accompanying drawings fully illustrate the specific embodiments of the present application so that those skilled in the art can practice them. The examples represent possible variations only. Unless explicitly required, separate components and functions are optional, and the order of operations can vary. The parts and features of some embodiments may be included in or replace the parts and features of other embodiments. The scope of the embodiments of the present application includes the entire scope of the claims, and all available equivalents of the claims. In this article, each embodiment may be represented individually or generally by the term "invention", which is only for convenience, and if more than one invention is disclosed in fact, it is not intended to automatically limit the scope of the application to any single invention or inventive concept. In this article, relational terms such as first and second, etc. are only configured to distinguish one entity or operation from another entity or operation, without requiring or implying any actual relationship or order between these entities or operations. Moreover, the term "include", "comprise" or any other variant thereof is intended to cover non-exclusive inclusion, so that the process, method or device including a series of elements includes not only those elements, but also other elements that are not explicitly listed. The various embodiments are described in a progressive manner herein, and each embodiment focuses on the differences from other embodiments. The same or similar parts between the various embodiments can be referred to each other. As for the structures, products, etc. disclosed in the embodiments, since they correspond to the parts disclosed in the embodiments, the description is relatively simple, and the relevant parts can be referred to the description of the method part.

[0028] At present, with the rapid development of network communication technology, the scale of wireless networking support is expanding day by day, especially in outdoor multi-hop network scenarios, the number of communication nodes and connection complexity of the network have increased significantly. Therefore, in order to improve network performance, how to find the optimal path in a complex network to build the optimal topology of the network has become a hot topic in research and application. Traditional network path optimization algorithms include minimum spanning tree algorithm, genetic algorithm, annealing algorithm, ant colony algorithm and fireworks algorithm, etc. These algorithms are based on different theories and models and are configured in different network topology optimization scenarios. Among them, the minimum spanning tree algorithm aims to select a tree with the smallest total weight value containing all communication nodes from a weighted connected graph. Prim algorithm and Kruskal algorithm are two more classic implementation methods of the minimum spanning tree algorithm. The principle of Prim algorithm is to start from a starting communication node and select the edge with the smallest weight value in turn to add the new communication node to the spanning tree. Kruskal algorithm sorts all edges by weight value and selects the edge with the smallest weight value that will not form a loop in turn until a tree covering all communication nodes is generated. Prim's algorithm and Kruskal's algorithm are efficient and accurate in calculating the optimal path of a simple network.

[0029] However, as the scale of wireless networks increases, the connection between communication nodes in the network is not just a simple relationship between the existence or non-existence, but also needs to consider the data transmission capacity between the communication nodes. When determining the network topology based on the traditional Prim algorithm, factors such as the data transmission capacity and communication parameters in the communication link in the wireless network are not fully considered. Some communication links cannot meet the data transmission requirements of the wireless network, resulting in poor reliability of the resulting wireless network. In addition, the edge selection strategy based on the traditional Prim algorithm does not consider the actual communication situation of the connection link. The data transmission performance of the connection link determined as the edge of the spanning tree is poor, making it difficult to generate the optimal network topology in a complex wireless network environment, resulting in poor performance of the wireless network.

[0030] In order to solve the above technical problems, the present application embodiment provides a method for determining a network topology, such as Figure 1 As shown, Figure 1 A flowchart of a network topology determination method provided in an embodiment of the present application. The network topology determination method provided in an embodiment of the present application can be executed by a network topology determination device, which can be implemented by software and / or hardware. The network topology determination device can be composed of two or more physical entities, or can be composed of one physical entity. For example, the network topology determination device can be a gateway, a server, or a router. The network topology determination method provided in an embodiment of the present application includes the following steps:

[0031] Step 101: Measure the signal strength between each communication node in the network to be generated, wherein each signal strength corresponds to a connection link.

[0032] In this embodiment, it is first necessary to measure the signal strength of each communication node in the network to be generated, so as to determine the possible connection links between each communication node based on the signal strength between each communication node. Exemplarily, the signal strength between each communication node can be determined by measuring the RSSI (received signal strength indication) value. After measuring the RSSI value between each communication node, an adjacency matrix is ​​constructed based on the RSSI value. The adjacency matrix records all possible connection links between communication nodes in the network and their corresponding signal strengths. In one embodiment, the communication node can be a dual-frequency node. When constructing the adjacency matrix, it is necessary to measure the RSSI values ​​of the dual-frequency nodes under different operating frequency bands.

[0033] Step 102: Calculate the weight value of the corresponding connection link based on each signal strength.

[0034] After determining the possible connection links between the various communication nodes, it is necessary to further determine the signal strength corresponding to each connection link to determine the weight value of the connection link. The weight value is the determining factor in the subsequent spanning tree algorithm edge selection process. By calculating the weight value according to the signal strength corresponding to each connection link, the subsequent spanning tree algorithm can consider the communication status of each connection link when selecting edges. Exemplarily, the weight value can be determined directly according to the signal strength. The greater the signal strength, the greater the weight value; or the maximum throughput of the connection link is predicted based on the signal strength, and the weight value of the connection link is determined based on the maximum throughput. The greater the maximum throughput, the greater the weight value.

[0035] Step 103: Select an initial node from each communication node, perform connection screening based on the set constraints in turn to obtain a filtered connection set, and add edge connections according to the filtered connection set, the spanning tree algorithm, and the weight value of each connection link in the filtered connection set to obtain the network topology structure of the network to be generated.

[0036] After determining the weight value corresponding to each connection link, a spanning tree can be constructed based on the spanning tree algorithm. Before iterating based on the spanning tree algorithm, it is necessary to determine the preset constraint conditions. In this embodiment, the constraint conditions are used to screen out connection links that meet the data transmission requirements to improve the overall topology performance and reliability of the subsequently generated network. The content of the preset conditions can be pre-set by the user according to actual needs. For example, the user can constrain at least one factor of the frequency band, node hop number, number of sub-nodes, signal strength, and fault status of the connection link in the constraint conditions.

[0037] In the process of constructing a spanning tree based on a spanning tree algorithm, it is first necessary to select an initial node from the communication node, for example, the initial node can be the root node in the communication node. After determining the initial node, the spanning tree algorithm is used to iterate the communication node. In each iteration, connection screening is performed in the connection links based on the set constraints in turn to eliminate the connection links that cannot meet the transmission requirements. The connection links retained constitute a screening connection set. After that, a target connection link can be determined as the edge of the spanning tree according to the weight value of each connection link in the retained screening connection set and the edge connection is added, and then it is iterated again. After the iteration is completed, the network topology of the network to be generated can be obtained according to the constructed spanning tree. In one embodiment, the spanning tree algorithm can adopt the Prim algorithm. When determining the network topology based on the Prim algorithm, it is first necessary to construct a selected node set and an unselected node set, add the initial node to the selected node set, and add other nodes to the unselected node set. Then the selected node set is iterated, and in each iteration, based on the set constraints, the connection links connecting the selected node set and the unselected node set are screened out to meet the data transmission requirements, and the target connection link with the largest weight value in the filtered connection set is used as the edge of the spanning tree and the spanning tree is constructed. After that, the selected node set, the unselected node set and the priority queue are updated, and the selected node set is iterated again. After the iteration end condition is reached, the network topology structure of the network to be generated can be determined according to the spanning tree.

[0038] As described above, an embodiment of the present application provides a method for determining a network topology. In the process of determining the network topology structure of the network to be generated, the embodiment of the present application can filter out a filter connection set in the connection link based on the set constraints, thereby eliminating the connection links that cannot meet the transmission requirements, so that the target connection links subsequently filtered out from the filter connection set have good data transmission performance and stability, thereby improving the overall performance and reliability of the network topology. In addition, the embodiment of the present application also optimizes the edge selection strategy, and by considering the signal strength of the connection link in the edge selection process, the network topology data transmission performance can be further improved. The embodiment of the present application solves the technical problem that it is difficult to generate the optimal network topology in a complex wireless network environment in the related art, resulting in poor network performance and reliability.

[0039] The present application also provides another method for determining network topology, such as Figure 2 As shown, Figure 2 A flowchart of another method for determining network topology provided in an embodiment of the present application is provided. Figure 2 The network topology determination method shown is a specific embodiment of the above-mentioned network topology determination method. The network topology determination method provided in the embodiment of the present application includes:

[0040] Step 201: Measure the signal strength between each communication node in the network to be generated, wherein each signal strength corresponds to a connection link.

[0041] Step 202: Calculate the theoretical maximum throughput of the corresponding connection link based on each signal strength.

[0042] After measuring the signal strength between each communication node, it is necessary to further calculate the theoretical maximum throughput of the corresponding connection link based on each signal strength. In one embodiment, the theoretical maximum throughput of each connection link can be predicted based on a pre-trained throughput prediction model. When training the throughput prediction model, after collecting the RSSI values ​​and actual throughput data between each communication node, dividing the training set and the test set based on the RSSI value and the actual throughput data, the training set is used to train the multivariate linear regression model, and the parameters are estimated by the optimization algorithm until the loss function converges. Then, a suitable evaluation indicator is selected to measure the performance of the multivariate linear regression model, and the test set is used for evaluation. After obtaining the trained throughput prediction model, the RSSI value can be input into the corresponding throughput prediction model to obtain the theoretical maximum throughput output by the throughput prediction model.

[0043] Step 203: Determine the sum of the number of parent node hops corresponding to each connection link and the historical load of the corresponding communication node.

[0044] While predicting the theoretical maximum throughput of the connection link, it is also necessary to determine the number of parent node hops corresponding to each connection link and the sum of the historical loads of the communication nodes in each connection link. The number of parent node hops corresponding to each connection link refers to the number of hops between the communication node close to the root node in each connection link and the root node, and the sum of the historical loads of the corresponding communication nodes refers to the sum of the historical loads of the two communication nodes corresponding to each connection link.

[0045] Step 204: Calculate the weight value of the corresponding connection link according to the theoretical maximum throughput, the number of parent node hops, and the sum of historical loads corresponding to each connection link.

[0046] After determining the theoretical maximum throughput, the number of parent node hops, and the sum of historical loads corresponding to each connection link, the weight value of each connection link can be calculated. In one embodiment, the weight value of the connection link can be determined by weighted summing the theoretical maximum throughput, the number of parent node hops, and the sum of historical loads corresponding to each connection link. In another embodiment, the weight value corresponding to each connection link can be obtained by introducing a correction factor by the product method to correct the theoretical maximum throughput, the number of parent node hops, and the sum of historical loads and then multiplying them.

[0047] Based on the above embodiment, in step 204, the weight value of the corresponding connection link is calculated according to the sum of the theoretical maximum throughput, the number of parent node hops and the historical load corresponding to each connection link, including:

[0048] Step 2041: determine a first weight coefficient, a second weight coefficient, and a third weight coefficient corresponding to the theoretical maximum throughput, the number of parent node hops, and the sum of the historical loads, respectively.

[0049] In one embodiment, when calculating the weight value of a connection link, it is first necessary to determine the first weight coefficient, the second weight coefficient, and the third weight coefficient corresponding to the theoretical maximum throughput, the number of parent node hops, and the sum of historical loads, respectively, wherein the specific values ​​of the first weight coefficient, the second weight coefficient, and the third weight coefficient can be set in advance and are not specifically limited in this embodiment.

[0050] Step 2042: According to the first weight coefficient, the second weight coefficient and the third weight coefficient, a weighted sum is performed on the theoretical maximum throughput, the number of parent node hops and the sum of the historical load corresponding to each connection link to obtain a weight value corresponding to each connection link.

[0051] After determining the first weight coefficient, the second weight coefficient, and the third weight coefficient, the theoretical maximum throughput, the number of parent node hops, and the sum of historical loads corresponding to each connection link can be weighted and summed to obtain the weight value corresponding to each connection link. l The specific calculation formula is as follows:

[0052] Weight l = a1*theoretical maximum throughput + a2*sum of historical loads + a3*number of parent node hops

[0053] Wherein a1, a2, a3 are the first weight coefficient, the second weight coefficient, and the third weight coefficient respectively.

[0054] Step 205: Add the root node among the communication nodes as the initial node to the selected node set, and add the other communication nodes to the unselected node set.

[0055] After determining the weight value corresponding to each connection link, the spanning tree can be constructed based on the spanning tree algorithm. Exemplarily, the spanning tree algorithm in this embodiment adopts the Prim algorithm, which first needs to construct a selected node set S1 and an unselected node set S2, and add the root node in the communication node as the initial node to the selected node set S1, and add other communication nodes to the unselected node set S2.

[0056] Step 206: Initialize a priority queue, where the priority queue is configured to store connection links connecting communication nodes in the selected node set and communication nodes in the unselected node set.

[0057] After initializing the selected node set and the unselected node set, it is necessary to further initialize a priority queue, wherein the priority queue is used to store connection links connecting the communication nodes in the selected node set and the communication nodes in the unselected node set. Figure 3 As shown, Figure 3 A schematic diagram of a communication node provided in an embodiment of the present application, Figure 3 The communication nodes in the example are dual-frequency nodes, and the working frequency bands are 6GH and 6GL respectively. Therefore, there are two connection links between the two communication nodes. In this embodiment, the root node N0 is added to the selected node set S1 as the initial node, and the nodes N1 to N5 are added to the unselected node set, that is, the selected node set S1 is {N0}, and the unselected node set is {N1, N2, N3, N4, N5, N6}. The priority queue is used to store the connection links between the N0 node and the N1 node, the N2 node, and the N3 node.

[0058] Step 207, iterate the selected node set based on the spanning tree algorithm. In each iteration, filter connections in the priority queue based on the set constraints to obtain a filtered connection set, and add edge connections based on the target connection link with the largest weight value in the filtered connection set.

[0059] After the priority queue is initialized, the selected node set can be iterated based on the spanning tree algorithm. Specifically, in each iteration, the connection links in the priority queue are screened based on the set constraints to eliminate the connection links that do not meet the data transmission requirements. The connection links retained in the priority queue are the screened connection set.

[0060] In one embodiment, the constraint condition includes at least one of a frequency band constraint condition, a hop count constraint condition, a sub-node quantity constraint condition, a signal strength constraint condition, and a fault status constraint condition.

[0061] The frequency band constraint is configured to constrain the working frequency band of the connection link to be different from the working frequency band of the uplink connection link. The frequency band constraint can eliminate the connection links with different working frequency bands from the uplink connection link in the priority queue, thereby avoiding co-frequency interference and improving network stability.

[0062] The signal strength constraint is configured to constrain the minimum signal strength of the connection link. The minimum signal strength can be set in advance by the user. The signal strength constraint can be used to remove the connection links in the priority queue whose signal strength is less than the minimum signal strength to improve the stability of the network.

[0063] The hop count constraint is configured to constrain the maximum hop count between the communication node and the root node of the connection link. The specific value of the maximum hop count can be set in advance by the user. The signal strength constraint can be used to eliminate the connection links between the communication node (parent node) and the root node in the priority queue whose hop count exceeds the maximum hop count. By limiting the maximum hop count of the communication node, the network delay can be controlled and the user experience can be improved.

[0064] The subnode quantity constraint is configured to constrain the maximum number of subnodes of the communication node of the connection link, where the specific value of the maximum subnode can be set in advance by the user. The subnode quantity constraint can limit the maximum number of subnodes of each communication node to prevent node overload and ensure the balance of the network. That is, it is necessary to remove the connection links that exceed the maximum number of subnodes in the connection links between the priority queue and the same communication node in the selected node set. For example, if there are 4 connection links between the priority queue and the same communication node A in the selected node set, and the connection links between communication node A and the other 3 communication nodes have been determined as the edges of the spanning tree, and the maximum number of subnodes of each communication node is 3, then the connection links connected to communication node A need to be removed from the priority queue.

[0065] The fault state constraint is configured to constrain the faulty communication nodes in the connection link to be leaf nodes in the spanning tree. The fault state constraint can detect the communication nodes with RF faults and avoid using the faulty communication nodes as relay nodes. The faulty communication nodes can only be connected to the network as leaf nodes, which reduces the failure rate of the network and improves the reliability and stability of the network.

[0066] After performing connection screening in the priority queue based on the set constraints to obtain a screened connection set, it is necessary to use the target connection link with the largest weight value in the screened connection set as the edge of the spanning tree and add the edge connection. In this embodiment, by selecting the target connection link with the largest weight value as the edge of the spanning tree, factors such as the maximum throughput of the connection link, node load, and number of hops can be comprehensively considered, the edge selection strategy is optimized, and the overall performance of the network and data transmission efficiency are improved.

[0067] Step 208: After updating the selected node set, the unselected node set and the priority queue based on the target connection link, the selected node set is iterated again until the iteration end condition is met to obtain the network topology structure of the network to be generated.

[0068] After the target connection link is determined in this iteration, the selected node set, the unselected node set and the priority queue can be further updated according to the target connection link. After the update is completed, the selected node set is iterated again until the iteration end condition is reached to obtain a complete spanning tree, and finally the network topology structure of the network to be generated can be obtained according to the complete spanning tree. Specifically, the communication nodes connected to the target connection link in the unselected node set can be added to the selected node set, and the selected node set and the unselected node set are updated. Afterwards, according to the updated selected node set and the updated unselected node set, the priority queue is updated, that is, the connection link between the updated selected node set and the updated unselected node set is re-determined to complete the update of the priority queue. It can be understood that the removed connection link does not need to be added to the priority queue. Finally, the selected node set is iterated again until the unselected node set is an empty set, and the network topology structure of the network to be generated is obtained.

[0069] For example, Figure 3 The communication node shown in FIG. 1 determines the target connection link as L1 after the first iteration. Figure 4 As shown, Figure 4 A schematic diagram of the generation process of a spanning tree provided in an embodiment of the present application. The communication node connected to L1 in the unselected node set is N1, so N1 can be added to the selected node set S1, and N1 can be deleted from the unselected node set S2. At this time, the selected node set S1 is {N0, N1}, and the unselected node set S2 is {N2, N3, N4, N5, N6}. After that, the priority queue is updated again and a second iteration is performed. In the second iteration, after eliminating the heterodyne and the signal strength lower than the minimum signal strength in the priority queue according to the constraint conditions, in the remaining filtered connection set, it is determined that the connection link with the largest weight value is L2. That is, the selected node set S1, the unselected node set S2 and the priority queue are updated according to the communication node N4 connected to L2, and then the next iteration is performed. The above iterative process is then repeated. When the unselected node set S2 is iterated to be an empty set, the iteration is terminated to obtain the final spanning tree. For example, as Figure 5 As shown, Figure 5 The schematic diagram of the final spanning tree provided in the embodiment of the present application, and finally the network topology of the network to be generated can be determined according to the final spanning tree. In addition, the time complexity of the prim algorithm in this embodiment is O(ElogV), and the space complexity is O(V+E), where E is the number of edges of the spanning tree and V is the number of nodes.

[0070] As described above, an embodiment of the present application provides a method for determining a network topology. In the process of determining the network topology structure of the network to be generated, the embodiment of the present application selects a filter connection set in the connection link based on the set constraint conditions, so that the filter connection set selected can be constrained in multiple dimensions such as frequency band, number of hops, number of sub-nodes, signal strength, and fault status, thereby improving the overall performance, reliability, and stability of the network, so that the subsequently generated network topology is more in line with actual application requirements. In addition, the embodiment of the present application also optimizes the edge selection strategy, and optimizes the edge selection strategy by comprehensively considering factors such as the maximum throughput, node load, and number of hops of the connection link in the process of edge selection, thereby improving the overall performance of the network and data transmission efficiency. The embodiment of the present application solves the technical problem that it is difficult to generate the optimal network topology in a complex wireless network environment in the related art, resulting in poor performance and reliability of the network.

[0071] The present application also provides a method for determining a network topology. Figure 6 As shown, Figure 6 A flowchart of another method for determining a network topology provided in an embodiment of the present application is shown below. Figure 6 The network topology determination method shown is a specific embodiment of the above-mentioned network topology determination method. The network topology determination method provided in the embodiment of the present application includes:

[0072] Step 301: Measure the signal strength between each communication node in the network to be generated, wherein each signal strength corresponds to a connection link.

[0073] Step 302: Calculate the weight value of the corresponding connection link based on each signal strength.

[0074] Step 303: Select an initial node from each communication node, perform connection screening based on the set constraints in turn to obtain a filtered connection set, and add edge connections according to the filtered connection set, the spanning tree algorithm, and the weight value of each connection link in the filtered connection set to obtain the network topology structure of the network to be generated.

[0075] Step 304: Determine the hop count, historical load, and available channels in the working frequency band of each communication node in the network topology.

[0076] In this embodiment, after determining the network topology, it is necessary to further allocate channels and bandwidth to each communication node in the network topology. Before allocating channels and bandwidth, it is first necessary to determine the number of hops, historical load, and available channels in the working frequency band of each communication node in the network topology, where the number of hops is the number of hops between the communication node and the root node. In addition, when the communication node is a dual-frequency node, it is necessary to determine the available channels of the communication node in different working frequency bands based on the hardware support, regulatory requirements, and surrounding environment of each communication node.

[0077] Step 305: According to the hop count and historical load of each communication node, a corresponding channel and bandwidth are allocated to each communication node in the available channels of each communication node.

[0078] After determining the number of hops, historical load, and available channels in the working frequency band of each communication node, further allocate corresponding channels and bandwidths to each communication node in the available channels in the working frequency band corresponding to each communication node according to the number of hops and historical load of each communication node. In one embodiment, when allocating channels and bandwidths, it is necessary to give priority to allocating frequency bands and channels to communication nodes with lower hops in the network to ensure the high performance of the backbone network, and at the same time, give priority to allocating larger bandwidths to communication nodes with higher historical loads to meet their business needs.

[0079] On the basis of the above embodiment, in step 305, according to the hop count and historical load of each communication node, a corresponding channel and bandwidth are allocated to each communication node in the available channels of each communication node, including:

[0080] Step 3051: Determine the hop count level corresponding to each communication node according to the hop count of each communication node. The smaller the hop count level, the closer the communication node is to the root node in the network.

[0081] Step 3052: Allocate channels to the communication nodes in each hop count level in order from small to large, and in the process of allocating channels, preferentially allocate channels with larger bandwidth to the communication nodes with larger historical loads.

[0082] In this embodiment, when allocating channels and bandwidths to communication nodes, it is first necessary to determine the hop count of the communication node, so as to determine the hop count level of the communication node according to the hop count, wherein the smaller the hop count level, the closer the communication node is to the root node in the network topology. For example, when the hop count is 1, it corresponds to the first hop count level, when the hop count is 2, it corresponds to the second hop count level, and so on, and other hop counts are deduced in the same way.

[0083] After determining the hop count level to which the communication node belongs, channels are allocated to the communication nodes in each hop count level in order from small to large according to the hop count level, so as to give priority to allocating frequency bands and channels to the communication nodes with lower hop counts in the network. In addition, in the process of allocating channels to the communication nodes in each hop count level, channels with larger bandwidths are allocated to the communication nodes with larger historical loads in priority. For example, the communication nodes in the hop count level can be sorted from large to small according to the historical load, and channels and bandwidths can be allocated to the communication nodes according to the sorting order, so as to give priority to allocating larger bandwidths to the communication nodes with higher historical loads. Specifically, first, any channel is allocated to the root node in the available channels of the root node, for example, any 160MHz channel can be selected from the available channels corresponding to the root node in different working frequency bands as the channel used in the working frequency band. Afterwards, for other communication nodes other than the root node, each hop count level is traversed in order from small to large according to the hop count level, and in the process of traversing each hop count level, each communication node in the hop count level is traversed in order from large to small according to the historical load. In the process of traversing each communication node, for the currently traversed communication node, the conflicting channels that have channel interference with other communication nodes in the corresponding available channels are eliminated based on the preset channel strength threshold, and the target channel with the largest bandwidth in the retained available channels is used as the channel used by the currently traversed communication node.

[0084] Specifically, for the currently traversed communication node, the conflicting communication node of the communication node in the adjacency matrix can be obtained according to the preset channel strength threshold, and the conflicting channel allocated to the conflicting communication node can be determined. After that, the conflicting channel is eliminated from the available channels of the currently traversed communication node to obtain the candidate channel set of the currently traversed communication node, and finally the target channel with the largest bandwidth in the candidate channel set is allocated to the currently traversed communication node.

[0085] In one embodiment, after selecting the target channel with the largest bandwidth among the reserved available channels as the channel used by the currently traversed communication node, the method further includes:

[0086] Step 3053: When the bandwidth of the target channel is less than the preset bandwidth threshold, increase the channel strength threshold corresponding to the currently traversed communication node to re-determine the conflicting channel and eliminate it, and use the target channel with the largest bandwidth in the re-reserved available channels as the channel used by the currently traversed communication node.

[0087] In one embodiment, if the bandwidth of the target channel allocated to the currently traversed communication node is less than the preset bandwidth threshold, for example, less than 40MHz, the channel needs to be readjusted. Specifically, the channel strength threshold corresponding to the currently traversed communication node can be increased in steps, thereby allowing a certain degree of interference to increase the number of available channels retained after eliminating the conflicting channels, and then the target channel with the largest bandwidth in the retained available channels is re-selected as the channel used by the currently traversed communication node. If the bandwidth of the re-determined target channel is still less than the preset bandwidth threshold, the channel strength threshold can be increased in steps and the channel can be reallocated again until the channel strength threshold reaches the preset maximum channel strength value or the bandwidth of the target channel is greater than the preset bandwidth threshold.

[0088] In one embodiment, after selecting the target channel with the largest bandwidth among the reserved available channels as the channel used by the currently traversed communication node, the method further includes:

[0089] Step 3054: When the bandwidth of the target signal is less than the preset bandwidth threshold, trace back to the first communication node to which the channel has been allocated, reduce the bandwidth of the first communication node, and re-allocate the channel to the currently traversed communication node.

[0090] In another embodiment, if the bandwidth of the target channel allocated to the currently traversed communication node is less than a preset bandwidth threshold, the channel allocation can also be reallocated by tracing back the bandwidth of the allocated channel. Specifically, the first communication node of the allocated channel can be traced back and its bandwidth can be reduced (for example, from 160 MHz to 80 MHz), and then the channel allocation can be reallocated to achieve bandwidth optimization of the overall network.

[0091] It should also be noted that the above two methods of reallocating channels can be selected according to actual needs, and the two methods of reallocating channels can be used in combination. For example, after the method of step 3053 fails to reallocate channels, the method of step 3054 can also be used to reallocate channels.

[0092] As described above, the embodiment of the present application provides a method for determining a network topology. After determining the network topology based on a spanning tree algorithm, the embodiment of the present application further allocates channels and bandwidths under the working frequency band to each communication node in the network, thereby reducing co-channel interference during communication between communication nodes, optimizing the utilization of network spectrum resources, and improving the communication quality of the network and the user experience.

[0093] The present application also provides a network topology determination device. Figure 7 As shown, Figure 7A schematic diagram of the structure of a network topology determination device provided in an embodiment of the present application, the network topology determination device includes:

[0094] The signal strength measurement module 401 is configured to measure the signal strength between each communication node in the network to be generated, wherein each signal strength corresponds to a connection link.

[0095] The weight value determination module 402 is configured to calculate the weight value of the corresponding connection link based on each signal strength.

[0096] The topology structure determination module 403 is configured to select an initial node from each communication node, perform connection screening based on the set constraints in turn to obtain a filtered connection set, and add edge connections according to the filtered connection set, the spanning tree algorithm, and the weight value of each connection link in the filtered connection set to obtain the network topology structure of the network to be generated.

[0097] The weight value determination module 402 includes:

[0098] The throughput determination submodule is configured to calculate a theoretical maximum throughput of a corresponding connection link based on each signal strength.

[0099] The hop load determination submodule is configured to determine the sum of the parent node hops corresponding to each connection link and the historical load of the corresponding communication node.

[0100] The weight value calculation submodule is configured to calculate the weight value of the corresponding connection link according to the sum of the theoretical maximum throughput, the number of parent node hops and the historical load corresponding to each connection link.

[0101] Among them, the weight value calculation submodule includes:

[0102] The coefficient determination unit is configured to respectively determine a first weight coefficient, a second weight coefficient, and a third weight coefficient corresponding to the theoretical maximum throughput, the number of parent node hops, and the sum of the historical load.

[0103] The weight value calculation unit is configured to perform weighted summation on the theoretical maximum throughput, the number of parent node hops, and the sum of the historical load corresponding to each connection link according to the first weight coefficient, the second weight coefficient, and the third weight coefficient to obtain the weight value corresponding to each connection link.

[0104] The topology structure determination module 403 includes:

[0105] The set updating submodule is configured to add the root node among the communication nodes as the initial node to the selected node set, and to add other communication nodes to the unselected node set.

[0106] The queue initialization submodule is configured to initialize a priority queue, and the priority queue is configured to store connection links connecting communication nodes in the selected node set and communication nodes in the unselected node set.

[0107] The edge determination submodule is configured to iterate the selected node set based on the spanning tree algorithm. In each iteration, the connection is filtered in the priority queue based on the set constraints to obtain a filtered connection set, and the edge connection is added according to the target connection link with the largest weight value in the filtered connection set.

[0108] The iteration submodule is configured to update the selected node set, the unselected node set and the priority queue based on the target connection link, and then re-iterate the selected node set until the iteration end condition is reached to obtain the network topology structure of the network to be generated.

[0109] Among them, the iterator module includes:

[0110] The set updating unit is configured to add the communication nodes in the unselected node set that are connected to the target connection link to the selected node set, and update the selected node set and the unselected node set.

[0111] The queue updating unit is configured to update the priority queue according to the updated selected node set and the updated unselected node set.

[0112] The topology determination unit is configured to re-iterate the selected node set until the unselected node set is an empty set, thereby obtaining a network topology structure of the network to be generated.

[0113] The communication node is a dual-band communication node, and the constraint condition includes at least one of a frequency band constraint condition, a hop count constraint condition, a sub-node quantity constraint condition, a signal strength constraint condition, and a fault state constraint condition.

[0114] The frequency band constraint condition is configured so that the working frequency band of the constrained connection link is different from the working frequency band of the uplink connection link.

[0115] The signal strength constraint condition is configured to constrain the minimum signal strength of the connection link.

[0116] The hop count constraint condition is configured to constrain the maximum hop count between the communication node of the connection link and the root node.

[0117] The sub-node quantity constraint condition is configured to constrain the maximum number of sub-nodes of the communication node connecting the link.

[0118] The fault state constraint condition is configured to constrain the faulty communication node in the connection link to be a leaf node in the spanning tree.

[0119] It also includes an information determination module, which is configured to determine the number of hops, historical load and available channels in the working frequency band of each communication node in the network topology structure after obtaining the network topology structure of the network to be generated.

[0120] The channel bandwidth allocation module is configured to allocate corresponding channels and bandwidths to each communication node in the available channels of each communication node according to the hop count and historical load of each communication node.

[0121] The channel bandwidth allocation module includes:

[0122] The hop count level determination submodule is configured to determine the hop count level corresponding to each communication node according to the hop count of each communication node. The smaller the hop count level, the closer the communication node is to the root node in the network.

[0123] The channel bandwidth allocation submodule is configured to allocate channels to communication nodes in each hop number level in order from small to large, and in the process of allocating channels, preferentially allocate channels with larger bandwidth to communication nodes with larger historical loads.

[0124] The channel bandwidth allocation submodule includes:

[0125] The first channel allocation unit is configured to allocate any one channel among the available channels of the root node to the root node.

[0126] The node traversal unit is configured to traverse each hop level in order from small to large for other communication nodes except the root node, and in the process of traversing each hop level, traverse each communication node in the hop level in order from large to small according to the historical load.

[0127] The second channel allocation unit is configured to, in the process of traversing each communication node, for the currently traversed communication node, eliminate the conflicting channels that have channel interference with other communication nodes in the corresponding available channels based on a preset channel strength threshold, and use the target channel with the largest bandwidth in the retained available channels as the channel used by the currently traversed communication node.

[0128] It also includes: a first channel reallocation module, which is configured to use the target channel with the largest bandwidth in the reserved available channels as the channel used by the currently traversed communication node, and then, when the bandwidth of the target channel is less than a preset bandwidth threshold, increase the channel strength threshold corresponding to the currently traversed communication node to re-determine the conflicting channel and eliminate it, and use the target channel with the largest bandwidth in the re-reserved available channels as the channel used by the currently traversed communication node.

[0129] It also includes: a second channel reallocation module, which is configured to use the target channel with the largest bandwidth in the reserved available channels as the channel used by the currently traversed communication node, and then, when the bandwidth of the target signal is less than a preset bandwidth threshold, trace back to the first communication node to which the channel has been allocated, reduce the bandwidth of the first communication node, and reallocate the channel to the currently traversed communication node.

[0130] The network topology determination apparatus provided in the embodiments of the present application is included in a network topology determination device, and can be configured to execute the network topology determination method provided in the above embodiments, and has corresponding functions and beneficial effects.

[0131] It is worth noting that in the embodiment of the above-mentioned network topology determination device, the various units and modules included are only divided according to functional logic, but are not limited to the above-mentioned division, as long as the corresponding functions can be achieved; in addition, the specific names of the functional units are only for the convenience of distinguishing each other, and are not configured to limit the scope of protection of this application.

[0132] Figure 8 A schematic diagram of a network topology determination device provided in an embodiment of the present application is shown in FIG. Figure 8 As shown, the network topology determination device further includes a processor 501, a memory 502, an input device 503, and an output device 504; the number of processors 501 in the device may be one or more. Figure 8 A processor 501 is taken as an example; the processor 501, the memory 502, the input device 503 and the output device 504 in the device can be connected by a bus or other means. Figure 8 The example of connection via bus is taken. The memory 502, as a computer-readable storage medium, can be used to store software programs, computer executable programs and modules, such as program instructions / modules corresponding to the network topology determination method in the embodiment of the present application. The processor 501 executes various functional applications and data processing of the device by running the software programs, instructions and modules stored in the memory 502, that is, implements the above-mentioned network topology determination method. The input device 503 can be used to receive input digital or character information, and generate signal input related to user settings and function control of the device. The output device 504 may include a display device such as a display screen.

[0133] The embodiment of the present application further provides a storage medium including computer executable instructions. When the computer executable instructions are executed by a computer processor, they are used to perform the above-mentioned network topology determination method. The network topology determination method includes:

[0134] Measuring the signal strength between each communication node in the network to be generated, wherein each signal strength corresponds to a connection link;

[0135] Calculate the weight value of the corresponding connection link based on each signal strength;

[0136] An initial node is selected from each communication node, and connection screening is performed based on the set constraints in turn to obtain a filtered connection set, and edge connections are added according to the filtered connection set, a spanning tree algorithm, and the weight value of each connection link in the filtered connection set to obtain the network topology structure of the network to be generated.

[0137] In some possible implementations, various aspects of the method provided in this application may also be implemented in the form of a program product, which includes a program code. When the program product is run on a computer device, the program code is configured to enable the computer device to execute the steps in the method according to various exemplary embodiments of the present application described above in this specification. For example, the computer device may execute the network topology determination method recorded in the embodiment of this application. The program product may be implemented in any combination of one or more readable media.

[0138] Note that the above are only preferred embodiments of the present application and the technical principles used. Those skilled in the art will understand that the present application is not limited to the specific embodiments herein, and that various obvious changes, readjustments and substitutions can be made to those skilled in the art without departing from the protection scope of the present application. Therefore, although the present application is described in more detail through the above embodiments, the present application is not limited to the above embodiments, and may include more other equivalent embodiments without departing from the concept of the present application, and the scope of the present application is determined by the scope of the appended claims.

Claims

1. A method for determining network topology, characterized in that: The method comprises: Measuring the signal strength between each communication node in the network to be generated, wherein each signal strength corresponds to a connection link; Calculate a weight value of a corresponding connection link based on each of the signal strengths; An initial node is selected from each of the communication nodes, and connection screening is performed in turn based on the set constraints to obtain a filtered connection set, and edge connections are added according to the filtered connection set, a spanning tree algorithm, and a weight value of each connection link in the filtered connection set to obtain a network topology structure of the network to be generated.

2. The network topology determination method according to claim 1, characterized in that: The calculating the weight value of the corresponding connection link based on each signal strength includes: Calculate the theoretical maximum throughput of the corresponding connection link based on each of the signal strengths; Determine the sum of the parent node hop count and the corresponding communication node historical load corresponding to each of the connection links; The weight value of the corresponding connection link is calculated according to the sum of the theoretical maximum throughput, the number of parent node hops and the historical load corresponding to each connection link.

3. The network topology determination method according to claim 2, characterized in that: The weight value of the corresponding connection link is calculated according to the sum of the theoretical maximum throughput, the number of parent node hops and the historical load corresponding to each connection link, including: respectively determining a first weight coefficient, a second weight coefficient, and a third weight coefficient corresponding to the theoretical maximum throughput, the number of parent node hops, and the sum of the historical load; According to the first weight coefficient, the second weight coefficient and the third weight coefficient, a weighted sum is performed on the theoretical maximum throughput, the number of parent node hops and the sum of the historical load corresponding to each connection link to obtain a weight value corresponding to each connection link.

4. The network topology determination method according to claim 1, characterized in that: The step of selecting an initial node from each of the communication nodes, performing connection screening based on set constraints in turn to obtain a screened connection set, and adding edge connections according to the screened connection set, a spanning tree algorithm, and a weight value of each connection link in the screened connection set to obtain a network topology structure of the network to be generated includes: Adding the root node among the communication nodes as the initial node to the selected node set, and adding other communication nodes to the unselected node set; Initializing a priority queue, the priority queue being configured to store connection links connecting communication nodes in the selected node set and communication nodes in the unselected node set; Iterating the selected node set based on a spanning tree algorithm, in each iteration, performing connection screening in the priority queue based on set constraints to obtain a screened connection set, and adding edge connections according to a target connection link with the largest weight value in the screened connection set; After the selected node set, the unselected node set and the priority queue are updated based on the target connection link, the selected node set is iterated again until an iteration end condition is reached to obtain a network topology structure of the network to be generated.

5. The network topology determination method according to claim 4, characterized in that: After the selected node set, the unselected node set, and the priority queue are updated based on the target connection link, the selected node set is iterated again until an iteration end condition is reached to obtain a network topology structure of the network to be generated, including: Adding the communication nodes in the unselected node set connected to the target connection link to the selected node set, and updating the selected node set and the unselected node set; Updating the priority queue according to the updated set of selected nodes and the updated set of unselected nodes; The selected node set is iterated again until the unselected node set is an empty set, thereby obtaining the network topology structure of the network to be generated.

6. The network topology determination method according to claim 4, characterized in that: The communication node is a dual-frequency communication node, and the constraint condition includes at least one of a frequency band constraint condition, a hop count constraint condition, a sub-node quantity constraint condition, a signal strength constraint condition, and a fault state constraint condition; The frequency band constraint condition is configured to constrain the working frequency band of the connection link to be different from the working frequency band of the uplink connection link; The signal strength constraint condition is configured to constrain the minimum signal strength of the connection link; The hop count constraint condition is configured to constrain the maximum hop count between the communication node and the root node of the connection link; The sub-node quantity constraint condition is configured to constrain the maximum number of sub-nodes of the communication node of the connection link; The fault state constraint condition is configured to constrain a faulty communication node in the connection link to be a leaf node in the spanning tree.

7. The network topology determination method according to any one of claims 1 to 6, characterized in that: After obtaining the network topology structure of the network to be generated, the method further includes: Determine the number of hops, historical load, and available channels in the working frequency band of each of the communication nodes in the network topology; According to the hop count and historical load of each communication node, a corresponding channel and bandwidth are allocated to each communication node in the available channels of each communication node.

8. The network topology determination method according to claim 7, characterized in that: The allocating a corresponding channel and bandwidth to each communication node in an available channel of each communication node according to the number of hops and the historical load of each communication node, comprises: Determining a hop count level corresponding to each communication node according to the hop count of each communication node, wherein the smaller the hop count level is, the closer the communication node is to a root node in the network; According to the hop count levels from small to large, channels are allocated in sequence to the communication nodes in each hop count level, and in the process of allocating the channels, channels with larger bandwidths are preferentially allocated to the communication nodes with larger historical loads.

9. The network topology determination method according to claim 8, characterized in that: The allocating channels to the communication nodes in each hop number level in order from small to large according to the hop number level, and in the process of allocating the channels, preferentially allocating channels with larger bandwidth to the communication nodes with larger historical loads, includes: Allocate any one channel among the available channels of the root node to the root node; For other communication nodes other than the root node, traverse each of the hop count levels in order from small to large according to the hop count level, and in the process of traversing each of the hop count levels, traverse each communication node in the hop count level in order from large to small according to the historical load; In the process of traversing each of the communication nodes, for the currently traversed communication node, the conflicting channels that have channel interference with other communication nodes in the corresponding available channels are eliminated based on the preset channel strength threshold, and the target channel with the largest bandwidth in the retained available channels is used as the channel used by the currently traversed communication node.

10. The network topology determination method according to claim 9, characterized in that: After the target channel with the largest bandwidth among the reserved available channels is used as the channel used by the currently traversed communication node, the method further includes: When the bandwidth of the target channel is less than the preset bandwidth threshold, the channel strength threshold corresponding to the currently traversed communication node is increased to redetermine the conflicting channel and eliminate it, and the target channel with the largest bandwidth among the re-reserved available channels is used as the channel used by the currently traversed communication node.

11. The network topology determination method according to claim 9, characterized in that: After the target channel with the largest bandwidth among the reserved available channels is used as the channel used by the currently traversed communication node, the method further includes: When the bandwidth of the target signal is less than a preset bandwidth threshold, the first communication node to which the channel has been allocated is traced back, the bandwidth of the first communication node is reduced, and a channel is re-allocated to the currently traversed communication node.

12. A network topology determination device, characterized in that: The network topology determining device comprises: A signal strength measurement module, configured to measure the signal strength between each communication node in the network to be generated, wherein each signal strength corresponds to a connection link; A weight value determination module, configured to calculate a weight value of a corresponding connection link based on each of the signal strengths; A topology structure determination module is configured to select an initial node from each of the communication nodes, perform connection screening based on set constraints in turn to obtain a screened connection set, and add edge connections based on the screened connection set, a spanning tree algorithm, and a weight value of each connection link in the screened connection set to obtain a network topology structure of the network to be generated.

13. A network topology determination device, characterized in that: The network topology determination device includes a processor and a memory; The memory is configured to store a computer program and transmit the computer program to the processor; The processor is configured to execute the network topology determination method according to any one of claims 1 to 11 according to the instructions in the computer program.

14. A storage medium storing computer executable instructions, characterized in that: When the computer executable instructions are executed by a computer processor, the computer executable instructions are configured to perform the network topology determination method according to any one of claims 1 to 11.

15. A computer program product comprising a computer program, characterized in that When the computer program is executed by a processor, the network topology determination method according to any one of claims 1 to 11 is implemented.

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