A method, device, equipment and storage medium for optimizing topological network structure

Abstract

The embodiment of the present invention discloses a method, device, equipment and storage medium for optimizing a topological network structure, wherein the method includes: obtaining a topological network structure to be optimized, and extracting a community structure in the topological network structure to be optimized; adjusting each of the community structures based on the preset connection parameters of each node in each of the community structures, and determining each updated community structure that meets the preset structural optimization standard; using each of the updated community structures as a community node, adjusting the connection relationship between each of the community nodes based on the preset connection parameters of each of the community nodes, and determining the optimized target topological network structure. The technical solution of the embodiment of the present invention solves the problem that when the prior art optimizes the topological network, the structure of the topological network before and after optimization is prone to major changes, and can reduce the difference in the topological network structure before and after optimization, and further improve the stability of the topological network.

Description

Technical Field

[0001] The embodiments of the present invention relate to the technical field related to structure optimization, and in particular, to a method, device, equipment and storage medium for optimizing a topological network structure. Background Art

[0002] Robustness is a parameter that describes the anti-interference ability of a topological network. The improvement of robustness is usually used as a reference standard for topological network structure optimization. In the process of topological network structure optimization, after randomly exchanging the connection relationship between connection points, if the robustness index of the entire topological network is improved, the random connection point exchange is maintained to obtain the optimized topological network structure. However, since only the robustness of the topological network is considered, the local structure of the topological network before and after optimization may change significantly, which may easily paralyze the topological network. Summary of the invention

[0003] The embodiments of the present invention provide a method, apparatus, device and storage medium for optimizing a topological network structure, which can reduce the difference in the topological network structure before and after optimization and further improve the stability of the topological network.

[0004] In a first aspect, an embodiment of the present invention provides a method for optimizing a topological network structure, the method comprising:

[0005] Acquire a topological network structure to be optimized, and extract a community structure in the topological network structure to be optimized;

[0006] Based on the preset connection parameters of each node in each community structure, each community structure is adjusted respectively, and each updated community structure that meets the preset structure optimization standard is determined;

[0007] Taking each of the updated community structures as a community node, adjusting the connection relationship between each of the community nodes based on the preset connection parameters of each of the community nodes, and determining an optimized target topology network structure.

[0008] In a second aspect, an embodiment of the present invention provides a topology network structure optimization device, the device comprising:

[0009] A community analysis module, used to obtain a topological network structure to be optimized, and extract a community structure in the topological network structure to be optimized;

[0010] A community structure adjustment module, for adjusting each of the community structures based on preset connection parameters of each node in each of the community structures, and determining each updated community structure that meets a preset structural optimization standard;

[0011] The inter-community structure adjustment module is used to use each of the updated community structures as a community node, adjust the connection relationship between each of the community nodes based on the preset connection parameters of each of the community nodes, and determine the optimized target topology network structure.

[0012] In a third aspect, an embodiment of the present invention provides a computer device, the computer device comprising:

[0013] one or more processors;

[0014] A memory for storing one or more programs;

[0015] When the one or more programs are executed by the one or more processors, the one or more processors implement the topology network structure optimization method described in any embodiment.

[0016] In a fourth aspect, an embodiment of the present invention provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the topology network structure optimization method described in any embodiment.

[0017] The technical solution provided by the embodiment of the present invention obtains the topological network structure to be optimized and extracts the community structure in the topological network structure to be optimized; based on the preset connection parameters of each node in each community structure, each community structure is adjusted respectively, and each updated community structure that meets the preset structural optimization standard is determined; with each updated community structure as the community node, the connection relationship between each community node is adjusted respectively based on the preset connection parameters of each community node, and the optimized target topological network structure is determined. The technical solution of the embodiment of the present invention solves the problem that when the prior art optimizes the topological network, the structure of the topological network before and after optimization is prone to major changes, which can reduce the difference in the topological network structure before and after optimization and further improve the stability of the topological network. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 It is a flow chart of a topology network structure optimization method provided by an embodiment of the present invention;

[0019] Figure 2 It is a flow chart of a method for optimizing a topological network structure within a community provided by an embodiment of the present invention;

[0020] Figure 3 It is a flow chart of a method for optimizing a topological network structure among communities provided by an embodiment of the present invention;

[0021] Figure 4 It is a structural schematic diagram of a topology network structure optimization device provided by an embodiment of the present invention;

[0022] Figure 5 It is a structural schematic diagram of a computer device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0023] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0024] Figure 1 It is a flow chart of a topology network structure optimization method provided by an embodiment of the present invention. The embodiment of the present invention can be applied to the scenario of optimizing the structure of a topology network. The method can be executed by a topology network structure optimization device, and the device can be implemented by software and / or hardware.

[0025] like Figure 1 As shown, the topology network structure optimization method includes the following steps:

[0026] S110: Acquire a topological network structure to be optimized, and extract a community structure in the topological network structure to be optimized.

[0027] The topological network structure to be optimized may be a topological network structure to be optimized, and the topological network structure is composed of multiple nodes connected according to a certain connection relationship. The community structure may be a local topological network structure in the topological network structure to be optimized, and each node in a community structure is usually a node with a certain similarity and determined by clustering. Specifically, the topological network to be optimized may be divided into multiple communities by a preset partitioning algorithm, thereby extracting the community structure of the topological network structure to be optimized. Each community structure contains at least one node.

[0028] S120: Based on the preset connection parameters of each node in each community structure, adjust each community structure respectively, and determine each updated community structure that meets the preset structure optimization standard.

[0029] The preset connection parameter may be a preset parameter representing the node connection relationship within the community structure, for example, the node degree may be used as the preset connection parameter. The preset structural optimization standard is a preset reference standard for judging whether the structural performance of the updated community structure is optimized, for example, the clustering coefficient and the robustness reference value may be used as the judging criteria of the preset structural optimization standard.

[0030] Specifically, for each community structure, the node degree of each node in the community structure can be calculated separately, and the node pairs for adjusting the inter-node connection relationship can be determined based on the difference between the node degree values. The inter-node connection relationship adjustment strategy can be determined for each node pair, and the community structure can be adjusted according to each inter-node connection relationship adjustment strategy. Subsequently, based on the preset structural optimization standard, an optimal updated structure can be determined from multiple adjusted community structures, thereby obtaining each updated community structure.

[0031] S130, taking each of the updated community structures as a community node, adjusting the connection relationship between each of the community nodes based on the preset connection parameters of each of the community nodes, and determining an optimized target topology network structure.

[0032] Among them, the target topological network structure represents the topological network structure that has been optimized. Each updated community structure can be used as a community node, and the connection relationship between each community node can be adjusted based on the preset connection parameters of each community node with reference to the above steps, and the optimized target topological network structure can be determined. For example, the community node degree of each community node in the topological network structure to be optimized can be calculated respectively, and the community node pairs for adjusting the connection relationship between community nodes can be determined based on the difference between the degree values ​​of each community node, and the connection relationship adjustment strategy between community nodes can be determined for each target community node pair, and then the structure between community structures can be adjusted according to each connection relationship adjustment strategy between community nodes. Subsequently, the optimal optimized topological network structure is selected from multiple adjusted community structures as the target topological network structure through the preset structural optimization standard.

[0033] The technical solution provided by the embodiment of the present invention obtains the topological network structure to be optimized and extracts the community structure in the topological network structure to be optimized; based on the preset connection parameters of each node in each community structure, each community structure is adjusted respectively, and each updated community structure that meets the preset structural optimization standard is determined; with each updated community structure as the community node, the connection relationship between each community node is adjusted respectively based on the preset connection parameters of each community node, and the optimized target topological network structure is determined. The technical solution of the embodiment of the present invention solves the problem that when the prior art performs topological network optimization, the structure of the topological network before and after optimization is prone to major changes, which can reduce the difference in the topological network structure before and after optimization, and further improve the stability of the topological network.

[0034] Figure 2It is a flow chart of a method for optimizing the topological network structure within a community provided by an embodiment of the present invention. The embodiment of the present invention can be applied to the scenario of optimizing the structure of the topological network within the community. Based on the above embodiment, this embodiment further illustrates how to adjust each community structure based on the preset connection parameters of each node in each community structure. The device can be implemented by software and / or hardware and integrated in a computer device with application development function.

[0035] like Figure 2 As shown, the topology network structure optimization method includes the following steps:

[0036] S210 , for each community structure, respectively calculating the node degree of each node in the community structure, and comparing the node degree values ​​of any two nodes in the community structure.

[0037] The community structure may be a local topological network structure in the overall topological network structure. Specifically, the overall topological network structure may be divided into multiple community structures according to a preset division rule. The node degree of a node may be the number of other nodes that are connected to the node. For each community structure, after calculating the node degree of each node in the community structure, the node degree values ​​of any two nodes in the community structure may be compared.

[0038] S220: When the difference between the node degree values ​​of any two nodes is less than a first preset difference upper limit threshold, the two nodes are used as a target node pair for adjusting the connection relationship between the nodes.

[0039] Among them, the first preset difference upper limit threshold can be a preset reference standard maximum value of the node degree difference. If the difference between the node degree values ​​of two nodes is greater than or equal to the first preset difference upper limit threshold, it means that the difference between the node degree values ​​of the two nodes is too large and it is not suitable to connect and replace the nodes with each other; if the difference between the node degree values ​​of the two nodes is less than the first preset difference upper limit threshold, it means that the difference between the node degree values ​​of the two nodes is within a reasonable difference range and can connect and replace the nodes with each other. The target node pair can be a pair of nodes used to adjust the connection relationship between nodes in the community structure. When the difference between the node degree values ​​of any two nodes is less than the first preset difference upper limit threshold, the two nodes can be used as the target node pair for adjusting the connection relationship between nodes.

[0040] S230: Cancel the connection relationship between at least one node other than the target node pair in the community structure and the first node in the target node pair.

[0041] The first node may be a node in the target node pair, and specifically, the first node and the second node in the target node pair may be determined according to a preset division rule. When the first node and the second node are combined to form the target node pair, the connection relationship between one or more other nodes in the community structure except the target node pair and the first node in the target node pair may be cancelled.

[0042] S240: Establish a connection relationship between at least one node other than the target node pair and a second node in the target node pair to determine at least one inter-node connection relationship adjustment strategy.

[0043] Among them, a connection relationship is established between other nodes except the target node pair and the second node in the target node pair, that is, the connection relationship between the nodes other than the target node pair and one node in the target node pair is transferred to another node in the target node pair, thereby realizing the adjustment of the community structure. For example, if point A and point B are the target node pair, point A is the first node in the target node pair, and point B is the second node in the target node pair, then the connection relationship between other node C and point A can be cancelled, and the connection relationship between point C and point B can be established. Since the node degrees of point A and point B are similar, if the connection relationship between point C and point A is adjusted to the connection relationship between point C and point B, the change in the structure of the community network topology will also be small, which can guarantee the stability of the local community topology network to a certain extent.

[0044] S250, respectively calculating the clustering coefficient and robustness of each candidate community structure.

[0045] The candidate community can be a community adjusted by the connection relationship between nodes in the community, the clustering coefficient can be a coefficient used to describe the degree of node clustering within the community, and the robustness can be a parameter describing the anti-interference ability of the community. Specifically, the clustering coefficient of each candidate community structure can be calculated respectively, and according to the node degree value of the node in each candidate community, each node is attacked from high to low, and the robustness of each candidate community structure is calculated.

[0046] S260: Selecting an updated community structure that meets a preset structural optimization standard from among the candidate community structures according to the clustering coefficient and the robustness.

[0047] Among them, the preset structural optimization standard can be a preset reference standard for judging the clustering coefficient and robustness of the updated candidate community, and comprehensively analyzing the two indicators of clustering coefficient and robustness. For example, weight values ​​can be set for the clustering coefficient and robustness respectively, and a weighted calculation can be performed between the two, and the candidate community structure corresponding to the highest value in the calculation result is used as the updated community structure. Alternatively, the candidate community structures can be sorted according to the robustness value, and the candidate community structure with high robustness and the clustering coefficient of the community structure that meets the preset clustering coefficient judgment condition is selected as the final updated community structure. Among them, the preset clustering coefficient judgment condition can be that the reduction in the clustering coefficient does not exceed a preset percentage.

[0048] The technical solution provided by the embodiment of the present invention calculates the node degree of each node in the community structure for each community structure, and compares the node degree values ​​of any two nodes in the community structure; when the difference between the node degree values ​​of any two nodes is less than the first preset difference upper limit threshold, the two nodes are used as the target node pair for adjusting the connection relationship between nodes; the connection relationship between at least one node other than the target node pair in the community structure and the first node in the target node pair is cancelled; the connection relationship between at least one node other than the target node pair and the second node in the target node pair is established to determine at least one node connection relationship adjustment strategy; the clustering coefficient and robustness of each candidate community structure are calculated respectively; according to the clustering coefficient and the robustness, the updated community structure that meets the preset structural optimization standard is selected from each candidate community structure to complete the structural optimization of the internal topological network of the community. The technical solution provided by the embodiment of the present invention can reduce the difference between the community topological network structure before and after optimization, and improve the stability of the community topological network and the overall topological network structure.

[0049] Figure 3 It is a flow chart of an inter-community topological network structure optimization method provided by an embodiment of the present invention. The embodiment of the present invention can be applied to the scenario of optimizing the structure of the inter-community topological network. Based on the above embodiment, this embodiment further illustrates how to use each updated community structure as a community node and adjust the connection relationship between each community node based on the preset connection parameters of each community node. The device can be implemented by software and / or hardware and integrated in a computer device with application development function.

[0050] like Figure 3 As shown, the topology network structure optimization method includes the following steps:

[0051] S310, respectively calculating the community node degree of each community node in the topological network structure to be optimized, and comparing the community node degree values ​​of any two community structures.

[0052] Among them, the topological network structure to be optimized can be a topological network structure that needs to optimize the connection relationship between communities. Furthermore, the updated community structures selected in the previous embodiment can be used as community nodes, and the community node degree can be the number of other community nodes that have a connection relationship with the community node. After calculating the community node degree of each community node in the community structure, the community node degree values ​​of any two community nodes in the community structure can be compared.

[0053] S320: When the difference between the community node degree values ​​of any two community structures is less than a second preset difference upper limit threshold, the two community structures are used as target community node pairs for connection relationship adjustment.

[0054] Among them, the second preset difference upper limit threshold can be a preset reference standard maximum value of the community node degree difference. If the difference between the community node degree values ​​of two community nodes is greater than or equal to the second preset difference upper limit threshold, it means that the difference between the community node degree values ​​of the two community nodes is too large and it is not suitable to replace each other as community nodes; if the difference between the community node degree values ​​of the two community nodes is less than the first preset difference upper limit threshold, it means that the difference between the community node degree values ​​of the two community nodes is within a reasonable difference range and can replace each other as community nodes. The target community node pair can be a pair of community nodes used to adjust the structural connection relationship between communities. When the difference between the community node degree values ​​of any two community nodes is less than the first preset difference upper limit threshold, the two community nodes are used as the target community node pair for adjusting the connection relationship between community nodes.

[0055] S330: Cancel the connection relationship between at least one community node other than the target community node pair in the topology network structure to be optimized and the first community node in the target community node pair.

[0056] The first community node may be a community node in the target community node pair. Specifically, the first community node and the second community node in the target community node pair may be determined according to a preset division rule. When the first community node and the second community node are combined to form the target community node pair, the connection relationship between one or more other community nodes in the community structure except the target community node pair and the first community node in the target community node pair may be cancelled.

[0057] S340: Establish a connection relationship between the at least one community node other than the target community node pair and the second community node in the target community node pair to determine at least one connection relationship adjustment strategy between community nodes.

[0058] Among them, a connection relationship is established between other community nodes except the target community node pair and the second community node in the target community node pair, that is, the connection relationship between the community nodes other than the target community node pair and a community node in the target community node pair is transferred to another community node in the target community node pair, thereby realizing the adjustment of the community structure. For example, if point A and point B are the target community node pair, point A is the first community node in the target community node pair, and point B is the second community node in the target community node pair, then the connection relationship between other community node point C and point A can be cancelled, and the connection relationship between point C and point B can be established. Since the community node degrees of point A and point B are similar, if the connection relationship between point C and point A is adjusted to the connection relationship between point C and point B, the change in the structure of the overall topological network will also be small, which can guarantee the stability of the overall topological network to a certain extent.

[0059] S350, respectively calculating the clustering coefficient and robustness of each candidate optimized topology network structure.

[0060] The candidate optimized topological network structure may be a topological network structure that has been adjusted for the connection relationship between community nodes, the clustering coefficient may be a coefficient used to describe the degree of clustering of community nodes, and the robustness may be a parameter describing the anti-interference ability of the topological network structure. Specifically, the clustering coefficient of each candidate optimized topological network structure may be calculated respectively, and according to the community node degree value of each candidate community node, each community node is attacked in order from high to low, and the robustness of each candidate community structure is calculated.

[0061] S360: Based on the clustering coefficient and robustness of each of the candidate optimized topology network structures, determine the target topology network structure from among the candidate optimized topology network structures according to a preset selection strategy.

[0062] Among them, the clustering coefficient and robustness of the candidate optimized topology network structure can be used as the preset selection strategy, and the two indicators of clustering coefficient and robustness can be comprehensively analyzed. For example, weight values ​​can be set for the clustering coefficient and robustness respectively, and weighted calculations can be performed between the two, and the candidate optimized topology network structure corresponding to the highest value in the calculation result can be used as the updated target topology network structure. Alternatively, the candidate optimized topology network structures can be sorted according to the robustness value, and the candidate optimized topology network structure with high robustness and the clustering coefficient of the community structure that meets the preset clustering coefficient judgment condition can be selected as the final target topology network structure. Among them, the preset clustering coefficient judgment condition can be that the reduction in the clustering coefficient does not exceed a preset percentage.

[0063] The technical solution provided by the embodiment of the present invention calculates the community node degree of each community node in the topological network structure to be optimized respectively, and compares the community node degree values ​​of any two community structures; when the difference in the community node degree values ​​between any two community structures is less than a second preset difference upper limit threshold, the two community structures are used as target community node pairs for connection relationship adjustment; the connection relationship between at least one community node other than the target community node pair in the topological network structure to be optimized and the first community node in the target community node pair is canceled; the connection relationship between at least one community node other than the target community node pair and the second community node in the target community node pair is established to determine at least one connection relationship adjustment strategy between community nodes; the clustering coefficient and robustness of each candidate optimized topological network structure are calculated respectively; based on the clustering coefficient and robustness of each candidate optimized topological network structure, the target topological network structure is determined in each candidate optimized topological network structure according to a preset selection strategy to complete the optimization of the structure of the inter-community topological network. The technical solution provided by the embodiment of the present invention can reduce the difference in the topological network structure between communities before and after optimization, and improve the stability of the topological network between communities and the overall topological network structure.

[0064] Figure 4 It is a structural diagram of a topology network structure optimization device provided in an embodiment of the present invention. The embodiment of the present invention can be applied to the scenario of optimizing the structure of a topology network. The device can be implemented by software and / or hardware and integrated into a computer device with application development function.

[0065] like Figure 4 As shown, the topology network structure optimization device includes: a community analysis module 410 , a community structure adjustment module 420 and an inter-community structure adjustment module 430 .

[0066] Among them, the community analysis module 410 is used to obtain the topological network structure to be optimized and extract the community structure in the topological network structure to be optimized; the community structure adjustment module 420 is used to adjust each community structure based on the preset connection parameters of each node in each community structure, and determine each updated community structure that meets the preset structure optimization standard; the inter-community structure adjustment module 430 is used to use each updated community structure as a community node, adjust the connection relationship between each community node based on the preset connection parameters of each community node, and determine the optimized target topological network structure.

[0067] The technical solution provided by the embodiment of the present invention obtains the topological network structure to be optimized and extracts the community structure in the topological network structure to be optimized; based on the preset connection parameters of each node in each community structure, each community structure is adjusted respectively, and each updated community structure that meets the preset structural optimization standard is determined; with each updated community structure as the community node, the connection relationship between each community node is adjusted respectively based on the preset connection parameters of each community node, and the optimized target topological network structure is determined. The technical solution of the embodiment of the present invention solves the problem that when the prior art performs topological network optimization, the structure of the topological network before and after optimization is prone to major changes, which can reduce the difference in the topological network structure before and after optimization, and further improve the stability of the topological network.

[0068] In an optional implementation, the community structure adjustment module 420 is specifically used to: for each community structure, calculate the node degree of each node in the community structure; determine at least one target node pair for adjusting the node connection relationship based on the difference between the node degree values, and determine at least one node connection relationship adjustment strategy for each target node pair; adjust the community structure according to each node connection relationship adjustment strategy to obtain a candidate community structure.

[0069] In an optional implementation, the community structure adjustment module 420 is further used to: compare the node degree values ​​of any two nodes in the community structure; when the difference between the node degree values ​​of any two nodes is less than a first preset difference upper limit threshold, use the two nodes as target node pairs for adjusting the connection relationship between the nodes.

[0070] In an optional embodiment, the community structure adjustment module 420 is also used to: cancel the connection relationship between at least one node other than the target node pair in the community structure and the first node in the target node pair; establish a connection relationship between at least one node other than the target node pair and the second node in the target node pair to determine at least one node connection relationship adjustment strategy.

[0071] In an optional implementation, the community structure adjustment module 420 is further used to: respectively calculate the clustering coefficient and robustness of each candidate community structure; and select an updated community structure that meets a preset structural optimization standard from each candidate community structure according to the clustering coefficient and the robustness.

[0072] In an optional implementation, the inter-community structure adjustment module 430 is specifically used to: respectively calculate the community node degree of each community node in the topological network structure to be optimized; determine at least one target community node pair for adjusting the connection relationship between community nodes based on the difference between the community node degree values, and determine at least one inter-community node connection relationship adjustment strategy for each target community node pair; perform structural adjustments between community structures according to each inter-community node connection relationship adjustment strategy to obtain a candidate optimized topological network structure.

[0073] In an optional implementation, the community structure adjustment module 430 is further used to: compare the community node degree values ​​of any two community structures; when the difference between the community node degree values ​​of any two community structures is less than a second preset difference upper limit threshold, use the two community structures as target community node pairs for connection relationship adjustment.

[0074] In an optional embodiment, the inter-community structure adjustment module 430 is also used to: cancel the connection relationship between at least one community node other than the target community node pair in the topological network structure to be optimized and the first community node in the target community node pair; establish a connection relationship between at least one community node other than the target community node pair and the second community node in the target community node pair to determine at least one inter-community node connection relationship adjustment strategy.

[0075] In an optional implementation, the inter-community structure adjustment module 430 is also used to: respectively calculate the clustering coefficient and robustness of each candidate optimized topology network structure; based on the clustering coefficient and robustness of each candidate optimized topology network structure, determine the target topology network structure in each candidate optimized topology network structure according to a preset selection strategy.

[0076] The topology network structure optimization device provided in the embodiment of the present invention can execute the topology network structure optimization method provided in any embodiment of the present invention, and has the corresponding functional modules and beneficial effects of the execution method.

[0077] Figure 5 A schematic diagram of the structure of a computer device provided in an embodiment of the present invention. Figure 5 A block diagram of an exemplary computer device 12 suitable for use in implementing embodiments of the present invention is shown. Figure 5 The computer device 12 shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present invention. The computer device 12 can be any terminal device with computing capability and can be configured in the topology network structure optimization device.

[0078] like Figure 5As shown, the computer device 12 is in the form of a general-purpose computing device. The components of the computer device 12 may include, but are not limited to: one or more processors or processing units 16, a system memory 28, and a bus 18 that connects various system components (including the system memory 28 and the processing unit 16).

[0079] The bus 18 may be one or more of several types of bus structures, including a memory bus or memory controller, a peripheral bus, an accelerated graphics port, a processor or a local bus using any of a variety of bus architectures. For example, these architectures include, but are not limited to, an Industry Standard Architecture (ISA) bus, a Micro Channel Architecture (MAC) bus, an Enhanced ISA bus, a Video Electronics Standards Association (VESA) local bus, and a Peripheral Component Interconnect (PCI) bus.

[0080] The computer device 12 typically includes a variety of computer system readable media. These media can be any available media that can be accessed by the computer device 12, including volatile and non-volatile media, removable and non-removable media.

[0081] The system memory 28 may include computer system readable media in the form of volatile memory, such as random access memory (RAM) 30 and / or cache 32. The computer device 12 may further include other removable / non-removable, volatile / non-volatile computer system storage media. By way of example only, the storage system 34 may be used to read and write non-removable, non-volatile magnetic media ( Figure 5 not shown, usually called a "hard drive"). Although Figure 5 Not shown in the figure, a disk drive for reading and writing to a removable non-volatile disk (e.g., a "floppy disk"), and an optical disk drive for reading and writing to a removable non-volatile optical disk (e.g., a CD-ROM, a DVD-ROM, or other optical media) may be provided. In these cases, each drive may be connected to the bus 18 via one or more data medium interfaces. The system memory 28 may include at least one program product having a set (e.g., at least one) of program modules that are configured to perform the functions of the various embodiments of the present invention.

[0082] A program / utility 40 having a set (at least one) of program modules 42 may be stored, for example, in system memory 28, such program modules 42 including, but not limited to, an operating system, one or more application programs, other program modules, and program data, each of which or some combination may include an implementation of a network environment. Program modules 42 generally perform the functions and / or methods of the embodiments described herein.

[0083] The computer device 12 may also communicate with one or more external devices 14 (e.g., keyboards, pointing devices, displays 24, etc.), one or more devices that enable a user to interact with the computer device 12, and / or any device that enables the computer device 12 to communicate with one or more other computing devices (e.g., network cards, modems, etc.). Such communication may be performed via an input / output (I / O) interface 22. Furthermore, the computer device 12 may also communicate with one or more networks (e.g., a local area network (LAN), a wide area network (WAN), and / or a public network, such as the Internet) via a network adapter 20. As shown, the network adapter 20 communicates with the other modules of the computer device 12 via the bus 18. It should be understood that although Figure 5 Not shown, other hardware and / or software modules may be used in conjunction with computer device 12, including but not limited to microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems.

[0084] The processing unit 16 executes various functional applications and data processing by running the program stored in the system memory 28, for example, implementing the topology network structure optimization method provided in the embodiment of the present invention, the method comprising:

[0085] Acquire road information within a preset distance in the driving direction of the controlled vehicle, and identify road characteristic parameters of road sampling points in the road information;

[0086] Determine the road type of the road in the driving direction according to the road characteristic parameter, input the road type and the road characteristic parameter value into a preset vehicle control information analysis model to obtain a target control parameter;

[0087] The target control parameter is sent to the actuator of the controlled vehicle to complete the driving control of the controlled vehicle.

[0088] This embodiment provides a computer-readable storage medium, on which a computer program is stored. When the program is executed by a processor, the method for optimizing a topological network structure provided in any embodiment of the present invention is implemented, including:

[0089] Acquire road information within a preset distance in the driving direction of the controlled vehicle, and identify road characteristic parameters of road sampling points in the road information;

[0090] Determine the road type of the road in the driving direction according to the road characteristic parameters, input the road type and the road characteristic parameter values ​​into a preset vehicle control information analysis model to obtain the target control parameters;

[0091] The target control parameters are sent to the actuator of the controlled vehicle to complete the driving control of the controlled vehicle.

[0092] The computer storage medium of the embodiment of the present invention can adopt any combination of one or more computer-readable media. The computer-readable medium can be a computer-readable signal medium or a computer-readable storage medium. The computer-readable storage medium can be, for example, but not limited to: an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, or any combination of the above. More specific examples (non-exhaustive list) of computer-readable storage media include: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In this document, a computer-readable storage medium can be any tangible medium containing or storing a program, which can be used by an instruction execution system, device or device or used in combination with it.

[0093] Computer-readable signal media may include data signals propagated in baseband or as part of a carrier wave, which carry computer-readable program code. Such propagated data signals may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. Computer-readable signal media may also be any computer-readable medium other than a computer-readable storage medium, which may send, propagate, or transmit a program for use by or in conjunction with an instruction execution system, apparatus, or device.

[0094] The program code embodied on the computer readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.

[0095] Computer program code for performing the operations of the present invention may be written in one or more programming languages ​​or combinations thereof, including object-oriented programming languages ​​such as Java, Smalltalk, C++, and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, as a separate 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 a remote computer, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0096] It should be understood by those skilled in the art that the modules or steps of the present invention described above can be implemented by a general-purpose computing device, they can be concentrated on a single computing device, or distributed on a network composed of multiple computing devices, optionally, they can be implemented by a program code executable by a computer device, so that they can be stored in a storage device and executed by the computing device, or they can be made into individual integrated circuit modules, or multiple modules or steps therein can be made into a single integrated circuit module for implementation. Thus, the present invention is not limited to any specific combination of hardware and software.

[0097] Note that the above are only preferred embodiments of the present invention and the technical principles used. Those skilled in the art will understand that the present invention is not limited to the specific embodiments herein, and that various obvious changes, readjustments and substitutions can be made by those skilled in the art without departing from the scope of protection of the present invention. Therefore, although the present invention has been described in more detail through the above embodiments, the present invention is not limited to the above embodiments, and may include more other equivalent embodiments without departing from the concept of the present invention, and the scope of the present invention is determined by the scope of the appended claims.

Claims

1. A method for optimizing a topological network structure, characterized in that: include: Acquire a topological network structure to be optimized, and extract a community structure in the topological network structure to be optimized; Based on the preset connection parameters of each node in each community structure, each community structure is adjusted respectively, and each updated community structure that meets the preset structure optimization standard is determined; Taking each of the updated community structures as a community node, adjusting the connection relationship between each of the community nodes based on the preset connection parameters of each of the community nodes, and determining an optimized target topology network structure; The adjusting of each community structure based on the preset connection parameters of each node in each community structure includes: For each of the community structures, respectively calculating the node degree of each node in the community structure; Determine at least one target node pair for adjusting the inter-node connection relationship based on the difference between the node degree values, and determine at least one inter-node connection relationship adjustment strategy for each of the target node pairs; Adjusting the community structure according to each of the node connection relationship adjustment strategies to obtain a candidate community structure; The method of using each of the updated community structures as a community node and adjusting the connection relationship between each of the community nodes based on the preset connection parameters of each of the community nodes includes: Respectively calculating the community node degree of each community node in the topological network structure to be optimized; Determine at least one target community node pair for adjusting the connection relationship between community nodes based on the difference between the degree values ​​of each community node, and determine at least one community node connection relationship adjustment strategy for each of the target community node pairs; The community structures are adjusted according to each of the connection relationship adjustment strategies between the community nodes to obtain a candidate optimized topology network structure.

2. The method according to claim 1, characterized in that: The step of determining at least one target node pair for adjusting the connection relationship between nodes based on the difference between the degree values ​​of each node includes: Comparing the node degree values ​​of any two nodes in the community structure; When the difference between the node degree values ​​of any two nodes is less than a first preset difference upper limit threshold, the two nodes are used as a target node pair for adjusting the connection relationship between the nodes.

3. The method according to claim 1, characterized in that: The determining at least one inter-node connection relationship adjustment strategy for each target node pair includes: canceling a connection relationship between at least one node other than the target node pair in the community structure and the first node in the target node pair; A connection relationship between the at least one node other than the target node pair and the second node in the target node pair is established to determine at least one inter-node connection relationship adjustment strategy.

4. The method according to claim 1, characterized in that: The step of determining each updated community structure that meets a preset structural optimization standard includes: Calculate the clustering coefficient and robustness of each candidate community structure respectively; According to the clustering coefficient and the robustness, an updated community structure that meets a preset structural optimization standard is selected from each of the candidate community structures.

5. The method according to claim 1, characterized in that: The step of determining at least one target community node pair for adjusting the connection relationship between community nodes based on the difference between the degree values ​​of each community node includes: Compare the community node degree values ​​of any two community structures; When the difference between the community node degree values ​​of any two community structures is less than a second preset difference upper limit threshold, the two community structures are used as target community node pairs for connection relationship adjustment.

6. The method according to claim 1, characterized in that The step of determining at least one connection relationship adjustment strategy between community nodes for each target community node pair includes: canceling a connection relationship between at least one community node other than the target community node pair in the topology network structure to be optimized and the first community node in the target community node pair; A connection relationship between the at least one community node other than the target community node pair and the second community node in the target community node pair is established to determine at least one connection relationship adjustment strategy between community nodes.

7. The method according to claim 1, characterized in that The step of determining the optimized target topology network structure includes: Calculate the clustering coefficient and robustness of each candidate optimized topology network structure respectively; Based on the clustering coefficient and robustness of each of the candidate optimized topology network structures, the target topology network structure is determined in each of the candidate optimized topology network structures according to a preset selection strategy.

8. A topology network structure optimization device, characterized in that: include: A community analysis module, used to obtain a topological network structure to be optimized, and extract a community structure in the topological network structure to be optimized; A community structure adjustment module, for adjusting each of the community structures based on preset connection parameters of each node in each of the community structures, and determining each updated community structure that meets a preset structural optimization standard; An inter-community structure adjustment module, used to use each of the updated community structures as a community node, adjust the connection relationship between each of the community nodes based on the preset connection parameters of each of the community nodes, and determine the optimized target topology network structure; The community structure adjustment module is specifically used for: For each community structure, calculate the node degree of each node in the community structure; Determine at least one target node pair for adjusting the inter-node connection relationship based on the difference between the degree values ​​of each node, and determine at least one inter-node connection relationship adjustment strategy for each target node pair; The community structure is adjusted according to the connection relationship adjustment strategy between each node to obtain the candidate community structure; The inter-community structure adjustment module is specifically used for: Calculate the community node degree of each community node in the topological network structure to be optimized respectively; Determine at least one target community node pair for adjusting the connection relationship between community nodes based on the difference between the degree values ​​of each community node, and determine at least one connection relationship adjustment strategy between community nodes for each target community node pair; According to the connection relationship adjustment strategy between each community node, the community structure is adjusted to obtain the candidate optimized topology network structure.

9. A computer device, characterized in that: The computer device comprises: one or more processors; A memory for storing one or more programs; When the one or more programs are executed by the one or more processors, the one or more processors implement the topology network structure optimization method as described in any one of claims 1-7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the topology network structure optimization method as described in any one of claims 1 to 7 is implemented.

Images