Screening method for nodes of self-organizing network
Through the multi-dimensional information scoring and sorting method, the screening of self-organized network nodes is optimized, and the problem of insufficient network stability and adaptability in the existing technology is solved, and high-quality network construction and dynamic optimization are achieved.
Patent Information
- Application Number
- CN202411494896.3
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-10-24
- Publication Date
- 2025-02-11
AI Technical Summary
The existing self-organized network node screening method only relies on a single indicator and cannot fully consider the energy level, location information and connection status of the node, resulting in poor network stability and adaptability.
By collecting multi-dimensional information on the signal strength, energy level, location information and connection status of the node, combining node requirements, node scores are generated, and ranking them based on the scores, a node priority list is generated to optimize network construction and update.
It realizes accurate evaluation of node communication status, breaks the limitations of filtering nodes with a single indicator, improves the performance, adaptability and stability of the network, and ensures that the network can always be adjusted and optimized according to actual conditions.
Smart Images
Figure CN119421178A_ABST
Abstract
Description
Technical Field
[0001] The present application relates to the technical field of self-organizing networks, and in particular to a method for screening nodes of a self-organizing network. Background Art
[0002] A large number of wind farm power facilities exist in deep mountains, with no public network signals or weak signal coverage. On-site networking is limited by environmental factors (such as high voltage electricity, terrain, buildings), technology and other factors. It is impossible to achieve full coverage using the existing network. At the same time, the terrain, landforms and some nature reserves make networking very difficult and difficult to build. The lack of public wireless network coverage and the construction of wired networks are also difficult, forming a de facto network-free zone. Without the network, emerging technologies such as automation, intelligence, and informatization are difficult to implement, and inspections and operations can only be carried out manually, which is inefficient, costly and difficult.
[0003] Therefore, whether it is to facilitate the collection and uploading of other newly added or temporarily deployed sensor data on site, or to realize the collection of high-definition audio and video information by on-site mobile terminals or the interactive collaboration between personnel in different locations, or even to solve the communication needs during emergencies, especially the needs of visual centralized control and unmanned or less-manned duty, it is necessary to achieve safe, reliable and efficient wireless communication coverage and meet all communication requirements inside and outside the wind farm tower and throughout the entire construction and production cycle.
[0004] Building a wireless private network with self-organizing network characteristics is the mainstream choice for the construction of wireless communication networks in wind farms. However, traditional methods for selecting nodes in self-organizing networks are often based on a single indicator and have great limitations. For example, selecting nodes based only on signal strength may ignore important factors such as the node's energy level, location information, and connection status. This may result in some nodes with high signal strength failing quickly due to insufficient energy during network operation, affecting the stability of the network. Alternatively, nodes with unreasonable locations may cause the transmission path to be too long, increasing network latency. In addition, if the connection status is not considered, some isolated nodes may be selected, unable to cooperate well with other nodes, and reducing the overall performance of the network. At the same time, the node requirements in the traditional method are not fully considered, and the network cannot be dynamically adjusted according to actual needs, making the network less adaptable. When the node requirements or node status change, it is difficult for traditional networks to make adjustments quickly, and it is impossible to ensure that the network is always in the optimal state.
[0005] In summary, the prior art urgently needs a technical solution for screening nodes of a self-organizing network to achieve the construction of a high-quality self-organizing network and improve network performance, adaptability and stability. Summary of the invention
[0006] The purpose of the present application is to provide a method for screening nodes of a self-organizing network to solve the technical problems raised in the above background technology.
[0007] To achieve the above purpose, the present application discloses the following technical solution: a method for screening nodes of a self-organizing network, comprising:
[0008] S1: Collect node information and node requirements, and generate corresponding node scores; wherein the node information includes signal strength, energy level, location information and connection status, the node requirements are used to characterize the signal strength requirements, energy level requirements, location information requirements and connection status requirements corresponding to the node information, and the node score is used to evaluate the communication status of the node in the self-organizing network;
[0009] S2: Obtain and sort the node requirements and the node scores based on the node requirements to generate a corresponding node priority list; wherein the node priority list stores node priorities corresponding to different node requirements;
[0010] S3: Acquire transmission path information, and use a preset self-organizing network mechanism and a corresponding node priority list to construct a self-organizing network; wherein the transmission path information at least includes a transmission starting point position and a transmission end point position, and the self-organizing network mechanism is used to dynamically guide the construction of the self-organizing network;
[0011] S4: When there is updated node information and / or updated node demand, the self-organizing network obtained in the supervision step S3 repeats steps S2 to S3 to update the self-organizing network; wherein the updated node information is the node information that has changed, and the updated node demand is the node demand that has changed.
[0012] Preferably, the node information is specifically:
[0013] The signal strength is used in the process of screening nodes that meet the signal strength requirement, and the quality of the signal is positively correlated with the signal strength;
[0014] The energy level is used in the process of screening nodes that meet the energy level requirement, and the endurance of the node during communication is positively correlated with the energy level;
[0015] The location information is used to screen nodes located in a specific area or having a specific location relationship according to the transmission path information;
[0016] The connection status is used in the process of screening nodes that meet the connection status requirements based on the connection stability of the nodes.
[0017] Preferably, the node score generation process includes:
[0018] Calculate the degree of compliance between the signal strength and the signal strength requirement to obtain a corresponding signal strength score; calculate the degree of compliance between the energy level and the energy level requirement to obtain a corresponding energy level score; calculate the degree of compliance between the location information and the location information requirement to obtain a corresponding location information score; calculate the degree of compliance between the connection state and the connection state requirement to obtain a corresponding connection state score;
[0019] The node score is calculated using the signal strength score, the energy level score, the location information score, and the connection status score.
[0020] Preferably, the process of generating the node priority list includes:
[0021] Obtaining the node score;
[0022] The node priority list is obtained by sorting based on the node scores.
[0023] Preferably, the node requirements are parsed, and when a corresponding node requirement weight parameter set exists, an adaptive node priority list is generated;
[0024] The generation process of the node demand weight parameter set includes:
[0025] The node requirements are used to generate corresponding application scenario characteristics, business criticality distribution and network performance indicators; wherein the application scenario characteristics are used to characterize the emphasis of different application scenarios on node requirements, the business criticality distribution is used to characterize and analyze the criticality of each node requirement for a specific business, and the network performance target is used to characterize the overall performance target of the self-organizing network;
[0026] In combination with the application scenario characteristics, the business criticality distribution and the network performance index, the signal strength requirement, the energy level requirement, the location information requirement and the connection status requirement are quantified to generate corresponding signal strength requirement weight parameters, energy level requirement weight parameters, location information requirement weight parameters and connection status requirement weight parameters;
[0027] The signal strength requirement weight parameter, the energy level requirement weight parameter, the location information requirement weight parameter and the connection status requirement weight parameter are packaged and defined as the node requirement weight parameter set.
[0028] Preferably, the process of generating the adaptive node priority list includes:
[0029] Acquire the node demand weight parameter set; calculate the adaptive node score using the node demand weight parameter set and the corresponding signal strength score, the energy level score, the location information score and the connection status score; and sort based on the adaptive node score to obtain the adaptive node priority list.
[0030] Preferably, the preset process of the self-organizing network mechanism includes:
[0031] Acquire a communication protocol corresponding to the node, store the communication protocol in the self-organizing network mechanism, and then train the self-organizing network mechanism to perform the following steps:
[0032] A1: Obtain the node priority list or the adaptive node priority list;
[0033] A2: Obtain and parse the transmission path information to obtain the corresponding path to be constructed that requires node screening;
[0034] A3: Using the path to be constructed, and selecting corresponding nodes in the corresponding node priority list;
[0035] A4: Using the nodes obtained in step A3 and calling the corresponding communication protocol to build a self-organizing network and output the self-organizing network.
[0036] Preferably, the process of constructing the self-organizing network includes:
[0037] Collect real-time node information and real-time node requirements, generate real-time node scores, and generate corresponding real-time node priority lists or real-time adaptive node priority lists;
[0038] Acquire real-time transmission path information, utilize the self-organizing network mechanism, and in combination with the corresponding real-time node priority list or the real-time adaptive node priority list, execute steps A1 to A4 to obtain a real-time self-organizing network.
[0039] Preferably, the supervision process of the self-organizing network includes:
[0040] The node information and / or the node requirements are continuously monitored and collected, and when there is a change in the node information and / or a change in the node requirements, corresponding updated node information and / or updated node requirements are generated.
[0041] Preferably, the updating process of the self-organizing network includes:
[0042] Collect update node information and / or update node requirements, generate update node scores, and generate corresponding update node priority lists or update adaptive node priority lists;
[0043] Obtain the corresponding transmission path information, utilize the self-organizing network mechanism, and in combination with the corresponding updated node priority list or the updated adaptive node priority list, execute steps A1 to A4 to obtain an updated self-organizing network.
[0044] Beneficial effect: The node screening method of the self-organizing network of the present application achieves accurate evaluation of the node communication status by comprehensively collecting multi-dimensional information such as signal strength, energy level, location information and connection status of the node, and generating node scores in combination with the corresponding node requirements, thereby breaking the limitation of screening nodes by a single indicator and providing a basis for building a high-quality self-organizing network. In addition, a priority list is generated by sorting based on node requirements and scores, so that the nodes that best meet the requirements can be selected in priority during network construction, thereby improving the performance and adaptability of the network. In combination with the transmission path information and the preset self-organizing network mechanism and dynamic updates, it ensures that the network can always be adjusted and optimized according to the actual situation, thereby optimizing the screening of nodes in the self-organizing network. BRIEF DESCRIPTION OF THE DRAWINGS
[0045] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For those skilled in the art, other drawings can be obtained based on these drawings without paying any creative work.
[0046] Figure 1 A flowchart of a method for screening nodes in a self-organizing network provided in an embodiment of the present application. DETAILED DESCRIPTION
[0047] The technical solutions in the embodiments of the present application are described clearly and completely below. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present application.
[0048] In this article, the term "comprising" is intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also includes other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of more restrictions, the elements defined by the sentence "comprising..." do not exclude the presence of other identical elements in the process, method, article or device including the elements.
[0049] This embodiment discloses Figure 1A method for screening nodes of a self-organizing network is shown, comprising:
[0050] S1: Collect node information and node requirements, and generate corresponding node scores; wherein the node information includes signal strength, energy level, location information and connection status, the node requirements are used to characterize the signal strength requirements, energy level requirements, location information requirements and connection status requirements corresponding to the node information, and the node score is used to evaluate the communication status of the node in the self-organizing network;
[0051] S2: Obtain and sort based on node requirements and node scores to generate a corresponding node priority list; wherein the node priority list stores node priorities corresponding to different node requirements;
[0052] S3: Acquire transmission path information, use a preset self-organizing network mechanism, and combine with a corresponding node priority list to build a self-organizing network; wherein the transmission path information at least includes a transmission starting point position and a transmission end point position, and the self-organizing network mechanism is used to dynamically guide the construction of the self-organizing network;
[0053] S4: Supervise the self-organizing network obtained in step S3. When there is updated node information and / or updated node demand, repeat steps S2 to S3 to update the self-organizing network; wherein the updated node information is the node information that has changed, and the updated node demand is the node demand that has changed.
[0054] Based on the above, this embodiment achieves accurate evaluation of node communication status by comprehensively collecting multi-dimensional information such as signal strength, energy level, location information and connection status of nodes, and generating node scores in combination with corresponding node requirements, thereby breaking the limitation of screening nodes by a single indicator, and providing a basis for building high-quality self-organizing networks. In addition, a priority list is generated by sorting based on node requirements and scores, so that nodes that best meet the requirements can be selected in network construction, thereby improving network performance and adaptability. Combined with transmission path information, preset self-organizing network mechanisms and dynamic updates, it ensures that the network can always be adjusted and optimized according to actual conditions, thereby optimizing the screening of nodes in self-organizing networks.
[0055] Specifically, the node information is as follows:
[0056] Signal strength is used to screen nodes that meet signal strength requirements, and the quality of the signal is positively correlated with the signal strength;
[0057] The energy level is used to select nodes that meet the energy level requirements, and the endurance of the node during communication is positively correlated with the energy level;
[0058] Location information is used to filter nodes located in a specific area or with a specific location relationship based on transmission path information;
[0059] The connection status is used to filter nodes that meet the connection status requirements based on the connection stability of the nodes.
[0060] It should be noted that the signal strength of this embodiment can be evaluated by measuring the received signal strength indication, the energy level can be evaluated by monitoring the battery power or energy reserve of the node, the location information can be collected by the locator, and the connection status can be evaluated by counting indicators such as the node's connection time and number of reconnections.
[0061] Based on the above, this embodiment achieves a comprehensive description of node information by acquiring the signal strength, energy level and location information of the node, thereby providing a data basis for node screening.
[0062] Specifically, the node score generation process includes:
[0063] Calculate the degree of conformity between the signal strength and the signal strength requirement to obtain the corresponding signal strength score; calculate the degree of conformity between the energy level and the energy level requirement to obtain the corresponding energy level score; calculate the degree of conformity between the location information and the location information requirement to obtain the corresponding location information score; calculate the degree of conformity between the connection status and the connection status requirement to obtain the corresponding connection status score;
[0064] The node score is calculated using the signal strength score, energy level score, location information score, and connection status score.
[0065] It should be noted that the signal strength score, energy level score, location information score and connection status score of the present embodiment are calculated using existing scoring methods to calculate the node scores. For example, the variance formula can be used to calculate the corresponding variance for the signal strength score, energy level score and connection status score, thereby characterizing the corresponding degree of conformity, wherein the smaller the variance, the higher the corresponding degree of conformity, i.e., the larger the corresponding score. The Euclidean distance can be used to calculate the location information score, and the corresponding location information score can be set based on the experience known to those skilled in the art, wherein the smaller the Euclidean distance, the larger the location information score.
[0066] Based on the above, this embodiment calculates the node score by integrating the signal strength score, energy level score, location information score and connection status score, thereby achieving accurate quantification of various factors and providing a data basis for building a self-organizing network.
[0067] Specifically, the process of generating the node priority list includes:
[0068] Get node score;
[0069] Sort by node scores to get a node priority list.
[0070] It should be noted that this embodiment realizes basic sorting of nodes by generating a node priority list, thereby providing basic data support for the construction of a self-organizing network.
[0071] In a simple example, in terms of signal strength, nodes that are closer to the signal strength requirements and have higher signal strength scores are given higher priority; in terms of energy level, nodes that meet the energy level requirements to a high degree and have a large energy level score have a higher priority; in terms of location information, nodes that better meet the requirements of a specific area or location relationship and have a high location information score have a higher priority; in terms of connection status, nodes with good connection stability, that meet the connection status requirements and have a high connection status score are ranked at the top. By comprehensively considering the sorting results of the above aspects, a node priority list is generated, which stores the node priorities corresponding to different node requirements, providing an important basis for building a self-organizing network, so that when building a network, nodes that meet the requirements to a high degree and have excellent performance can be given priority, thereby improving the performance and stability of the self-organizing network.
[0072] Specifically, the node requirements are parsed, and when there is a corresponding node requirement weight parameter set, an adaptive node priority list is generated;
[0073] The generation process of the node demand weight parameter set includes:
[0074] Node requirements are used to generate corresponding application scenario characteristics, business criticality distribution, and network performance indicators; among them, application scenario characteristics are used to characterize the emphasis of different application scenarios on node requirements, business criticality distribution is used to characterize and analyze the criticality of each node requirement for a specific business, and network performance targets are used to characterize the overall performance target of the self-organizing network;
[0075] Combined with application scenario characteristics, business criticality distribution and network performance indicators, quantify signal strength requirements, energy level requirements, location information requirements and connection status requirements, and generate corresponding signal strength requirement weight parameters, energy level requirement weight parameters, location information requirement weight parameters and connection status requirement weight parameters;
[0076] The signal strength requirement weight parameter, energy level requirement weight parameter, location information requirement weight parameter and connection status requirement weight parameter are packaged and defined as a node requirement weight parameter set.
[0077] It should be noted that this embodiment is based on the analysis of application scenario characteristics, business criticality distribution and network performance indicators, and utilizes existing weight parameter formulation methods, such as the hierarchical analysis method to achieve dynamic updating of the node demand weight parameter set. It constructs the evaluation factors of node demand into a hierarchical model, determines the relative importance of each factor through pairwise comparison, and then calculates the weight value of each factor to improve the scientific nature of weight allocation.
[0078] Based on the above, this embodiment provides optimized data support for the self-organizing network by generating a node demand weight parameter set for the generation of an adaptive node priority list, and realizes the dynamic update of the node demand weight parameter set, so that the self-organizing network can better adapt to different application scenarios, business requirements and network performance changes, thereby improving the flexibility and adaptability of the network.
[0079] Specifically, the process of generating the adaptive node priority list includes:
[0080] Obtain a node demand weight parameter set; calculate an adaptive node score using the node demand weight parameter set and corresponding signal strength scores, energy level scores, location information scores, and connection status scores; and sort based on the adaptive node scores to obtain an adaptive node priority list.
[0081] It should be noted that the adaptive node scoring of this embodiment corresponds to the node scoring in the previous text. It uses the node demand weight parameter set to achieve optimization based on the calculation of the node scoring in the previous text. Its calculation principle is the same as that of the node scoring in the previous text. This text will not go into details here. It is only necessary to increase the node demand weight parameters accordingly during the calculation.
[0082] Specifically, the preset process of the self-organizing network mechanism includes:
[0083] Obtain the communication protocol corresponding to the node, store the communication protocol in the self-organizing network mechanism, and then train the self-organizing network mechanism to perform the following steps:
[0084] A1: Get the node priority list or adaptive node priority list;
[0085] A2: Obtain and parse the transmission path information to obtain the corresponding path to be constructed that requires node screening;
[0086] A3: Use the path to be constructed and select the corresponding node in the corresponding node priority list;
[0087] A4: Using the nodes obtained in step A3 and calling the corresponding communication protocol to build a self-organizing network and output the self-organizing network.
[0088] It should be noted that the communication protocol of this embodiment may be a ZigBee protocol, a Bluetooth protocol, a WiFi Direct protocol, etc. Furthermore, the transmission path information of this embodiment may include, in addition to the transmission starting point location and the transmission end point location, also artificially set nodes that must be transmitted, thereby further improving the flexibility and adaptability of the self-organizing network.
[0089] Based on the above, this embodiment provides a technical basis for constructing a real-time self-organizing network through a preset self-organizing network mechanism.
[0090] Specifically, the process of building a self-organizing network includes:
[0091] Collect real-time node information and real-time node requirements, generate real-time node scores, and generate corresponding real-time node priority lists or real-time adaptive node priority lists;
[0092] Acquire real-time transmission path information, utilize the self-organizing network mechanism, and execute steps A1 to A4 in combination with the corresponding real-time node priority list or the real-time adaptive node priority list to obtain a real-time self-organizing network.
[0093] It should be noted that in actual applications, there are situations where the network environment changes dynamically and the node status changes continuously. For example, the signal strength of the node may fluctuate due to interference, the energy level may gradually decrease with the use time, the location of the node may move, and the connection status may become unstable due to various factors. At the same time, different application scenarios and business requirements may also change at any time. Therefore, this embodiment adopts two modes of real-time node priority list or real-time adaptive node priority list in design, so as to solve the existing problems of network dynamics and demand diversity.
[0094] Based on the above, the real-time node priority list of this embodiment can quickly generate priority sorting according to the current node status and demand, adapt to real-time changes in node information and demand, and use the real-time adaptive node priority list to further combine application scenario characteristics, business criticality distribution, network performance indicators and other factors to dynamically adjust node demand weight parameters, more flexibly adapt to complex and changeable network environments and business needs, and improve the construction efficiency and performance stability of self-organizing networks.
[0095] Specifically, the supervision process of the self-organizing network includes:
[0096] Node information and / or node requirements are continuously monitored and collected, and when there is changed node information and / or changed node requirements, corresponding updated node information and / or updated node requirements are generated.
[0097] It is understandable that in actual applications, changes in node information or node requirements will generate updates to the self-organizing network. Therefore, through continuous supervision and collection of node information and / or node requirements, comprehensive and real-time supervision of the self-organizing network is achieved.
[0098] Specifically, the update process of the self-organizing network includes:
[0099] Collect update node information and / or update node requirements, generate update node scores, and generate corresponding update node priority lists or update adaptive node priority lists;
[0100] The corresponding transmission path information is obtained, and the self-organizing network mechanism is used, and in combination with the corresponding updated node priority list or updated adaptive node priority list, steps A1 to A4 are executed to obtain an updated self-organizing network.
[0101] It should be noted that the update of the self-organizing network in this embodiment corresponds to the construction of the self-organizing network in the previous text. Only the real-time node priority list or the real-time adaptive node priority list in the previous text is updated to the corresponding updated node priority list or updated adaptive node priority list. Therefore, the update of the self-organizing network in this embodiment that is not specifically described may include but is not limited to the function definition, working principle and technical effects, etc., which can all refer to the construction of the self-organizing network in the previous text and will not be elaborated in this text.
[0102] In summary, the node screening method of the self-organizing network of the present embodiment achieves accurate evaluation of the node communication status by comprehensively collecting multi-dimensional information such as signal strength, energy level, location information and connection status of the nodes, and generating node scores in combination with the corresponding node requirements, thereby breaking the limitation of screening nodes by a single indicator, providing a basis for building a high-quality self-organizing network, and generating a priority list based on sorting of node requirements and scores, so that the nodes that best meet the requirements can be selected in the network construction, thereby improving the performance and adaptability of the network, and combining the transmission path information and the preset self-organizing network mechanism and dynamic update, it ensures that the network can always be adjusted and optimized according to the actual situation, thereby realizing the screening of nodes in the optimized self-organizing network.
[0103] In the embodiments provided in the present application, it should be understood that the embodiments described herein can be implemented in hardware, software, firmware, middleware, code or any appropriate combination thereof. For hardware implementation, the processor can be implemented in one or more of the following units: application specific integrated circuit (ASIC), digital signal processor (DSP), digital signal processing device (DSPD), programmable logic device (PLD), field programmable gate array (FPGA), processor, controller, microcontroller, microprocessor, other electronic units designed to implement the functions described herein or their combination. For software implementation, part or all of the flow of the embodiment can be completed by instructing the relevant hardware through a computer program. When implemented, the above program can be stored in a computer-readable storage medium or transmitted as one or more instructions or codes on a computer-readable storage medium. Computer-readable storage media include computer storage media and communication media, wherein the communication medium includes any medium that is convenient for transmitting a computer program from one place to another. The storage medium can be any available medium that a computer can access. The computer-readable storage medium can include but is not limited to RAM, ROM, EEPROM, CD-ROM or other optical disk storage, disk storage medium or other magnetic storage device, or any other medium that can be used to carry or store the desired program code in the form of an instruction or data structure and can be accessed by a computer.
[0104] Finally, it should be noted that the above is only a preferred embodiment of the present application and is not intended to limit the present application. Although the present application has been described in detail with reference to the aforementioned embodiments, it is still possible for those skilled in the art to modify the technical solutions described in the aforementioned embodiments or to make equivalent substitutions for some of the technical features therein. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present application shall be included in the protection scope of the present application.
Claims
1. A method for screening nodes of a self-organizing network, characterized in that: include: S1: Collect node information and node requirements, and generate corresponding node scores; wherein the node information includes signal strength, energy level, location information and connection status, the node requirements are used to characterize the signal strength requirements, energy level requirements, location information requirements and connection status requirements corresponding to the node information, and the node score is used to evaluate the communication status of the node in the self-organizing network; S2: Obtain and sort the node requirements and the node scores based on the node requirements to generate a corresponding node priority list; wherein the node priority list stores node priorities corresponding to different node requirements; S3: Acquire transmission path information, and use a preset self-organizing network mechanism and a corresponding node priority list to construct a self-organizing network; wherein the transmission path information at least includes a transmission starting point position and a transmission end point position, and the self-organizing network mechanism is used to dynamically guide the construction of the self-organizing network; S4: When there is updated node information and / or updated node demand, the self-organizing network obtained in the supervision step S3 repeats steps S2 to S3 to update the self-organizing network; wherein the updated node information is the node information that has changed, and the updated node demand is the node demand that has changed.
2. The method for selecting nodes of a self-organizing network according to claim 1, characterized in that: The node information is specifically: The signal strength is used in the process of screening nodes that meet the signal strength requirement, and the quality of the signal is positively correlated with the signal strength; The energy level is used in the process of screening nodes that meet the energy level requirement, and the endurance of the node during communication is positively correlated with the energy level; The location information is used to screen nodes located in a specific area or having a specific location relationship according to the transmission path information; The connection status is used in the process of screening nodes that meet the connection status requirements based on the connection stability of the nodes.
3. The method for selecting nodes of a self-organizing network according to claim 1, characterized in that: The node score generation process includes: Calculate the degree of compliance between the signal strength and the signal strength requirement to obtain a corresponding signal strength score; calculate the degree of compliance between the energy level and the energy level requirement to obtain a corresponding energy level score; calculate the degree of compliance between the location information and the location information requirement to obtain a corresponding location information score; calculate the degree of compliance between the connection state and the connection state requirement to obtain a corresponding connection state score; The node score is calculated using the signal strength score, the energy level score, the location information score, and the connection status score.
4. The method for selecting nodes of a self-organizing network according to claim 3, characterized in that: The generation process of the node priority list includes: Obtain the node scores; and sort the nodes based on the node scores to obtain the node priority list.
5. The method for selecting nodes of a self-organizing network according to claim 4, characterized in that: Analyzing the node requirements, and generating an adaptive node priority list when there is a corresponding node requirement weight parameter set; The generation process of the node demand weight parameter set includes: The node requirements are used to generate corresponding application scenario characteristics, business criticality distribution and network performance indicators; wherein the application scenario characteristics are used to characterize the emphasis of different application scenarios on node requirements, the business criticality distribution is used to characterize and analyze the criticality of each node requirement for a specific business, and the network performance target is used to characterize the overall performance target of the self-organizing network; In combination with the application scenario characteristics, the business criticality distribution and the network performance index, the signal strength requirement, the energy level requirement, the location information requirement and the connection status requirement are quantified to generate corresponding signal strength requirement weight parameters, energy level requirement weight parameters, location information requirement weight parameters and connection status requirement weight parameters; The signal strength requirement weight parameter, the energy level requirement weight parameter, the location information requirement weight parameter and the connection status requirement weight parameter are packaged and defined as the node requirement weight parameter set.
6. The method for selecting nodes of a self-organizing network according to claim 5, characterized in that: The process of generating the adaptive node priority list includes: Acquire the node demand weight parameter set; calculate the adaptive node score using the node demand weight parameter set and the corresponding signal strength score, the energy level score, the location information score and the connection status score; and sort based on the adaptive node score to obtain the adaptive node priority list.
7. The method for selecting nodes of a self-organizing network according to claim 6, characterized in that: The preset process of the self-organizing network mechanism includes: Acquire a communication protocol corresponding to the node, store the communication protocol in the self-organizing network mechanism, and then train the self-organizing network mechanism to perform the following steps: A1: Obtain the node priority list or the adaptive node priority list; A2: Obtain and parse the transmission path information to obtain the corresponding path to be constructed that requires node screening; A3: Using the path to be constructed, and selecting corresponding nodes in the corresponding node priority list; A4: Using the nodes obtained in step A3 and calling the corresponding communication protocol to build a self-organizing network and output the self-organizing network.
8. The method for selecting nodes of a self-organizing network according to claim 7, characterized in that: The construction process of the self-organizing network includes: Collect real-time node information and real-time node requirements, generate real-time node scores, and generate corresponding real-time node priority lists or real-time adaptive node priority lists; Acquire real-time transmission path information, utilize the self-organizing network mechanism, and in combination with the corresponding real-time node priority list or the real-time adaptive node priority list, execute steps A1 to A4 to obtain a real-time self-organizing network.
9. The method for selecting nodes of a self-organizing network according to claim 8, characterized in that: The supervision process of the self-organizing network includes: The node information and / or the node requirements are continuously monitored and collected, and when there is a change in the node information and / or a change in the node requirements, corresponding updated node information and / or updated node requirements are generated.
10. The method for selecting nodes of a self-organizing network according to claim 9, characterized in that: The updating process of the self-organizing network includes: Collect update node information and / or update node requirements, generate update node scores, and generate corresponding update node priority lists or update adaptive node priority lists; Obtain the corresponding transmission path information, utilize the self-organizing network mechanism, and in combination with the corresponding updated node priority list or the updated adaptive node priority list, execute steps A1 to A4 to obtain an updated self-organizing network.