Adaptive Energy Consumption Optimization Control Method and System for Sensor Networks

Abstract

The present invention discloses an adaptive energy consumption optimization control method and system for a sensor network, which is applied to an adaptive energy consumption optimization control system of a sensor network. The adaptive energy consumption optimization control system of the sensor network includes a plurality of sensor sub-networks. Each sensor sub-network includes several sink nodes and a plurality of sensor nodes, and the several sink nodes and the plurality of sensor nodes in each sensor sub-network are communicatively connected. In the embodiment of the present invention, after intelligently determining the main sink node in each sensor sub-network of the sensor network, the main sink node dynamically adjusts the communication parameters of each sensor node based on a communication power control strategy to achieve adaptive energy consumption optimization control during the communication process and ensure the communication quality between the sensor nodes and the main sink node.

Description

Technical Field

[0001] The present invention relates to the technical field of energy consumption control in sensor networks, and particularly to an adaptive energy consumption optimization control method and system for sensor networks. Background Art

[0002] Generally, a sensor network includes at least one sink node and multiple sensor nodes. The multiple sensor nodes are responsible for collecting data from monitored objects (such as device status, environmental status, or security status, etc.) and uploading it to the sink node for data aggregation processing to support subsequent data analysis and applications. However, when each sensor node in the current sensor network communicates with the sink node, its communication parameters (such as transmission power) are generally pre-configured and remain fixed during subsequent operation. This makes it impossible to flexibly adjust when the communication effect between the sensor node and the sink node is not good, thus unable to ensure the continuity and stability of the data transmission process. Summary of the Invention

[0003] Embodiments of the present invention provide an adaptive energy consumption optimization control method and system for sensor networks, aiming to solve the problem in the prior art that when each sensor node in the sensor network communicates with the sink node, its communication parameters are pre-configured and remain fixed during subsequent operation, which makes it impossible to flexibly adjust when the communication effect between the sensor node and the sink node is not good, thus unable to ensure the continuity and stability of the data transmission process.

[0004] In a first aspect, embodiments of the present invention provide an adaptive energy consumption optimization control method for a sensor network, which is applied to an adaptive energy consumption optimization control system of the sensor network. The adaptive energy consumption optimization control system of the sensor network includes multiple sensor sub-networks. Each sensor sub-network includes several sink nodes and multiple sensor nodes, and several sink nodes and multiple sensor nodes in each sensor sub-network are communicatively connected. For each sensor sub-network in the adaptive energy consumption optimization control system of the sensor network, the adaptive energy consumption optimization control method includes:

[0005] Several sink nodes in the sensor sub-network determine one sink node as the main sink node based on a preset main node selection strategy;

[0006] If the main aggregation node detects a node energy consumption optimization instruction, it obtains the current communication parameters of each sensor node among multiple sensor nodes in the sensor sub-network, obtains the adjusted communication parameters corresponding to each sensor node based on a preset communication power control strategy, and sends each adjusted communication parameter to the corresponding sensor node; wherein, the current communication parameters at least include communication distance and communication channel;

[0007] Each sensor node among the multiple sensor nodes sends the node acquisition data collected by it to the main aggregation node based on the corresponding adjusted communication parameter.

[0008] In a second aspect, an embodiment of the present invention further provides an adaptive energy consumption optimization control system for a sensor network, which includes a plurality of sensor sub-networks. Each sensor sub-network includes several aggregation nodes and multiple sensor nodes, and the several aggregation nodes and multiple sensor nodes in each sensor sub-network are all communicatively connected; for each sensor sub-network in the adaptive energy consumption optimization control system of the sensor network:

[0009] Several aggregation nodes in the sensor sub-network determine one of the aggregation nodes as the main aggregation node based on a preset main node screening strategy;

[0010] If the main aggregation node detects a node energy consumption optimization instruction, it obtains the current communication parameters of each sensor node among multiple sensor nodes in the sensor sub-network, obtains the adjusted communication parameters corresponding to each sensor node based on a preset communication power control strategy, and sends each adjusted communication parameter to the corresponding sensor node; wherein, the current communication parameters at least include communication distance and communication channel;

[0011] Each sensor node among the multiple sensor nodes is configured to send the node acquisition data collected by it to the main aggregation node based on the corresponding adjusted communication parameter.

[0012] The embodiments of the present invention provide an adaptive energy consumption optimization control method and system for a sensor network, which are applied to an adaptive energy consumption optimization control system of a sensor network. The adaptive energy consumption optimization control system of the sensor network includes multiple sensor sub-networks. Each sensor sub-network includes several aggregation nodes and multiple sensor nodes, and the several aggregation nodes and multiple sensor nodes in each sensor sub-network are communicatively connected. For each sensor sub-network in the adaptive energy consumption optimization control system of the sensor network, the adaptive energy consumption optimization control method includes: several aggregation nodes in the sensor sub-network determine one aggregation node as the main aggregation node based on a preset main node selection strategy; if the main aggregation node detects a node energy consumption optimization instruction, it obtains the current communication parameters of each sensor node among the multiple sensor nodes in the sensor sub-network, obtains the adjusted communication parameters corresponding to each sensor node based on a preset communication power control strategy, and sends the adjusted communication parameters to the corresponding sensor nodes; wherein, the current communication parameters at least include communication distance and communication channel; each sensor node among the multiple sensor nodes sends the collected node acquisition data to the main aggregation node based on the corresponding adjusted communication parameters. The embodiments of the present invention can first intelligently determine the main aggregation node in each sensor sub-network of the sensor network, and then the main aggregation node dynamically adjusts the communication parameters of each sensor node based on the communication power control strategy to achieve adaptive energy consumption optimization control during the communication process and ensure the communication quality between the sensor nodes and the main aggregation node. BRIEF DESCRIPTION OF THE DRAWINGS

[0013] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for the description of the embodiments will be briefly introduced below. Obviously, the drawings in the following description are some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0014] Figure 1 It is a schematic diagram of the application scenario of the adaptive energy consumption optimization control method for the sensor network provided by the embodiments of the present invention;

[0015] Figure 2 It is a schematic flowchart of the adaptive energy consumption optimization control method for the sensor network provided by the embodiments of the present invention;

[0016] Figure 3 It is a schematic sub-flowchart of the adaptive energy consumption optimization control method for the sensor network provided by the embodiments of the present invention;

[0017] Figure 4 It is a schematic sub-flowchart of the adaptive energy consumption optimization control method for the sensor network provided by the embodiments of the present invention;

[0018] Figure 5 Schematic diagram of a sub - process of the adaptive energy - consumption optimization control method for a sensor network provided by an embodiment of the present invention;

[0019] Figure 6 Schematic block diagram of an adaptive energy - consumption optimization control system for a sensor network provided by an embodiment of the present invention;

[0020] Figure 7 Schematic block diagram of a computer device provided by an embodiment of the present invention. Detailed implementation manners

[0021] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are some, but not all, of the embodiments of the present invention. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0022] It should be understood that when used in this specification and the appended claims, the terms "comprises" and "comprising" indicate the presence of the described features, wholes, steps, operations, elements, and / or components, but do not preclude the presence or addition of one or more other features, wholes, steps, operations, elements, components, and / or their combinations.

[0023] It should also be understood that the terms used in this specification of the present invention are only for the purpose of describing specific embodiments and are not intended to limit the present invention. As used in this specification of the present invention and the appended claims, unless the context clearly dictates otherwise, the singular forms "a", "an", and "the" are intended to include the plural forms.

[0024] It should be further understood that the term "and / or" used in this specification of the present invention and the appended claims refers to any combination and all possible combinations of one or more of the associated listed items, and includes these combinations.

[0025] Please refer to both Figure 1 and Figure 2 wherein Figure 1 is a scenario diagram of the adaptive energy - consumption optimization control method for a sensor network in an embodiment of the present invention, Figure 2 is a flowchart of the adaptive energy - consumption optimization control method for a sensor network provided by an embodiment of the present invention. As Figure 1As shown in the figure, the adaptive energy consumption optimization control method for a sensor network provided by an embodiment of the present invention is applied to an adaptive energy consumption optimization control system for a sensor network. The adaptive energy consumption optimization control system for the sensor network includes multiple sensor sub-networks. Each sensor sub-network 100 includes several aggregation nodes 110 and multiple sensor nodes 120, and the several aggregation nodes and the multiple sensor nodes 120 in each sensor sub-network 100 are communicatively connected.

[0026] As Figure 2 shown, the method includes the following steps S110 - S130.

[0027] S110. Several aggregation nodes in the sensor sub-network determine one aggregation node as the main aggregation node based on a preset main node screening strategy.

[0028] In this embodiment, in the adaptive energy consumption optimization control system for a sensor network, there are multiple sensor sub-networks. The adaptive energy consumption optimization control method for the sensor network can be executed in each sensor sub-network. At this time, the technical solution of the present application is described by taking the process of executing the adaptive energy consumption optimization control method for the sensor network in one sensor sub-network as an example.

[0029] Since one sensor sub-network includes several aggregation nodes and multiple sensor nodes, when the total number of aggregation nodes in the sensor sub-network is greater than 1, one aggregation node can be first determined as the main aggregation node based on a preset main node screening strategy. Then, the sensor data collected by the sensor nodes in the sensor sub-network is transmitted to the main aggregation node.

[0030] In one embodiment, as Figure 3 shown, step S110 includes:

[0031] S111. For each aggregation node among the several aggregation nodes, the aggregation node obtains the current data collection scenario information and obtains the scenario preference processing label pre-configured locally;

[0032] S112. If the aggregation node determines that the current data collection scenario information is the same as the scenario preference processing label, the aggregation node adds the node information of the aggregation node to the candidate main aggregation node set;

[0033] S113. If the aggregation node determines that the number of aggregation nodes included in the candidate main aggregation node set is one, the aggregation node included in the candidate main aggregation node set is used as the main aggregation node;

[0034] S114. If it is determined that the number of aggregation nodes in the candidate primary aggregation node set is greater than one, the system performance parameters corresponding to each aggregation node in the candidate primary aggregation node set are obtained, and the aggregation node with the optimal system performance parameter is used as the primary aggregation node.

[0035] In this embodiment, during the initialization configuration, regular configuration, or irregular configuration in the sensor sub-network, the determination of the primary aggregation node needs to be completed during this configuration process. Specifically, first, a random aggregation node is selected as the temporary primary aggregation node in the sensor sub-network; then, each aggregation node in the sensor sub-network sends the scene preference processing tags stored locally to the temporary primary aggregation node (where the scene preference processing tag of the temporary primary aggregation node itself is also known); then, because the temporary primary aggregation node receives the current data collection scene information (such as temperature data collection, working voltage data collection, etc.) sent by the server (such as an edge server or a cloud server, etc.) or the user terminal, it can also compare and match the scene preference processing tags of each aggregation node with the current data collection scene information. If it is determined that the scene preference processing tag of an aggregation node is the same as the current data collection scene information, the node information of the aggregation node is added to the candidate primary aggregation node set; finally, if it is determined that the number of aggregation nodes in the candidate primary aggregation node set is one in the temporary primary aggregation node, the aggregation node included in the candidate primary aggregation node set is used as the primary aggregation node; or if it is determined that the number of aggregation nodes in the candidate primary aggregation node set is greater than one, the system performance parameters (such as CPU usage rate, memory usage rate, request response time, etc.) corresponding to each aggregation node in the candidate primary aggregation node set are obtained, and the aggregation node with the optimal system performance parameter is used as the primary aggregation node.

[0036] In one embodiment, after step S110, it further includes:

[0037] If the primary aggregation node detects the current data collection scene setting information, it determines the target data collection frequency corresponding to the current data collection scene setting information based on the locally preset mapping relationship between the collection scene and the collection frequency, and sends the target data collection frequency to each sensor collection node in the multiple sensor collection nodes in the sensor sub-network.

[0038] In this embodiment, after the selection process of the main aggregation node is completed in the sensor sub-network, it is also possible to receive the current data acquisition scenario setting information (such as temperature data acquisition, operating voltage data acquisition, etc.) from a server (such as an edge server or a cloud server, etc.) or a user terminal (such as a smart phone, a tablet computer, etc.). Then, the current data acquisition scenario setting information is compared and matched with the acquisition scenario and acquisition frequency mapping relationship including multiple acquisition scenario and acquisition frequency mapping data, and the target acquisition scenario and acquisition frequency mapping data with the same acquisition scenario as the current data acquisition scenario setting information is screened out, and is sent to each sensor acquisition node among the multiple sensor acquisition nodes in the sensor sub-network at the target data acquisition frequency in the target acquisition scenario and acquisition frequency mapping data.

[0039] Specifically, the acquisition scenario and acquisition frequency mapping relationship can also be set to include multiple acquisition scenario priorities and acquisition frequency mapping data, and in the main aggregation node, the current acquisition scenario priority corresponding to the current data acquisition scenario setting information can also be determined. Then, the target acquisition scenario priority and acquisition frequency mapping data corresponding to the current acquisition scenario priority are obtained from the multiple acquisition scenario priorities and acquisition frequency mapping data, and the target data acquisition frequency corresponding to the target acquisition scenario priority and acquisition frequency mapping data is sent to each sensor acquisition node among the multiple sensor acquisition nodes in the sensor sub-network. For example, for data with a low data acquisition priority, the acquisition frequency is reduced; for data that changes rapidly and has a high data acquisition priority, the acquisition frequency is increased.

[0040] S120. If the main aggregation node detects a node energy consumption optimization instruction, it acquires the current communication parameters of each sensor node among the multiple sensor nodes in the sensor sub-network, obtains the adjusted communication parameters corresponding to each sensor node based on a preset communication power control strategy, and sends each adjusted communication parameter to the corresponding sensor node.

[0041] Among them, at least the communication distance and the communication channel are included in the current communication parameters.

[0042] In this embodiment, after the sensor sub-network determines the main aggregation node and detects a node energy consumption optimization instruction regularly or irregularly, it is first necessary to obtain the current communication parameters of each sensor node among the multiple sensor nodes in the sensor sub-network (this current communication parameter can be understood as the parameter saved by the sensor node after the communication parameter adjustment was last completed), and then obtain the adjusted communication parameters corresponding to each sensor node through the communication power control strategy and the current communication parameters, and send each adjusted communication parameter to the corresponding sensor node, so as to adjust the communication parameters of each sensor node and ensure that each sensor node maintains a communication connection with the main aggregation node at the optimal communication power.

[0043] In one embodiment, as the first embodiment of the communication power control strategy, as Figure 4 shown, step S120 includes:

[0044] S121A. For each sensor node among the multiple sensor nodes of the sensor sub-network, obtain the current bit error rate corresponding to the sensor node;

[0045] S122A. If it is determined that the current bit error rate is greater than a preset bit error rate threshold, obtain the first current transmission power corresponding to the current communication parameter, increase the first current transmission power by a first preset adjustment power value to update the first current transmission power, and form the adjusted communication parameter with the current communication parameter.

[0046] In this embodiment, as the first embodiment of the communication power control strategy, it can be that the main aggregation node obtains the current bit error rate corresponding to each sensor node among the multiple sensor nodes of the sensor sub-network (the greater the current bit error rate, the worse the communication quality of the sensor node, and the smaller the current bit error rate, the better the communication quality of the sensor node). For example, taking the analysis of the current bit error rate of one sensor node as an example, when it is determined that the current bit error rate of the sensor node is greater than the preset bit error rate threshold, it means that when the sensor node maintains the current transmission power, it can neither ensure the stability of the data transmission process nor maintain the optimal energy consumption. It is necessary to directly obtain or correspondingly determine the first current transmission power from the current communication parameter corresponding to the sensor node, and then increase the first current transmission power by a first preset adjustment power value to update the first current transmission power, and form the adjusted communication parameter with the current communication parameter. The above power adjustment process is a fine-tuning process, which can not only effectively improve the stability of the data transmission process, but also does not greatly increase the energy consumption of the sensor node.

[0047] In one embodiment, as the second embodiment of the communication power control strategy, as Figure 5 shown, step S120 includes:

[0048] S121B. For each sensor node among the multiple sensor nodes of the sensor sub-network, obtain the current signal-to-noise ratio corresponding to the sensor node;

[0049] S122B. If it is determined that the current signal-to-noise ratio is less than a preset signal-to-noise ratio threshold, obtain the current communication channel corresponding to the current communication parameter, and adjust it to any other communication channel among the multiple communication channels corresponding to the main aggregation node except the current communication channel, so as to update the current communication channel corresponding to the current communication parameter;

[0050] S123B. Obtain the second current transmission power corresponding to the current communication parameter, and when it is determined that the historical continuous adjustment times of the adjusted communication parameter of the sensor node exceed a preset adjustment times threshold, increase the second current transmission power by a second preset adjustment power value to update the second current transmission power, and form the adjusted communication parameter with the current communication parameter.

[0051] In this embodiment, as the second embodiment of the communication power control strategy, the main aggregation node may obtain the current signal-to-noise ratio for each of the multiple sensor nodes in the sensor sub-network (the larger the current signal-to-noise ratio, the better the communication quality of the sensor node, and the smaller the current bit error rate, the better the communication quality of the sensor node). For example, taking the analysis of the current signal-to-noise ratio of one of the sensor nodes as an example, when it is determined that the current signal-to-noise ratio of the sensor node is less than the preset signal-to-noise ratio threshold, it means that when the sensor node maintains the current transmission power, it can neither ensure the stability of the data transmission process nor maintain the optimal energy consumption. It is necessary to first obtain the current communication channel corresponding to the current communication parameter and adjust it to any other communication channel except the current communication channel among the multiple communication channels corresponding to the main aggregation node to update the current communication channel corresponding to the current communication parameter. After completing the adjustment of the communication channel between the sensor node and the main aggregation node, then obtain the second current transmission power corresponding to the current communication parameter. Moreover, when it is determined that the historical continuous adjustment times of the adjusted communication parameter of the sensor node exceed the preset adjustment times threshold (such as the preset adjustment times threshold is set as a custom positive integer such as 3, 5, 10, etc.), increase the second current transmission power by the second preset adjustment power value (in specific implementation, the second preset adjustment power value is greater than the first preset adjustment power value in the above example and can be an integer multiple of it, that is, the second preset adjustment power value = N1 * the first preset adjustment power value, where N1 is a positive integer) to update the second current transmission power, and form the adjusted communication parameter with the current communication parameter. The above power adjustment process can also be a fine-tuning process, which adjusts both the communication channel and the transmission power, not only effectively improving the stability of the data transmission process, but also not significantly increasing the energy consumption of the sensor node.

[0052] S130. Each of the multiple sensor nodes sends the node acquisition data collected based on the corresponding adjusted communication parameter to the main aggregation node.

[0053] In this embodiment, after the main aggregation node completes the determination of the adjusted communication parameters for each of the multiple sensor nodes in the sensor sub-network, each sensor node sends the node acquisition data collected by it to the main aggregation node based on the corresponding adjusted communication parameters, thereby completing the data transmission and aggregation processing process. It should be noted that when steps S120 - S130 are executed once, it is an adaptive energy consumption optimization control process of the sensor network when the main aggregation node detects the current node energy consumption optimization instruction and the next node energy consumption optimization instruction has not been detected yet. After each detection of a node energy consumption optimization instruction, the control process of steps S120 - S130 will be repeatedly executed. It can be seen that through the above control method, the adaptive energy consumption optimization control of each sensor node in the sensor network is realized.

[0054] In one embodiment, after step S130, it further includes:

[0055] If the multiple sensor nodes determine that the main aggregation node is in a faulty state and determine that the total number of aggregation nodes included in the sensor sub-network is greater than one, they obtain other aggregation nodes among several aggregation nodes in the sensor sub-network except the main aggregation node in the faulty state, and form a candidate main aggregation node set;

[0056] The multiple sensor nodes send the node cache acquisition data cached locally to one of the aggregation nodes in the candidate main aggregation node set based on a preset data balanced transmission strategy.

[0057] In this embodiment, when the multiple sensor nodes send node acquisition data to the corresponding main aggregation node, it is possible that the main aggregation node fails and cannot recover to normal in a short time. At this time, if it is determined that the main aggregation node is in a faulty state and the total number of aggregation nodes included in the sensor sub-network is greater than 1, other aggregation nodes among several aggregation nodes in the sensor sub-network except the main aggregation node in the faulty state are obtained to form a candidate main aggregation node set. After that, all the aggregation nodes in the candidate main aggregation node set can receive the node cache acquisition data cached locally by each sensor node in the sensor sub-network. The node cache acquisition data cached locally by the sensor node can be understood as the data collected by the sensor node during the time period from the time point when the previous main aggregation node is detected to be in a faulty state until the candidate main aggregation node set is determined again. It can be seen that through the above method, when the main aggregation node fails, other aggregation nodes in the same sensor sub-network can quickly serve as data receiving nodes, ensuring the continuity and stability of the data transmission process.

[0058] In one embodiment, the multiple sensor nodes send the node cache acquisition data cached locally to one of the aggregation nodes in the candidate primary aggregation node set based on a preset data balancing transmission strategy, including:

[0059] For each sensor node among the multiple sensor nodes, obtain the current real-time data reception weight values corresponding to each aggregation node in the candidate primary aggregation node set, and select the aggregation node with the maximum current real-time data reception weight value and correspondingly send the node cache acquisition data.

[0060] In this embodiment, when the multiple sensor nodes send the node cache acquisition data cached locally to one of the aggregation nodes in the candidate primary aggregation node set based on a preset data balancing transmission strategy, it can be that each sensor node first determines the current real-time data reception weight value corresponding to an aggregation node from the candidate primary aggregation node set (for example, when each aggregation node in the candidate primary aggregation node set receives a piece of node acquisition data, the reciprocal of the total number of data it has received is used as the current real-time data reception weight value), and selects the aggregation node with the maximum current real-time data reception weight value and correspondingly sends the node cache acquisition data. It can be seen that through the above method, the data reception amounts of the aggregation nodes in the candidate primary aggregation node set can be effectively adjusted, so that each aggregation node can evenly receive the node cache acquisition data from the sensor nodes.

[0061] It can be seen that the embodiment implementing this method can first intelligently determine the primary aggregation node in each sensor sub-network in the sensor network, and then the primary aggregation node dynamically adjusts the communication parameters of each sensor node based on the communication power control strategy to achieve adaptive energy consumption optimization control during the communication process and ensure the communication quality between the sensor nodes and the primary aggregation node.

[0062] Figure 6 It is a schematic block diagram of an adaptive energy consumption optimization control system for a sensor network provided by an embodiment of the present invention. As Figure 6 shown, corresponding to the above-mentioned adaptive energy consumption optimization control method for a sensor network, the present invention also provides an adaptive energy consumption optimization control system for a sensor network. As Figure 1 and Figure 6 shown, the adaptive energy consumption optimization control system 10 of the sensor network includes multiple sensor sub-networks 11. Each sensor sub-network 100 in the multiple sensor sub-networks 11 includes several aggregation nodes 110 and multiple sensor nodes 120, and several aggregation nodes and multiple sensor nodes 120 in each sensor sub-network 100 are all communicatively connected.

[0063] A number of sink nodes 110 in the sensor sub-network 100 are used to determine one of the sink nodes as the main sink node based on a preset main node screening strategy.

[0064] In this embodiment, the adaptive energy consumption optimization control system of the sensor network includes multiple sensor sub-networks. The adaptive energy consumption optimization control method of the sensor network can be executed in each sensor sub-network. At this time, the technical solution of this application is described by taking the process of executing the adaptive energy consumption optimization control method of the sensor network in one sensor sub-network as an example.

[0065] Since a sensor sub-network includes a number of sink nodes and multiple sensor nodes, when the total number of sink nodes in the sensor sub-network is greater than 1, one of the sink nodes can be determined as the main sink node based on a preset main node screening strategy. Then, the sensor data collected by the sensor nodes in the sensor sub-network is transmitted to the main sink node.

[0066] In one embodiment, the number of sink nodes 110 in the sensor sub-network 100 are specifically used for:

[0067] For each sink node among the number of sink nodes, the sink node obtains the current data collection scenario information and obtains the scenario preference processing label pre-configured locally;

[0068] If the sink node determines that the current data collection scenario information is the same as the scenario preference processing label, the node information of the sink node is added to the candidate main sink node set;

[0069] If the sink node determines that the number of sink nodes included in the candidate main sink node set is one, the sink node included in the candidate main sink node set is used as the main sink node;

[0070] If the sink node determines that the number of sink nodes included in the candidate main sink node set is greater than one, the system performance parameters corresponding to each sink node in the candidate main sink node set are obtained, and the sink node with the optimal system performance parameter is used as the main sink node.

[0071] In this embodiment, when performing initialization configuration, periodic configuration, or irregular configuration in the sensor sub-network, it is necessary to determine the main aggregation node during this configuration process. Specifically, first, a random aggregation node is selected in the sensor sub-network as the temporary main aggregation node; then, each aggregation node in the sensor sub-network sends the scene preference processing tags stored locally to the temporary main aggregation node (where the scene preference processing tag of the temporary main aggregation node itself is also known); then, since the temporary main aggregation node receives the current data acquisition scene information (such as temperature data acquisition, working voltage data acquisition, etc.) sent by the server (such as an edge server or a cloud server, etc.) or the user terminal, it can also compare and match the scene preference processing tags of each aggregation node with the current data acquisition scene information. If it is determined that the scene preference processing tag of an aggregation node is the same as the current data acquisition scene information, the node information of the aggregation node is added to the candidate main aggregation node set; finally, if it is determined that the number of aggregation nodes included in the candidate main aggregation node set is one in the temporary main aggregation node, the aggregation node included in the candidate main aggregation node set is used as the main aggregation node; or if it is determined that the number of aggregation nodes included in the candidate main aggregation node set is greater than one, the system performance parameters (such as CPU usage rate, memory usage rate, request response time, etc.) corresponding to each aggregation node in the candidate main aggregation node set are obtained, and the aggregation node with the optimal system performance parameters is used as the main aggregation node.

[0072] In one embodiment, the main aggregation node is used for:

[0073] If the current data acquisition scene setting information is detected, based on the mapping relationship between the locally preset acquisition scene and the acquisition frequency, determine the target data acquisition frequency corresponding to the current data acquisition scene setting information, and send the target data acquisition frequency to each sensor acquisition node in the multiple sensor acquisition nodes in the sensor sub-network.

[0074] In this embodiment, after the selection process of the main aggregation node is completed in the sensor sub-network, it is also possible to receive the current data acquisition scene setting information (such as temperature data acquisition, working voltage data acquisition, etc.) from the server (such as an edge server or a cloud server, etc.) or the user terminal (such as a smart phone, a tablet computer, etc.). Then, compare and match the current data acquisition scene setting information with the mapping relationship between the acquisition scene and the acquisition frequency, which includes multiple pieces of mapping data of the acquisition scene and the acquisition frequency, and screen out the target acquisition scene and acquisition frequency mapping data with the same acquisition scene as the current data acquisition scene setting information, and send the target data acquisition frequency in the target acquisition scene and acquisition frequency mapping data to each sensor acquisition node in the multiple sensor acquisition nodes in the sensor sub-network.

[0075] In specific implementation, the mapping relationship between the collection scenario and the collection frequency can also be set to include multiple pieces of mapping data of the collection scenario priority and the collection frequency. Moreover, in the main aggregation node, the corresponding current collection scenario priority can be determined based on the current data collection scenario setting information. Then, the target collection scenario priority and the mapping data of the collection frequency corresponding to the current collection scenario priority are obtained from the multiple pieces of mapping data of the collection scenario priority and the collection frequency, and the target data collection frequency corresponding to the target collection scenario priority and the mapping data of the collection frequency is sent to each sensor collection node in the multiple sensor collection nodes of the sensor sub-network. For example, for data with a low data collection priority, the collection frequency is reduced; for data that changes rapidly and has a high data collection priority, the collection frequency is increased.

[0076] The main aggregation node is used to, if a node energy consumption optimization instruction is detected, obtain the current communication parameters of each sensor node in the multiple sensor nodes of the sensor sub-network, obtain the adjusted communication parameters corresponding to each sensor node based on a preset communication power control strategy, and send each adjusted communication parameter to the corresponding sensor node.

[0077] Among them, at least the communication distance and the communication channel are included in the current communication parameters.

[0078] In this embodiment, after the main aggregation node is determined in the sensor sub-network, when a node energy consumption optimization instruction is detected regularly or irregularly, first, the current communication parameters of each sensor node in the multiple sensor nodes of the sensor sub-network need to be obtained (this current communication parameter can be understood as the parameter saved by the sensor node after the communication parameter adjustment was completed last time). Then, the adjusted communication parameters corresponding to each sensor node are obtained through the communication power control strategy and the current communication parameters, and each adjusted communication parameter is sent to the corresponding sensor node, so as to adjust the communication parameters of each sensor node and ensure that each sensor node maintains a communication connection with the main aggregation node with the optimal communication power.

[0079] In one embodiment, as the first embodiment of the communication power control strategy, the main aggregation node is specifically used for:

[0080] For each sensor node in the multiple sensor nodes of the sensor sub-network, obtain the current bit error rate corresponding to the sensor node;

[0081] If it is determined that the current bit error rate is greater than a preset bit error rate threshold, obtain the first current transmission power corresponding to the current communication parameters, increase the first current transmission power by a first preset adjustment power value to update the first current transmission power, and form the adjusted communication parameter with the current communication parameters.

[0082] In this embodiment, as the first embodiment of the communication power control strategy, the main aggregation node may obtain the current bit error rate for each of the multiple sensor nodes in the sensor sub-network (the larger the current bit error rate, the worse the communication quality of the sensor node, and the smaller the current bit error rate, the better the communication quality of the sensor node). For example, taking the analysis of the current bit error rate of one of the sensor nodes as an example, when it is determined that the current bit error rate of the sensor node is greater than the preset bit error rate threshold, it means that when the sensor node maintains the current transmission power, it can neither ensure the stability of the data transmission process nor maintain the optimal energy consumption. First, the first current transmission power needs to be directly obtained or correspondingly determined from the current communication parameters corresponding to the sensor node, and then the first current transmission power is increased by a first preset adjustment power value to update the first current transmission power, and the adjusted communication parameters are formed with the current communication parameters. The above power adjustment process is a fine-tuning process, which can not only effectively improve the stability of the data transmission process, but also does not significantly increase the energy consumption of the sensor node.

[0083] In one embodiment, as the second embodiment of the communication power control strategy, the main aggregation node is specifically used for:

[0084] For each of the multiple sensor nodes in the sensor sub-network, obtain the current signal-to-noise ratio corresponding to the sensor node;

[0085] If it is determined that the current signal-to-noise ratio is less than the preset signal-to-noise ratio threshold, obtain the current communication channel corresponding to the current communication parameters, and adjust to any other communication channel except the current communication channel among the multiple communication channels corresponding to the main aggregation node to update the current communication channel corresponding to the current communication parameters;

[0086] Obtain the second current transmission power corresponding to the current communication parameters, and when it is determined that the historical continuous adjustment times of the adjusted communication parameters of the sensor node exceed the preset adjustment times threshold, increase the second current transmission power by a second preset adjustment power value to update the second current transmission power, and form the adjusted communication parameters with the current communication parameters.

[0087] In this embodiment, as the second embodiment of the communication power control strategy, the main aggregation node may obtain the current signal-to-noise ratio for each of the multiple sensor nodes in the sensor sub-network (the larger the current signal-to-noise ratio, the better the communication quality of the sensor node, and the smaller the current bit error rate, the better the communication quality of the sensor node). For example, taking the analysis of the current signal-to-noise ratio of one of the sensor nodes as an example, when it is determined that the current signal-to-noise ratio of the sensor node is less than the preset signal-to-noise ratio threshold, it means that when the sensor node maintains the current transmission power, it can neither ensure the stability of the data transmission process nor maintain the optimal energy consumption. It is necessary to first obtain the current communication channel corresponding to the current communication parameter and adjust it to any other communication channel except the current communication channel among the multiple communication channels corresponding to the main aggregation node to update the current communication channel corresponding to the current communication parameter. After completing the adjustment of the communication channel between the sensor node and the main aggregation node, then obtain the second current transmission power corresponding to the current communication parameter. Moreover, when it is determined that the historical continuous adjustment times of the adjusted communication parameter of the sensor node exceed the preset adjustment times threshold (such as the preset adjustment times threshold is set to custom positive integers such as 3, 5, 10, etc.), increase the second current transmission power by the second preset adjustment power value (in specific implementation, the second preset adjustment power value is greater than the first preset adjustment power value in the above example and can be an integer multiple of it, that is, the second preset adjustment power value = N1 * the first preset adjustment power value, where N1 is a positive integer) to update the second current transmission power, and form the adjusted communication parameter with the current communication parameter. The above power adjustment process can also be a fine-tuning process, which adjusts both the communication channel and the transmission power, not only effectively improving the stability of the data transmission process, but also not significantly increasing the energy consumption of the sensor node.

[0088] Each sensor node among the multiple sensor nodes 120 is used to send the node acquisition data collected based on the corresponding adjusted communication parameter to the main aggregation node.

[0089] In this embodiment, after the main aggregation node completes the determination of the adjusted communication parameters for each of the multiple sensor nodes in the sensor sub-network, each sensor node sends the node acquisition data collected based on the corresponding adjusted communication parameter to the main aggregation node, thereby completing the data transmission and aggregation processing process. It can be seen that through the above control method, the adaptive energy consumption optimization control of each sensor node in the sensor network is realized.

[0090] In one embodiment, the multiple sensor nodes 120 are further used for:

[0091] If it is determined that the master aggregation node is in a faulty state and it is determined that the total number of aggregation nodes included in the sensor sub-network is greater than one, then obtain other aggregation nodes among several aggregation nodes in the sensor sub-network except the master aggregation node in the faulty state, and form a candidate master aggregation node set;

[0092] The multiple sensor nodes send the node cached acquisition data cached locally to one of the aggregation nodes in the candidate master aggregation node set based on a preset data balanced transmission strategy.

[0093] In this embodiment, when the multiple sensor nodes send node acquisition data to the corresponding master aggregation node, it may happen that the master aggregation node fails and cannot recover to normal in a short time. At this time, if it is determined that the master aggregation node is in a faulty state and it is determined that the total number of aggregation nodes included in the sensor sub-network is greater than 1, then obtain other aggregation nodes among several aggregation nodes in the sensor sub-network except the master aggregation node in the faulty state, and form a candidate master aggregation node set. After that, all the aggregation nodes in the candidate master aggregation node set can receive the node cached acquisition data cached locally by each sensor node in the sensor sub-network before. The node cached acquisition data cached locally by the sensor node can be understood as the data collected by the sensor node from the time point when it detects that the previous master aggregation node is in a faulty state until the candidate master aggregation node set is determined again. It can be seen that through the above method, when the master aggregation node fails, other aggregation nodes in the same sensor sub-network can quickly be used as data receiving nodes, ensuring the continuity and stability of the data transmission process.

[0094] In one embodiment, the multiple sensor nodes send the node cached acquisition data cached locally to one of the aggregation nodes in the candidate master aggregation node set, including:

[0095] For each sensor node among the multiple sensor nodes, obtain the current real-time data reception weight value corresponding to each aggregation node in the candidate master aggregation node set, and select the aggregation node with the maximum current real-time data reception weight value and send the node cached acquisition data correspondingly.

[0096] In this embodiment, when multiple sensor nodes send the node cache acquisition data cached locally to one of the aggregation nodes in the candidate primary aggregation node set based on a preset data balancing transmission strategy, each sensor node can first determine a current real-time data reception weight value corresponding to an aggregation node from the candidate primary aggregation node set (for example, when each aggregation node in the candidate primary aggregation node set receives a piece of node acquisition data, the reciprocal of the total number of data items it has received cumulatively is used as the current real-time data reception weight value), and select the aggregation node with the largest current real-time data reception weight value and send the node cache acquisition data accordingly. It can be seen that through the above method, the data reception amounts of the aggregation nodes in the candidate primary aggregation node set can be effectively adjusted, so that each aggregation node can receive the node cache acquisition data from the sensor nodes evenly.

[0097] It can be seen that after the main aggregation node is intelligently determined in each sensor sub-network in the sensor network in the embodiment of implementing this system, the main aggregation node dynamically adjusts the communication parameters of each sensor node based on the communication power control strategy to achieve adaptive energy consumption optimization control during the communication process and ensure the communication quality between the sensor node and the main aggregation node.

[0098] The above-mentioned adaptive energy consumption optimization control system for the sensor network can be implemented in the form of a computer program, and this computer program can run on a computer device as shown in Figure 7 shown.

[0099] Please refer to Figure 7 , Figure 7 which is a schematic block diagram of a computer device provided by an embodiment of the present invention. This computer device integrates any one of the adaptive energy consumption optimization control systems for the sensor network provided by the embodiment of the present invention.

[0100] Refer to Figure 7 , this computer device 400 includes a processor 402, a memory, and a network interface 405 connected through a system bus 401. Among them, the memory may include a storage medium 403 and an internal memory 404.

[0101] The storage medium 403 can store an operating system 4031 and a computer program 4032. This computer program 4032 includes program instructions, and when these program instructions are executed, the processor 402 can be made to execute an adaptive energy consumption optimization control method for a sensor network.

[0102] The processor 402 is used to provide computing and control capabilities to support the operation of the entire computer device.

[0103] The internal memory 404 provides an environment for the operation of the computer program 4032 in the storage medium 403. When the computer program 4032 is executed by the processor 402, the processor 402 can be caused to execute the above-mentioned adaptive energy consumption optimization control method for the sensor network.

[0104] The network interface 405 is used for network communication with other devices. Those skilled in the art can understand that Figure 7 the structure shown in is only a block diagram of some structures related to the solution of the present invention, and does not constitute a limitation on the computer device to which the solution of the present invention is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine some components, or have different component arrangements.

[0105] Among them, the processor 402 is used to run the computer program 4032 stored in the memory to implement the above-mentioned adaptive energy consumption optimization control method for the sensor network.

[0106] It should be understood that in the embodiment of the present invention, the processor 402 may be a central processing unit (CPU), and the processor 402 may also be other general-purpose processors, digital signal processors (DSPs), application specific integrated circuits (ASICs), off-the-shelf programmable gate arrays (FPGAs) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. Among them, the general-purpose processor may be a microprocessor or the processor may also be any conventional processor, etc.

[0107] Those of ordinary skill in the art can understand that all or part of the processes in the methods of the above embodiments can be completed by instructing relevant hardware through a computer program. The computer program includes program instructions, and the computer program can be stored in a storage medium, and the storage medium is a computer-readable storage medium. The program instructions are executed by at least one processor in the computer system to implement the process steps of the embodiments of the above methods.

[0108] Therefore, the present invention also provides a computer-readable storage medium. The computer-readable storage medium stores a computer program, where the computer program includes program instructions. When the program instructions are executed by the processor, the processor is caused to execute the above-mentioned adaptive energy consumption optimization control method for the sensor network.

[0109] The storage medium may be a variety of computer-readable storage media such as a USB flash drive, a portable hard drive, a read-only memory (ROM), a magnetic disk, or an optical disc, etc., which can store program codes.

[0110] Those of ordinary skill in the art can realize that the units and algorithm steps of each example described in combination with the embodiments disclosed herein can be implemented by electronic hardware, computer software, or a combination of both. To clearly illustrate the interchangeability of hardware and software, the composition and steps of each example have been generally described according to functions in the above description. Whether these functions are executed in a hardware or software manner depends on the specific application and design constraints of the technical solution. Professional technicians can use different methods to implement the described functions for each specific application, but such implementation should not be considered to exceed the scope of the present invention.

[0111] In several embodiments provided by the present invention, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are only illustrative. For example, the division of each unit is only a logical function division, and there may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed.

[0112] The steps in the method embodiments of the present invention can be adjusted, combined, and deleted according to actual needs. The units in the device embodiments of the present invention can be combined, divided, and deleted according to actual needs. In addition, the functional units in each embodiment of the present invention can be integrated into one processing unit, or each unit can exist physically alone, or two or more units can be integrated into one unit.

[0113] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a storage medium. Based on such an understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions for causing a computer device (which may be a personal computer, a terminal, or a network device, etc.) to execute all or part of the steps of the methods described in each embodiment of the present invention.

[0114] As described above, only the specific embodiments of the present invention are provided, but the protection scope of the present invention is not limited thereto. Any person skilled in the art within the technical scope disclosed by the present invention can easily think of various equivalent modifications or substitutions, and these modifications or substitutions should all be covered within the protection scope of the present invention. Therefore, the protection scope of the present invention should be subject to the protection scope of the claims.

Claims

1. An adaptive energy consumption optimization control method for a sensor network, applied to an adaptive energy consumption optimization control system for a sensor network, characterized in that: The adaptive energy consumption optimization control system of the sensor network includes multiple sensor sub-networks, each of which includes multiple aggregation nodes and multiple sensor nodes, and the multiple aggregation nodes and multiple sensor nodes in each sensor sub-network are all communicatively connected; for each sensor sub-network in the adaptive energy consumption optimization control system of the sensor network, the adaptive energy consumption optimization control method of the sensor network includes: The plurality of sink nodes in the sensor sub-network determine one of the sink nodes as a master sink node based on a preset master node screening strategy; If the master aggregation node detects a node energy consumption optimization instruction, it obtains the current communication parameters of each sensor node in the multiple sensor nodes in the sensor subnetwork, obtains the adjusted communication parameters corresponding to each sensor node based on a preset communication power control strategy, and sends each adjusted communication parameter to the corresponding sensor node; wherein the current communication parameters include at least a communication distance and a communication channel; Each sensor node in the plurality of sensor nodes sends the collected node collection data to the main aggregation node based on the corresponding adjusted communication parameters; The plurality of sink nodes determine one of the sink nodes as the master sink node based on a preset master node screening strategy, including: For each of the plurality of sink nodes, the sink node obtains current data collection scene information and obtains a locally pre-configured scene preference processing tag; If the sink node determines that the current data collection scenario information is the same as the scenario preference processing label, then the node information of the sink node is added to the candidate main sink node set; If the sink node determines that the number of sink nodes included in the candidate main sink node set is one, the sink node included in the candidate main sink node set is used as the main sink node; If the aggregation node determines that the number of aggregation nodes included in the candidate main aggregation node set is greater than one, it obtains the system performance parameters corresponding to each aggregation node in the candidate main aggregation node set, and uses the aggregation node with the best system performance parameters as the main aggregation node.

2. The method according to claim 1, characterized in that After the step of each sensor node in the plurality of sensor nodes sending the collected node collection data to the main aggregation node based on the corresponding adjusted communication parameter, the method further includes: If the multiple sensor nodes determine that the main sink node is in a fault state and determine that the total number of sink nodes included in the sensor subnetwork is greater than one, then obtain other sink nodes except the main sink node in the fault state from among the sink nodes in the sensor subnetwork to form a candidate main sink node set; The multiple sensor nodes send the node cache collection data cached locally to one of the sink nodes in the candidate main sink node set based on a preset data balance transmission strategy.

3. The method according to claim 1, characterized in that The step of obtaining the current communication parameters of each sensor node in the plurality of sensor nodes in the sensor subnetwork and obtaining the adjusted communication parameters corresponding to each sensor node based on a preset communication power control strategy includes: For each sensor node among the plurality of sensor nodes of the sensor subnetwork, obtaining a current bit error rate corresponding to the sensor node; If it is determined that the current bit error rate is greater than a preset bit error rate threshold, a first current transmission power corresponding to the current communication parameter is obtained, the first current transmission power is increased by a first preset adjustment power value to update the first current transmission power, and the first current transmission power is combined with the current communication parameter to form the adjusted communication parameter.

4. The method according to claim 1, characterized in that: The step of obtaining the current communication parameters of each sensor node in the plurality of sensor nodes in the sensor subnetwork and obtaining the adjusted communication parameters corresponding to each sensor node based on a preset communication power control strategy includes: For each sensor node among the plurality of sensor nodes of the sensor subnetwork, obtaining a current signal-to-noise ratio corresponding to the sensor node; If it is determined that the current signal-to-noise ratio is less than a preset signal-to-noise ratio threshold, the current communication channel corresponding to the current communication parameter is obtained, and adjusted to any one of the multiple communication channels corresponding to the main convergence node except the current communication channel, so as to update the current communication channel corresponding to the current communication parameter; Obtain a second current transmission power corresponding to the current communication parameter, and when it is determined that the number of historical continuous adjustments of the communication parameter of the sensor node exceeds a preset adjustment number threshold, increase the second current transmission power by a second preset adjustment power value to update the second current transmission power, and form the adjusted communication parameter with the current communication parameter.

5. The method according to claim 1, characterized in that After the step of determining, by a plurality of sink nodes in the sensor subnetwork, one of the sink nodes as a master sink node based on a preset master node screening strategy, the method further comprises: If the main aggregation node detects the current data acquisition scene setting information, it determines the target data acquisition frequency corresponding to the current data acquisition scene setting information based on the locally preset acquisition scene and acquisition frequency mapping relationship, and sends the target data acquisition frequency to each sensor acquisition node in the multiple sensor acquisition nodes in the sensor subnetwork.

6. The method according to claim 2, characterized in that The multiple sensor nodes send the node cache collection data cached locally to one of the sink nodes in the candidate main sink node set based on a preset data balancing transmission strategy, including: For each sensor node in the multiple sensor nodes, the current real-time data receiving weight value corresponding to each sink node in the candidate main sink node set is obtained, and the sink node with the largest current real-time data receiving weight value is selected and the corresponding sending node cache collects data.

7. An adaptive energy consumption optimization control system for a sensor network, characterized in that: The invention comprises a plurality of sensor sub-networks, each of which comprises a plurality of sink nodes and a plurality of sensor nodes, and the plurality of sink nodes and the plurality of sensor nodes in each sensor sub-network are communicatively connected; for each sensor sub-network in the adaptive energy consumption optimization control system of the sensor network: The plurality of sink nodes in the sensor sub-network determine one of the sink nodes as a master sink node based on a preset master node screening strategy; If the master aggregation node detects a node energy consumption optimization instruction, it obtains the current communication parameters of each sensor node in the multiple sensor nodes in the sensor subnetwork, obtains the adjusted communication parameters corresponding to each sensor node based on a preset communication power control strategy, and sends each adjusted communication parameter to the corresponding sensor node; wherein the current communication parameters include at least a communication distance and a communication channel; Each sensor node among the plurality of sensor nodes is used to send the collected node collection data to the main aggregation node based on the corresponding adjusted communication parameters; The plurality of sink nodes determine one of the sink nodes as the master sink node based on a preset master node screening strategy, including: For each of the plurality of sink nodes, the sink node obtains current data collection scene information and obtains a locally pre-configured scene preference processing tag; If the sink node determines that the current data collection scenario information is the same as the scenario preference processing label, then the node information of the sink node is added to the candidate main sink node set; If the sink node determines that the number of sink nodes included in the candidate main sink node set is one, the sink node included in the candidate main sink node set is used as the main sink node; If the aggregation node determines that the number of aggregation nodes included in the candidate main aggregation node set is greater than one, it obtains the system performance parameters corresponding to each aggregation node in the candidate main aggregation node set, and uses the aggregation node with the best system performance parameters as the main aggregation node.

8. The adaptive energy consumption optimization control system of the sensor network according to claim 7, characterized in that: The plurality of sensor nodes are further configured to: If it is determined that the main sink node is in a fault state and it is determined that the total number of sink nodes included in the sensor subnetwork is greater than one, then obtaining other sink nodes except the main sink node in the fault state from among a number of sink nodes in the sensor subnetwork to form a candidate main sink node set; The node cache collection data cached locally is sent to one of the aggregation nodes in the candidate main aggregation node set based on a preset data balancing transmission strategy.

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