Dynamic uncertain underwater intelligent Internet of Things node optimization reconstruction method and system

Abstract

The invention discloses a dynamic uncertain underwater intelligent Internet of Things node optimization reconstruction method and system, and relates to the communication technology, and the method comprises the steps: determining the communication mode of a node according to the underwater attenuation degree of sound waves of different frequencies; initializing the sensor network; under the condition that the state of any Internet of Things node is converted into a fault or a temporary fault, reducing the sending frequency of the any Internet of Things node; the method comprises the steps of sending a first node capable of sensing a neighbor node in other nodes, initiating a connection request to the sensed neighbor node, updating the neighbor node as a father node of the first node after the first node receives a response, and marking a second node incapable of sensing the neighbor node in other nodes, and thus, network reconstruction is completed. According to the method provided by the invention, the intelligent Internet of Things node optimization and reconstruction under the underwater dynamic uncertain condition can be realized under the condition that a temporary fault node appears.

Description

Technical Field

[0001] The present application relates to the field of communication technology, and in particular to a method and system for optimizing and reconstructing dynamic uncertain underwater intelligent Internet of Things nodes. Background Art

[0002] The temperature, salinity and ocean currents of the underwater environment will have an adverse effect on the communication capabilities of the sensors carried by the underwater Internet of Things, often causing them to temporarily malfunction, resulting in the sensors being able to only sense information but unable to transmit information to their neighbors. To address this problem, existing technologies usually adopt a processing strategy of pre-setting redundant nodes underwater and activating redundant nodes when a failure occurs. However, temporary node failures are often random and short-lived, and pre-set redundant nodes will be on standby for a long time, resulting in a significant waste of resources. Summary of the invention

[0003] The embodiment of the present application provides a method and system for optimizing and reconfiguring underwater intelligent IoT nodes under dynamic uncertain conditions, which can realize adaptive reconstruction of network topology by adjusting communication frequency and information transmission path without presetting redundant nodes. The method of the present application can realize the optimization and reconstruction of intelligent IoT nodes under dynamic uncertain conditions underwater when temporary fault nodes occur.

[0004] The present application embodiment provides a method for optimizing and reconstructing a dynamic uncertain underwater intelligent Internet of Things node, including:

[0005] Determine the communication mode of the node in advance based on the attenuation of sound waves of different frequencies underwater;

[0006] Initializing the sensor network to distinguish the node conditions of the corresponding network topology after initialization, wherein the sensor network has a plurality of Internet of Things nodes, and a communication connection can be established between two Internet of Things nodes;

[0007] When the state of any IoT node changes to a fault or a temporary fault, reduce the transmission frequency of any IoT node, and control other nodes that were in communication connection with any IoT node before the fault or the temporary fault to initiate link sensing, and change the states of other nodes in the network topology based on the link sensing results;

[0008] A first node that can sense a neighbor node among the other nodes initiates a connection request to the sensed neighbor node, and after the first node receives a response, updates the neighbor node to be the parent node of the first node, and marks a second node that cannot sense the neighbor node among the other nodes, so as to complete network reconstruction.

[0009] Optionally, determining the communication mode of the node according to the attenuation degree of sound waves of different frequencies underwater includes:

[0010] According to the attenuation degree of sound waves of different frequencies underwater, the path loss of underwater acoustic communication signals satisfies:

[0011] A(d,f)=A0d k a(f) d (1)

[0012] Where A0 is the normalization constant, f is the signal frequency, d is the signal transmission distance, k is the path loss, and a(f) is the absorption coefficient, which is defined as:

[0013]

[0014] The signal-to-noise ratio at distance d is:

[0015]

[0016] Where S(f) is the power spectral density of the transmitted signal.

[0017] Optionally, according to the attenuation degree of sound waves of different frequencies underwater, determining the communication mode of the node also includes:

[0018] A normal communication mode and a fault communication mode are configured, wherein the normal communication mode is to select the optimal communication frequency for communication according to the distance between nodes, and the fault communication mode is to extend the communication distance by reducing the communication frequency.

[0019] Optionally, initializing the sensor network to distinguish node conditions of the corresponding network topology after initialization includes:

[0020] After initialization, in the corresponding network topology, according to the communication mode configuration:

[0021] Normal nodes that can normally receive and transmit information;

[0022] A temporarily faulty node that can sense the surrounding physical environment but cannot send information to neighboring nodes;

[0023] The class Temporarily Faulted Node for a node whose parent node has experienced a temporary fault.

[0024] Optionally, it also includes configuring corresponding node identifiers for different types of nodes in the network topology, and updating the corresponding node identifiers after the node status changes.

[0025] Optionally, marking the second node among the other nodes that cannot perceive the neighbor node includes: marking the second node among the other nodes that cannot perceive the neighbor node as a quasi-temporary fault node, switching the communication mode and sending information indicating that the second node has become a temporary fault node to the child nodes of the second node.

[0026] Optionally, it also includes: after the child node of the second node receives the information that the second node has become a quasi-temporary fault node, closing the connection response with other nodes and sending a connection request to the neighbor node of the child node; after the neighbor node of the child node responds, the child node marks the neighbor node of the child node as a parent node.

[0027] An embodiment of the present application also proposes an intelligent Internet of Things system, including a sensor network, wherein the sensor network includes multiple Internet of Things nodes, and any Internet of Things node is provided with a processor and a memory, wherein a computer program is stored in the memory, and when the computer program is executed by the processor, the steps of the aforementioned dynamic uncertain underwater intelligent Internet of Things node optimization and reconstruction method are jointly implemented.

[0028] The method of the embodiment of the present application can realize adaptive reconstruction of network topology without pre-setting redundant nodes, only by adjusting the communication frequency and information transmission path. The method of the present application can realize the optimization reconstruction of intelligent Internet of Things nodes under underwater dynamic uncertain conditions when temporary fault nodes occur.

[0029] The above description is only an overview of the technical solution of the present application. In order to more clearly understand the technical means of the present application, it can be implemented in accordance with the contents of the specification. In order to make the above and other purposes, features and advantages of the present application more obvious and easy to understand, the specific implementation methods of the present application are listed below. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] Various other advantages and benefits will become apparent to those of ordinary skill in the art by reading the detailed description of the preferred embodiments below. The accompanying drawings are only for the purpose of illustrating the preferred embodiments and are not to be considered as limiting the present application. Also, the same reference symbols are used throughout the accompanying drawings to represent the same components. In the accompanying drawings:

[0031] Figure 1 This is a schematic diagram of the overall process of the intelligent Internet of Things node optimization and reconstruction method according to an embodiment of the present application;

[0032] Figure 2 It is the network initial state of the application example of the intelligent Internet of Things node optimization and reconstruction method of the embodiment of the present application;

[0033] Figure 3 is the network status of the failed node in the application example of the intelligent Internet of Things node optimization and reconstruction method according to the embodiment of the present application;

[0034] Figure 4 It is the network starting reconstruction state in the application example of the intelligent Internet of Things node optimization and reconstruction method of the embodiment of the present application;

[0035] Figure 5 It is the network reconstruction completion state in the application example of the intelligent Internet of Things node optimization and reconstruction method in the embodiment of the present application. DETAILED DESCRIPTION

[0036] The exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although the exemplary embodiments of the present disclosure are shown in the accompanying drawings, it should be understood that the present disclosure can be implemented in various forms and should not be limited by the embodiments set forth herein. On the contrary, these embodiments are provided to enable a more thorough understanding of the present disclosure and to fully convey the scope of the present disclosure to those skilled in the art.

[0037] The present application embodiment proposes a dynamic uncertain underwater intelligent Internet of Things node optimization and reconstruction method, which mainly uses the following technologies:

[0038] Intelligent switching technology for communication modes. Nodes communicate underwater through hydroacoustic technology. The higher the communication frequency, the faster the signal attenuation. When a node has a temporary failure, it automatically switches to a lower communication frequency to extend the communication distance, thereby achieving information transmission in the event of a node failure.

[0039] Communication link adaptive reconstruction technology. When a node has a temporary failure, the communication mode intelligent switching technology is used to appropriately reduce the frequency to extend the communication distance, and initiate connection requests to other nodes within the communication range. At the same time, the child nodes of the failed node cannot receive information from the parent node, and the communication frequency is also reduced.

[0040] The method of the present application proposes a dual communication mode. When a normal node fails, it switches to a low-frequency mode to transmit its reconnaissance storage information to its parent node. Secondly, a class fault node is defined and a node connection reconstruction technology is designed. When a parent node becomes a class fault node, the child node can quickly find a new parent node and pass information to the parent node. The specific embodiment of the present application provides a dynamic uncertain underwater intelligent Internet of Things node optimization and reconstruction method, such as Figure 1 As shown, the following steps are included:

[0041] In step S101, the communication mode of the node is determined in advance according to the attenuation degree of sound waves of different frequencies underwater. In some embodiments, the communication mode of the node is determined in advance according to the attenuation degree of sound waves of different frequencies underwater, including:

[0042] According to the attenuation degree of sound waves of different frequencies underwater, the path loss of underwater acoustic communication signals satisfies:

[0043] A(d,f)=A0d k a(f) d (1)

[0044] Where A0 is the normalization constant, f is the signal frequency, d is the signal transmission distance, k is the path loss, which can be between 1 and 2, and a(f) is the absorption coefficient, which is defined as:

[0045]

[0046] It can be seen that the higher the frequency, the faster the attenuation. The signal-to-noise ratio at distance d is:

[0047]

[0048] Among them, S(f) is the power spectrum density of the transmitted signal. It can be seen that when the optimal signal-to-noise ratio is achieved, the higher the node communication frequency, the longer the transmission distance.

[0049] In some embodiments, determining the communication mode of the node according to the attenuation degree of sound waves of different frequencies underwater further includes:

[0050] Configure a normal communication mode and a fault communication mode, wherein the normal communication mode selects the optimal communication frequency for communication according to the distance between nodes; the fault communication mode extends the communication distance by reducing the communication frequency, and the current reconnaissance storage data can be sent to the parent node in a low-bandwidth manner.

[0051] In step S102, the sensor network is initialized to distinguish the node conditions of the corresponding network topology after initialization, wherein the sensor network has multiple Internet of Things nodes, and a communication connection can be established between two Internet of Things nodes. Figure 2 As shown, the embodiment of the present application and subsequent embodiments are illustrated by taking a network topology structure in which a sensor network includes 13 underwater Internet of Things nodes as an example. The specific number of nodes is only for describing the method of the embodiment of the present application, and the number and topology structure are not limited.

[0052] In step S103, when the state of any IoT node changes to a fault or a temporary fault, the sending frequency of the IoT node is reduced, and other nodes that are communicatively connected with the IoT node before the fault or the temporary fault are controlled to initiate link perception, and the states of the other nodes in the network topology are changed based on the link perception results.

[0053] like Figure 2As shown in the figure, node C (any IoT node) becomes a temporary fault node, represented by a triangle. At this time, the sending frequency of node C is reduced to ensure that it can send its own information. Node C becomes a temporary fault node, which makes node E (other nodes) and node F (other nodes) unable to receive feedback from node C, so nodes E and F start to initiate link perception. Node E can perceive neighbor node D, however, node F has no other neighbor nodes except child nodes, so node F becomes a quasi-temporary fault node, represented by a square.

[0054] In step S104, the first node that can perceive the neighbor node among the other nodes initiates a connection request to the perceived neighbor node. After the first node receives a response, the neighbor node is updated to be the parent node of the first node, and the second node that cannot perceive the neighbor node among the other nodes is marked to complete the network reconstruction.

[0055] like Figure 3 In the example, node E (first node) initiates a connection request to node D (a perceived neighbor node), and after receiving a response, updates node D as its new parent node. Node F (second node) marks itself as a quasi-temporary fault node, switches the communication mode, and sends the information that it is a temporary fault node to its child nodes.

[0056] The method of the embodiment of the present application can realize adaptive reconstruction of network topology without pre-setting redundant nodes, only by adjusting the communication frequency and information transmission path. The method of the present application can realize the optimization reconstruction of intelligent Internet of Things nodes under underwater dynamic uncertain conditions when temporary fault nodes occur.

[0057] In some embodiments, initializing the sensor network to distinguish node conditions of the corresponding network topology after initialization includes:

[0058] After initialization, in the corresponding network topology, according to the communication mode configuration:

[0059] Normal nodes that can normally receive and transmit information;

[0060] A temporarily faulty node that can sense the surrounding physical environment but cannot send information to neighboring nodes;

[0061] The class Temporarily Faulted Node for a node whose parent node has experienced a temporary fault.

[0062] Further references Figure 2In the network topology composed of 13 underwater IoT nodes, the solid arrows represent normal communication connections, and the dotted lines represent communication connections that can be established but have not yet been established. Among them, a normal node refers to a node that can normally receive and transmit information; a temporary fault node refers to a node that can sense the surrounding physical environment but cannot send information to its neighbors; a quasi-temporary fault node refers to a node whose parent node has a temporary fault.

[0063] In some embodiments, it also includes configuring corresponding node identifiers for different types of nodes in the network topology, and updating the corresponding node identifiers after the node status changes. For example, node F becomes a temporary fault node, which is represented by a square.

[0064] In some embodiments, marking the second node among the other nodes that cannot sense the neighboring node includes: marking the second node among the other nodes that cannot sense the neighboring node as a quasi-temporary fault node, switching the communication mode and sending information that the second node has become a temporary fault node to a child node of the second node. Figure 3 In the example, node F (the second node) marks itself as a quasi-temporary fault node, switches the communication mode and sends the information that it is a temporary fault node to its child nodes.

[0065] In some embodiments, it also includes: after the child node of the second node receives the information that the second node has become a quasi-temporary fault node, closing the connection response with other nodes, and sending a connection request to the neighbor node of the child node, after the neighbor node of the child node responds, the child node marks the neighbor node of the child node as a parent node.

[0066] like Figure 4 As shown in FIG. 1 , after receiving the information that its parent node F has become a quasi-temporary fault node, node H first closes the connection response with other nodes, and then sends a connection request to its neighbor nodes (excluding its parent node and child nodes). Figure 4 After receiving the response from node G, node H marks node G as the new parent node.

[0067] At this point, the optimization and reconstruction of underwater intelligent IoT nodes is completed. The reconstructed network structure is as follows: Figure 5 shown.

[0068] The method of the present application does not require pre-setting redundant nodes, and can achieve adaptive reconstruction of network topology by simply adjusting the communication frequency and information transmission path. The invention can achieve optimized reconstruction of intelligent Internet of Things nodes under underwater dynamic uncertain conditions when temporary fault nodes occur.

[0069] An embodiment of the present application also proposes an intelligent Internet of Things system, including a sensor network, wherein the sensor network includes multiple Internet of Things nodes, and any Internet of Things node is provided with a processor and a memory, wherein a computer program is stored in the memory, and when the computer program is executed by the processor, the steps of the aforementioned dynamic uncertain underwater intelligent Internet of Things node optimization and reconstruction method are jointly implemented.

[0070] It should be noted that in the various embodiments of the present application, the terms "include", "comprise" or any other variants thereof are 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 further restrictions, an element defined by the sentence "includes a ..." does not exclude the presence of other identical elements in the process, method, article or device including the element.

[0071] The serial numbers of the above-mentioned embodiments of the present application are for description only and do not represent the advantages or disadvantages of the embodiments.

[0072] Through the description of the above implementation methods, those skilled in the art can clearly understand that the above-mentioned embodiment methods can be implemented by means of software plus a necessary general hardware platform, and of course by hardware, but in many cases the former is a better implementation method. Based on such an understanding, the technical solution of the present application, or the part that contributes to the prior art, can be embodied in the form of a software product, which is stored in a storage medium (such as ROM / RAM, a magnetic disk, or an optical disk), and includes a number of instructions for a terminal (which can be a mobile phone, a computer, a server, an air conditioner, or a network device, etc.) to execute the methods described in each embodiment of the present application.

[0073] The embodiments of the present application are described above in conjunction with the accompanying drawings, but the present application is not limited to the above-mentioned specific implementation methods. The above-mentioned specific implementation methods are merely illustrative and not restrictive. Under the guidance of the present application, ordinary technicians in this field can also make many forms without departing from the purpose of the present application and the scope of protection of the claims, all of which are within the protection of the present application.

Claims

1. A dynamic uncertain underwater intelligent Internet of Things node optimization and reconstruction method, characterized in that: include: Determine the communication mode of the node in advance based on the attenuation of sound waves of different frequencies underwater; Initializing the sensor network to distinguish the node conditions of the corresponding network topology after initialization, wherein the sensor network has a plurality of Internet of Things nodes, and a communication connection can be established between two Internet of Things nodes; When the state of any IoT node changes to a fault or a temporary fault, reduce the transmission frequency of any IoT node, and control other nodes that were in communication connection with any IoT node before the fault or the temporary fault to initiate link sensing, and change the states of other nodes in the network topology based on the link sensing results; A first node that can sense a neighbor node among the other nodes initiates a connection request to the sensed neighbor node, and after the first node receives a response, updates the neighbor node to be the parent node of the first node, and marks a second node that cannot sense the neighbor node among the other nodes, so as to complete network reconstruction.

2. The dynamic uncertain underwater intelligent Internet of Things node optimization and reconstruction method according to claim 1 is characterized in that: The communication modes of the nodes are determined in advance based on the attenuation of sound waves of different frequencies underwater: According to the attenuation degree of sound waves of different frequencies underwater, the path loss of underwater acoustic communication signals satisfies: A(d,f)=A0d k amnesty) d (1) Where A0 is the normalization constant, f is the signal frequency, d is the signal transmission distance, k is the path loss, and a(f) is the absorption coefficient, which is defined as: The signal-to-noise ratio at distance d is: Where S(f) is the power spectral density of the transmitted signal.

3. The dynamic uncertain underwater intelligent Internet of Things node optimization and reconstruction method according to claim 2 is characterized in that: According to the attenuation of sound waves of different frequencies underwater, the communication mode of the node is also determined by: A normal communication mode and a fault communication mode are configured, wherein the normal communication mode is to select the optimal communication frequency for communication according to the distance between nodes, and the fault communication mode is to extend the communication distance by reducing the communication frequency.

4. The dynamic uncertain underwater intelligent Internet of Things node optimization and reconstruction method according to claim 3 is characterized in that: Initializing the sensor network to distinguish the node conditions of the corresponding network topology after initialization includes: After initialization, in the corresponding network topology, according to the communication mode configuration: Normal nodes that can normally receive and transmit information; A temporarily faulty node that can sense the surrounding physical environment but cannot send information to neighboring nodes; The class Temporarily Faulted Node for a node whose parent node has experienced a temporary fault.

5. The method for optimizing and reconstructing the dynamic uncertain underwater intelligent Internet of Things nodes according to claim 4, characterized in that: It also includes configuring corresponding node identifiers for different types of nodes in the network topology, and updating the corresponding node identifiers after the node status changes.

6. The dynamic uncertain underwater intelligent Internet of Things node optimization and reconstruction method according to claim 4, characterized in that: Marking the second node among the other nodes that cannot sense the neighboring node includes: marking the second node among the other nodes that cannot sense the neighboring node as a quasi-temporary fault node, switching the communication mode and sending information that the second node has become a temporary fault node to the child nodes of the second node.

7. The method for optimizing and reconstructing the dynamic uncertain underwater intelligent Internet of Things nodes according to claim 6, characterized in that: Also includes: After the child node of the second node receives the information that the second node has become a quasi-temporary fault node, it closes the connection response with other nodes and sends a connection request to the neighbor node of the child node. After the neighbor node of the child node responds, the child node marks the neighbor node of the child node as a parent node.

8. An intelligent Internet of Things system, characterized in that: The invention comprises a sensor network, wherein the sensor network comprises a plurality of Internet of Things nodes, and any Internet of Things node is provided with a processor and a memory, wherein a computer program is stored in the memory, and when the computer program is executed by the processor, the steps of the method for optimizing and reconstructing a dynamic uncertain underwater intelligent Internet of Things node as described in any one of claims 1 to 7 are jointly implemented.

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