Path construction method and device, equipment, storage medium and program product

Abstract

The invention discloses a path construction method, apparatus and device, a storage medium and a program product, the method is applied to a control device in an Internet of Things network, and the specific technical scheme comprises the steps of obtaining a historical delivery probability between adjacent nodes in the Internet of Things network, and obtaining a data transmission request based on the historical delivery probability and preset data transmission demand information; determining a relay node between the source node and the destination node; constructing a routing path between the source node and the destination node by using the relay node; for each routing path, calculating a comprehensive trust value between adjacent nodes in the routing path; aiming at each routing path, taking the minimum value in the comprehensive trust values corresponding to the routing path as the path trust value of the routing path; and taking the routing path with the maximum path trust value as a target routing path. Therefore, the node in the routing path with the maximum comprehensive trust value can forward the data sent by the source node in time, so that the data transmission time delay is effectively reduced.

Description

Technical Field

[0001] The present application belongs to the technical field of Internet of Things, and in particular, relates to a method, device, equipment, storage medium and program product for path construction. Background Art

[0002] In the IoT network, a node can determine its neighboring nodes through the service discovery protocol, and then the source node can determine the routing path from the source node to the destination node based on the neighboring nodes of each node.

[0003] However, due to the selfish nature of nodes in IoT networks, nodes tend to prioritize their own performance in terms of resource utilization and information transmission, resulting in large data transmission delays in IoT networks. Summary of the invention

[0004] The embodiments of the present application provide a method, apparatus, device, storage medium, and program product for path construction, which can reduce the data transmission delay of an Internet of Things network.

[0005] In a first aspect, an embodiment of the present application provides a method for path construction, which is applied to a control device in an Internet of Things network, and the method includes:

[0006] Acquire a historical delivery probability between adjacent nodes in the Internet of Things network, where the historical delivery probability indicates a possibility of data transmission between adjacent nodes in the Internet of Things network;

[0007] Determining a relay node between a source node and a destination node based on the historical delivery probability and preset data transmission demand information;

[0008] constructing a routing path between the source node and the destination node using the relay node;

[0009] For each routing path, calculating a comprehensive trust value between adjacent nodes in the routing path, wherein the comprehensive trust value is used to characterize the security level between adjacent nodes in the routing path;

[0010] For each routing path, taking the minimum value of the comprehensive trust values ​​corresponding to the routing path as the path trust value of the routing path;

[0011] The routing path with the largest path trust value is used as the target routing path.

[0012] In a possible implementation, determining a relay node between a source node and a destination node based on the historical delivery probability and preset data transmission requirement information includes:

[0013] Based on the historical delivery probability, calculating the delivery probability between the source node and a target node in the Internet of Things network other than the source node;

[0014] For each target node, the target node whose delivery probability is greater than a preset probability threshold is used as the first relay node corresponding to the source node;

[0015] For each target node, a target relay node that meets the preset data transmission requirement information is determined from the neighboring nodes of the target node.

[0016] In a possible implementation manner, before calculating the delivery probability between the source node and a target node other than the source node in the Internet of Things network based on the historical delivery probability, the method further includes:

[0017] Obtaining movement information of each node in the Internet of Things network;

[0018] For each node, determining a movement trend of the node according to the movement information;

[0019] Determining whether the node is within the message sending range of the source node according to the movement trend of the node;

[0020] Taking nodes within the message sending range of the source node as range nodes;

[0021] The calculating, based on the historical delivery probability, the delivery probability between the source node and a target node other than the source node in the Internet of Things network includes:

[0022] Based on the historical delivery probabilities, a delivery probability between the source node and the range nodes is calculated.

[0023] In a possible implementation, the calculating, based on the historical delivery probability, the delivery probability between the source node and a target node other than the source node in the Internet of Things network includes:

[0024] For each target node, when the target node is a direct node, the delivery probability between the source node and the direct node is calculated using a first preset algorithm and the historical delivery probability, where the direct node refers to a node that directly receives a data packet from the source node;

[0025] For each target node, when the target node is a transmission node, the delivery probability between the source node and the transmission node is calculated using a second preset algorithm and the historical delivery probability. The transmission node refers to a node that forwards the data packet of the source node through a node other than the transmission node in the Internet of Things network.

[0026] In a possible implementation, when the target node is a direct node, calculating the delivery probability between the source node and the direct node by using a first preset algorithm and the historical delivery probability includes:

[0027] Obtain the historical communication time and local time of the historical communication behavior of the direct node;

[0028] Calculate the time difference between the historical communication time and the local time;

[0029] In the case where the time difference is greater than a preset time threshold, a third preset algorithm and the historical delivery probability are used to calculate the delivery probability between the source node and the direct node.

[0030] In a possible implementation manner, after calculating the time difference between the historical communication time and the local time, the method further includes:

[0031] When the time difference is less than or equal to the preset time threshold, the delivery probability between the source node and the direct node is calculated using a fourth preset algorithm and the historical delivery probability.

[0032] In a possible implementation manner, determining a target relay node that meets the preset data transmission requirement information from neighboring nodes of the target node includes:

[0033] Get the parameter values ​​of the preset indicators;

[0034] Taking nodes whose parameter values ​​of the preset indicators meet the preset data transmission requirement information as candidate relay nodes;

[0035] Acquire historical interaction record information of the candidate relay node from a dynamic matrix, wherein the historical interaction record information includes the number of historical interactions and historical delivery probabilities between the candidate relay node and other nodes in the Internet of Things network except the candidate relay node;

[0036] For each candidate relay node, determine the forwarding probability according to the historical number of interactions or the historical delivery probability corresponding to the candidate relay node;

[0037] For each candidate relay node, the candidate relay node whose forwarding probability is greater than a preset probability threshold is used as the target relay node.

[0038] In a possible implementation manner, the calculating the comprehensive trust value between adjacent nodes in the routing path includes:

[0039] A historical trust value between adjacent nodes in the routing path is calculated based on historical interaction record information between adjacent nodes in the routing path, where the historical trust value is used to characterize the probability of successful data interaction between adjacent nodes in the routing path;

[0040] For each node in the routing path, the credibility score of the neighboring nodes of the node is calculated according to the historical interaction record information;

[0041] For each node in the routing path, calculating the difference between the credibility scores of the adjacent nodes to obtain the evaluation difference;

[0042] For each node in the routing path, according to the preset correspondence between the evaluation difference and the indirect trust value, determine the indirect trust value corresponding to the node, the indirect trust value is used to characterize the probability of successful data interaction between adjacent nodes in the routing path;

[0043] A comprehensive trust value between adjacent nodes in the routing path is calculated based on the historical trust value and the indirect trust value.

[0044] In a possible implementation, the calculating, according to the historical interaction records between the adjacent nodes in the routing path, the historical trust values ​​between the adjacent nodes in the routing path includes:

[0045] The historical trust value between adjacent nodes in the routing path is calculated according to the following formula:

[0046]

[0047] Among them, DT (i,j) represents the historical trust value between node i and node j, w represents the preset reward and punishment factor, r (t) represents the number of historical positive feedbacks from node i to node j at time t, s (t) represents the number of historical negative feedbacks from the node i to the node j at time t;

[0048]

[0049] in, is the time t i The time decay factor on Indicates the historical interaction success time in the historical interaction record;

[0050]

[0051] in, is the time t i The time decay factor on Indicates the historical interaction failure time in the historical interaction record.

[0052] In a possible implementation, the calculating based on the historical trust value and the indirect trust value to obtain a comprehensive trust value between adjacent nodes in the routing path includes:

[0053] The comprehensive trust value between adjacent nodes in the routing path is calculated according to the following formula:

[0054] CT (i,j) =ηDT (i,j) +(1-η)RT (i,j)

[0055] Among them, CT (i,j) represents the comprehensive trust value between the node i and the node j, η represents the preset weight, RT (i,j) Represents the indirect trust value between the node i and the node j.

[0056] In a second aspect, an embodiment of the present application provides a path construction device, which is applied to a control device in an Internet of Things network, and the device includes:

[0057] An acquisition module, used to acquire the historical delivery probability between adjacent nodes in the IoT network, where the historical delivery probability indicates the possibility of data transmission between adjacent nodes in the IoT network;

[0058] A determination module, used to determine a relay node between a source node and a destination node based on historical delivery probabilities and preset data transmission demand information;

[0059] A construction module, used to construct a routing path between a source node and a destination node using a relay node;

[0060] A calculation module, used to calculate, for each routing path, a comprehensive trust value between adjacent nodes in the routing path, where the comprehensive trust value is used to characterize the security level between adjacent nodes in the routing path;

[0061] A determination module, configured to use, for each routing path, a minimum value among the comprehensive trust values ​​corresponding to the routing path as the path trust value of the routing path;

[0062] The determination module is also used to take the routing path with the largest path trust value as the target routing path.

[0063] In a fourth aspect, an embodiment of the present application provides an electronic device, the device comprising: a processor and a memory storing computer program instructions;

[0064] When the processor executes the computer program instructions, the path construction method as described in any one of the first aspects is implemented.

[0065] In a fifth aspect, an embodiment of the present application provides a computer-readable storage medium, on which computer program instructions are stored. When the computer program instructions are executed by a processor, the path construction method as described in any one of the first aspects is implemented.

[0066] In a sixth aspect, an embodiment of the present application provides a computer program product. When instructions in the computer program product are executed by a processor of an electronic device, the electronic device executes the path construction method as described in any one of the first aspects.

[0067] A method, device, equipment, storage medium and program product for path construction in an embodiment of the present application obtains the historical delivery probability between adjacent nodes in an Internet of Things network, and then determines the relay node between the source node and the destination node based on the historical delivery probability and preset data transmission demand information. The routing path between the source node and the destination node is constructed using the relay node. On the basis of the constructed routing path, the comprehensive trust value between the adjacent nodes in each routing path is calculated, wherein the comprehensive trust value is used to characterize the security between the adjacent nodes in the routing path, that is, to measure whether the nodes in the routing path can forward the data sent by the source node in a timely manner. After obtaining the comprehensive trust value of each routing path, the routing path with the largest comprehensive trust value is used as the target routing path. In this way, the nodes in the routing path with the largest comprehensive trust value can forward the data sent by the source node in a timely manner, thereby effectively reducing the data transmission delay. BRIEF DESCRIPTION OF THE DRAWINGS

[0068] In order to more clearly illustrate the technical solution of the embodiments of the present application, the following is a brief introduction to the drawings required for use in the embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0069] Figure 1 is an exemplary schematic diagram of an Internet of Things network architecture provided by an embodiment of the present application;

[0070] Figure 2 It is a flowchart of a method for path construction provided in an embodiment of the present application;

[0071] Figure 3 It is a flowchart of a method for determining a target relay node provided by an embodiment of the present application;

[0072] Figure 4 is an exemplary schematic diagram of a method for calculating a delivery probability provided in an embodiment of the present application;

[0073] Figure 5It is a flowchart of a method for determining a target relay node provided by an embodiment of the present application;

[0074] Figure 6 is an exemplary schematic diagram of another Internet of Things network architecture provided in an embodiment of the present application;

[0075] Figure 7 is an exemplary schematic diagram of a routing path provided in an embodiment of the present application;

[0076] Figure 8 It is a flowchart of a method for calculating a comprehensive trust value provided by an embodiment of the present application;

[0077] Fig. 9 is an exemplary schematic diagram of a path construction method provided in an embodiment of the present application;

[0078] Fig.10 It is a structural schematic diagram of a path construction device provided in an embodiment of the present application;

[0079] Fig.11 It is a structural schematic diagram of an electronic device provided in yet another embodiment of the present application. DETAILED DESCRIPTION

[0080] The features and exemplary embodiments of various aspects of the present application will be described in detail below. In order to make the purpose, technical solutions and advantages of the present application clearer, the present application will be further described in detail below in conjunction with the accompanying drawings and specific embodiments. It should be understood that the specific embodiments described herein are only intended to explain the present application, rather than to limit the present application. For those skilled in the art, the present application can be implemented without the need for some of these specific details. The following description of the embodiments is only to provide a better understanding of the present application by illustrating the examples of the present application.

[0081] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, 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 other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the statement "include..." do not exclude the presence of other identical elements in the process, method, article or device including the elements.

[0082] At present, when determining the routing path, the source node in the IoT network usually determines the relay node based on the current adjacent nodes, that is, the distance between the IoT node and the source node is calculated, and the node with a distance less than the preset distance threshold is used as the relay node of the source node. Figure 1 As shown, Figure 1 An exemplary schematic diagram of an Internet of Things network provided in this application, Figure 1 Multiple nodes are shown in the figure. Among them, the source node calculates that the relay nodes whose distance is less than the preset distance threshold are node A, node B and node C. In this way, since the position of each node in the IoT network is changing, after the source node determines the routing path, the relay node in the routing path may move into the message sending range of the source node, resulting in the relay node being unable to receive the data sent by the source node, resulting in data transmission failure.

[0083] In order to solve the problems existing in the prior art, the embodiments of the present application provide a method, apparatus, device, storage medium and program product for data synchronization. Figure 2 A method for path construction provided in an embodiment of the present application is introduced. The method is applied to control devices in an Internet of Things network, such as Figure 2 As shown, the method includes:

[0084] S201. Obtain historical delivery probabilities between adjacent nodes in an Internet of Things network.

[0085] Among them, the historical delivery probability represents the possibility of data transmission between adjacent nodes in the IoT network.

[0086] Specifically, the initial delivery probability between adjacent nodes is a preset initial value. After the control device calculates the delivery probability, the delivery probability is stored locally. When the control device calculates the delivery probability again, the delivery probability calculated last time is used as the historical delivery probability to calculate the delivery probability between the current adjacent nodes.

[0087] The method for calculating the delivery probability is described in detail in the subsequent embodiments.

[0088] S202: Determine a relay node between a source node and a destination node based on historical delivery probabilities and preset data transmission demand information.

[0089] The preset data transmission requirement information refers to the requirement that the node itself meets when transmitting data. The preset data transmission requirement information is preset according to the actual business scenario.

[0090] For example, the data transmission requirement information may be power requirement information or buffer space requirement information. When the parameters of the node itself meet the power requirement information or buffer space requirement information, the data can be smoothly forwarded.

[0091] It should be noted that the embodiments of the present application do not limit the preset data transmission requirement information.

[0092] S203: Use the relay node to construct a routing path between the source node and the destination node.

[0093] There may be multiple relay nodes, and the control device determines all routing paths between the source node and the destination node based on the calculated relay nodes in an exhaustive manner.

[0094] S204: For each routing path, calculate the comprehensive trust value between adjacent nodes in the routing path.

[0095] Among them, the comprehensive trust value is used to characterize the security level between adjacent nodes in the routing path.

[0096] It can be understood that the higher the comprehensive trust value is, the greater the possibility that the adjacent node corresponding to the comprehensive trust value can successfully complete the data transmission.

[0097] S205 . For each routing path, take the minimum value of the comprehensive trust values ​​corresponding to the routing path as the path trust value of the routing path.

[0098] It can be understood that each routing path includes multiple nodes, and for two adjacent nodes in the routing path, a comprehensive trust value can be calculated, that is, each routing path corresponds to multiple comprehensive trust values. The security of each routing path is determined by the minimum comprehensive trust value, so the minimum value of the comprehensive trust value corresponding to the routing path is used as the path trust value of the routing path.

[0099] In one example, the routing path is: source node - node 1 - node 2 - node 3 - node 4, the calculated comprehensive trust value between the source node and node 1 is 0.6, the comprehensive trust value between node 1 and node 2 is 0.5, the comprehensive trust value between node 2 and node 3 is 0.3, and the comprehensive trust value between node 3 and node 4 is 0.5. Then the path trust value corresponding to the routing path is min{0.6, 0.5, 0.3, 0.5}=0.3.

[0100] S206: Use the routing path with the largest path trust value as the target routing path.

[0101] The above method is used to obtain the historical delivery probability between adjacent nodes in the Internet of Things network, and then the relay node between the source node and the destination node is determined based on the historical delivery probability and the preset data transmission demand information. The routing path between the source node and the destination node is constructed using the relay node. On the basis of the constructed routing path, the comprehensive trust value between the adjacent nodes in each routing path is calculated, wherein the comprehensive trust value is used to characterize the security between the adjacent nodes in the routing path, that is, to measure whether the nodes in the routing path can forward the data sent by the source node in a timely manner. After obtaining the comprehensive trust value of each routing path, the routing path with the largest comprehensive trust value is used as the target routing path. In this way, the nodes in the routing path with the largest comprehensive trust value can forward the data sent by the source node in a timely manner, thereby effectively reducing the data transmission delay.

[0102] In some embodiments of the present application, Figure 3 The method for determining a relay node provided in an embodiment of the present application is introduced, such as Figure 3 As shown, the above S202, determining the relay node between the source node and the destination node based on the historical delivery probability and the preset data transmission demand information, can be implemented as follows:

[0103] S2021. Based on the historical delivery probability, calculate the delivery probability between the source node and the target node other than the source node in the IoT network.

[0104] Among them, the control device can correct the delivery probability at the current moment according to the historical delivery probability, so as to obtain the delivery probability between the source node and the target node at the current moment.

[0105] S2022. For each target node, a target node whose delivery probability is greater than a preset probability threshold is used as the first relay node corresponding to the source node.

[0106] It can be understood that when the delivery probability is greater than the preset probability threshold, it means that the target node and the source node have a high possibility of data interaction. Therefore, the target node can be used as the first relay node of the source node.

[0107] S2023. For each target node, determine a target relay node that meets preset data transmission requirement information from the neighboring nodes of the target node.

[0108] By adopting the method provided in the embodiment of the present application, the delivery probability of the current source node and the target node is corrected using the historical delivery probability between the source node and the target node, thereby obtaining an accurate delivery probability. On the basis of the calculated delivery probability, the target node whose delivery probability is greater than the preset probability threshold is used as the first relay node of the source node. In this way, the possibility of data interaction between the first relay node and the source node is high, thereby improving the success rate of smooth data transmission. In addition, for each target node, the target relay node of the target node can be accurately determined using the preset data transmission requirement information, thereby ensuring smooth data transmission.

[0109] In order to reduce the workload of the control device, the nodes within the message sending range of the source node can be determined in advance in the IoT network, and then the relay nodes can be determined based on the nodes within the message sending range. Specifically, before the above S2021, based on the historical delivery probability, calculates the delivery probability between the source node and the target node other than the source node in the IoT network, the control device can obtain the movement information of each node in the IoT network. For each node, the movement trend of the node is determined based on the movement information; based on the movement trend of the node, it is determined whether the node is within the message sending range of the source node; the nodes within the message sending range of the source node are used as range nodes.

[0110] The movement information may be the movement direction, movement trajectory and movement speed. Based on the movement information, the control device can predict the movement trend of each node according to the target time for the source node to transmit data, and determine whether the node can be in the message sending range of the source node at the target time, thereby ensuring that the range node can receive the data sent by the source node and avoid data packet loss.

[0111] Accordingly, the above S2021, calculating the delivery probability between the source node and the target node other than the source node in the IoT network based on the historical delivery probability, can be implemented as follows:

[0112] Based on the historical delivery probabilities, the delivery probabilities between the source node and the range nodes are calculated.

[0113] In this way, the control node obtains the mobility information of each node in advance, and then uses Mobile Western Sydney to determine the mobility trend of the node. According to the mobility trend, it can be determined whether the node can move within the message sending range of the source node when the source node sends data. On this basis, the delivery probability of the range node and the source node is calculated for the range node. The calculation of the delivery probability of the source node and each node in the IoT network is avoided, thereby reducing the amount of calculation and improving work efficiency.

[0114] Specifically, when calculating the delivery probability between the source node and the target node, the method of calculating the delivery probability is different depending on the type of the target node, including the following two cases:

[0115] Case 1: For each target node, when the target node is a direct node, the delivery probability between the source node and the direct node is calculated using the first preset algorithm and the historical delivery probability.

[0116] The direct node refers to a node that directly receives data packets from the source node.

[0117] For example, the source node can directly send data to node A, node B and node C, then node A, node B and node C are direct nodes of the source node.

[0118] It should be noted that, when the target node is a direct node, the control device can also obtain the historical communication time and local time of the direct node's historical communication behavior; calculate the time difference between the historical communication time and the local time; and determine the method for calculating the delivery probability through the time difference.

[0119] When the time difference is greater than a preset time threshold, the delivery probability between the source node and the direct node is calculated using a third preset algorithm and historical delivery probabilities.

[0120] It is understandable that in actual application, if there is no communication between two nodes for a long time, the delivery probability between the two nodes will decrease. Therefore, the historical delivery probability is corrected by presetting the aging factor to ensure the accuracy of the calculation result.

[0121] Specifically, the control device may calculate the delivery probability using a third preset algorithm as shown in formula (1):

[0122] P (a,b) =P (a,b)old(t-1) *Y k +(1-(P (a,b)old(t-1) *Y k ))*P init Formula (1)

[0123] Among them, P (a,b)old(t-1) represents the historical delivery probability at time t-1. Y represents the preset aging factor, k represents the total number of unit times of historical communication time and local time, and P init are preset constants.

[0124] When the time difference is less than or equal to the preset time threshold, the fourth preset algorithm and the historical delivery probability are used to calculate the delivery probability between the source node and the direct node.

[0125] Specifically, the control device may calculate the delivery probability using a fourth preset algorithm as shown in formula (2):

[0126] P (a,b) =P(a,b)old +(1-P (a,b)old )*P init Formula (2)

[0127] Among them, P (a,b) represents the delivery probability between the source node and the node, P (a,b)old represents the historical delivery probability, P init Represents a preset constant.

[0128] In this way, the control device determines whether the source node and the target node have not communicated for a long time by calculating the time difference. The time difference can be used to indicate the trust level of the source node in the target node, that is, whether the target node can process the data sent by the source node in time. The faster the target node processes, the higher the trust level of the source node in the target node, and the smaller the time difference calculated above. Therefore, different calculation methods are used to calculate the delivery probability, thereby improving the accuracy of the calculation results.

[0129] Case 2: For each target node, when the target node is a delivery node, the delivery probability between the source node and the delivery node is calculated using the second preset algorithm and the historical delivery probability.

[0130] The transmission node refers to a node that forwards a data packet of a source node obtained through nodes other than the transmission node in the Internet of Things network.

[0131] For example, the source node needs to send data to node B first, and node B forwards the data to node D, so node D is the source node transmission node.

[0132] Specifically, the control device may calculate the delivery probability using a fourth preset algorithm as shown in formula (3):

[0133] P (a,c) =P (a,c)old +(1-P (a,c)old )*P (a,b) *P (b,c) *β Formula (3)

[0134] Among them, P (a,c) represents the delivery probability between the source node and the delivery node, P (a,c)old represents the historical delivery probability between the source node and the delivery node, P (a,b) represents the historical delivery probability of the previous node of the source node and the delivery node, P (b,c) represents the historical delivery probability of the transmission node and the previous node of the transmission node, and β represents the transmission influence factor.

[0135] By adopting the method provided in the embodiment of the present application, for different types of target nodes, when the target nodes are direct nodes or indirect nodes, different calculation methods are adopted to calculate the delivery probability between the source node and the target node, thereby improving the accuracy of the calculation results.

[0136] The following combination Figure 4 The process of controlling the calculation of delivery probabilities of direct nodes and transfer nodes is introduced, such as Figure 4 As shown, the method specifically includes:

[0137] S401: Determine that the target node is a direct node.

[0138] S402: Whether the source node and the direct node have historical communication behavior.

[0139] If yes, execute S404, if no, execute S403.

[0140] S403: Set the historical delivery probability to 0 and calculate the delivery probability.

[0141] Specifically, the above formula (2) is used to calculate the delivery probability.

[0142] S404: Whether the time difference between the communication time and the current time is greater than a preset non-communication time threshold.

[0143] If yes, execute S406, if no, execute S405.

[0144] Among them, the communication time is the historical communication time in the above embodiment, the time is the local time in the above embodiment, and the preset non-communication time threshold is the preset time threshold in the above embodiment.

[0145] S405: Calculate the delivery probability.

[0146] Specifically, the above formula (3) is used to calculate the delivery probability.

[0147] S406. Calculate the historical delivery probability after aging based on the historical delivery probability.

[0148] Specifically, the historical delivery probability after aging is calculated using the following formula:

[0149] P (a,b) =P (a,b)old(t-1) *Y k

[0150] S407: Calculate the delivery probability based on the historical delivery probability after aging.

[0151] Specifically, the above formula (1) is used to calculate the delivery probability.

[0152] In this way, the control device determines whether the source node and the target node have not communicated for a long time by calculating the time difference. The time difference can be used to indicate the trust level of the source node in the target node, that is, whether the target node can process the data sent by the source node in time. The faster the target node processes, the higher the trust level of the source node in the target node, and the smaller the time difference calculated above. Therefore, different calculation methods are used to calculate the delivery probability, thereby improving the accuracy of the calculation results.

[0153] In some embodiments of the present application, Figure 5 As shown, for the above S2023, for each target node, a target relay node that meets the preset data transmission requirement information is determined from the neighboring nodes of the target node, which can be specifically implemented as follows:

[0154] S501: Obtain parameter values ​​of preset indicators.

[0155] The preset indicator is preset based on experience and actual business scenarios. For example, the preset indicator may be an energy indicator or a buffer space indicator.

[0156] S502: Nodes whose parameter values ​​of preset indicators meet preset data transmission requirement information are selected as candidate relay nodes.

[0157] Continuing with the above example, when the preset indicators are an energy indicator and a buffer space indicator, when the parameter value corresponding to the energy indicator is greater than the preset energy threshold, and the parameter value corresponding to the buffer space indicator is greater than the data to be sent, the target node is used as a candidate relay node.

[0158] S503: Acquire historical interaction record information of the candidate relay nodes from the dynamic matrix.

[0159] The historical interaction record information includes the historical interaction times and historical delivery probabilities between the candidate relay node and other nodes in the IoT network except the candidate relay node. The dynamic matrix contains the historical interaction times and historical delivery probabilities.

[0160] Specifically, the dynamic matrix is ​​as follows:

[0161]

[0162] Among them, EC i (node1) represents the historical interaction record information between node i and node 1.

[0163] S504: For each candidate relay node, determine a forwarding probability according to the historical number of interactions or the historical delivery probability corresponding to the candidate relay node.

[0164] In one implementation, the control device directly uses the historical interaction times or the historical interaction probability as the forwarding probability of the candidate relay node.

[0165] In another implementation, the control device may sort the candidate relay nodes according to the number of historical interactions or the historical delivery probability, and determine the forwarding probability of each candidate relay node according to a preset corresponding relationship between the sorting and the forwarding probability.

[0166] S505 . For each candidate relay node, select a candidate relay node whose forwarding probability is greater than a preset probability threshold as a target relay node.

[0167] The preset probability threshold is preset based on experience.

[0168] According to the method provided in the embodiment of the present application, after determining the candidate relay nodes that meet the preset data transmission demand information using the parameter values ​​of the preset indicators, the historical interaction record information is obtained from the dynamic matrix, wherein the historical interaction record information includes the historical number of interactions and the historical delivery probability. The forwarding probabilities corresponding to the candidate relay nodes are statistically analyzed by the historical number of interactions and the historical delivery probability, so as to obtain the order of the forwarding probabilities between each candidate relay node, and thus the candidate relay nodes whose forwarding probabilities are greater than the preset probability threshold are used as the target relay nodes. In this way, the dynamic matrix is ​​used to perform a secondary screening of the candidate relay nodes, so as to obtain the target relay nodes with higher forwarding probabilities, thereby ensuring the success rate of data transmission in the Internet of Things network.

[0169] The following combination Figure 6 Introduce the method of building routing paths, such as Figure 6 As shown, Figure 6 An IoT network architecture is exemplarily shown, wherein the IoT network includes nodes A to K and a source node.

[0170] The control device calculates the first relay nodes in the range nodes as node B, node D and node E according to the above method for calculating the delivery probability, and then screens the adjacent nodes of node B, node D and node E according to the preset data transmission requirement information and historical interaction information records to obtain the second relay node corresponding to the first relay. The control device repeats the above steps of determining the second relay node to determine the third relay node to the Nth relay node.

[0171] The control device determines the relay node based on the above, and obtains the routing path between the source node and the destination node by exhaustive enumeration. Figure 7 As shown, Figure 7The connection relationship between the relay nodes is exemplarily shown. The control device constructs a routing path from the source node to the destination node K based on the connection relationship between the relay nodes, and obtains the following twelve routing paths, which are:

[0172] Routing path 1: source node—node B—node C—node H—node I—node K.

[0173] Routing path 2: source node—node B—node C—node H—node J—node K.

[0174] Routing path 3: source node—node B—node C—node G—node H—node I—node K.

[0175] Routing path 4: source node—node B—node C—node G—node H—node J—node K.

[0176] Routing path 5: source node—node D—node C—node H—node I—node K.

[0177] Routing path 6: source node—node D—node C—node H—node J—node K.

[0178] Routing path 7: source node—node D—node G—node H—node I—node K.

[0179] Routing path 8: source node—node D—node G—node H—node J—node K.

[0180] Routing path 9: source node—node E—node G—node H—node I—node K.

[0181] Routing path 10: source node—node E—node G—node H—node J—node K.

[0182] Routing path 11: source node—node E—node H—node I—node K.

[0183] Routing path 12: source node—node E—node H—node J—node K.

[0184] After constructing the routing path, the control device calculates the comprehensive trust value of the routing path using the historical trust value and the indirect trust value. Figure 8 As shown, the above S204, for each routing path, calculates the comprehensive trust value between adjacent nodes in the routing path, which can be specifically implemented as follows:

[0185] S2041. Calculate historical trust values ​​between adjacent nodes in the routing path according to historical interaction records between adjacent nodes in the routing path.

[0186] Among them, the historical trust value is used to characterize the probability of successful data interaction between adjacent nodes in the routing path.

[0187] Specifically, the historical trust value between adjacent nodes in the routing path is calculated according to the following formula (4):

[0188]

[0189] Among them, DT (i,j) represents the historical trust value between node i and node j, w represents the preset reward and punishment factor, r (t) represents the number of historical positive feedbacks from node i to node j at time t, s (t) Represents the number of historical negative feedbacks from node i to node j at time t. The number of historical positive feedbacks refers to the number of successful interactions, and the number of historical negative feedbacks refers to the number of failed interactions.

[0190]

[0191] in, is the time t i The time decay factor on Indicates the historical interaction success time in the historical interaction record information;

[0192]

[0193] in, is the time t i The time decay factor on Indicates the historical interaction failure time in the historical interaction record information.

[0194] S2042: For each node in the routing path, the credibility scores of the neighboring nodes of the node are calculated according to the historical interaction record information.

[0195] The credibility score is used to represent the degree of trust that the neighboring nodes have in the node. The higher the success rate of data transmission between the neighboring nodes and the node, the higher the credibility score. Conversely, the lower the success rate of data transmission between the neighboring nodes and the node, the lower the credibility score.

[0196] Specifically, the data transmission success rate can be calculated using the packet loss rate, bit error rate, etc., and then the node's credibility score is determined based on the preset correspondence between the data transmission success rate and the credibility score. It should be noted that the embodiment of the present application does not specifically limit the method for calculating the credibility score.

[0197] S2043: For each node in the routing path, calculate the difference between the credibility scores of adjacent nodes to obtain the evaluation difference.

[0198] S2044: For each node in the routing path, determine the indirect trust value corresponding to the node according to the preset corresponding relationship between the evaluation difference and the indirect trust value.

[0199] Among them, the indirect trust value is used to characterize the probability of successful data interaction between adjacent nodes in the routing path.

[0200] S2045. Calculate the comprehensive trust value between adjacent nodes in the routing path based on the historical trust value and the indirect trust value.

[0201] Specifically, the comprehensive trust value is calculated using formula (6):

[0202] CT (i,j) =ηDT (i,j) +(1-v)RT (i,j) Formula (6)

[0203] Among them, CT (i,j) represents the comprehensive trust value between node i and node j, η represents the preset weight, RT (i,j) Represents the indirect trust value between node i and node j.

[0204] The method provided in the embodiment of the present application is used to calculate the historical trust value between adjacent nodes based on the historical interaction record information, and then calculate the indirect trust value between adjacent nodes based on the difference in the evaluation of the target node by the adjacent nodes and the similarity of the recommended nodes. In this way, the comprehensive trust value between adjacent nodes is calculated from two dimensions: the historical interaction record information and the evaluation of the target node by other nodes, thereby improving the accuracy of the calculation result of the comprehensive trust value.

[0205] The following combination Fig. 9 A method for constructing a path provided in an embodiment of the present application is introduced, such as Fig. 9 As shown, the method specifically includes:

[0206] S901. Determine a first relay node based on the delivery probability between the source node and other nodes.

[0207] Among them, the other nodes are the target nodes in the above embodiment.

[0208] S902: Based on the first relay node, determine all neighboring nodes of the first relay node.

[0209] Specifically, the neighboring node is the candidate relay node in the above embodiment. The method for determining the candidate relay node is described in the above embodiment, and will not be described in detail here.

[0210] S903: Determine the forwarding probability of the neighboring nodes of the first relay node according to the number of contacts and historical delivery probabilities between each neighboring node of the first relay node and other nodes in the network.

[0211] The number of contacts is the number of historical interactions in the above embodiment.

[0212] S904: Select a node with a forwarding probability greater than 0 from the adjacent nodes of the first relay node to determine a routing path.

[0213] Specifically, in the embodiment of the present application, the preset probability threshold is 0. The method for controlling the device to construct a routing path is described in the above embodiment, which will not be repeated here.

[0214] S905 . Determine a comprehensive trust value of each routing path based on the trust value between each node in the routing path, and select a target routing path based on the comprehensive trust value.

[0215] By adopting the method provided in the embodiment of the present application, a statistical analysis is performed based on the number of contacts and the historical delivery probability to determine whether the adjacent nodes of the first relay node can provide data transmission services, thereby determining the target relay node, ensuring the success rate of smooth data transmission of the target relay node, thereby improving the data transmission performance of the Internet of Things network and reducing the data transmission delay. In addition, by calculating the comprehensive trust value between adjacent nodes in the routing path, the trust between nodes is taken into account, thereby filtering out selfish nodes, ensuring that data packets can be transmitted from the source node to the destination node, and reducing network delays.

[0216] Based on the same concept, the embodiment of the present application provides a path construction device, which is applied to a control device in an Internet of Things network, such as Fig.10 , the device comprises:

[0217] An acquisition module 1001 is used to acquire a historical delivery probability between adjacent nodes in the Internet of Things network, where the historical delivery probability indicates the possibility of data transmission between adjacent nodes in the Internet of Things network;

[0218] A determination module 1002, configured to determine a relay node between a source node and a destination node based on a historical delivery probability and preset data transmission requirement information;

[0219] A construction module 1003 is used to construct a routing path between a source node and a destination node using a relay node;

[0220] A calculation module 1004 is used to calculate, for each routing path, a comprehensive trust value between adjacent nodes in the routing path, where the comprehensive trust value is used to characterize the security level between adjacent nodes in the routing path;

[0221] A determination module 1002 is used to use, for each routing path, a minimum value among the comprehensive trust values ​​corresponding to the routing path as the path trust value of the routing path;

[0222] The determination module 1002 is further configured to use the routing path with the largest path trust value as the target routing path.

[0223] In a possible implementation, the determination module 1002 is specifically configured to:

[0224] Based on the historical delivery probability, the delivery probability between the source node and the target node other than the source node in the IoT network is calculated;

[0225] For each target node, the target node whose delivery probability is greater than a preset probability threshold is used as the first relay node corresponding to the source node;

[0226] For each target node, a target relay node that meets preset data transmission requirement information is determined from the neighboring nodes of the target node.

[0227] In a possible implementation, the device further includes:

[0228] The acquisition module 1001 is also used to obtain the movement information of each node in the Internet of Things network;

[0229] The prediction module is used to determine the movement trend of each node based on the movement information;

[0230] A judgment module, used to judge whether a node is within the message sending range of the source node according to the movement trend of the node;

[0231] A determination module 1002 is used to take nodes within the message sending range of the source node as range nodes;

[0232] The calculation module 1004 is specifically used for:

[0233] Based on the historical delivery probabilities, the delivery probabilities between the source node and the range nodes are calculated.

[0234] In a possible implementation, the calculation module 1004 is specifically configured to:

[0235] For each target node, when the target node is a direct node, the delivery probability between the source node and the direct node is calculated using the first preset algorithm and the historical delivery probability, where the direct node refers to a node that directly receives a data packet from the source node;

[0236] For each target node, when the target node is a transmission node, the delivery probability between the source node and the transmission node is calculated using the second preset algorithm and the historical delivery probability. The transmission node refers to a node that forwards the data packet of the source node through nodes other than the transmission node in the Internet of Things network.

[0237] In a possible implementation, the calculation module 1004 is specifically configured to:

[0238] Get the historical communication time and local time of the direct node's historical communication behavior;

[0239] Calculate the time difference between historical communication time and local time;

[0240] When the time difference is greater than a preset time threshold, the delivery probability between the source node and the direct node is calculated using a third preset algorithm and historical delivery probabilities.

[0241] In a possible implementation, the calculation module 1004 is specifically configured to:

[0242] When the time difference is less than or equal to the preset time threshold, the fourth preset algorithm and the historical delivery probability are used to calculate the delivery probability between the source node and the direct node.

[0243] In a possible implementation, the determining module 1002 is configured to:

[0244] Get the parameter values ​​of the preset indicators;

[0245] The nodes whose parameter values ​​of the preset indicators meet the preset data transmission requirement information are selected as candidate relay nodes;

[0246] Obtaining historical interaction record information of the candidate relay node from the dynamic matrix, the historical interaction record information including the historical interaction times and historical delivery probabilities between the candidate relay node and other nodes in the IoT network except the candidate relay node;

[0247] For each candidate relay node, determine the forwarding probability according to the historical number of interactions or historical delivery probability corresponding to the candidate relay node;

[0248] For each candidate relay node, a candidate relay node whose forwarding probability is greater than a preset probability threshold is used as a target relay node.

[0249] In a possible implementation, the calculation module 1004 is specifically configured to:

[0250] A historical trust value between adjacent nodes in the routing path is calculated based on historical interaction record information between adjacent nodes in the routing path, where the historical trust value is used to characterize the probability of successful data interaction between adjacent nodes in the routing path;

[0251] For each node in the routing path, the credibility score of the neighboring nodes of the node is calculated according to the historical interaction record information;

[0252] For each node in the routing path, calculating the difference between the credibility scores of the adjacent nodes to obtain the evaluation difference;

[0253] For each node in the routing path, according to the preset correspondence between the evaluation difference and the indirect trust value, determine the indirect trust value corresponding to the node, the indirect trust value is used to characterize the probability of successful data interaction between adjacent nodes in the routing path;

[0254] A comprehensive trust value between adjacent nodes in the routing path is calculated based on the historical trust value and the indirect trust value.

[0255] In a possible implementation, the calculation module 1004 is specifically configured to:

[0256] The historical trust value between adjacent nodes in the routing path is calculated according to the following formula:

[0257]

[0258] Among them, DT (i,j) represents the historical trust value between node i and node j, w represents the preset reward and punishment factor, r (t) represents the number of historical positive feedbacks from node i to node j at time t, s (t) Represents the number of historical negative feedbacks from node i to node j at time t;

[0259]

[0260] in, is the time t i The time decay factor on Indicates the historical interaction success time in the historical interaction record;

[0261]

[0262] in, is the time t i The time decay factor on Indicates the historical interaction failure time in the historical interaction records.

[0263] In a possible implementation, the calculation module 1004 is specifically configured to:

[0264] The comprehensive trust value between adjacent nodes in the routing path is calculated according to the following formula:

[0265] CT (i,j) =ηDT (i,j) +(1-η)RT (i,j)

[0266] Among them, CT (i,j) represents the comprehensive trust value between node i and node j, η represents the preset weight, RT (i,j) Represents the indirect trust value between node i and node j.

[0267] It should be noted that the device for path construction is a device corresponding to the method for application path construction described above, and all implementation methods in the above method embodiments are applicable to the embodiments of the device and can achieve the same technical effects.

[0268] Fig.11 A schematic diagram of the hardware structure of an electronic device provided in an embodiment of the present application is shown.

[0269] The electronic device may include a processor 1101 and a memory 1102 storing computer program instructions.

[0270] Specifically, the processor 1101 may include a central processing unit (CPU), or an application specific integrated circuit (ASIC), or may be configured to implement one or more integrated circuits of the embodiments of the present application.

[0271] The memory 1102 may include a large capacity memory for data or instructions. By way of example and not limitation, the memory 1102 may include a hard disk drive (HDD), a floppy disk drive, a flash memory, an optical disk, a magneto-optical disk, a magnetic tape, or a universal serial bus (USB) drive or a combination of two or more of these. In appropriate cases, the memory 1102 may include a removable or non-removable (or fixed) medium. In appropriate cases, the memory 1102 may be inside or outside the integrated gateway disaster recovery device. In a specific embodiment, the memory 1102 is a non-volatile solid-state memory.

[0272] The memory may include read-only memory (ROM), random access memory (RAM), magnetic disk storage media devices, optical storage media devices, flash memory devices, electrical, optical or other physical / tangible memory storage devices. Thus, typically, the memory includes one or more tangible (non-transitory) computer-readable storage media (e.g., memory devices) encoded with software including computer-executable instructions, and when the software is executed (e.g., by one or more processors), it is operable to perform the operations described with reference to the method according to an aspect of the present disclosure.

[0273] The processor 1101 implements any one of the file access methods in the above embodiments by reading and executing computer program instructions stored in the memory 1102 .

[0274] In one example, the electronic device may further include a communication interface 1103 and a bus 1104. Fig.11 As shown, the processor 1101, the memory 1102, and the communication interface 1103 are connected via a bus 1104 and communicate with each other.

[0275] The communication interface 1103 is mainly used to implement communication between various modules, devices, units and / or equipment in the embodiments of the present application.

[0276] Bus 1104 includes hardware, software or both, and the parts of electronic equipment are coupled to each other.For example, but not limitation, bus may include accelerated graphics port (AGP) or other graphics bus, enhanced industrial standard architecture (EISA) bus, front side bus (FSB), hypertransport (HT) interconnection, industrial standard architecture (ISA) bus, infinite bandwidth interconnection, low pin count (LPC) bus, memory bus, micro channel architecture (MCA) bus, peripheral component interconnection (PCI) bus, PCI-Express (PCI-X) bus, serial advanced technology attachment (SATA) bus, video electronics standard association local (VLB) bus or other suitable bus or two or more of these combinations. In appropriate cases, bus 1104 may include one or more buses. Although the present application embodiment describes and shows a specific bus, the application considers any suitable bus or interconnection.

[0277] In addition, in combination with the path construction method in the above embodiment, the embodiment of the present application can provide a computer storage medium for implementation. The computer storage medium stores computer program instructions; when the computer program instructions are executed by a processor, any one of the path construction methods in the above embodiment is implemented.

[0278] In combination with the path construction method in the above embodiments, an embodiment of the present application may provide a computer program product. When the instructions in the computer program product are executed by a processor of an electronic device, the electronic device executes any path construction method in the above embodiments.

[0279] It should be clear that the present application is not limited to the specific configuration and processing described above and shown in the figures. For the sake of simplicity, a detailed description of the known method is omitted here. In the above embodiments, several specific steps are described and shown as examples. However, the method process of the present application is not limited to the specific steps described and shown, and those skilled in the art can make various changes, modifications and additions, or change the order between the steps after understanding the spirit of the present application.

[0280] The functional blocks shown in the above-described block diagram can be implemented as hardware, software, firmware or a combination thereof. When implemented in hardware, it can be, for example, an electronic circuit, an application specific integrated circuit (ASIC), appropriate firmware, a plug-in, a function card, etc. When implemented in software, the elements of the present application are programs or code segments that are used to perform the required tasks. The program or code segment can be stored in a machine-readable medium, or transmitted on a transmission medium or a communication link by a data signal carried in a carrier wave. "Machine-readable medium" can include any medium capable of storing or transmitting information. Examples of machine-readable media include electronic circuits, semiconductor memory devices, ROM, flash memory, erasable ROM (EROM), floppy disks, CD-ROMs, optical disks, hard disks, optical fiber media, radio frequency (RF) links, etc. The code segment can be downloaded via a computer network such as the Internet, an intranet, etc.

[0281] It should also be noted that the exemplary embodiments mentioned in this application describe some methods or systems based on a series of steps or devices. However, this application is not limited to the order of the above steps, that is, the steps can be performed in the order mentioned in the embodiment, or in a different order from the embodiment, or several steps can be performed simultaneously.

[0282] Aspects of the present disclosure are described above with reference to the flowchart and / or block diagram of the method, device (system) and computer program product according to the embodiment of the present disclosure. It should be understood that each box in the flowchart and / or block diagram and the combination of each box in the flowchart and / or block diagram can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device to produce a machine so that these instructions executed by the processor of the computer or other programmable data processing device enable the implementation of the function / action specified in one or more boxes of the flowchart and / or block diagram. Such a processor can be, but is not limited to, a general-purpose processor, a special-purpose processor, a special application processor, or a field programmable logic circuit. It can also be understood that each box in the block diagram and / or flowchart and the combination of boxes in the block diagram and / or flowchart can also be implemented by dedicated hardware that performs a specified function or action, or can be implemented by a combination of dedicated hardware and computer instructions.

[0283] The above is only a specific implementation of the present application. Those skilled in the art can clearly understand that for the convenience and simplicity of description, the specific working processes of the systems, modules and units described above can refer to the corresponding processes in the aforementioned method embodiments, and will not be repeated here. It should be understood that the protection scope of the present application is not limited to this. Any technician familiar with the technical field can easily think of various equivalent modifications or replacements within the technical scope disclosed in this application, and these modifications or replacements should be included in the protection scope of this application.

Claims

1. A method for path construction, characterized in that: Applied to a control device in an Internet of Things network, the method comprises: Acquire a historical delivery probability between adjacent nodes in the Internet of Things network, where the historical delivery probability indicates a possibility of data transmission between adjacent nodes in the Internet of Things network; Determining a relay node between a source node and a destination node based on the historical delivery probability and preset data transmission demand information; constructing a routing path between the source node and the destination node using the relay node; For each routing path, calculating a comprehensive trust value between adjacent nodes in the routing path, wherein the comprehensive trust value is used to characterize the security level between adjacent nodes in the routing path; For each routing path, taking the minimum value of the comprehensive trust values ​​corresponding to the routing path as the path trust value of the routing path; The routing path with the largest path trust value is used as the target routing path.

2. The method according to claim 1, characterized in that The determining of a relay node between a source node and a destination node based on the historical delivery probability and preset data transmission requirement information includes: Based on the historical delivery probability, calculating the delivery probability between the source node and a target node in the Internet of Things network other than the source node; For each target node, the target node whose delivery probability is greater than a preset probability threshold is used as the first relay node corresponding to the source node; For each target node, a target relay node that meets the preset data transmission requirement information is determined from the neighboring nodes of the target node.

3. The method according to claim 2, characterized in that Before calculating the delivery probability between the source node and a target node other than the source node in the Internet of Things network based on the historical delivery probability, the method further includes: Obtaining movement information of each node in the Internet of Things network; For each node, determining a movement trend of the node according to the movement information; Determining whether the node is within the message sending range of the source node according to the movement trend of the node; Taking nodes within the message sending range of the source node as range nodes; The calculating, based on the historical delivery probability, the delivery probability between the source node and a target node other than the source node in the Internet of Things network includes: Based on the historical delivery probabilities, a delivery probability between the source node and the range nodes is calculated.

4. The method according to claim 2, characterized in that: The calculating, based on the historical delivery probability, the delivery probability between the source node and a target node other than the source node in the Internet of Things network includes: For each target node, when the target node is a direct node, the delivery probability between the source node and the direct node is calculated using a first preset algorithm and the historical delivery probability, where the direct node refers to a node that directly receives a data packet from the source node; For each target node, when the target node is a transmission node, the delivery probability between the source node and the transmission node is calculated using a second preset algorithm and the historical delivery probability. The transmission node refers to a node that forwards the data packet of the source node through a node other than the transmission node in the Internet of Things network.

5. The method according to claim 4, characterized in that When the target node is a direct node, calculating the delivery probability between the source node and the direct node by using a first preset algorithm and the historical delivery probability includes: Obtain the historical communication time and local time of the historical communication behavior of the direct node; Calculate the time difference between the historical communication time and the local time; In the case where the time difference is greater than a preset time threshold, a third preset algorithm and the historical delivery probability are used to calculate the delivery probability between the source node and the direct node.

6. The method according to claim 5, characterized in that After calculating the time difference between the historical communication time and the local time, the method further includes: When the time difference is less than or equal to the preset time threshold, the delivery probability between the source node and the direct node is calculated using a fourth preset algorithm and the historical delivery probability.

7. The method according to claim 2, characterized in that The determining, from the neighboring nodes of the target node, a target relay node that meets the preset data transmission requirement information includes: Get the parameter values ​​of the preset indicators; Taking nodes whose parameter values ​​of the preset indicators meet the preset data transmission requirement information as candidate relay nodes; Acquire historical interaction record information of the candidate relay node from a dynamic matrix, wherein the historical interaction record information includes the number of historical interactions and historical delivery probabilities between the candidate relay node and other nodes in the Internet of Things network except the candidate relay node; For each candidate relay node, determine the forwarding probability according to the historical number of interactions or the historical delivery probability corresponding to the candidate relay node; For each candidate relay node, the candidate relay node whose forwarding probability is greater than a preset probability threshold is used as the target relay node.

8. The method according to claim 1, characterized in that The calculating the comprehensive trust value between adjacent nodes in the routing path includes: A historical trust value between adjacent nodes in the routing path is calculated based on historical interaction record information between adjacent nodes in the routing path, where the historical trust value is used to characterize the probability of successful data interaction between adjacent nodes in the routing path; For each node in the routing path, the credibility score of the neighboring nodes of the node is calculated according to the historical interaction record information; For each node in the routing path, calculating the difference between the credibility scores of the adjacent nodes to obtain the evaluation difference; For each node in the routing path, according to the preset correspondence between the evaluation difference and the indirect trust value, determine the indirect trust value corresponding to the node, the indirect trust value is used to characterize the probability of successful data interaction between adjacent nodes in the routing path; A comprehensive trust value between adjacent nodes in the routing path is calculated based on the historical trust value and the indirect trust value.

9. The method according to claim 8, characterized in that The calculating, according to the historical interaction record information between the adjacent nodes in the routing path, the historical trust value between the adjacent nodes in the routing path includes: The historical trust value between adjacent nodes in the routing path is calculated according to the following formula: Among them, DT (i,j) represents the historical trust value between node i and node j, w represents the preset reward and punishment factor, r (t) represents the number of historical positive feedbacks from node i to node j at time t, s (t) represents the number of historical negative feedbacks from the node i to the node j at time t; in, is the time t i The time decay factor on Indicates the historical interaction success time in the historical interaction record; in, is the time t i The time decay factor on Indicates the historical interaction failure time in the historical interaction record.

10. The method according to claim 9, characterized in that The calculating based on the historical trust value and the indirect trust value to obtain the comprehensive trust value between the adjacent nodes in the routing path includes: The comprehensive trust value between adjacent nodes in the routing path is calculated according to the following formula: CT (i,j) =ηDT (i,j) +(1-n)RT (i,j) Among them, CT (i,j) represents the comprehensive trust value between the node i and the node j, η represents the preset weight, RT (i,j) Represents the indirect trust value between the node i and the node j.

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