5G + Internet of Things time slot allocation defect optimization method, system, equipment and medium
By using the 5G+ IoT time slot allocation disadvantage optimization method in industrial sensor networks, the problem that traditional prediction models are difficult to accurately predict the peak of data mutations in network security events is solved, and the security and stability of data transmission is achieved, ensuring the improvement of data accuracy and network performance.
Patent Information
- Application Number
- CN202411876038.5
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-12-19
- Publication Date
- 2025-04-04
AI Technical Summary
Traditional timing prediction models are difficult to accurately predict mutation peaks of network security event data, and there is a problem of information loss in processing non-stationary time series data.
The 5G+ IoT time slot allocation disadvantage optimization method is adopted, and the optimal line is determined by using the TSCH scheduling method in the industrial sensor network to allocate time slots, and the weight value of each line is calculated based on the heavy weighted balance strategy model. At the same time, the node shrinkage method is used to improve the transmission efficiency, and when the destination node receives the abnormal data, it performs extraction and analysis based on the time slot allocation abnormal characteristics.
It improves the security and stability of data transmission, ensures the accuracy of data acquisition by sensors, optimizes time slot allocation, and improves the performance and data diversity of the entire network.
Smart Images
Figure CN119767417A_ABST
Abstract
Description
Technical Field
[0001] The present invention relates to the field of network security technology, and specifically to a method, system, device and medium for optimizing the drawbacks of 5G+ Internet of Things time slot allocation. Background Art
[0002] Network security data judgment mainly refers to the use of scientific theories, methods and existing experience to judge and predict the development trend and harm of major security incidents found in the network system. It is an important stage of network security situation awareness and the main goal of network security situation awareness. To predict network security events, it is necessary to analyze potential and possible attack paths and predict attack paths based on the vulnerabilities of our network and system. Continuously learn new attack patterns, and reveal and understand the confusion and deception of attackers. In the current complex network security situation, the mutation peaks generated by network security event data may indicate important changes in the network situation. This is the key point of attention, but traditional time series prediction models are difficult to accurately predict mutation peaks. Moreover, when using traditional time series models to predict non-stationary time series data, how to convert data into a relatively stable time series data without losing its own information is always a difficult problem. Summary of the invention
[0003] The purpose of the present invention is to provide a method, system, device and medium for optimizing the drawbacks of 5G+IoT time slot allocation to improve data security and stability.
[0004] To achieve the above purpose, the technical solution provided by the present invention is:
[0005] The first aspect of the present application provides a method for optimizing the disadvantages of 5G+IoT time slot allocation, comprising the following steps:
[0006] In industrial sensor networks, the TSCH scheduling method is used to allocate time slots for transmission from source nodes to destination nodes;
[0007] Based on the weighted balance strategy model, the weights of the nodes along the way from the source node to the destination node of each route are calculated and the weight values are accumulated, and the route with the highest weight value is taken as the optimal route;
[0008] The nodes along the optimal route are grouped into a set, and the node contraction method is used to contract the nodes along the route and their neighboring nodes into a new node, thereby improving the transmission efficiency of the optimal route.
[0009] When the destination node receives abnormal transmission data, it checks the line and extracts and analyzes the abnormal features based on time slot allocation.
[0010] To optimize the above technical solutions, the specific measures taken also include:
[0011] In the reweighted balance strategy model, for a dataset with C categories, where category i∈[1,...,C] has N i samples, the weight wi of the category i is calculated as:
[0012]
[0013] Among them, θ is the adjustment factor for adjusting the difference between weights of different categories, θ ≥ 0;
[0014] When θ = 0, the loss function with the added weighting strategy is equivalent to the original loss function; as θ gradually increases, the loss function gradually shifts toward the tail category.
[0015] Furthermore, for a sample with label i, the corresponding weighted loss is Calculated as:
[0016]
[0017] Among them, x i is the model output logits of the sample in category i, softmax(x i ) is the predicted probability corresponding to the sample in category i.
[0018] Furthermore, the optimal route is composed of a set of nodes, and the node contraction method is used to contract the node and its neighboring nodes into a new node, specifically: the core node of the network is contracted, and the degree of cohesion of the network contraction is It is expressed as:
[0019]
[0020] Among them, d ij Represents node ν i With node ν j The shortest path length between them; n is the adjustment parameter.
[0021] Furthermore, node v i The importance index IMC(i) is expressed as:
[0022]
[0023] in, Indicates that the node v i The cohesion of the network obtained after shrinkage.
[0024] When the destination node receives abnormal transmission data, it checks the line and extracts and analyzes abnormal features based on time slot allocation, including: using intelligent models and safety indicators to check the optimal line and eliminate relevant abnormal features.
[0025] When troubleshooting lines, use CIO control threads to reduce channel switching.
[0026] The second aspect of the present application provides a 5G+IoT time slot allocation disadvantage optimization system, including:
[0027] A time slot allocation module is used to allocate time slots for transmission from a source node to a destination node using a TSCH scheduling method in an industrial sensor network;
[0028] The re-weighting module is used to calculate the weights of the nodes along the way from the source node to the destination node of each line based on the re-weighting balance strategy model, and then accumulate the weight values, and take the line with the highest weight value as the optimal line;
[0029] The node contraction module is used to form a set of nodes along the optimal route, and use the node contraction method to contract the nodes along the route and their neighboring nodes into a new node, thereby improving the transmission efficiency of the optimal route.
[0030] The abnormal data troubleshooting module is used to check the line when the destination node receives abnormal transmission data, and to extract and analyze the abnormal characteristics based on time slot allocation;
[0031] The third aspect of the present application provides an electronic device, comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, the method for optimizing the disadvantages of 5G+IoT time slot allocation as described above is implemented.
[0032] The fourth aspect of the present application provides a computer-readable storage medium storing a computer program, wherein the computer program enables a computer to execute the 5G+IoT time slot allocation disadvantage optimization method as described above.
[0033] Compared with the prior art, the present invention has the following beneficial effects:
[0034] The present invention aims at the deficiency of real-time sensor network time slot allocation in the deep integration process of wireless communication and artificial intelligence technology. Firstly, the TSCH scheduling method is adopted in the industrial sensor network to allocate time slots for transmission from the source node to the destination node. During the data transmission process of the industrial sensor network, nodes with poor channel conditions may obtain fewer time slots. This unfair allocation method may affect the performance of the entire network and the diversity of data. At the same time, the network complexity also increases the network cost. The present invention adopts a balanced strategy model based on re-weighting to calculate the weights of the path nodes between each source node and the destination node, and then accumulates the weight values to obtain the optimal route. After the path nodes of the optimal route are formed into a set, the node and its neighboring nodes are shrunk into a new node by the node contraction method, so as to further improve the transmission efficiency of the optimal route. If the destination node receives abnormal transmission data, the route is checked, and the abnormal data that may exist is extracted and analyzed based on the abnormal characteristics of time slot allocation, so as to ensure the accuracy of the sensor collection data. BRIEF DESCRIPTION OF THE DRAWINGS
[0035] Figure 1 : Flow chart of the 5G+IoT time slot allocation disadvantage optimization method of the present invention.
[0036] Figure 2 : Schematic diagram of node scheduling strategy in an embodiment of the present invention. DETAILED DESCRIPTION
[0037] The above contents of the present invention are further described in detail below in the form of embodiments, but this should not be understood as the scope of the above subject matter of the present invention being limited to the following embodiments, and all technologies realized based on the above contents of the present invention belong to the scope of the present invention.
[0038] Some of the terms involved in the solution of the present invention are explained as follows:
[0039] Timeslot: The smallest unit of circuit-switched aggregate information transmission.
[0040] In one embodiment of the present invention, a method for optimizing the drawbacks of 5G+IoT time slot allocation is proposed, and the flow chart is as follows: Figure 1 As shown, the whole method includes the following steps:
[0041] In industrial sensor networks, the TSCH scheduling method is used to allocate time slots for transmission from source nodes to destination nodes;
[0042] Based on the weighted balance strategy model, the weights of the nodes along the way from the source node to the destination node of each route are calculated and the weight values are accumulated, and the route with the highest weight value is taken as the optimal route;
[0043] The nodes along the optimal route are grouped into a set, and the node contraction method is used to contract the nodes along the route and their neighboring nodes into a new node, thereby improving the transmission efficiency of the optimal route.
[0044] When the destination node receives abnormal transmission data, it checks the line and extracts and analyzes the abnormal features based on time slot allocation.
[0045] In the reweighted balanced strategy model, for a dataset with C categories, where category i∈[1,…,C] has N i samples, the weight wi of the category i is calculated as:
[0046]
[0047] Among them, θ is the adjustment factor for adjusting the difference between weights of different categories, θ ≥ 0;
[0048] When θ = 0, the loss function with the added weighting strategy is equivalent to the original loss function; as θ gradually increases, the loss function gradually shifts toward the tail category.
[0049] For a sample with label i, the corresponding weighted loss Calculated as:
[0050]
[0051] Among them, x i is the model output logits of the sample in category i, softmax(x i ) is the predicted probability corresponding to the sample in category i.
[0052] The nodes along the optimal route are grouped into a set, and the node contraction method is used to contract the nodes along the route and their neighboring nodes into a new node. Specifically, the core nodes of the network are contracted, and the degree of network contraction is It is expressed as:
[0053]
[0054] Among them, d ij Represents node ν i With node v j The shortest path length between them; n is the adjustment parameter.
[0055] Node v i The importance index IMC(i) is expressed as:
[0056]
[0057] in, Indicates that the node v i The cohesion of the network obtained after shrinkage.
[0058] When the destination node receives abnormal transmission data, it checks the line and extracts and analyzes abnormal features based on time slot allocation, including: using intelligent models and safety indicators to check the optimal line and eliminate related abnormal features.
[0059] When troubleshooting lines, use CIO control threads to reduce channel switching.
[0060] The technical solution of the present invention is further described in detail below in conjunction with specific embodiments:
[0061] like Figure 1 As shown in FIG. 1 , in a wireless network consisting of three nodes, the forwarding node B uses the TSCH-based scheduling method. If node B receives a data packet from node C at receiving unit R1 (superframe 1), node B needs to wait for two units before sending unit T1 (superframe 1) to forward the data from node C to node A. The delay between the two units is shown in FIG. Figure 1 Similarly, if Node B receives a data packet at receiving unit R2 (superframe 1), it needs to wait for 7 units to forward the data at receiving unit T1 (superframe 2), where the delay of 7 units is Figure 2 .
[0062] The upper limit of the number of time slots required for all data to be transmitted from the source node to the destination node (the upper limit of the delay) is very important for delay-sensitive industrial applications. In the tree topology, the minimum scheduling length is max(2n k -1, N), where n k is the maximum number of nodes in any subtree, and N is the number of source nodes. The scheduling method must provide an appropriate time slot allocation for each data flow, taking into account the link quality of the destination node path; otherwise, the node may not have a time slot for transmission when it needs to forward a data packet.
[0063] The buffer occupancy rate has a great relationship with real-time performance and reliability. When the media access control delay is large, the possibility of buffer overflow at the forwarding node will also increase. Figure 2 In the network topology and scheduling method shown, if node B receives data packets between two consecutive receiving units (R1 and R2), node B will store two data packets before the next sending unit (T1 and T2) arrives; if the buffer is very small, some data packets will have to be discarded. Although the transmission process is reliable, the entire system is unreliable.
[0064] In another embodiment, the present invention proposes a 5G+IoT time slot allocation disadvantage optimization system, including:
[0065] A time slot allocation module is used to allocate time slots for transmission from a source node to a destination node using a TSCH scheduling method in an industrial sensor network;
[0066] The re-weighting module is used to calculate the weights of the nodes along the way from the source node to the destination node of each line based on the re-weighting balance strategy model, and then accumulate the weight values, and take the line with the highest weight value as the optimal line;
[0067] The node contraction module is used to form a set of nodes along the optimal route, and use the node contraction method to contract the nodes along the route and their neighboring nodes into a new node, thereby improving the transmission efficiency of the optimal route.
[0068] The abnormal data troubleshooting module is used to check the line when the destination node receives abnormal transmission data, and to extract and analyze the abnormal characteristics based on time slot allocation;
[0069] In another embodiment, the present invention proposes an electronic device, comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the above-mentioned method for optimizing the disadvantages of 5G+IoT time slot allocation is implemented.
[0070] In another embodiment, the present invention proposes a computer-readable storage medium storing a computer program, wherein the computer program enables a computer to execute the above-mentioned method for optimizing the disadvantages of 5G+IoT time slot allocation.
[0071] In the embodiments disclosed in the present application, the computer storage medium can be a tangible medium that can contain or store a program for use by or in conjunction with an instruction execution system, device or equipment. The computer storage medium can include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices or equipment, or any suitable combination of the above. More specific examples of computer storage media can include electrical connections based on one or more lines, portable computer disks, hard disks, random access memories (RAM), read-only memories (ROM), erasable programmable read-only memories (EPROM or flash memory), optical fibers, portable compact disk read-only memories (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the above.
[0072] The above description is only a preferred embodiment of the present invention and does not limit the present invention in any form. Any technician familiar with the profession, without departing from the scope of the technical solution of the present invention, according to the technical essence of the present invention, any simple modification, equivalent replacement and improvement made to the above embodiment still falls within the protection scope of the technical solution of the present invention.
Claims
1. A method for optimizing the drawbacks of 5G+IoT time slot allocation, characterized in that: The following steps are involved: In industrial sensor networks, the TSCH scheduling method is used to allocate time slots for transmission from source nodes to destination nodes; Based on the weighted balance strategy model, the weights of the nodes along the way from the source node to the destination node of each route are calculated and the weight values are accumulated, and the route with the highest weight value is taken as the optimal route; The nodes along the optimal route are grouped into a set, and the node contraction method is used to contract the nodes along the route and their neighboring nodes into a new node, thereby improving the transmission efficiency of the optimal route. When the destination node receives abnormal transmission data, it checks the line and extracts and analyzes the abnormal features based on time slot allocation.
2. The 5G+IoT time slot allocation optimization method according to claim 1 is characterized in that: In the reweighted balance strategy model, for a dataset with C categories, where category i∈[1,…,C] has N i samples, the weight wi of the category i is calculated as: Among them, θ is the adjustment factor for adjusting the difference between weights of different categories, θ ≥ 0; When θ = 0, the loss function with the added weighting strategy is equivalent to the original loss function; as θ gradually increases, the loss function gradually shifts toward the tail category.
3. The 5G+IoT time slot allocation optimization method according to claim 2 is characterized in that: For a sample with label i, the corresponding weighted loss Calculated as: Among them, x i is the model output logits of the sample in category i, softmax(x i ) is the predicted probability corresponding to the sample in category i.
4. The 5G+IoT time slot allocation optimization method according to claim 3 is characterized in that: The optimal route is composed of a set of nodes, and the node contraction method is used to contract the node and its neighboring nodes into a new node, specifically: contracting the core nodes of the network, and the degree of network contraction It is expressed as: Among them, d ij Represents node v i With node v j The shortest path length between them; n is the adjustment parameter.
5. The 5G+IoT time slot allocation optimization method according to claim 4 is characterized in that: Node v i The importance index IMC(i) is expressed as: in, Indicates that the node ν i The cohesion of the network obtained after shrinkage.
6. The 5G+IoT time slot allocation optimization method according to claim 1 is characterized in that: When the destination node receives abnormal transmission data, it checks the line and extracts and analyzes abnormal features based on time slot allocation, including: using intelligent models and safety indicators to check the optimal line and eliminate relevant abnormal features.
7. The 5G+IoT time slot allocation optimization method according to claim 1 or 6, characterized in that: When troubleshooting lines, use CIO control threads to reduce channel switching.
8. A 5G+IoT time slot allocation optimization system, characterized in that: include: A time slot allocation module is used to allocate time slots for transmission from a source node to a destination node using a TSCH scheduling method in an industrial sensor network; The re-weighting module is used to calculate the weights of the nodes along the way from the source node to the destination node of each line based on the re-weighting balance strategy model, and then accumulate the weight values, and take the line with the highest weight value as the optimal line; The node contraction module is used to form a set of nodes along the optimal route, and use the node contraction method to contract the nodes along the route and their neighboring nodes into a new node, thereby improving the transmission efficiency of the optimal route. The abnormal data troubleshooting module is used to check the line when the destination node receives abnormal transmission data, and to extract and analyze the abnormal characteristics based on time slot allocation; The system is used to execute the 5G+IoT time slot allocation disadvantage optimization method as described in any one of claims 1 to 7.
9. An electronic device, characterized in that: include: A memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the method for optimizing the disadvantages of 5G+IoT time slot allocation as described in any one of claims 1 to 7 is implemented.
10. A computer-readable storage medium storing a computer program, wherein the computer program enables a computer to execute the 5G+IoT time slot allocation disadvantage optimization method as described in any one of claims 1-7.