Sensor bandwidth allocation method, system and device based on industrial internet of things

Abstract

This application discloses a sensor bandwidth allocation method, system, and device based on the Industrial Internet of Things (IIoT), relating to the technical field of IIoT. The method includes: acquiring the status information of each static sensor node, planning a movement path for a mobile relay device based on the status information, configuring a dedicated channel for the mobile relay device, and determining a reference service time window; during movement, generating a channel trigger command based on the real-time location and real-time movement speed of the mobile relay device and the reference service time window of the target service segment; generating a global network time slot scheduling strategy based on the activation timing of the dedicated channel; distributing the global time slot scheduling strategy to the static sensor nodes, and distributing the movement path and the reference service time window to the mobile relay device. This application improves the accuracy of response to spatially dynamic unbalanced loads.

Description

Technical Field

[0001] This application relates to the technical field of industrial Internet of Things (IIoT), and in particular to sensor bandwidth allocation methods, systems, and devices based on IIoT. Background Technology

[0002] In Industrial Internet of Things (IIoT) systems, a large number of static sensor nodes are widely deployed to monitor the environment, equipment status, or production processes. These nodes transmit the collected data back to the aggregation node via a wireless network. However, due to the inherent characteristics of the monitored targets and events, the amount of data (i.e., workload) generated by nodes in different geographical areas at different times varies significantly and dynamically, resulting in an uneven distribution of network load in space.

[0003] Faced with such spatially dynamic and unbalanced service loads, existing mainstream bandwidth allocation methods, such as time division multiple access (TDMA) or polling mechanisms based on fixed periods, typically employ static / semi-static resource allocation strategies with pre-set or long adjustment periods. These strategies cannot perceive and respond to changes in load across the spatial dimension in real time. Their inherent flaws lead to two coexisting consequences: in low-load areas, a large amount of pre-allocated channel resources (time slots) remain idle, resulting in wasted spectrum resources; in high-load areas, fixed resource quotas cannot meet sudden or continuous data transmission demands, causing data congestion, increased transmission latency, and decreased reliability. Although some improved schemes exist that dynamically schedule based on node requests, most focus on local or single-node needs, lacking global perception and collaborative optimization capabilities regarding the status of all network nodes (such as geographical location, data urgency, queue length, etc.). Therefore, they cannot fundamentally solve the overall network performance bottleneck caused by spatial load imbalance at the system level. Summary of the Invention

[0004] To improve the accuracy of response to spatially dynamic unbalanced loads, this application provides a sensor bandwidth allocation method, system, and device based on the Industrial Internet of Things.

[0005] Firstly, this application provides a sensor bandwidth allocation method based on the Industrial Internet of Things, employing the following technical solution: A sensor bandwidth allocation method based on the Industrial Internet of Things (IIoT) is used in an IIoT system. The IIoT system includes a management platform, a sensor network platform, and an object platform that are sequentially connected in communication. The object platform includes a aggregation node, multiple static sensor nodes, and at least one mobile relay device. The method is executed by the object platform and includes: The status information of each static sensor node is obtained, and a mobile path is planned for the mobile relay device based on the status information. A dedicated channel independent of the common channel is configured for the mobile relay device. The mobile path is divided into multiple consecutive service segments. Each service segment is associated with a group of target static sensor nodes to be served. The reference service time window of each service segment is determined based on a preset reference speed. During the movement, based on the real-time location and real-time movement speed of the mobile relay device, and according to the reference service time window of the target service segment, a channel triggering command is generated to activate the dedicated channel when the mobile relay device enters the target service segment. Based on the activation timing of the dedicated channel, a global network time slot scheduling strategy is generated to instruct the target static sensor node associated with the target service segment to switch to the dedicated channel to communicate with the mobile relay device when the dedicated channel is activated, and to instruct non-target static sensor nodes to communicate with the aggregation node. The global time slot scheduling strategy is sent to the static sensor nodes, and the mobile path and the reference service time window are sent to the mobile relay device to coordinate the channel switching, data transmission, and channel control and data relay of each node.

[0006] By adopting the above technical solution, the status information of each static sensor node is obtained, and a mobile path is planned for the mobile relay device based on the status information. The mobile relay device is also configured with a dedicated channel independent of the common channel. The mobile path is divided into multiple consecutive service segments, each associated with a group of target static sensor nodes to be served. A reference service time window for each service segment is determined based on a preset reference speed. During the movement, based on the real-time location and speed of the mobile relay device and the reference service time window of the target service segment, a channel trigger command is generated to activate the dedicated channel when the mobile relay device enters the target service segment. Then, based on the activation timing of the dedicated channel, a global network time slot scheduling strategy is generated to instruct the target static sensor nodes associated with the target service segment to switch to the dedicated channel to communicate with the mobile relay device when the dedicated channel is activated. It also instructs non-target static sensor nodes to communicate with the aggregation node. Finally, the global time slot scheduling strategy is distributed to the static sensor nodes, and the mobile path and reference service time window are distributed to the mobile relay device to coordinate channel switching, data transmission, and channel control and data relay of the mobile relay device. In this invention, state awareness is used to plan paths and configure dedicated channels for mobile relays. The paths are divided into service segments associated with high-load nodes, and time windows are pre-calculated. Based on real-time location and speed, the triggering timing is predicted, and dedicated channels are accurately activated. This generates a global time slot strategy, enabling target nodes to communicate with mobile relays on dedicated channels. At the same time, communication of non-target nodes on common channels is dynamically rescheduled to avoid conflicts. Finally, through coordinated deployment, a precise response to spatially dynamic unbalanced loads is achieved. This collaborative optimization in the spatial, spectral, and temporal dimensions resolves the contradiction between resource waste and performance bottlenecks, and improves transmission efficiency in high-load areas and overall network spectrum utilization.

[0007] Optionally, the step of acquiring the status information of each of the static sensor nodes and planning a mobile path for the mobile relay device based on the status information includes: Obtain the status information of each of the static sensor nodes, wherein the status information includes geographical location, data urgency level, and amount of data to be transmitted; Based on the communication radius of the mobile relay device, cluster analysis is performed on the geographical location of the static sensor node to obtain at least one service area; A path planning model is constructed, wherein minimizing the total mobile path length is the first optimization objective, and balancing the total amount of data to be transmitted in each of the service areas is the second optimization objective. Based on the genetic algorithm, the path planning model is solved to obtain the optimal access order for each of the service areas; Based on the optimal access order, an initial movement path connecting each of the service areas is generated. For each service area, the path segment serving that service area in the initial movement path is optimized according to the spatial distribution of the static sensor nodes in that service area to obtain the movement path. The optimized path segment is defined as the service segment in the movement path. For each service segment in the movement path, a corresponding target static sensor node is determined from the static sensor nodes based on the data urgency level of each static sensor node within that service segment.

[0008] By adopting the above technical solution, in order to plan the movement path of the mobile relay device, the status information of each static sensor node is obtained, including geographical location, data urgency level, and amount of data to be transmitted. Then, based on the communication radius of the mobile relay device, the geographical locations of the static sensor nodes are clustered to obtain at least one service area. Then, a path planning model is constructed, with minimizing the total movement path length as the first optimization objective and balancing the total amount of data to be transmitted in each service area as the second optimization objective. Then, based on the genetic algorithm, the path planning model is solved to obtain the optimal access order of each service area. Then, based on the optimal access order, an initial movement path connecting each service area is generated. For each service area, according to the spatial distribution of static sensor nodes in the service area, the path segment serving the service area in the initial movement path is optimized to obtain the movement path. The optimized path segment is defined as a service segment in the movement path. Then, for each service segment in the movement path, the corresponding target static sensor node is determined from the static sensor nodes according to the data urgency level of each static sensor node in the service segment.

[0009] Optionally, the step of configuring a dedicated channel independent of the common channel for the mobile relay device includes: From the available spectrum resources of the system, at least one candidate dedicated channel orthogonal to the common channel is delineated; For each service segment, predict the co-channel interference intensity of the mobile relay device in that service segment, and assess the total amount of target data to be transmitted for the target static sensor node associated with that service segment. Based on the co-channel interference intensity and the total amount of data to be transmitted, a dedicated channel is allocated for the service segment from the at least one candidate dedicated channel; A channel switching schedule table is generated, wherein the channel switching schedule table is used to instruct the mobile relay device to switch the current channel to the corresponding dedicated channel when entering the next service segment.

[0010] By adopting the above technical solution, in order to configure a dedicated channel, at least one candidate dedicated channel orthogonal to the common channel is divided from the available spectrum resources of the system. Then, for each service segment, the co-channel interference intensity of the mobile relay device in the service segment is predicted, and the total amount of target data to be transmitted of the target static sensor nodes associated with the service segment is evaluated. Then, based on the co-channel interference intensity and the total amount of target data to be transmitted, a dedicated channel is allocated to the service segment from at least one candidate dedicated channel. Then, a channel switching schedule table is generated, wherein the channel switching schedule table is used to instruct the mobile relay device to switch the current channel to the corresponding dedicated channel when entering the next service segment.

[0011] Optionally, the step of determining the reference service time window for each service segment based on a preset reference speed includes: Based on the movement path, determine the path length of each service segment; Based on the preset reference speed and the path length, the theoretical service duration of the mobile relay device in each of the service segments is determined; For each service segment, the corresponding time buffer is extended forward and backward respectively to obtain the reference service time window for that service segment.

[0012] By adopting the above technical solution, in order to determine the reference service time window for each service segment, the path length of each service segment is determined according to the mobile path. Then, based on the preset reference speed and path length, the theoretical service duration of the mobile relay device in each service segment is determined. Then, for each service segment, the corresponding time buffer is extended forward and backward respectively to obtain the reference service time window of that service segment.

[0013] Optionally, the step of generating a channel triggering command based on the real-time location and real-time moving speed of the mobile relay device and according to the reference service time window of the target service segment includes: Continuously acquire the real-time location and real-time moving speed of the mobile relay device; Based on the real-time location and the movement path, calculate the remaining journey of the mobile relay device to the target service area; Based on the remaining journey and the real-time moving speed, calculate the estimated arrival time of the mobile relay device to the target service area; The expected arrival time is compared with the reference service time window corresponding to the target service segment to generate a channel triggering command for activating the dedicated channel.

[0014] By adopting the above technical solution, in order to generate a channel triggering command, the real-time location and real-time moving speed of the mobile relay device are continuously acquired. Then, based on the real-time location and moving path, the remaining distance from the mobile relay device to the target service segment is calculated. Then, based on the remaining distance and real-time moving speed, the estimated arrival time of the mobile relay device to the target service segment is calculated. Then, the estimated arrival time is compared with the reference service time window corresponding to the target service segment to generate a channel triggering command for activating the dedicated channel.

[0015] Optionally, the step of generating a global network time slot scheduling strategy based on the activation timing of the dedicated channel includes: For each target service segment, the amount of data to be transmitted for each of the target static sensor nodes associated with that target service segment is obtained, and the channel quality of the dedicated channel is obtained. Based on the amount of data to be transmitted and the real-time channel status, a dedicated time slot is allocated for the communication link between the mobile relay device and each of the target static sensor nodes on the dedicated channel; Based on the dedicated time slot, the original time slot resources on the common channel are de-allocated, and the communication time slots for the non-target static sensor nodes are reallocated, wherein the reallocated communication time slots are orthogonal to the dedicated time slots; A global network time slot scheduling strategy is generated based on the dedicated time slots and the reallocated communication time slots.

[0016] By adopting the above technical solution, in order to generate a global network time slot scheduling strategy, for each target service segment, the amount of data to be transmitted of each target static sensor node associated with the target service segment is obtained, and the channel quality of the dedicated channel is obtained. Then, based on the amount of data to be transmitted and the real-time channel status, a dedicated time slot is allocated for the communication link between the mobile relay device and each target static sensor node on the dedicated channel. Then, based on the dedicated time slot, the original time slot resources on the public channel are released, and the communication time slots for non-target static sensor nodes are reallocated. The reallocated communication time slots are orthogonal to the dedicated time slots. Finally, a global network time slot scheduling strategy is generated based on the dedicated time slots and the reallocated communication time slots.

[0017] Optionally, the step of obtaining the channel quality of the dedicated channel includes: During the movement of the mobile relay device, the signal-to-noise ratio (SNR) and bit error rate (BER) of the dedicated channel are periodically measured and recorded to form an SNR time series and a BER time series. Based on the pre-trained signal-to-noise ratio (SNR) prediction model and bit error rate (BER) prediction model, and according to the SNR time series sequence and the BER time series sequence, the expected SNR and expected BER of the dedicated channel when the mobile relay device is in the target service area are determined, and the expected SNR and expected BER are used as the channel quality of the dedicated channel.

[0018] By adopting the above technical solution, in order to obtain the channel quality of the dedicated channel, the signal-to-noise ratio (SNR) and bit error rate (BER) of the dedicated channel are periodically measured and recorded during the movement of the mobile relay device, forming an SNR time series and a BER time series. Then, based on the pre-trained SNR prediction model and BER prediction model, and according to the SNR time series and BER time series, the expected SNR and expected BER of the dedicated channel when the mobile relay device is in the target service area are determined, and the expected SNR and expected BER are used as the channel quality of the dedicated channel.

[0019] Optionally, the training process of the signal-to-noise ratio prediction model includes: Historical signal-to-noise ratio (SNR) data is acquired, and the historical SNR data is preprocessed and the dataset is divided to obtain training set and test set; Based on the training set, the pre-selected recurrent neural network model is iteratively trained with the optimization objective of minimizing the error between the model's predicted value and the measured signal-to-noise ratio, thereby obtaining the trained recurrent neural network model. Based on the test set, the performance of the trained recurrent neural network model is verified to obtain the signal-to-noise ratio prediction model.

[0020] By adopting the above technical solution, in order to train the signal-to-noise ratio (SNR) prediction model, historical SNR data is obtained, and the historical SNR data is preprocessed and the dataset is divided to obtain training set and test set. Then, based on the training set, the pre-selected recurrent neural network model is iteratively trained with the optimization objective of minimizing the error between the model's predicted value and the measured SNR value to obtain the trained recurrent neural network model. Finally, based on the test set, the performance of the trained recurrent neural network model is verified to obtain the SNR prediction model.

[0021] Secondly, this application also provides a sensor bandwidth allocation system based on the Industrial Internet of Things, which adopts the following technical solution: A sensor bandwidth allocation system based on the Industrial Internet of Things (IIoT) includes a management platform, a sensor network platform, and an object platform that are sequentially connected in communication. The object platform includes a convergence node, multiple static sensor nodes, and at least one mobile relay device. The object platform is configured with: The path and channel planning module is used to obtain the status information of each of the static sensor nodes, plan a mobile path for the mobile relay device according to the status information, and configure a dedicated channel independent of the public channel for the mobile relay device. The mobile path is divided into multiple consecutive service segments, each service segment is associated with a group of target static sensor nodes to be served, and the reference service time window of each service segment is determined based on a preset reference speed. The channel triggering control module is used to generate a channel triggering command during movement based on the real-time location and real-time movement speed of the mobile relay device and the reference service time window of the target service segment, so as to activate the dedicated channel when the mobile relay device enters the target service segment. The time slot scheduling strategy generation module is used to generate a global network time slot scheduling strategy according to the activation timing of the dedicated channel, so as to instruct the target static sensor node associated with the target service segment to switch to the dedicated channel to communicate with the mobile relay device when the dedicated channel is activated, and to instruct non-target static sensor nodes to communicate with the aggregation node. The coordination and distribution module is used to distribute the global time slot scheduling strategy to the static sensor nodes and the mobile path and the reference service time window to the mobile relay device, so as to coordinate the channel switching, data transmission of each node and the channel control and data relay of the mobile relay device.

[0022] Thirdly, this application also provides a computer device, which adopts the following technical solution: A computer device includes a memory and a processor, the memory storing a computer program executable on the processor, the processor executing the computer program to implement the method described in the first aspect.

[0023] In summary, this application includes at least the following beneficial technical effects: acquiring the status information of each static sensor node, planning a movement path for the mobile relay device based on the status information, and configuring a dedicated channel independent of the common channel for the mobile relay device. The movement path is divided into multiple consecutive service segments, each service segment is associated with a group of target static sensor nodes to be served, and a reference service time window for each service segment is determined based on a preset reference speed. Then, during movement, prediction is made based on the real-time location and real-time movement speed of the mobile relay device, and according to the reference service time window of the target service segment, to generate... A channel trigger command is used to activate a dedicated channel when the mobile relay device enters the target service segment. Then, based on the activation timing of the dedicated channel, a global network time slot scheduling strategy is generated to instruct target static sensor nodes associated with the target service segment to switch to the dedicated channel to communicate with the mobile relay device when the dedicated channel is activated, and to instruct non-target static sensor nodes to communicate with the aggregation node. The global time slot scheduling strategy is then distributed to the static sensor nodes, and the mobile path and reference service time window are distributed to the mobile relay device to coordinate the channel switching, data transmission, and channel control and data relay of each node. In this invention, state awareness is used to plan paths and configure dedicated channels for mobile relays. The paths are divided into service segments associated with high-load nodes, and time windows are pre-calculated. Based on real-time location and speed, the triggering timing is predicted, and dedicated channels are accurately activated. This generates a global time slot strategy, enabling target nodes to communicate with mobile relays on dedicated channels. At the same time, communication of non-target nodes on common channels is dynamically rescheduled to avoid conflicts. Finally, through coordinated deployment, a precise response to spatially dynamic unbalanced loads is achieved. This collaborative optimization in the spatial, spectral, and temporal dimensions resolves the contradiction between resource waste and performance bottlenecks, and improves transmission efficiency in high-load areas and overall network spectrum utilization. Attached Figure Description

[0024] Figure 1 This is a schematic diagram of the overall process of an embodiment of this application.

[0025] Figure 2 This is a structural diagram of one application scenario of the system according to an embodiment of this application.

[0026] Figure 3 This is a structural diagram of another application scenario of the system according to an embodiment of this application.

[0027] Figure 4 This is a structural block diagram of the computer device described in this application. Detailed Implementation

[0028] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0029] This application discloses a sensor bandwidth allocation method based on the Industrial Internet of Things.

[0030] Reference Figure 1 A sensor bandwidth allocation method based on the Industrial Internet of Things (IIoT) is provided for use in an IIoT system. The IIoT system includes a management platform, a sensor network platform, and an object platform that are sequentially connected in communication. The object platform includes a convergence node, multiple static sensor nodes, and at least one mobile relay device. The method is executed by the object platform and includes: Step S11: Obtain the status information of each static sensor node, plan a mobile path for the mobile relay device based on the status information, and configure a dedicated channel independent of the public channel for the mobile relay device. The mobile path is divided into multiple consecutive service segments, each service segment is associated with a group of target static sensor nodes to be served, and the reference service time window for each service segment is determined based on a preset reference speed.

[0031] It should be noted that in step S11, multi-dimensional state information of each static sensor node is acquired and fused. This state information explicitly includes its geographical location, the amount of data to be transmitted, and the data urgency level. Subsequently, this fused information is used as a joint input for collaborative decision analysis: on the one hand, clustering is performed based on the geographical distribution of nodes and the communication radius of the mobile relay, dividing the network into multiple continuous service segments in space; on the other hand, the data to be transmitted and the urgency level of nodes within each segment are combined to dynamically filter and determine the target node group associated with that segment; simultaneously, a dedicated channel independent of the public channel is allocated to the mobile relay in the spectrum, decoupling its communication resources from the physical path; finally, based on the preset reference speed and the path length of each segment, the corresponding reference service time window is calculated. Thus, this step establishes a unified and interconnected collaborative planning framework for the mobile data collection task in three dimensions: space (i.e., mobile path and service segment), spectrum (dedicated channel), and time (reference service time window).

[0032] Step S12: During the movement, based on the real-time location and real-time movement speed of the mobile relay device and the prediction according to the reference service time window of the target service segment, a channel triggering command is generated to activate the dedicated channel when the mobile relay device enters the target service segment.

[0033] It should be noted that in step S12, during the mobile relay's journey along the planned path, the system continuously acquires its reported real-time location and speed. Using these dynamic parameters, combined with the known path topology, the system calculates and predicts in real-time the estimated arrival time of the mobile relay at the starting boundary of the next target service segment. By comparing this dynamically predicted arrival time with the start time of the predefined reference service time window of the target service segment, and determining whether the time difference is less than a preset trigger threshold, a channel activation command is generated at the most appropriate time. The core function of this step is to ensure that the dedicated channel is activated precisely when the mobile relay actually arrives at the service area through a closed-loop real-time prediction and threshold comparison mechanism, achieving a precise transition from static planning to dynamic execution.

[0034] Step S13: Generate a global network time slot scheduling strategy based on the activation timing of the dedicated channel, so that when the dedicated channel is activated, the target static sensor node associated with the target service segment is instructed to switch to the dedicated channel to communicate with the mobile relay device, and the non-target static sensor node is instructed to communicate with the aggregation node.

[0035] It should be noted that in step S13, when the activation time of the dedicated channel arrives, the system uses this as a driving event to perform a two-level resource allocation: First, at the dedicated channel level, based on the amount of data to be transmitted from the target node group and the channel quality, a dedicated transmission time slot is allocated to the communication link between the mobile relay and each target node; second, at the common channel level, to avoid conflicts with the aforementioned dedicated transmission time slots, the system actively reconstructs the original global time slot table. Specifically, it releases the time slot resources originally planned for communication between non-target nodes and aggregation nodes during the dedicated time slot period; subsequently, these released communication tasks are rescheduled to available time resources outside the dedicated time slots. The output of this step is a unified, time-conflict-free global network time slot scheduling strategy, the technical effect of which is to enable orthogonal time-division multiplexing of mobile data collection and static data backhaul services in the time dimension.

[0036] Step S14: The global time slot scheduling strategy is sent to the static sensor nodes, and the mobile path and reference service time window are sent to the mobile relay device to coordinate the channel switching, data transmission and channel control and data relay of each node.

[0037] It should be noted that in step S14, the system distributes the global network time slot scheduling strategy generated in step S13 to all static sensor nodes. This strategy explicitly indicates the channel and communication target that each node should use at a specific time. Simultaneously, the system distributes the mobile path planned in step S11 and the reference service time window for each service segment to the mobile relay device to guide its physical movement and provide a time synchronization reference. Through this centralized distribution, the system coordinates the mobile relay's movement control and channel switching, the target node's data upload on dedicated channels, and the off-peak communication of non-target nodes on public channels. Ultimately, this step enables all network entities to operate collaboratively based on a unified time-space-frequency plan, achieving a closed loop from centralized optimization to distributed execution, and fulfilling the core objective of improving overall network resource utilization and data transmission performance.

[0038] In the above implementation, the status information of each static sensor node is acquired, and a mobile path is planned for the mobile relay device based on the status information. A dedicated channel, independent of the common channel, is configured for the mobile relay device. The mobile path is divided into multiple consecutive service segments, each associated with a group of target static sensor nodes to be served. A reference service time window for each service segment is determined based on a preset reference speed. During the movement, based on the real-time location and real-time movement speed of the mobile relay device, and prediction based on the reference service time window of the target service segment, a channel trigger command is generated to activate the dedicated channel when the mobile relay device enters the target service segment. Then, based on the activation timing of the dedicated channel, a global network time slot scheduling strategy is generated to instruct the target static sensor nodes associated with the target service segment to switch to the dedicated channel to communicate with the mobile relay device when the dedicated channel is activated, and to instruct non-target static sensor nodes to communicate with the aggregation node. The global time slot scheduling strategy is then distributed to the static sensor nodes, and the mobile path and reference service time window are distributed to the mobile relay device to coordinate channel switching, data transmission, and channel control and data relay of the mobile relay device. In this invention, state awareness is used to plan paths and configure dedicated channels for mobile relays. The paths are divided into service segments associated with high-load nodes, and time windows are pre-calculated. Based on real-time location and speed, the triggering timing is predicted, and dedicated channels are accurately activated. This generates a global time slot strategy, enabling target nodes to communicate with mobile relays on dedicated channels. At the same time, communication of non-target nodes on common channels is dynamically rescheduled to avoid conflicts. Finally, through coordinated deployment, a precise response to spatially dynamic unbalanced loads is achieved. This collaborative optimization in the spatial, spectral, and temporal dimensions resolves the contradiction between resource waste and performance bottlenecks, and improves transmission efficiency in high-load areas and overall network spectrum utilization.

[0039] As a further implementation of the method, the step of acquiring the status information of each static sensor node and planning a mobile path for the mobile relay device based on the status information includes: Step S21: Obtain the status information of each static sensor node, including geographical location, data urgency level, and amount of data to be transmitted.

[0040] Step S22: Based on the communication radius of the mobile relay device, perform cluster analysis on the geographical location of the static sensor nodes to obtain at least one service area.

[0041] Step S23: Construct a path planning model, wherein minimizing the total mobile path length is the first optimization objective, and balancing the total amount of data to be transmitted in each service area is the second optimization objective.

[0042] Step S24: Based on the genetic algorithm, solve the path planning model to obtain the optimal access order for each service area.

[0043] Step S25: Based on the optimal access order, an initial movement path connecting each service area is generated. For each service area, the path segment serving that service area in the initial movement path is optimized according to the spatial distribution of static sensor nodes in that service area to obtain the movement path. The optimized path segment is defined as the service segment in the movement path.

[0044] Step S26: For each service segment in the mobile path, determine the corresponding target static sensor node from the static sensor nodes according to the data urgency level of each static sensor node in the service segment.

[0045] In the above implementation, in order to plan the movement path of the mobile relay device, the status information of each static sensor node is obtained, including geographical location, data urgency level, and amount of data to be transmitted. Then, based on the communication radius of the mobile relay device, the geographical locations of the static sensor nodes are clustered to obtain at least one service area. Then, a path planning model is constructed, with minimizing the total movement path length as the first optimization objective and balancing the total amount of data to be transmitted in each service area as the second optimization objective. Then, based on a genetic algorithm, the path planning model is solved to obtain the optimal access order for each service area. Then, based on the optimal access order, an initial movement path connecting each service area is generated. For each service area, according to the spatial distribution of static sensor nodes in the service area, the path segment serving the service area in the initial movement path is optimized to obtain the movement path. The optimized path segment is defined as a service segment in the movement path. Then, for each service segment in the movement path, the corresponding target static sensor node is determined from the static sensor nodes according to the data urgency level of each static sensor node in the service segment.

[0046] As a further implementation of the method, the step of configuring a dedicated channel for the mobile relay device, independent of the common channel, includes: Step S31: From the available spectrum resources of the system, at least one candidate dedicated channel orthogonal to the common channel is delineated.

[0047] Step S32: For each service segment, predict the co-channel interference intensity of the mobile relay device in that service segment, and assess the total amount of target data to be transmitted for the target static sensor nodes associated with that service segment.

[0048] Step S33: Based on the co-channel interference intensity and the total amount of data to be transmitted, allocate a dedicated channel for the service segment from at least one candidate dedicated channel.

[0049] Step S34: Generate a channel switching schedule table, wherein the channel switching schedule table is used to instruct the mobile relay device to switch the current channel to the corresponding dedicated channel when entering the next service segment.

[0050] In the above implementation, in order to configure a dedicated channel, at least one candidate dedicated channel orthogonal to the common channel is divided from the available spectrum resources of the system. Then, for each service segment, the co-channel interference intensity of the mobile relay device in the service segment is predicted, and the total amount of target data to be transmitted of the target static sensor nodes associated with the service segment is evaluated. Then, based on the co-channel interference intensity and the total amount of target data to be transmitted, a dedicated channel is allocated to the service segment from at least one candidate dedicated channel. Then, a channel switching schedule table is generated, wherein the channel switching schedule table is used to instruct the mobile relay device to switch the current channel to the corresponding dedicated channel when entering the next service segment.

[0051] As a further implementation of the method, the step of determining the reference service time window for each service segment based on a preset reference speed includes: Step S41: Determine the path length of each service segment based on the movement path.

[0052] Step S42: Based on the preset reference speed and path length, determine the theoretical service duration of the mobile relay device in each service segment.

[0053] Step S43: For each service segment, extend the corresponding time buffer forward and backward respectively to obtain the reference service time window for that service segment.

[0054] In the above implementation, in order to determine the reference service time window for each service segment, the path length of each service segment is determined according to the movement path. Then, based on the preset reference speed and path length, the theoretical service duration of the mobile relay device in each service segment is determined. Then, for each service segment, the corresponding time buffer is extended forward and backward respectively to obtain the reference service time window of that service segment.

[0055] As a further implementation of the method, the step of generating a channel triggering command based on the real-time location and real-time moving speed of the mobile relay device and prediction according to the reference service time window of the target service segment includes: Step S51: Continuously acquire the real-time location and real-time moving speed of the mobile relay device.

[0056] Step S52: Calculate the remaining journey from the mobile relay device to the target service area based on the real-time location and movement path.

[0057] Step S53: Calculate the estimated arrival time of the mobile relay device to the target service segment based on the remaining journey and real-time moving speed.

[0058] Step S54: Compare the expected arrival time with the reference service time window corresponding to the target service segment to generate a channel triggering command for activating the dedicated channel.

[0059] In the above implementation, in order to generate a channel triggering command, the real-time location and real-time moving speed of the mobile relay device are continuously acquired. Then, based on the real-time location and moving path, the remaining distance from the mobile relay device to the target service segment is calculated. Then, based on the remaining distance and real-time moving speed, the estimated arrival time of the mobile relay device to the target service segment is calculated. Then, the estimated arrival time is compared with the reference service time window corresponding to the target service segment to generate a channel triggering command for activating the dedicated channel.

[0060] As a further implementation of the method, the step of generating a global network time slot scheduling strategy based on the activation timing of the dedicated channel includes: Step S61: For each target service segment, obtain the amount of data to be transmitted for each target static sensor node associated with the target service segment, and obtain the channel quality of the dedicated channel.

[0061] Step S62: Based on the amount of data to be transmitted and the real-time channel status, allocate dedicated time slots for the communication link between the mobile relay device and each target static sensor node on the dedicated channel.

[0062] Step S63: Based on the dedicated time slot, the original time slot resources on the public channel are released and the communication time slots for non-target static sensor nodes are reallocated. The reallocated communication time slots are orthogonal to the dedicated time slots.

[0063] Step S64: Generate a global network time slot scheduling strategy based on the dedicated time slot and the reallocated communication time slot.

[0064] In the above implementation, in order to generate a global network time slot scheduling strategy, for each target service segment, the amount of data to be transmitted for each target static sensor node associated with the target service segment is obtained, and the channel quality of the dedicated channel is obtained. Then, based on the amount of data to be transmitted and the real-time channel status, a dedicated time slot is allocated for the communication link between the mobile relay device and each target static sensor node on the dedicated channel. Then, based on the dedicated time slot, the original time slot resources on the public channel are released, and the communication time slots for non-target static sensor nodes are reallocated. The reallocated communication time slots are orthogonal to the dedicated time slots. Finally, a global network time slot scheduling strategy is generated based on the dedicated time slots and the reallocated communication time slots.

[0065] As a further implementation of the method, the step of obtaining the channel quality of the dedicated channel includes: Step S71: During the movement of the mobile relay device, the signal-to-noise ratio and bit error rate of the dedicated channel are periodically measured and recorded to form a signal-to-noise ratio time sequence and a bit error rate time sequence.

[0066] Step S72: Based on the pre-trained signal-to-noise ratio (SNR) prediction model and bit error rate (BER) prediction model, and according to the SNR time series sequence and BER time series sequence, determine the expected SNR and expected BER of the dedicated channel when the mobile relay device is in the target service area, and use the expected SNR and expected BER as the channel quality of the dedicated channel.

[0067] In the above embodiments, in order to obtain the channel quality of the dedicated channel, the signal-to-noise ratio (SNR) and bit error rate (BER) of the dedicated channel are periodically measured and recorded during the movement of the mobile relay device, forming an SNR time series and a BER time series. Then, based on the pre-trained SNR prediction model and BER prediction model, and according to the SNR time series and BER time series, the expected SNR and expected BER of the dedicated channel when the mobile relay device is in the target service area are determined, and the expected SNR and expected BER are used as the channel quality of the dedicated channel.

[0068] As a further implementation of the method, the training process of the signal-to-noise ratio prediction model includes: Step S81: Obtain historical signal-to-noise ratio data, and preprocess and divide the historical signal-to-noise ratio data to obtain training set and test set.

[0069] Step S82: Based on the training set, iteratively train the pre-selected recurrent neural network model, with the optimization objective being to minimize the error between the model's predicted value and the measured signal-to-noise ratio, to obtain the trained recurrent neural network model.

[0070] Step S83: Based on the test set, perform performance verification on the trained recurrent neural network model to obtain the signal-to-noise ratio prediction model.

[0071] In the above implementation, in order to train the signal-to-noise ratio (SNR) prediction model, historical SNR data is acquired, and the historical SNR data is preprocessed and the dataset is divided to obtain a training set and a test set. Then, based on the training set, a pre-selected recurrent neural network model is iteratively trained with the optimization objective of minimizing the error between the model's predicted value and the measured SNR value to obtain a trained recurrent neural network model. Then, based on the test set, the performance of the trained recurrent neural network model is verified to obtain the SNR prediction model.

[0072] This application also discloses a sensor bandwidth allocation system based on the Industrial Internet of Things.

[0073] refer to Figure 2 A sensor bandwidth allocation system based on the Industrial Internet of Things (IIoT) includes a management platform, a sensor network platform, and an object platform that are sequentially connected in communication. The object platform includes a convergence node, multiple static sensor nodes, and at least one mobile relay device. The object platform is configured with: The path and channel planning module is used to obtain the status information of each static sensor node, plan a mobile path for the mobile relay device based on the status information, and configure a dedicated channel for the mobile relay device that is independent of the public channel. The mobile path is divided into multiple consecutive service segments, each service segment is associated with a group of target static sensor nodes to be served, and the reference service time window of each service segment is determined based on a preset reference speed. The channel triggering control module is used to generate a channel triggering command based on the real-time location and real-time moving speed of the mobile relay device and the reference service time window of the target service segment during the movement process, so as to activate the dedicated channel when the mobile relay device enters the target service segment. The time slot scheduling strategy generation module is used to generate a global network time slot scheduling strategy based on the activation timing of the dedicated channel. When the dedicated channel is activated, it instructs the target static sensor nodes associated with the target service segment to switch to the dedicated channel to communicate with the mobile relay device, and instructs non-target static sensor nodes to communicate with the aggregation node. The coordination and distribution module is used to distribute the global time slot scheduling strategy to the static sensor nodes and the mobile path and reference service time window to the mobile relay device, so as to coordinate the channel switching, data transmission and channel control and data relay of each node.

[0074] The overall framework of another application scenario of the sensor bandwidth allocation system based on the Industrial Internet of Things of this invention is as follows: Figure 3 As shown, the system can include a user platform, a service platform, a management platform, a sensor network platform, and an object platform that interact sequentially, forming a five-platform architecture based on the Industrial Internet of Things (IIoT). The service platform consists of a central service database, multiple service sub-platforms, and multiple service sub-databases. The management platform includes a path and channel planning module, a channel triggering control module, a time slot scheduling strategy generation module, and a coordination and distribution module. The management platform can interact with the sensor network platform and the service platform. The sensor network platform can include a central sensor database, multiple sensor network sub-platforms, and multiple sensor sub-databases. In this embodiment, there are n sensor network sub-platforms and n sensor sub-databases. Each sensor network sub-platform has a corresponding sensor sub-database. The sensor network platform can interact with the object platform.

[0075] By leveraging the interaction between the various functional platforms of the industrial IoT-based sensor bandwidth allocation system, which is based on the aforementioned three or five platforms, a complete closed-loop information operation logic is established, ensuring the orderly operation of sensing and control information and realizing intelligent equipment management.

[0076] Specifically, the sensor bandwidth allocation system based on the Industrial Internet of Things in this embodiment includes a management platform. The platform is configured to: acquire the status information of each static sensor node, plan a movement path for the mobile relay device based on the status information, and configure a dedicated channel independent of the public channel for the mobile relay device. The movement path is divided into multiple consecutive service segments, each service segment is associated with a group of target static sensor nodes to be served, and a reference service time window for each service segment is determined based on a preset reference speed. During movement, based on the real-time location and real-time movement speed of the mobile relay device, and according to the reference service time window of the target service segment... The system predicts service time windows and generates channel triggering commands to activate dedicated channels when the mobile relay device enters the target service segment. Based on the activation timing of the dedicated channels, a global network time slot scheduling strategy is generated to instruct target static sensor nodes associated with the target service segment to switch to the dedicated channels to communicate with the mobile relay device when the dedicated channels are activated, and to instruct non-target static sensor nodes to communicate with the aggregation nodes. The global time slot scheduling strategy is then distributed to the static sensor nodes, and the mobile path and reference service time window are distributed to the mobile relay device to coordinate channel switching, data transmission, and channel control and data relay of the mobile relay device.

[0077] The sensor bandwidth allocation system based on the Industrial Internet of Things (IIoT) of the present invention can implement any of the sensor bandwidth allocation methods based on the Industrial Internet of Things, and the specific working process of the sensor bandwidth allocation system based on the Industrial Internet of Things of the present invention can refer to the corresponding process in the above-mentioned sensor bandwidth allocation methods based on the Industrial Internet of Things.

[0078] This application also discloses a computer device.

[0079] refer to Figure 4 A computer device includes a memory and a processor, wherein the memory stores a computer program that can run on the processor, and the processor executes the computer program to implement any of the above-described methods for sensor bandwidth allocation based on the Industrial Internet of Things.

[0080] This application also discloses a computer-readable storage medium.

[0081] A computer-readable storage medium storing a computer program that can be loaded by a processor and executed any of the above-described sensor bandwidth allocation methods based on the Industrial Internet of Things.

[0082] The computer-readable storage medium can be any tangible medium that contains or stores a program that can be used by or in connection with an instruction execution system, apparatus, or device; the program code contained on the computer-readable medium can be transmitted using any suitable medium, including but not limited to wireless, wire, optical fiber, RF, etc., or any suitable combination thereof.

[0083] The above are all preferred embodiments of this application and are not intended to limit the scope of protection of this application. Any feature disclosed in this specification (including the abstract and drawings) may be replaced by other equivalent or similar features unless specifically stated otherwise. That is, unless specifically stated otherwise, each feature is only one example of a series of equivalent or similar features.

Claims

1. A sensor bandwidth allocation method based on the Industrial Internet of Things, characterized in that, For an industrial Internet of Things (IIoT) system, the IIoT system includes a management platform, a sensor network platform, and an object platform that are sequentially and communicatively connected. The object platform includes a convergence node, multiple static sensor nodes, and at least one mobile relay device. The method is executed by the object platform and includes: The status information of each static sensor node is obtained, and a mobile path is planned for the mobile relay device based on the status information. A dedicated channel independent of the common channel is configured for the mobile relay device. The mobile path is divided into multiple consecutive service segments. Each service segment is associated with a group of target static sensor nodes to be served. The reference service time window of each service segment is determined based on a preset reference speed. During the movement, based on the real-time location and real-time movement speed of the mobile relay device, and according to the reference service time window of the target service segment, a channel triggering command is generated to activate the dedicated channel when the mobile relay device enters the target service segment. Based on the activation timing of the dedicated channel, a global network time slot scheduling strategy is generated to instruct the target static sensor node associated with the target service segment to switch to the dedicated channel to communicate with the mobile relay device when the dedicated channel is activated, and to instruct non-target static sensor nodes to communicate with the aggregation node. The global time slot scheduling strategy is sent to the static sensor nodes, and the mobile path and the reference service time window are sent to the mobile relay device to coordinate the channel switching, data transmission, and channel control and data relay of each node.

2. The sensor bandwidth allocation method based on the Industrial Internet of Things according to claim 1, characterized in that, The step of acquiring the status information of each of the static sensor nodes and planning a mobile path for the mobile relay device based on the status information includes: Obtain the status information of each of the static sensor nodes, wherein the status information includes geographical location, data urgency level, and amount of data to be transmitted; Based on the communication radius of the mobile relay device, cluster analysis is performed on the geographical location of the static sensor node to obtain at least one service area; A path planning model is constructed, wherein minimizing the total mobile path length is the first optimization objective, and balancing the total amount of data to be transmitted in each of the service areas is the second optimization objective. Based on the genetic algorithm, the path planning model is solved to obtain the optimal access order for each of the service areas; Based on the optimal access order, an initial movement path connecting each of the service areas is generated. For each service area, the path segment serving that service area in the initial movement path is optimized according to the spatial distribution of the static sensor nodes in that service area to obtain the movement path. The optimized path segment is defined as the service segment in the movement path. For each service segment in the movement path, a corresponding target static sensor node is determined from the static sensor nodes based on the data urgency level of each static sensor node within that service segment.

3. The sensor bandwidth allocation method based on the Industrial Internet of Things according to claim 2, characterized in that, The step of configuring a dedicated channel independent of the public channel for the mobile relay device includes: From the available spectrum resources of the system, at least one candidate dedicated channel orthogonal to the common channel is delineated; For each service segment, predict the co-channel interference intensity of the mobile relay device in that service segment, and assess the total amount of target data to be transmitted for the target static sensor node associated with that service segment. Based on the co-channel interference intensity and the total amount of data to be transmitted, a dedicated channel is allocated for the service segment from the at least one candidate dedicated channel; A channel switching schedule table is generated, wherein the channel switching schedule table is used to instruct the mobile relay device to switch the current channel to the corresponding dedicated channel when entering the next service segment.

4. The sensor bandwidth allocation method based on the Industrial Internet of Things according to claim 1, characterized in that, The step of determining the reference service time window for each service segment based on a preset reference speed includes: Based on the movement path, determine the path length of each service segment; Based on the preset reference speed and the path length, the theoretical service duration of the mobile relay device in each of the service segments is determined; For each service segment, the corresponding time buffer is extended forward and backward respectively to obtain the reference service time window for that service segment.

5. The sensor bandwidth allocation method based on the Industrial Internet of Things according to claim 1, characterized in that, The step of generating a channel triggering command based on the real-time location and real-time moving speed of the mobile relay device, and by predicting according to the reference service time window of the target service segment, includes: Continuously acquire the real-time location and real-time moving speed of the mobile relay device; Based on the real-time location and the movement path, calculate the remaining journey of the mobile relay device to the target service area; Based on the remaining journey and the real-time moving speed, calculate the estimated arrival time of the mobile relay device to the target service area; The expected arrival time is compared with the reference service time window corresponding to the target service segment to generate a channel triggering command for activating the dedicated channel.

6. The sensor bandwidth allocation method based on the Industrial Internet of Things according to claim 1, characterized in that, The step of generating a global network time slot scheduling strategy based on the activation timing of the dedicated channel includes: For each target service segment, the amount of data to be transmitted for each of the target static sensor nodes associated with that target service segment is obtained, and the channel quality of the dedicated channel is obtained. Based on the amount of data to be transmitted and the real-time channel status, a dedicated time slot is allocated for the communication link between the mobile relay device and each of the target static sensor nodes on the dedicated channel; Based on the dedicated time slot, the original time slot resources on the common channel are de-allocated, and the communication time slots for the non-target static sensor nodes are reallocated, wherein the reallocated communication time slots are orthogonal to the dedicated time slots; A global network time slot scheduling strategy is generated based on the dedicated time slots and the reallocated communication time slots.

7. The sensor bandwidth allocation method based on the Industrial Internet of Things according to claim 6, characterized in that, The step of obtaining the channel quality of the dedicated channel includes: During the movement of the mobile relay device, the signal-to-noise ratio (SNR) and bit error rate (BER) of the dedicated channel are periodically measured and recorded to form an SNR time series and a BER time series. Based on the pre-trained signal-to-noise ratio (SNR) prediction model and bit error rate (BER) prediction model, and according to the SNR time series sequence and the BER time series sequence, the expected SNR and expected BER of the dedicated channel when the mobile relay device is in the target service area are determined, and the expected SNR and expected BER are used as the channel quality of the dedicated channel.

8. The sensor bandwidth allocation method based on the Industrial Internet of Things according to claim 7, characterized in that, The training process of the signal-to-noise ratio prediction model includes: Historical signal-to-noise ratio (SNR) data is acquired, and the historical SNR data is preprocessed and the dataset is divided to obtain training set and test set; Based on the training set, the pre-selected recurrent neural network model is iteratively trained with the optimization objective of minimizing the error between the model's predicted value and the measured signal-to-noise ratio, thereby obtaining the trained recurrent neural network model. Based on the test set, the performance of the trained recurrent neural network model is verified to obtain the signal-to-noise ratio prediction model.

9. A sensor bandwidth allocation system based on the Industrial Internet of Things, characterized in that, The system includes a management platform, a sensor network platform, and an object platform that are sequentially connected in communication. The object platform includes a convergence node, multiple static sensor nodes, and at least one mobile relay device. The object platform is configured with: The path and channel planning module is used to obtain the status information of each of the static sensor nodes, plan a mobile path for the mobile relay device according to the status information, and configure a dedicated channel independent of the public channel for the mobile relay device. The mobile path is divided into multiple consecutive service segments, each service segment is associated with a group of target static sensor nodes to be served, and the reference service time window of each service segment is determined based on a preset reference speed. The channel triggering control module is used to generate a channel triggering command during movement based on the real-time location and real-time movement speed of the mobile relay device and the reference service time window of the target service segment, so as to activate the dedicated channel when the mobile relay device enters the target service segment. The time slot scheduling strategy generation module is used to generate a global network time slot scheduling strategy according to the activation timing of the dedicated channel, so as to instruct the target static sensor node associated with the target service segment to switch to the dedicated channel to communicate with the mobile relay device when the dedicated channel is activated, and to instruct non-target static sensor nodes to communicate with the aggregation node. The coordination and distribution module is used to distribute the global time slot scheduling strategy to the static sensor nodes and the mobile path and the reference service time window to the mobile relay device, so as to coordinate the channel switching, data transmission of each node and the channel control and data relay of the mobile relay device.

10. A computer device, characterized in that, The method includes a memory and a processor, wherein the memory stores a computer program that can run on the processor, and the processor executes the computer program to implement the method of any one of claims 1 to 8.

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