Data sharing system based on 5G Internet of Things

Abstract

A data sharing system based on the 5G Internet of Things comprises a monitoring center, and the monitoring center is in communication connection with a data acquisition module, a data storage module, a data processing module, a data analysis module and a data scheduling module. The data acquisition module acquires shared resource data information; the data processing module generates a node execution capability value of each node in each resource sharing job queue, and establishes 5G network slices of different time spans for each resource sharing job queue according to the node execution capability value; the data analysis module sets execution priorities for the nodes, sets processing priorities for the resource sharing job queues, and compares and analyzes historical resource sharing completion time of the nodes in the resource sharing job queues with a 5G network slice time span of the queues; and the data scheduling module schedules the remaining idle time period in the 5G network slice time span after the resource sharing of the queue node in the resource sharing job queue is completed, so that the data sharing efficiency is remarkably improved.

Description

Technical Field

[0001] The present invention relates to the technical field of data sharing, and specifically to a data sharing system based on 5G Internet of Things. Background Art

[0002] With the advent of the information age, the Internet of Things plays a huge role in the development of the network. It is an expansion and development of the Internet, which can ensure information exchange and sharing between any items. The Internet of Things collects various required information of any objects or processes that need to be monitored, connected, and interacted in real time through various information sensing devices, and forms a huge network in combination with the Internet. These shared resources are limited. If the shared resources in the Internet of Things cannot be evenly distributed, some unimportant data may occupy most or even all of the shared resources, easily resulting in a poor utilization rate of the shared resources in the Internet of Things. Reasonable scheduling of the Internet of Things resources can reduce redundant data and improve the network performance of the Internet of Things.

[0003] In this state, how to effectively schedule the shared resource data in the Internet of Things has become the main problem to be solved urgently in this field. Summary of the Invention

[0004] In order to solve the above technical problems, the purpose of the present invention is to provide a data sharing system based on 5G Internet of Things.

[0005] The purpose of the present invention can be achieved through the following technical solutions: A data sharing system based on 5G Internet of Things, including a monitoring center, characterized in that the monitoring center is communicatively connected to a data acquisition module, a data storage module, a data processing module, a data analysis module, and a data scheduling module;

[0006] The data acquisition module is used to collect the shared resource data information uploaded by each node in the 5G Internet of Things data sharing platform and generate a resource sharing job queue;

[0007] The data storage module is used to communicate with the middleware node 5G and send the data information to multiple distributed databases for storage according to different middleware nodes;

[0008] The data processing module is used to generate the node execution ability value of each node in each resource sharing job queue, and establish 5G network slices with different time spans for each resource sharing job queue according to the expected node scheduling number of each resource sharing job queue and the time span constraint condition of scheduling shared resources;

[0009] The data analysis module sets the execution priority for the nodes and the processing priority for the resource sharing job queue. When network congestion occurs, it compares the historical resource sharing completion time of the nodes in the resource sharing job queue with the 5G network slice time span of the queue, and decides whether to change the resource sharing job queue where the nodes are located according to the comparison result;

[0010] The data scheduling module is used to schedule the remaining idle time periods within the 5G network slice time span after the resource sharing of the nodes in the resource sharing job queue of this queue is completed.

[0011] Furthermore, the process of the data acquisition module acquiring the shared resource data information uploaded by each node in the 5G Internet of Things data sharing platform includes:

[0012] Several middleware nodes are built between the data acquisition module and the 5G Internet of Things data sharing platform. Each middleware node is linked to a corresponding distributed database. The acquisition period is set and the acquisition time of the data information is marked, and the acquired data information is sent to the middleware node; among them, the data information includes the resource scheduling start time and the resource scheduling end time.

[0013] Furthermore, the process of the data storage module sending the data information to multiple distributed databases for storage according to different middleware nodes includes:

[0014] It is 5G communication-connected to the middleware node, and is provided with a real-time database and an offline database; the real-time database includes multiple distributed real-time databases, and the offline database includes multiple distributed offline databases. The data information collected in the current acquisition period is sent to multiple distributed real-time databases for storage according to different middleware nodes. When the real-time database detects new data information in the next acquisition period, the data information collected in multiple distributed real-time databases in the current acquisition period is sent to multiple distributed offline databases for storage, and it is marked as historical data.

[0015] Furthermore, the process of the data processing module generating the node execution ability value of each node in each resource sharing job queue includes:

[0016] Obtain the historical resource sharing completion time of the node according to the historical resource scheduling start time and the historical resource scheduling end time of the node, and obtain the node execution ability value according to the historical resource sharing completion time.

[0017] Furthermore, the process of the data processing module establishing 5G network slices with different time spans for each resource sharing job queue according to the expected node scheduling slot number of each resource sharing job queue and the time span constraint condition of scheduling shared resources includes:

[0018] Set the time span constraint condition and the expected number of node scheduling slots for the resource sharing job queue, generate the data processing capacity value of the resource sharing job queue according to the time span constraint condition and the expected number of node scheduling slots for the resource sharing job queue, set the 5G network slice comparison table, and match the generated data processing capacity value of the resource sharing job queue with the 5G network slice comparison table to obtain the 5G network slice corresponding to the time span.

[0019] Further, the process of the data analysis module setting the execution priority for the nodes and the processing priority for the resource sharing job queue includes:

[0020] Sort the nodes in each resource sharing job queue according to the node execution ability value in descending order to set the execution priority, and at the same time sort the 5G network slice time spans of each resource sharing job queue in ascending order to set the processing priority.

[0021] Further, when network congestion occurs, the process of the data analysis module comparing the historical resource sharing completion time of the nodes in the resource sharing job queue with the 5G network slice time span of the queue and deciding whether to change the resource sharing job queue where the node is located includes:

[0022] When the historical resource sharing completion time of the node is greater than the 5G network slice time span of the queue, allocate it to the resource sharing job queue with a lower processing priority, and compare it with the 5G network slice time span of the resource sharing job queue with a lower processing priority. If the historical resource sharing completion time of the node is still greater than the 5G network slice time span of the queue, then allocate it to the resource sharing job queue with an even lower processing priority and repeat the 5G network slice time span comparison until the historical resource sharing completion time of the node is less than or equal to the 5G network slice time span of the resource sharing job queue.

[0023] Further, the process of the data scheduling module scheduling the remaining idle time period within the 5G network slice time span after the resource sharing of the nodes in the resource sharing job queue is completed includes:

[0024] Judge whether there is a remaining idle time period within the 5G network slice time span after the resource sharing of the nodes in the resource sharing job queue is completed. If there is a remaining idle time period, select the nodes with a historical resource sharing completion time less than the remaining idle time period from the queue with a lower processing priority, allocate them to the remaining idle time period, and repeat this operation until there is no remaining idle time period in the resource sharing job queue or there are no nodes that meet the condition that the historical resource sharing completion time is less than or equal to the remaining idle time period.

[0025] Compared with the prior art, the beneficial effects of the present invention are as follows: First, by scheduling the remaining idle time period within the 5G network slice time span after the resource sharing of the nodes in the resource sharing job queue is completed, the present invention can, compared with the prior art which sets the data transmission rate as a fixed parameter, prevent a certain data stream from breaking through to the port rate even when there is no congestion in the network. The data sharing system of the present invention sets resource sharing queues for different network slices, enabling flexible switching of data sharing among nodes and greatly improving the system resource utilization efficiency.

[0026] Second, when the network encounters congestion, by comparing and analyzing the historical resource sharing completion time of the nodes in the resource sharing job queue with the 5G network slice time span of the queue, the data sharing of the nodes with low execution priority in the queue with high data sharing processing capacity is reduced, improving the data sharing efficiency of important data.

[0027] Third, in the present invention, the data processing module calculates the node execution ability value H of the node according to the collected data of the node i , the time span and data size P of the 5G network slice of the resource sharing job queue where the node is located i , calculates the execution priority K of each node i , sorts the data in ascending order according to the size of the execution priority K of each node i , and sequentially transmits the corresponding data to the data processing module according to the sorting of the node data, making the data processing more hierarchical and orderly. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] Figure 1 It is a schematic diagram of a data sharing system based on 5G Internet of Things according to an embodiment of the present application. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0029] The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are some, but not all, of the embodiments of the present application. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present application without creative efforts shall fall within the protection scope of the present application.

[0030] As Figure 1 shown, a data sharing system based on 5G Internet of Things includes a monitoring center, characterized in that the monitoring center is communicatively connected to a data acquisition module, a data storage module, a data processing module, a data analysis module, and a data scheduling module;

[0031] The data acquisition module is used to collect the shared resource data information uploaded by each node in the 5G Internet of Things data sharing platform and generate a resource sharing job queue;

[0032] The data storage module is used to communicate with the middleware node 5G and send the data information to multiple distributed databases for storage according to different middleware nodes;

[0033] The data processing module is used to generate the node execution ability values of each node in each resource sharing job queue and establish 5G network slices with different time spans for each resource sharing job queue according to the expected node scheduling number and the time span constraint conditions of scheduling shared resources in each resource sharing job queue;

[0034] The data analysis module sets the execution priority for the nodes and sets the processing priority for the resource sharing job queue. When network congestion occurs, it compares the historical resource sharing completion time of the nodes in the resource sharing job queue with the 5G network slice time span of the queue and decides whether to change the resource sharing job queue where the node is located according to the comparison result;

[0035] The data scheduling module is used to schedule the remaining idle time period within the 5G network slice time span after the node resources in the resource sharing job queue are shared.

[0036] It should be further noted that in the specific implementation process, the process of the data acquisition module collecting the shared resource data information uploaded by each node in the 5G Internet of Things data sharing platform includes:

[0037] Several middleware nodes are constructed between the data acquisition module and the 5G Internet of Things data sharing platform. Each middleware node is linked to a corresponding distributed database. The acquisition period is set and the acquisition time of the data information is marked, and the acquired data information is sent to the middleware node; among them, the data information includes the resource scheduling start time and the resource scheduling end time.

[0038] It should be further noted that in the specific implementation process, the process of the data storage module sending the data information to multiple distributed databases for storage according to different middleware nodes includes:

[0039] It is 5G communication-connected to the middleware node and is provided with a real-time database and an offline database; the real-time database includes multiple distributed real-time databases, and the offline database includes multiple distributed offline databases. The data information collected in the current collection cycle is sent to multiple distributed real-time databases for storage according to different middleware nodes. When the real-time database detects new data information in the next collection cycle, the data information collected in multiple distributed real-time databases in the current collection cycle is sent to multiple distributed offline databases for storage, and it is marked as historical data.

[0040] It should be further noted that, in the specific implementation process, the process by which the data processing module generates the node execution ability values of each node in each resource sharing job queue includes:

[0041] Obtain the historical resource sharing completion time T of the node according to the historical resource scheduling start time and historical resource scheduling end time of the node A , and obtain the node execution ability value H according to the historical resource sharing completion time i .

[0042] It should be further noted that, in the specific implementation process, the process by which the data processing module obtains the historical resource sharing completion time of the node includes:

[0043] The data analysis module obtains the mean value of the resource sharing completion time within the historical collection cycle. The data analysis module sets the first historical collection cycle, the second historical collection cycle, and the third historical collection cycle, and the resource sharing completion time of the first historical collection cycle is T1, the data regression value of the second historical collection cycle is T2, and the data regression value of the third historical collection cycle is T3. Set the mean value T of the resource sharing completion time within the historical collection cycle A , set T A =(T1 + T2 + T3) / 3;

[0044] It should be further noted that, in the specific implementation process, the calculation method by which the data processing module obtains the node execution ability value is:

[0045] H i =W i1 *T A

[0046] where, H i represents the node execution ability value of the i-th node device; W i1 represents the weight value of the node execution ability value of the i-th node device;

[0047] It should be further noted that in the specific implementation process, the process of the data processing module establishing 5G network slices with different time spans for each resource sharing job queue according to the expected node scheduling slots of each resource sharing job queue and the time span constraint conditions for scheduling shared resources includes:

[0048] Set the time span constraint condition T B and the expected node scheduling slots N of the resource sharing job queue I , according to the time span constraint condition T B and the expected node scheduling slots N of the resource sharing job queue I Generate the data processing capacity value of the resource sharing job queue, set up a 5G network slice comparison table, match the generated data processing capacity value of the resource sharing job queue with the 5G network slice comparison table, and obtain the 5G network slice T corresponding to the time span Gi .

[0049] It should be further noted that in the specific implementation process, the calculation method for the data processing module to obtain the 5G network slice time span T Gi is as follows:

[0050] T GI =W I2 *T B +W I3 *N I

[0051] Among them, T GI represents the time span of the 5G network slice of the I-th resource sharing job queue; T B represents the time span constraint condition; N I represents the expected node scheduling slots of the I-th resource sharing job queue; W I2 represents the weight value of the time span constraint condition; W I3 represents the weight value of the expected node scheduling slots of the I-th resource sharing job queue; I represents the number of each resource sharing job queue;

[0052] It should be further noted that in the specific implementation process, the process of the data analysis module setting the execution priority for the nodes and setting the processing priority for the resource sharing job queue includes:

[0053] Sort and set the execution priority according to the node execution ability values of the nodes in each resource sharing job queue in the order from high to low, and at the same time sort and set the processing priority according to the length of the 5G network slice time span of each resource sharing job queue in the order from low to high.

[0054] It should be further noted that in the specific implementation process, each node sets the execution priority Ki The calculation method is as follows:

[0055]

[0056] Where K i represents the execution priority of the i-th node in the resource sharing job queue; T B represents the time span constraint of the i-th node; T GI represents the time span of the 5G network slice in the I-th resource sharing job queue; H i represents the node execution ability value of the i-th node device in the resource sharing job queue; N i represents the total number of the i-th nodes in the resource sharing job queue; δ i represents the autocorrelation coefficient between the time span of the 5G network slice in the I-th resource sharing job queue and the node execution ability value of the i-th node device in the resource sharing job queue;

[0057] It should be further noted that in the specific implementation process, when network congestion occurs, the data analysis module compares the historical resource sharing completion time of the nodes in the resource sharing job queue with the time span of the 5G network slice of the queue, and decides whether to change the resource sharing job queue where the node is located according to the comparison result. The process includes:

[0058] When the historical resource sharing completion time of the node is greater than the time span of the 5G network slice of the queue, it is assigned to a resource sharing job queue with a lower processing priority, and the time span of the 5G network slice is compared with the resource sharing job queue with a lower processing priority. If the historical resource sharing completion time of the node is still greater than the time span of the 5G network slice of the queue, it is then assigned to a resource sharing job queue with an even lower processing priority and the 5G network slice time span comparison is repeated until the historical resource sharing completion time of the node is less than or equal to the time span of the 5G network slice of the resource sharing job queue.

[0059] It should be further noted that in the specific implementation process, the process of the data scheduling module scheduling the remaining idle time period within the time span of the 5G network slice after the resource sharing of the nodes in the resource sharing job queue is completed includes:

[0060] Determine whether there is a remaining idle time period within the 5G network slice time span after the resource sharing of the nodes in the resource sharing job queue is completed. If there is a remaining idle time period, select nodes from the lower-level processing priority queue whose historical resource sharing completion time is less than the remaining idle time period, and allocate them to the remaining idle time period. Repeat this operation until there is no remaining idle time period in the resource sharing job queue or there are no nodes that meet the condition that the historical resource sharing completion time is less than or equal to the remaining idle time period, thereby reducing redundant data and improving the performance of the 5G Internet of Things data sharing platform.

[0061] The above embodiments are only used to illustrate the technical method of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those of ordinary skill in the art should understand that the technical method of the present invention can be modified or equivalently replaced without departing from the spirit and scope of the technical method of the present invention.

Claims

1. A data sharing system based on 5G Internet of Things, including a monitoring center, characterized in that, The monitoring center is communicatively connected to a data acquisition module, a data storage module, a data processing module, a data analysis module, and a data scheduling module; The data acquisition module is used to collect the shared resource data information uploaded by each node in the 5G Internet of Things data sharing platform and generate a resource sharing job queue; The data storage module is used to be communicatively connected to the middleware node 5G and send data information to multiple distributed databases for storage according to different middleware nodes; The data processing module is used to generate the node execution ability values of each node in each resource sharing job queue, and establish 5G network slices with different time spans for each resource sharing job queue according to the expected node scheduling number and the time span constraint condition of scheduling shared resources in each resource sharing job queue; The data analysis module sets the execution priority for the nodes and sets the processing priority for the resource sharing job queue. When network congestion occurs, it compares the historical resource sharing completion time of the nodes in the resource sharing job queue with the time span of the 5G network slice of the queue, and decides whether to change the resource sharing job queue where the node is located according to the comparison result; The data scheduling module is used to schedule the remaining idle time periods within the time span of the 5G network slice after the node resources in the resource sharing job queue are shared.

2. The data sharing system based on 5G Internet of Things according to claim 1, wherein The process of the data acquisition module collecting the shared resource data information uploaded by each node in the 5G Internet of Things data sharing platform includes: Several middleware nodes are built between the data acquisition module and the 5G Internet of Things data sharing platform. Each middleware node is linked to a corresponding distributed database. The acquisition period is set and the acquisition time of the data information is marked, and the acquired data information is sent to the middleware node; wherein, the data information includes the resource scheduling start time and the resource scheduling end time.

3. The data sharing system based on 5G Internet of Things according to claim 2, characterized in that, The process of the data storage module sending data information to multiple distributed databases for storage according to different middleware nodes includes: It is communicatively connected to the middleware node 5G and is provided with a real-time database and an offline database; the real-time database includes multiple distributed real-time databases, and the offline database includes multiple distributed offline databases. The data information collected in the current acquisition period is sent to multiple distributed real-time databases for storage according to different middleware nodes. When the real-time database detects new data information in the next acquisition period, the data information collected in multiple distributed real-time databases in the current acquisition period is sent to multiple distributed offline databases for storage, and it is marked as historical data.

4. The data sharing system based on 5G Internet of Things according to claim 3, characterized in that, The process of the data processing module generating the node execution ability values of each node in each resource sharing job queue includes: Obtain the historical resource sharing completion time of the node according to the historical resource scheduling start time and the historical resource scheduling end time of the node, and obtain the node execution ability value according to the historical resource sharing completion time.

5. A data sharing system based on 5G Internet of Things according to claim 4, characterized in that, The process of the data processing module establishing 5G network slices with different time spans for each resource sharing job queue according to the expected node scheduling slot number and the time span constraint condition of scheduling shared resources in each resource sharing job queue includes: Set the time-span constraint conditions and the expected number of node scheduling slots for the resource sharing job queue. Generate the data processing capacity value of the resource sharing job queue according to the time-span constraint conditions and the expected number of node scheduling slots for the resource sharing job queue. Set up the 5G network slice comparison table, match the generated data processing capacity value of the resource sharing job queue with the 5G network slice comparison table, and obtain the 5G network slice corresponding to the time span.

6. A data sharing system based on 5G Internet of Things according to claim 5, characterized in that, The process of the data analysis module setting the execution priority for nodes and setting the processing priority for the resource sharing job queue includes: Sort and set the execution priority according to the nodes in each resource sharing job queue by the method of sorting the node execution capacity values from high to low. At the same time, sort and set the processing priority by the method of sorting the 5G network slice time spans of each resource sharing job queue from low to high.

7. A data sharing system based on 5G Internet of Things according to claim 6, characterized in that, When network congestion occurs, the process of the data analysis module comparing the historical resource sharing completion time of the nodes in the resource sharing job queue with the 5G network slice time span of the queue and deciding whether to change the resource sharing job queue where the nodes are located includes: When the historical resource sharing completion time of a node is greater than the 5G network slice time span of the queue, allocate it to a resource sharing job queue with a lower processing priority, and compare it with the 5G network slice time span of the resource sharing job queue with a lower processing priority. If the historical resource sharing completion time of the node is still greater than the 5G network slice time span of the queue, then allocate it to a resource sharing job queue with an even lower processing priority and repeat the 5G network slice time span comparison until the historical resource sharing completion time of the node is less than or equal to the 5G network slice time span of the resource sharing job queue.

8. A data sharing system based on 5G Internet of Things according to claim 7, characterized in that, The process of the data scheduling module scheduling the remaining idle time period within the 5G network slice time span after the resource sharing of the nodes in the resource sharing job queue is completed includes: Judge whether there is a remaining idle time period within the 5G network slice time span after the resource sharing of the nodes in the resource sharing job queue is completed. If there is a remaining idle time period, select nodes with a historical resource sharing completion time less than the remaining idle time period from the queue with a lower processing priority, allocate them to the remaining idle time period, and repeat this operation until there is no remaining idle time period in the resource sharing job queue or there are no nodes that meet the condition that the historical resource sharing completion time is less than or equal to the remaining idle time period.

Images