Resource scheduling system and method of Internet of Things platform

Abstract

The invention provides a resource scheduling system and method of an Internet of Things platform, and belongs to the technical field of Internet of Things. The system comprises an Internet of Things management center, an Internet of Things service center, an Internet of Things resource allocation service module and an Internet of Things load state cache service module. The method comprises the steps of dynamically increasing and decreasing the number of the Internet of Things service centers and dynamically distributing the Internet of Things service centers to the Internet of Things device. According to the invention, the number of the Internet of Things service centers can be dynamically increased or decreased through the Internet of Things management center according to the connection of the Internet of Things equipment and the load change of the processing request. Therefore, when the system accesses a large number of Internet of Things devices, the service capability can be quickly expanded, and meanwhile, the situation that resources are wasted when the access quantity of the devices is small is also avoided.

Description

Technical Field

[0001] The invention relates to a resource scheduling system and method for an Internet of Things platform, and belongs to the technical field of the Internet of Things. Background Art

[0002] The rapid development of IoT technology has brought great changes to our lives. From smart homes to smart cities, they have achieved smarter and more efficient operations by connecting different devices. However, with the popularity of IoT devices, the number of IoT devices in the IoT platform is increasing, and more IoT service centers are needed to jointly provide services.

[0003] As the number of IoT devices increases day by day, more IoT service centers are needed to jointly provide services. IoT service centers are dynamically allocated to each IoT device that needs to use the IoT platform, so that each IoT service center can balance the load and avoid some IoT service centers being overloaded and unable to provide services normally. In addition, the number of IoT service centers is dynamically increased or decreased between the peak and off-peak periods of the IoT service center load to ensure that the IoT platform can provide services of sufficient quality. In traditional technical solutions, when it is found that resources are about to be insufficient by monitoring relevant resource indicators, resource expansion plans are arranged to maintain the IoT platform resources to maintain the desired quality standards. Traditional practices are not conducive to rapid response and rapid execution of adjustments, so a more flexible resource scheduling method is envisioned. Summary of the invention

[0004] The purpose of the present invention is to provide a resource scheduling system and method for an Internet of Things platform to achieve a suitable balance between service quality and resource consumption.

[0005] In order to achieve the above object, the present invention is implemented through the following technical solutions: IoT management center: configured to increase or decrease the number of IoT service centers according to the load changes of IoT device connections and processing requests; monitor the load status of IoT service centers in real time; IoT Service Center: It is configured as the server of the IoT platform, establishes connections with IoT devices, and processes requests from IoT devices; when IoT devices go online or offline, it updates the online status information of IoT devices to the IoT load status cache service module; it regularly updates the resource usage status of this service center to the IoT load status cache service module; IoT resource allocation service module: configured to provide authentication functions to ensure that only authorized IoT devices can use the services of the IoT platform; allocate IoT service centers to IoT devices and update information to the IoT load status cache service module; IoT load status cache service module: configured to record and query the IoT service center information assigned to the IoT device; update the number of online devices and online device information of each IoT service center in real time; cache the key performance indicators of the IoT service center, including CPU and memory usage; and determine whether the IoT service center has the ability to add new IoT devices.

[0006] Preferably, the load status of the Internet of Things service center includes the number of online Internet of Things devices, CPU usage, and memory usage, which are obtained by querying the Internet of Things load status cache service.

[0007] Preferably, the Internet of Things service center comprises a link keep-alive module for ensuring that the connection between the Internet of Things device and the Internet of Things service center remains valid.

[0008] A resource scheduling method for an Internet of Things platform includes: dynamically increasing or decreasing the number of Internet of Things service centers and dynamically allocating Internet of Things service centers to Internet of Things devices.

[0009] Preferably, the specific method for dynamically increasing or decreasing the number of IoT service centers is as follows: The IoT management center periodically queries the IoT load status cache service to obtain indicators of various load statuses; When the load status indicator reaches a high load condition, the IoT management center establishes a new IoT service center; updates the IoT load status cache service, and marks the newly established IoT service center as a place where new IoT devices can be added; When the load status indicator reaches a low load condition, the IoT load status cache service is updated, and the IoT service center to be closed is marked as not being able to add new IoT devices; Adjust the IoT device replacement service center that uses the IoT service center marked as not being able to add new IoT devices.

[0010] Preferably, the IoT load status cache service is checked regularly to confirm whether the number of online IoT devices in the IoT service center to be closed has returned to zero. If so, the resources of the IoT service center are released.

[0011] Preferably, the specific method of dynamically allocating the Internet of Things service center to the Internet of Things device is as follows: The IoT management center queries the IoT load status cache service to check whether the IoT device has an assigned IoT service center; If there is one, the IoT service center will be used; if not, the IoT load status cache service module will be used to query the IoT service center with the lowest current load and to which new devices can be added, the IoT device will be added to the IoT service center, and the information in the IoT load status cache service will be updated; If no IoT service center is found to which the new device can be added, an IoT service center is added, the newly added IoT service center is allocated to the IoT device, and the information in the IoT load status cache service is updated.

[0012] The advantages of the present invention are that the Internet of Things management center of the present invention can dynamically increase or decrease the number of Internet of Things service centers according to the load changes of the connection and processing requests of the Internet of Things devices. This ensures that the system can quickly expand its service capabilities when facing a large number of Internet of Things devices, and also avoids the waste of resources when the number of device accesses is small.

[0013] Through the IoT resource allocation service module, the system can allocate the best service center for IoT devices based on the real-time load of the IoT service center. This ensures that the load of each service center is relatively balanced, improving the overall performance and response speed of the system.

[0014] The IoT load status cache service module updates and caches the load information and performance indicators of each service center in real time, such as CPU and memory usage. This enables the IoT management center to make more accurate resource scheduling decisions based on this information and optimize resource utilization.

[0015] The link keep-alive module included in the IoT service center ensures that the connection between the IoT device and the service center remains valid, reduces service interruptions caused by network fluctuations or equipment failures, and improves service reliability and continuity.

[0016] The authentication function provided by the IoT resource allocation service module ensures that only authorized IoT devices can use the services of the IoT platform, improving the security of the system.

[0017] The IoT management center monitors the load status of the IoT service center and automatically schedules resources, which greatly reduces the administrator's workload and improves the convenience of management. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] The accompanying drawings are used to provide further understanding of the present invention and constitute a part of the specification. They are used to explain the present invention together with the embodiments of the present invention and do not constitute a limitation of the present invention.

[0019] Figure 1 This is a schematic diagram of the process of dynamically increasing or decreasing the number of Internet of Things service centers in the present invention.

[0020] Figure 2 This is a schematic diagram of the process of dynamically allocating an Internet of Things service center to an Internet of Things device according to the present invention. DETAILED DESCRIPTION

[0021] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0022] Example 1 A resource scheduling system and method for an Internet of Things platform achieves a proper balance between service quality and resource consumption.

[0023] In order to achieve the above object, the present invention is implemented through the following technical solutions: IoT Management Center: is configured to increase or decrease the number of IoT service centers according to the load changes of IoT device connections and processing requests; and monitor the load status of IoT service centers in real time.

[0024] Internet of Things Service Center: configured as the server of the Internet of Things platform, establishing connections with Internet of Things devices and processing requests from Internet of Things devices; updating the online status information of the Internet of Things devices to the Internet of Things load status cache service module when the Internet of Things devices go online or go offline; regularly updating the resource usage status of this service center to the Internet of Things load status cache service module; the load status of the Internet of Things service center includes the number of online Internet of Things devices, CPU usage rate, and memory usage rate, which are obtained by querying the Internet of Things load status cache service; the Internet of Things service center includes a link keep-alive module to ensure that the connection between the Internet of Things devices and the Internet of Things service center is continuously valid.

[0025] IoT resource allocation service module: configured to provide authentication functions to ensure that only authorized IoT devices can use the services of the IoT platform; allocate IoT service centers to IoT devices, and update information to the IoT load status cache service module.

[0026] IoT load status cache service module: configured to record and query the IoT service center information assigned to the IoT device; update the number of online devices and online device information of each IoT service center in real time; cache the key performance indicators of the IoT service center, including CPU and memory usage; and determine whether the IoT service center has the ability to add new IoT devices.

[0027] It should be noted that the IoT management center can dynamically increase or decrease the number of IoT service centers according to the load changes of IoT device connections and processing requests. This dynamic scaling capability enables the system to quickly adapt to the access of IoT devices of different sizes, greatly improving the scalability of the system. By monitoring the load status of the IoT service center in real time and dynamically allocating IoT devices to the service center based on this information, the system can ensure that the load of each service center is relatively balanced, avoiding resource waste and bottlenecks, thereby optimizing resource utilization. The link keep-alive module included in the IoT service center ensures that the connection between the IoT device and the service center is continuously effective, reduces service interruptions caused by network fluctuations or equipment failures, and improves service reliability and stability. The authentication function provided by the IoT resource allocation service module ensures that only authorized IoT devices can use the services of the IoT platform, effectively preventing the access of unauthorized devices and enhancing the security of the system. The IoT management center automatically monitors the load status, dynamically increases and decreases the number of service centers, and allocates IoT devices, greatly reducing the workload of administrators and improving management efficiency. Through dynamic resource scheduling and load balancing, the system can maintain fast response and low latency, provide high-quality services for IoT devices, and thus improve user experience. By optimizing resource utilization and dynamic scaling, the system can reduce unnecessary hardware and software investment and lower operating costs.

[0028] Example 2 A resource scheduling method for an Internet of Things platform includes: dynamically increasing or decreasing the number of Internet of Things service centers and dynamically allocating Internet of Things service centers to Internet of Things devices.

[0029] Optional, such as Figure 1 As shown, the specific methods for dynamically increasing or decreasing the number of IoT service centers are as follows: The IoT management center periodically queries the IoT load status cache service to obtain indicators of various load statuses.

[0030] When the load status indicator reaches a high load condition, the Internet of Things Management Center establishes a new Internet of Things service center; updates the Internet of Things load status cache service, and marks the newly established Internet of Things service center as a place where new Internet of Things devices can be added.

[0031] When the indicator of the load status reaches a low load condition, the IoT load status cache service is updated, and the IoT service center to be closed is marked as not being able to add new IoT devices.

[0032] Adjust the IoT device replacement service center that uses the IoT service center marked as not being able to add new IoT devices.

[0033] The IoT load status cache service is checked regularly to confirm whether the number of online IoT devices in the IoT service center to be closed has returned to zero. If so, the resources of the IoT service center are released.

[0034] Optional, such as Figure 2 As shown, the specific method of dynamically allocating the IoT service center to the IoT device is as follows: The IoT management center queries the IoT load status cache service to check whether the IoT device has an assigned IoT service center; If there is one, the IoT service center will be used; if not, the IoT load status cache service module will be used to query the IoT service center with the lowest current load and to which new devices can be added, the IoT device will be added to the IoT service center, and the information in the IoT load status cache service will be updated; If no IoT service center is found to which the new device can be added, an IoT service center is added, the newly added IoT service center is allocated to the IoT device, and the information in the IoT load status cache service is updated.

[0035] This embodiment also relates to interaction scenarios between an IoT device and an IoT platform, including but not limited to the following scenarios: (1) The IoT device goes online, that is, the IoT device establishes a link with the IoT platform and uses its services.

[0036] (1-1) The IoT device sends a device online request to the IoT resource allocation service.

[0037] (1-2) After receiving the above request, the IoT resource allocation service checks whether the IoT device has the authority to use the IoT platform. If so, it proceeds to (1-3); otherwise, it feeds the result back to the IoT device.

[0038] (1-3) Dynamically assign IoT service centers to IoT devices that need to use the IoT platform. Feedback IoT service center information to IoT devices.

[0039] (1-4) The IoT device establishes an IoT link with the IoT service center.

[0040] (2) The IoT platform requires the IoT device to replace the IoT service center.

[0041] (2-1) The IoT platform sends a reconnection request to the IoT device.

[0042] (2-2) After receiving the above request, the IoT device disconnects the IoT link and performs step (1) again to bring the IoT device online.

[0043] The embodiment of the present disclosure also provides a resource scheduling device for an Internet of Things platform, including a processor and a memory. Optionally, the device may also include a communication interface and a bus. The processor, the communication interface, and the memory may communicate with each other through the bus. The communication interface may be used for information transmission. The processor may call the logic instructions in the memory to execute the resource scheduling method for the Internet of Things platform of the above embodiment.

[0044] In addition, the logic instructions in the above-mentioned memory can be implemented in the form of software functional units and can be stored in a computer-readable storage medium when sold or used as an independent product.

[0045] The memory, as a computer-readable storage medium, can be used to store software programs and computer executable programs, such as program instructions / modules corresponding to the method in the embodiment of the present disclosure. The processor executes the functional application and data processing by running the program instructions / modules stored in the memory, that is, the resource scheduling method of the Internet of Things platform in the above embodiment is implemented.

[0046] The memory may include a program storage area and a data storage area, wherein the program storage area may store an operating system and an application required for at least one function; the data storage area may store data created according to the use of the terminal device, etc. In addition, the memory may include a high-speed random access memory and may also include a non-volatile memory.

[0047] The embodiment of the present disclosure provides a computer-readable storage medium storing computer-executable instructions, wherein the computer-executable instructions are configured to execute the resource scheduling method of the Internet of Things platform.

[0048] The computer-readable storage medium mentioned above may be a transient computer-readable storage medium or a non-transitory computer-readable storage medium.

[0049] The technical solution of the embodiment of the present disclosure can be embodied in the form of a software product, which is stored in a storage medium and includes one or more instructions for enabling a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the method described in the embodiment of the present disclosure. The aforementioned storage medium may be a non-transient storage medium, including: a USB flash drive, a mobile hard disk, a read-only memory (ROM, Read-Only Memory), a random access memory (RAM, Random Access Memory), a disk or an optical disk, and other media that can store program codes, or a transient storage medium.

[0050] Finally, it should be noted that the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art can still modify the technical solutions described in the aforementioned embodiments or replace some of the technical features therein by equivalents. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A resource scheduling system for an Internet of Things platform, characterized in that: include: IoT Management Center: is configured to increase or decrease the number of IoT service centers based on the load changes of IoT device connections and processing requests; Real-time monitoring of the load status of the IoT service center; IoT Service Center: It is configured as the server of the IoT platform, establishes connections with IoT devices, and processes requests from IoT devices; when IoT devices go online or offline, it updates the online status information of IoT devices to the IoT load status cache service module; it regularly updates the resource usage status of this service center to the IoT load status cache service module; IoT resource allocation service module: configured to provide authentication functions to ensure that only authorized IoT devices can use the services of the IoT platform; allocate IoT service centers to IoT devices and update information to the IoT load status cache service module; IoT load status cache service module: configured to record and query IoT service center information assigned to IoT devices; Update the number and information of online devices in each IoT service center in real time; Cache key performance indicators of the IoT service center, including CPU and memory usage; Determine whether the IoT service center has the ability to add new IoT devices.

2. The resource scheduling system of the Internet of Things platform according to claim 1, characterized in that: The load status of the IoT service center includes the number of online IoT devices, CPU usage, and memory usage, which can be obtained by querying the IoT load status cache service.

3. The resource scheduling system of the Internet of Things platform according to claim 1, characterized in that: The IoT service center includes a link keep-alive module that ensures that the connection between the IoT device and the IoT service center remains valid.

4. A resource scheduling method for an Internet of Things platform using the system described in any one of claims 1 to 3, characterized in that: include: Dynamically increase or decrease the number of IoT service centers and dynamically allocate IoT service centers to IoT devices.

5. The resource scheduling method of the Internet of Things platform according to claim 4, characterized in that: The specific methods for dynamically increasing or decreasing the number of IoT service centers are as follows: The IoT management center periodically queries the IoT load status cache service to obtain indicators of various load statuses; When the load status indicator reaches a high load condition, the IoT management center establishes a new IoT service center; updates the IoT load status cache service, and marks the newly established IoT service center as a place where new IoT devices can be added; When the load status indicator reaches a low load condition, the IoT load status cache service is updated, and the IoT service center to be closed is marked as not being able to add new IoT devices; Adjust the IoT device replacement service center that uses the IoT service center marked as not being able to add new IoT devices.

6. The resource scheduling method of the Internet of Things platform according to claim 5, characterized in that: The IoT load status cache service is checked regularly to confirm whether the number of online IoT devices in the IoT service center to be closed has returned to zero. If so, the resources of the IoT service center are released.

7. The resource scheduling method of the Internet of Things platform according to claim 4, characterized in that: The specific method of dynamically allocating IoT service centers to IoT devices is as follows: The IoT management center queries the IoT load status cache service to check whether the IoT device has an assigned IoT service center; If there is one, the IoT service center will be used; if not, the IoT load status cache service module will be used to query the IoT service center with the lowest current load and to which new devices can be added, the IoT device will be added to the IoT service center, and the information in the IoT load status cache service will be updated; If no IoT service center is found to which the new device can be added, an IoT service center is added, the newly added IoT service center is allocated to the IoT device, and the information in the IoT load status cache service is updated.

8. A resource scheduling device for an Internet of Things platform, comprising a processor and a memory storing program instructions, characterized in that: The processor is configured to execute the resource scheduling method for the Internet of Things platform as described in any one of claims 4-7 when running the program instructions.

9. A computer-readable storage medium, characterized in that: A computer program is stored thereon, and when the program is executed by a processor, the method described in any one of claims 4 to 7 is implemented.

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