Ubiquitous computing power sharing method and device, equipment and storage medium

Abstract

The invention discloses a ubiquitous computing power sharing method and device, equipment and a medium, and the ubiquitous computing power sharing method comprises the steps: carrying out the resource detection and system configuration of target equipment through a built-in operation system of a non-intrusive ubiquitous computing power sharing hardware medium, and uploading the hardware resource information of the equipment to a cloud platform; virtualizing the idle disk sector into a virtual disk, and synchronizing resource information of the virtual disk to a cloud; after analyzing the resource condition of the target equipment, the cloud platform allocates a proper computing power task to the equipment; the built-in operating system creates a plurality of virtual machines on the target equipment and executes the computing power task, and finally, the task result information is transmitted back to the cloud platform; and after the verification result of the cloud platform is valid, the built-in operating system automatically recovers the original state of the target equipment. Efficient and secure computing power sharing for devices that can interface with non-intrusive ubiquitous computing power sharing hardware media is achieved.

Description

Technical Field

[0001] The present invention relates to the field of computing power sharing, and particularly to a ubiquitous computing power sharing method, device, equipment and storage medium. Background Art

[0002] With the rapid development of emerging technologies such as artificial intelligence (AI), big data, blockchain, and the metaverse, the global demand for distributed computing power of GPUs is increasing day by day. However, the construction and maintenance costs of computing power resources are high, and many enterprises and individuals are deterred by the high investment. At the same time, devices such as personal computers, data centers, and enterprise servers often have a large amount of idle computing power during daily use. If these wasted resources can be effectively utilized, the overall utilization efficiency of global computing power resources will be greatly improved. However, for devices such as personal computers, data centers, and enterprise servers, installing and configuring computing power sharing software has a certain technical threshold for users, and it has a certain degree of invasiveness to the devices. A large amount of software work is required to maintain security while sharing computing power, which hinders the enthusiasm of users of devices that can provide computing power for ubiquitous computing power sharing. Therefore, there is an urgent need for a ubiquitous computing power sharing method to solve the problem that it is not convenient for devices not connected to the ubiquitous computing power sharing network to achieve ubiquitous computing power sharing under the existing technology. Summary of the Invention

[0003] Embodiments of the present invention provide a ubiquitous computing power sharing method, device, equipment and storage medium, aiming to solve the problem that it is not convenient for devices not connected to the computing power sharing network to achieve computing power sharing under the existing technology.

[0004] In a first aspect, embodiments of the present invention provide a ubiquitous computing power sharing method, which is applied to a non-intrusive ubiquitous computing power sharing hardware medium. The ubiquitous computing power sharing hardware medium is equipped with a built-in operating system, and the ubiquitous computing power sharing hardware medium is hot-pluggably docked with a target device through an interface. The method includes:

[0005] Detecting resources and configuring the system of the target device through the built-in operating system, and uploading the hardware resource information of the target device to the cloud platform;

[0006] Virtualizing continuous and idle sectors into a virtual disk through the built-in operating system, and uploading the resource information of the virtual disk to the cloud platform;

[0007] Analyzing the resource information of the virtual disk and the hardware resource information of the target device by the cloud platform to allocate appropriate computing power tasks to the target device;

[0008] The built-in operating system constructs multiple virtual machines on the target device according to the computing power task to execute the computing power task and obtain result information, and uploads the result information to the cloud platform;

[0009] After the cloud platform verifies that the result information is valid, the built-in operating system restores the original state of the target device.

[0010] In a second aspect, an embodiment of the present invention further provides an ubiquitous computing power sharing device, including units for executing the ubiquitous computing power sharing method as described above.

[0011] In a third aspect, an embodiment of the present invention further provides a computer device, which includes a memory and a processor connected to the memory; the memory is used to store a computer program; the processor is used to run the computer program stored in the memory to execute the steps of the above-mentioned ubiquitous computing power sharing method.

[0012] In a fourth aspect, an embodiment of the present invention further provides a computer-readable storage medium, the storage medium stores a computer program, the computer program includes program instructions, and the program instructions can implement the steps of the above-mentioned ubiquitous computing power sharing method when executed by a processor.

[0013] Compared with the prior art, the beneficial effects of the present invention are:

[0014] In the technical solution of the present invention, the built-in operating system of the non-intrusive ubiquitous computing power sharing hardware medium is used to detect the resources of the target device and configure the system, and upload the hardware resource information of the device to the cloud platform; virtualize the idle disk sectors into virtual disks, and synchronize the resource information of the virtual disks to the cloud; after the cloud platform analyzes the resource situation of the target device, allocate suitable computing power tasks to the device; the built-in operating system creates multiple virtual machines on the target device and executes the computing power tasks, and finally transmits the task result information back to the cloud platform; after the cloud platform verifies that the result is valid, the built-in operating system automatically restores the original state of the target device. It realizes efficient and secure computing power sharing for devices that can be docked with non-intrusive ubiquitous computing power sharing hardware media. Description of the Drawings

[0015] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following will briefly introduce the drawings required for the description of the embodiments. Obviously, the following drawings are some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained according to these drawings without creative efforts.

[0016] Figure 1 It is a flowchart of the ubiquitous computing power sharing method provided by the present invention;

[0017] Figure 2 It is the first sub - flowchart of the ubiquitous computing power sharing method provided by the present invention;

[0018] Figure 3 It is the second sub - flowchart of the ubiquitous computing power sharing method provided by the present invention;

[0019] Figure 4 It is the third sub - flowchart of the ubiquitous computing power sharing method provided by the present invention;

[0020] Figure 5 It is the fourth sub - flowchart of the ubiquitous computing power sharing method provided by the present invention;

[0021] Figure 6 It is the fifth sub - flowchart of the ubiquitous computing power sharing method provided by the present invention;

[0022] Figure 7 It is a schematic block diagram of the unit of the ubiquitous computing power sharing device provided by the present invention;

[0023] Figure 8 It is a schematic block diagram of the computer device provided by the embodiments of the present invention. Detailed implementation manners

[0024] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, rather than all of the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0025] It should be understood that when used in this specification and the appended claims, the terms "comprising" and "including" indicate the presence of the described features, wholes, steps, operations, elements, and / or components, but do not exclude the presence or addition of one or more other features, wholes, steps, operations, elements, components, and / or their combinations.

[0026] It should also be understood that the terms used in this specification of the present invention are only for the purpose of describing specific embodiments and are not intended to limit the present invention. As used in this specification of the present invention and the appended claims, unless the context clearly indicates otherwise, the singular forms "a", "an", and "the" are intended to include the plural forms.

[0027] It should be further understood that the term "and / or" used in this specification of the present invention and the appended claims refers to any combination and all possible combinations of one or more of the associated listed items, and includes these combinations.

[0028] To solve the problem that it is not convenient for devices not connected to the computing power sharing network to achieve computing power sharing in the prior art, the present invention proposes a ubiquitous computing power sharing method. The ubiquitous computing power sharing method is applied to a non-intrusive ubiquitous computing power sharing hardware medium, which is equipped with a built-in operating system. The ubiquitous computing power sharing hardware medium is hot-pluggable and docked with the target device through an interface. Refer to Figures 1 to 6 , the method includes:

[0029] S110. Detect the resources of the target device and configure the system through the built-in operating system, and upload the hardware resource information of the target device to the cloud platform;

[0030] For the ubiquitous computing power sharing hardware medium, its architecture mainly includes a storage medium, an embedded system, and an interface. At the same time, it supports the hot-pluggable function, that is, a pre-installed hot-pluggable driver protocol stack is used, and the target device does not need to be restarted when inserted or removed, realizing seamless docking with the target device. The so-called storage medium is a high-performance solid-state drive (SSD) or a large-capacity USB flash drive, which is used to support fast read and write operations. The so-called embedded system uses a built-in lightweight Linux operating system in actual operation to ensure compatibility and convenience. It is customized based on the Linux kernel, optimizes resource occupancy, and supports multi-tasking. In terms of the interface, in order to be compatible with various devices such as personal computers and servers, a docking solution using general interfaces such as USB3.0 / 3.1 and PCIe is used. In addition, in specific implementation, the ubiquitous computing power sharing hardware medium also integrates an ARM / x86 processor module.

[0031] The ubiquitous computing power sharing hardware medium is hot-pluggable and docked with the target device through an interface. After the device connection is successful, the ubiquitous computing power sharing hardware medium starts its built-in operating system. The built-in operating system first comprehensively detects the hardware resources of the target device, specifically including the status and capacity of resources such as the CPU, memory, and storage, to ensure the availability of device resources. The detection process is implemented through the hardware interface and communicates with the hardware of the target device through the connection protocol. After the detection is completed, the built-in operating system uploads the hardware resource information of the target device, such as the number of CPU cores, memory capacity, and hard disk space, to the cloud platform for subsequent computing power task allocation and scheduling.

[0032] Further, refer to Figure 2 , step S110 includes:

[0033] S111. Boot the built-in operating system through UEFI / MBR, and perform working environment configuration and driver loading;

[0034] S112. Check the status of the hardware resources of the target device, and read the overall parameters and integrate them into the hardware resource information;

[0035] S113. Establish a secure connection with the cloud platform through an encrypted channel, register the hardware resource information, and complete authentication and authorization.

[0036] In an embodiment of the present invention, after the ubiquitous computing power sharing hardware medium is hot-plugged into the target device, the startup process of the built-in operating system is completed by the UEFI or MBR bootloader. By guiding through UEFI / MBR during the computer startup process, it can ensure the correct loading of the built-in operating system on the target device. During the startup process, the UEFI / MBR bootloader first loads the core part of the built-in operating system and performs necessary initialization operations, such as memory allocation, device detection, and hardware initialization. This process ensures that the system can smoothly enter the operating state and lays a foundation for subsequent hardware resource detection and task execution. When the built-in operating system starts, it configures the working environment and loads the drivers required by the target device. During this process, the built-in operating system automatically identifies the hardware architecture of the target device and loads the corresponding drivers according to the hardware type. For example, for the storage device, network interface, display device, etc. of the target device, the built-in operating system ensures that their drivers are correctly installed so that the device resources can be reasonably utilized in subsequent task execution. At this time, the system ensures that all functions of the device work properly, and the device enters the available state for computing power contribution.

[0037] With the completion of the working environment configuration, the built-in operating system comprehensively checks the hardware resources of the target device. At this time, the built-in operating system reads the status information of the hardware such as the CPU, memory, hard disk, network interface, etc. of the target device, and combines the hardware specifications and performance parameters of the device to integrate them into a complete hardware resource information table. The hardware resource information table includes the resource type, resource capacity, and performance status of the target device, such as CPU load, memory occupancy, remaining storage capacity, etc., providing a basis for subsequent computing power task allocation.

[0038] To ensure the security of data transmission, the built-in operating system connects to the cloud platform through an encrypted channel. During specific operations, the built-in operating system adopts encryption protocols such as SSL / TLS to ensure the security and integrity of data during transmission. After the connection is established, the built-in operating system uploads the hardware resource information of the target device to the cloud platform for registration. During the upload process, the system performs authentication and authorization operations to ensure the legitimacy of the device and prevent unauthorized devices from accessing shared resources. This process usually includes steps such as device key authentication and user credential verification to ensure that only legally authorized devices can upload hardware resource information and participate in computing power sharing. After the authentication is passed, the built-in operating system sends an authorization request to the cloud platform, and the cloud platform decides whether to allow the device to join the computing power sharing network based on the authorization information of the target device. The process of authentication and authorization guarantees security and avoids the access of malicious devices and resource abuse.

[0039] S120. Virtualize consecutive and idle sectors into a virtual disk through the built-in operating system, and upload the resource information of the virtual disk to the cloud platform;

[0040] After completing the resource detection of the target device, the built-in operating system scans the hard disk of the target device to identify consecutive and unused idle disk sectors. According to the situation of the idle resources, the built-in operating system virtualizes these idle sectors into a virtual disk and generates corresponding virtual disk resource information. Essentially, a virtual disk divides a part of the physical disk into a logical storage unit for subsequent virtual machines to use. The built-in operating system uploads the relevant information of the virtual disk to the cloud platform and records it in the resource information of the target device for the cloud platform to analyze.

[0041] Further, referring to Figure 3 , step S120 includes:

[0042] S121. Detect the disk sectors of the target device through the built-in operating system and mark consecutive and idle sectors;

[0043] S122. Virtualize the consecutive and idle sectors into independent virtual disks through KVM, and upload the resource information of the virtual disks to the cloud platform through the encrypted channel.

[0044] In an embodiment of the present invention, after the built-in operating system is started and configured, the system will perform a comprehensive scan of the hard disk of the target device to identify each sector on the disk. Among them, the disk includes the ubiquitous computing power sharing hardware medium of the present invention and the disks of other storage devices connected in a non-invasive manner. In this process, the built-in operating system will check the usage status of each disk sector to determine which sectors are free and do not contain any valid data or applications. This detection process is carried out by accessing the file system structure of the hard disk, and the operating system marks all consecutive and free sectors as available resources for virtualization processing.

[0045] After the built-in operating system identifies consecutive and free disk sectors, the next step is to use KVM (Kernel-based Virtual Machine) virtualization technology to virtualize these free sectors into independent virtual disks. Through KVM, the built-in operating system can aggregate and virtualize consecutive free disk sectors into a logical storage unit, that is, a virtual disk. Attributes such as the size and performance of the virtual disk are dynamically configured according to the actual space and I / O performance of the virtualized disk sectors. During the virtualization process, the built-in operating system will create a virtual disk device through KVM and mount it to the system to ensure that the virtual disk can be accessed and managed like a normal disk. At this time, the storage space of the virtual disk is ready and can be used by subsequent virtual machines or for storing data generated during the execution of computing power tasks.

[0046] After the virtual disk is created, the built-in operating system will collect and organize the relevant resource information of the virtual disk, such as capacity, I / O performance, usage status, etc., and establish a secure connection with the cloud platform through an encrypted channel. The built-in operating system uploads the resource information of the virtual disk to the cloud platform through this encrypted channel. After receiving this information, the cloud platform will merge it with the hardware resource information of the device and store and manage it in the cloud database. The uploaded resource information of the virtual disk also includes the availability and expected load capacity of the disk, so that the cloud platform can perform reasonable computing power task allocation according to the resource status of the target device. Through the upload of the virtual disk, the cloud platform can keep track of the virtualization resource status of the target device in real time, thereby optimizing resource scheduling to ensure that computing tasks can be executed on the most suitable device.

[0047] S130. Analyze the resource information of the virtual disk and the hardware resource information of the target device through the cloud platform to allocate appropriate computing power tasks to the target device;

[0048] The cloud platform comprehensively analyzes the resource information uploaded by the target device, evaluates the computing power and storage resources of the device, and determines the type and scale of computing power tasks that it can undertake. The cloud platform also considers factors such as the network bandwidth and computing load of the target device, selects suitable computing power tasks, and schedules the tasks to the target device. Task scheduling not only allocates according to the device's hardware resources but also takes into account the current state of the device to ensure that the task allocation maximally utilizes the device resources and avoids overloading.

[0049] Further, referring to Figure 4 , step S130 includes:

[0050] S131. Evaluate the computing power provided by the target device through the cloud platform based on the hardware resource information and the resource information of the virtual disk to obtain an evaluation result;

[0051] S132. The cloud platform allocates computing power tasks to the target device according to the evaluation result;

[0052] S133. The cloud platform transmits multiple computing power task data packets allocated to the target device to the built-in operating system through the encrypted channel.

[0053] In an embodiment of the present invention, after the hardware resource information and the virtual disk resource information of the target device are uploaded to the cloud platform, the cloud platform first comprehensively analyzes this information. The information that needs to be comprehensively analyzed includes the hardware resource information and the virtual disk resource information. The hardware resource information includes the CPU model, number of cores, memory size, storage space, network bandwidth, etc. of the target device, while the virtual disk resource information includes the capacity, I / O performance, current load, etc. of the virtual disk. Among them, the storage space includes the storage space resources of the ubiquitous computing power sharing hardware medium of the present invention and other storage devices accessed in a non-invasive manner. Based on this information, the cloud platform evaluates the overall computing power of the target device through a preset evaluation algorithm. The goal of the evaluation is to determine whether the device currently has the ability to process certain computing tasks and its optimal performance parameters when processing tasks. For example, if the CPU performance of the target device is strong but its storage I / O performance is weak, the cloud platform may preferentially allocate compute-intensive tasks rather than storage-intensive tasks, and vice versa. Through the comprehensive evaluation of the hardware and virtual disk resources, the cloud platform can accurately understand the computing power and bottlenecks of each device, and thus provide data support for subsequent task allocation. In particular, when the target device holder continues to use the target device, the built-in operating system will also continuously upload the information that needs to be comprehensively analyzed through real-time monitoring to ensure that both the computing power provider and the computing power demander can normally complete their respective work requirements when the target device is in use.

[0054] After the evaluation is completed, the cloud platform makes a reasonable computing power task allocation for the target device according to the evaluation results. According to the resource status of the target device, the cloud platform can dynamically allocate suitable tasks for it. The type, quantity, and complexity of the tasks will be adjusted according to the available resources of the device. The cloud platform will also consider other factors, such as the priority of the tasks, the computing requirements of the tasks, the current load of the device, and the communication latency between the device and the cloud platform. Through the scheduling of the cloud platform, the utilization efficiency of the device resources can be maximized, and tasks can be prevented from exceeding the processing capacity range of the device, thereby improving the overall performance of the computing power sharing system. After the task allocation is completed, the cloud platform encapsulates multiple computing power tasks allocated to the target device into data packets and transmits them to the built-in operating system of the target device through an encrypted channel. After receiving the encrypted data packets, the built-in operating system decrypts the tasks and loads the task content onto the target device for execution.

[0055] S140. Use the built-in operating system to construct multiple virtual machines on the target device according to the computing power tasks to execute the computing power tasks to obtain result information, and upload the result information to the cloud platform;

[0056] After the task allocation is completed, the built-in operating system dynamically creates multiple virtual machines on the target device according to the computing power tasks allocated by the cloud platform. Each virtual machine is allocated a certain amount of computing resources to execute the allocated tasks. Through virtualization technology, multiple virtual machines can run in parallel on the target device, which not only improves the resource utilization rate but also avoids direct intrusion into the original device system. During the process of the virtual machines executing the computing power tasks, the built-in operating system will monitor the running status of the virtual machines in real time to ensure the stability and efficiency of task execution. When the virtual machines complete the computing power tasks, the generated result information will be uploaded to the cloud platform through a secure channel.

[0057] Further, referring to Figure 5 , step S140 includes:

[0058] S141. Divide the virtual disk resources and the hardware resources according to the multiple computing power tasks;

[0059] S142. Use the built-in operating system to set multiple execution containers through Docker according to the division results;

[0060] S143. Inject a sub-operating system into each execution container through the built-in operating system to obtain multiple execution virtual machines

[0061] S144. Allocate an independent virtual network card to each execution virtual machine through the built-in operating system;

[0062] S145. Execute multiple said computing power tasks through multiple execution virtual machines to obtain result information, package it, and transmit it to the cloud platform via the encrypted channel.

[0063] In an embodiment of the present invention, after the cloud platform completes task allocation according to the evaluation results of the hardware resources and virtual disk resources of the target device, the built-in operating system needs to perform resource partitioning on the target device. First, the operating system will reasonably allocate the available virtual disk space and the hardware resources of the device according to the requirements of the computing power tasks. Specifically, the operating system will dynamically adjust the amount of resources required for each task according to the size, complexity of the task, and its resource requirements. The purpose is to ensure that each virtual machine or container can execute tasks within an independent resource pool, while ensuring the maximization of resource utilization and the non-interference between tasks. For example, if some tasks have high requirements for computing performance, the operating system will allocate more CPU cores and memory, while for storage-intensive tasks, more virtual disk space will be allocated to them.

[0064] After completing the partitioning of the hardware and virtual disk resources, the built-in operating system will, based on these partitioning results, use Docker containerization technology to create corresponding execution containers for each computing power task. The built-in operating system will allocate specific resources to each container, such as the number of CPU cores, memory size, storage space, etc., and assign tasks to the corresponding containers for execution. These containers will share the operating system kernel of the host machine, but each container is isolated from each other, thus ensuring the security and stability of task execution.

[0065] Furthermore, the CPU, memory, and I / O resources of each container are restricted through Cgroups technology to avoid resource competition. In actual use, the LUKS encryption technology will also be adopted to encrypt the file system of the container to ensure the security of data during storage and transmission. The Linux-based AppArmor or SELinux technology will also be used to restrict the access rights of the container to the file system of the target device, thereby ensuring the information security of the device of the computing power provider when sharing computing power.

[0066] In order to further improve the independence and flexibility of task execution, the built-in operating system also injects a sub-operating system into each Docker container, such as a lightweight virtual operating system or a customized operating system. Thus, each container not only has its own resource environment but also has an independent operating system running environment, enabling it to run tasks completely independently like a virtual machine. In this way, each execution virtual machine created by the built-in operating system in the container can simulate the behavior of a physical machine, possess the complete functions of an operating system, and be able to independently execute the computing power tasks assigned to it. The combination of containerization and virtualization makes the execution environment of each task more flexible and controllable, while also simplifying the allocation and management of resources.

[0067] To ensure that network communication between multiple execution virtual machines does not interfere with each other, the built-in operating system configures an independent virtual network card for each execution virtual machine. Each virtual network card corresponds to an independent network interface and can perform secure network communication with other virtual machines, the host machine, and the cloud platform. By allocating an independent virtual network card to each execution virtual machine, the built-in operating system can ensure network traffic isolation between virtual machines, preventing data leakage or unnecessary interference. These virtual network cards can be connected to the physical network interface of the host machine through a virtual switch, thereby enabling communication with the cloud platform or other devices.

[0068] After resources are allocated to each execution virtual machine, the operating system is injected, and the network is configured, multiple execution virtual machines start to execute their respective allocated computing power tasks in parallel. Each virtual machine runs independently in an isolated execution environment according to the requirements of the task, processes the computing power task, and generates result information. Since each virtual machine has independent resources and a network environment, they can efficiently process multiple computing power tasks in parallel, thus greatly improving the task processing efficiency. After the task is completed, the virtual machine aggregates the calculation results through the task management module of the built-in operating system and prepares to upload them to the cloud platform.

[0069] After all computing power tasks are executed, the built-in operating system packages the result information of each virtual machine to form a unified result data packet. This result information usually includes the execution status of the task, the calculation result, and the log data generated during the execution process, etc. To ensure the security and integrity of the data, the packaged data will be transmitted to the cloud platform through an encrypted channel.

[0070] S150. When the cloud platform verifies that the result information is valid, the built-in operating system restores the original state of the target device.

[0071] After the cloud platform receives the result information uploaded by the target device, it first verifies the task result to ensure that there are no errors or data leakage during the execution process. After passing the verification, the cloud platform will archive the task result and update the corresponding resource usage record. At this time, the built-in operating system will automatically restore the original state of the target device according to the verification result. The restoration process includes stopping the virtual machine, releasing the virtual disk resources, and cleaning the temporary data of the device to ensure that the device returns to the normal working state without affecting the subsequent use of the device.

[0072] Further, referring to Figure 6 , step S150 includes:

[0073] S151. Decrypt and verify the result information through the cloud platform;

[0074] S152. After the cloud platform verifies that the task result is valid, it sends a release instruction to the built-in operating system;

[0075] S153. After receiving the release instruction through the built-in operating system, it automatically clears all temporary data and caches and restores the original state of the target device;

[0076] S154. Through the built-in operating system, it reports the device exit information to the cloud platform via the encrypted channel, including the result information and the device exit status.

[0077] In an embodiment of the present invention, after multiple computing power tasks are executed and the task results are uploaded to the cloud platform through the encrypted channel, the cloud platform first verifies the received result information. This verification process includes two important steps: decryption and data verification. Since the task result information is encrypted during transmission, the cloud platform will first use the preset encryption key to decrypt the received data packet. After decryption, the cloud platform can restore the original result information, including the task execution status, calculation results, and log data that may be generated during the task execution. After decryption, the cloud platform will perform data verification. The content of the verification usually includes integrity check of task execution, verification of result correctness, and troubleshooting of errors or exceptions during task execution. Specifically, the cloud platform may compare the task result with the expected result, or use techniques such as verification and digital signature to ensure the integrity and accuracy of the data. If the task result is not tampered with and meets the expectations, the cloud platform will consider the task execution to be valid.

[0078] Once the cloud platform confirms that the task execution result is valid, it will send a release instruction to the built-in operating system of the target device. The purpose of this instruction is to notify the built-in operating system that the task has been completed and the result has been verified, and the next step of resource release and cleaning work can be carried out. The release instruction usually includes restoring resources, clearing temporary data, and restoring the state. Specifically, the release instruction will require the operating system to release the computing resources allocated for the task back to the device's resource pool, and require the operating system to clear all temporary data, cache data, etc. related to task execution to ensure that the resources of the target device are fully released and prevent any useless data from occupying the device's storage space. It will also require the built-in operating system to restore the target device to its original state before task execution to ensure that the device can continue to execute other tasks or enter the standby state.

[0079] After the execution of the release instruction, the built-in operating system not only restores the device to its original state but also reports the device's exit information to the cloud platform through an encrypted channel. The report includes task result information and the device's exit status. The task result information is the final calculation result of the previous task execution, including but not limited to task output data, calculation logs, execution status, etc. The built-in operating system will organize this information into a standard format and upload it to the cloud platform through an encrypted channel. The device exit status refers to the state of the device recorded by the built-in operating system after the task execution, reporting whether the device is currently in an idle state, whether it has been successfully restored to the original configuration, and indicating whether the device is ready to accept new tasks or enter the standby mode. If an exception or error occurs during the task execution, the exit status report will also include the device's exception information, such as whether there are resources that have not been fully released, caches that have not been cleared, or whether the device has crashed or restarted. These status information can help the cloud platform timely understand the actual situation of the device and ensure the healthy management of computing power resources.

[0080] In addition, after receiving the exit information sent by the built-in operating system, the cloud platform will further process the report. The cloud platform first decrypts the received task result information and verifies its integrity to ensure that the data has not been tampered with or damaged. The platform will check whether the task result is consistent with the expected output. If an abnormality is found, necessary audits and processing will be carried out. The cloud platform will also determine whether the device can continue to accept new tasks or whether further inspections are needed based on the device exit status. If the report shows that the device is in an abnormal state, the platform may mark the device as unavailable until it is repaired or maintained. The cloud platform will also record the transaction records of the computing power providers and demanders for fee calculation. The cloud platform also needs to update the available resource status of the device based on the device's exit report and mark whether the device is in the "idle" or "restored" state in the resource pool to ensure efficient and accurate task allocation in the cloud.

[0081] Figure 7 It is a schematic block diagram of a ubiquitous computing power sharing device 600 provided by an embodiment of the present invention. As Figure 7 shown, corresponding to the above ubiquitous computing power sharing method, the present invention also provides a ubiquitous computing power sharing device 600. The ubiquitous computing power sharing device includes units for executing the above ubiquitous computing power sharing device method, and the device can be configured in terminals such as desktop computers, tablet computers, smart phones, etc. Specifically, please refer to Figure 7 and, the ubiquitous computing power sharing device includes:

[0082] A resource detection and system configuration unit 610, configured to perform resource detection and system configuration on the target device through the built-in operating system, and upload the hardware resource information of the target device to the cloud platform;

[0083] A virtual disk construction unit 620, configured to virtualize consecutive and free sectors into a virtual disk through the built-in operating system, and upload resource information of the virtual disk to the cloud platform;

[0084] A task allocation unit 630, configured to analyze the resource information of the virtual disk and the hardware resource information of the target device through the cloud platform to allocate appropriate computing power tasks to the target device;

[0085] A virtual machine construction unit 640, configured to construct multiple virtual machines on the target device according to the computing power tasks through the built-in operating system to execute the computing power tasks to obtain result information, and upload the result information to the cloud platform;

[0086] A finishing unit 650, configured to restore the original state of the target device by the built-in operating system after the cloud platform verifies that the result information is valid.

[0087] Further, the resource detection and system configuration unit 610 includes:

[0088] A boot startup unit, configured to boot the built-in operating system through UEFI / MBR, and perform working environment configuration and driver loading;

[0089] A hardware resource status check unit, configured to check the status of the hardware resources of the target device, and read overall parameters to integrate them into the hardware resource information;

[0090] A node registration unit, configured to establish a secure connection with the cloud platform through an encrypted channel, register the hardware resource information, and complete authentication and authorization.

[0091] Further, the virtual disk construction unit 620 includes:

[0092] A disk detection unit, configured to detect the disk sectors of the target device through the built-in operating system, and mark consecutive and free sectors;

[0093] A KVM virtualization unit, configured to virtualize the consecutive and free sectors into independent virtual disks through KVM, and upload the resource information of the virtual disks to the cloud platform through the encrypted channel.

[0094] Further, the task allocation unit 630 includes:

[0095] A computing power evaluation unit, configured to evaluate the computing power provided by the target device through the cloud platform based on the hardware resource information and the resource information of the virtual disk to obtain an evaluation result;

[0096] A task matching unit, configured to enable the cloud platform to allocate computing power tasks to the target device according to the evaluation results;

[0097] A downlink transmission unit, configured to enable the cloud platform to transmit multiple computing power task data packets allocated to the target device to the built-in operating system through the encrypted channel.

[0098] Further, the virtual machine construction unit 640 includes:

[0099] A resource partitioning unit, configured to partition the virtual disk resources and the hardware resources according to the multiple computing power tasks;

[0100] A container generation unit, configured to enable the built-in operating system to set up multiple execution containers through Docker according to the partitioning results;

[0101] A subroutine injection unit, configured to enable the built-in operating system to inject a sub-operating system into each execution container to obtain multiple execution virtual machines

[0102] A virtual network card allocation unit, configured to enable the built-in operating system to allocate an independent virtual network card to each execution virtual machine;

[0103] , configured to execute the multiple computing power tasks through the multiple execution virtual machines to obtain result information, package the result information and transmit the result information to the cloud platform through the encrypted channel.

[0104] Further, the ending unit 650 includes:

[0105] A result verification unit, configured to enable the cloud platform to verify, decrypt and perform data verification on the result information;

[0106] A release instruction issuing unit, configured to send a release instruction to the built-in operating system when the cloud platform verifies that the task result is valid;

[0107] A resource release unit, configured to enable the built-in operating system to automatically clear all temporary data and caches and restore the original state of the target device after receiving the release instruction;

[0108] An exit information confirmation unit, configured to enable the built-in operating system to report the device exit information, including the result information and the device exit status, to the cloud platform through the encrypted channel.

[0109] The above ubiquitous computing power sharing device 600 can be implemented in the form of a computer program, and the computer program can run on a computer device as shown in Figure 8 shown.

[0110] Please refer to Figure 8 , Figure 8It is a schematic block diagram of a computer device provided by an embodiment of the present application. The computer device 500 can be a terminal or a server. Among them, the terminal can be an electronic device with communication functions such as a desktop computer, a tablet computer, or a smart phone. The server can be an independent server or a server cluster composed of multiple servers.

[0111] Refer to Figure 8 , the computer device 500 includes a processor 502, a memory, and a network interface 505 connected through a system bus 501. Among them, the memory can include a non-volatile storage medium 503 and an internal memory 504.

[0112] The non-volatile storage medium 503 can store an operating system 5031 and a computer program 5032. The computer program 5032 includes program instructions. When the program instructions are executed, the processor 502 can be caused to execute a ubiquitous computing power sharing method.

[0113] The processor 502 is used to provide computing and control capabilities to support the operation of the entire computer device 500.

[0114] The internal memory 504 provides an environment for the operation of the computer program 5032 in the non-volatile storage medium 503. When the computer program 5032 is executed by the processor 502, the processor 502 can be caused to execute a ubiquitous computing power sharing method.

[0115] The network interface 505 is used for network communication with other devices. Those skilled in the art can understand that Figure 7 the structure shown in

[0116] is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device 500 to which the solution of the present application is applied. The specific computer device 500 may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0117] It should be understood that in the embodiments of the present application, the processor 502 may be a central processing unit (CPU), and the processor 502 may also be other general-purpose processors, digital signal processors (DSPs), application specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. Among them, the general-purpose processor may be a microprocessor or the processor may also be any conventional processor, etc.

[0118] Those of ordinary skill in the art can understand that all or part of the processes in the methods of the above embodiments can be completed by instructing relevant hardware through a computer program. The computer program includes program instructions, and the computer program can be stored in a storage medium, and the storage medium is a computer-readable storage medium. The program instructions are executed by at least one processor in the computer system to implement the process steps of the above method embodiments.

[0119] Therefore, the present invention also provides a storage medium. The storage medium may be a computer-readable storage medium. The storage medium stores a computer program, where the computer program includes program instructions. When the program instructions are executed by the processor, the processor executes the steps of the above method.

[0120] The storage medium may be various computer-readable storage media such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a magnetic disk, or an optical disc that can store program codes.

[0121] Those of ordinary skill in the art can realize that the units and algorithm steps of the examples described in combination with the embodiments disclosed herein can be implemented by electronic hardware, computer software, or a combination of the two. To clearly illustrate the interchangeability of hardware and software, the components and steps of the examples have been generally described according to their functions in the above description. Whether these functions are executed in a hardware or software manner depends on the specific application and design constraints of the technical solution. Professional technicians can use different methods to implement the described functions for each specific application, but such implementation should not be considered to exceed the scope of the present invention.

[0122] In several embodiments provided by the present invention, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For example, the division of each unit is only a logical function division, and there may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed.

[0123] The steps in the method embodiments of the present invention can be adjusted, combined, and deleted according to actual needs. The units in the device embodiments of the present invention can be combined, divided, and deleted according to actual needs. In addition, the functional units in each embodiment of the present invention can be integrated into a processing unit, or each unit can exist physically alone, or two or more units can be integrated into one unit.

[0124] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes several instructions for causing a computer device (which can be a personal computer, a terminal, or a network device, etc.) to execute all or part of the steps of the methods described in each embodiment of the present invention.

[0125] As described above, the above are only specific embodiments of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art within the technical scope disclosed by the present invention can easily think of various equivalent modifications or substitutions, and these modifications or substitutions should be covered by the protection scope of the present invention. Therefore, the protection scope of the present invention should be subject to the protection scope of the claims.

Claims

1. A ubiquitous computing power sharing method, characterized in that: Applied to a non-intrusive ubiquitous computing power sharing hardware medium, the ubiquitous computing power sharing hardware medium is equipped with a built-in operating system, the ubiquitous computing power sharing hardware medium is hot-plugged and connected to a target device through an interface, and the method includes: Perform resource detection and system configuration on the target device through the built-in operating system, and upload the hardware resource information of the target device to the cloud platform; Virtualizing continuous and idle sectors into a virtual disk through the built-in operating system, and uploading resource information of the virtual disk to a cloud platform; Analyzing the resource information of the virtual disk and the hardware resource information of the target device through the cloud platform to allocate a suitable computing task to the target device; Constructing multiple virtual machines on the target device according to the computing task through the built-in operating system to execute the computing task to obtain result information, and uploading the result information to the cloud platform; When the cloud platform verifies that the result information is valid, the built-in operating system restores the original state of the target device.

2. The ubiquitous computing power sharing method according to claim 1, characterized in that: The step of performing resource detection and system configuration on the target device through the built-in operating system and uploading the hardware resource information of the target device to the cloud platform includes: Boot the built-in operating system through UEFI / MBR to configure the working environment and load the driver; Check the status of the hardware resources of the target device, and read the overall parameters to integrate them into the hardware resource information; A secure connection is established with the cloud platform through an encrypted channel, the hardware resource information is registered, and identity authentication and authorization are completed.

3. The ubiquitous computing power sharing method according to claim 2, characterized in that: The step of virtualizing continuous and idle sectors into a virtual disk through the built-in operating system and uploading resource information of the virtual disk to the cloud platform includes: Detecting the disk sectors of the target device through the built-in operating system and marking continuous and free sectors; The continuous and idle sectors are virtualized into independent virtual disks through KVM, and the resource information of the virtual disks is uploaded to the cloud platform through the encrypted channel.

4. The ubiquitous computing power sharing method according to claim 3, characterized in that: The step of analyzing the resource information of the virtual disk and the hardware resource information of the target device through the cloud platform to allocate a suitable computing task to the target device includes: Evaluating the computing power provided by the target device through the cloud platform according to the hardware resource information and the resource information of the virtual disk to obtain an evaluation result; The cloud platform allocates computing tasks to the target device according to the evaluation result; The cloud platform transmits multiple computing task data packets assigned to the target device to the built-in operating system through the encrypted channel.

5. The ubiquitous computing power sharing method according to claim 4, characterized in that: The step of constructing multiple virtual machines on the target device according to the computing task by the built-in operating system to execute the computing task to obtain result information, and uploading the result information to the cloud platform includes: Dividing the virtual disk resources and the hardware resources according to a plurality of the computing tasks; Using the built-in operating system, multiple execution containers are set through Docker according to the partitioning result; By injecting a sub-operating system into each execution container through the built-in operating system, a plurality of execution virtual machines are obtained; Allocate an independent virtual network card to each executing virtual machine through the built-in operating system; The plurality of computing tasks are executed by a plurality of execution virtual machines to obtain result information, which is packaged and transmitted to the cloud platform via the encrypted channel.

6. The ubiquitous computing power sharing method according to claim 5, characterized in that: After the cloud platform verifies that the result information is valid, the step of restoring the target device to its original state by the built-in operating system includes: Verify the result information through the cloud platform to perform decryption and data verification; When the cloud platform verifies that the task result is valid, it sends a release instruction to the built-in operating system; After receiving the release instruction, the built-in operating system automatically cleans up all temporary data and caches to restore the original state of the target device.

7. The ubiquitous computing power sharing method according to claim 6, characterized in that: After the step of automatically cleaning up all temporary data and cache after receiving the release instruction by the built-in operating system and restoring the original state of the target device, the step further includes: The built-in operating system reports the device's exit information to the cloud platform via the encrypted channel, including the result information and the device exit status.

8. A ubiquitous computing power sharing device, characterized in that: Used to execute the ubiquitous computing power sharing method as described in any one of claims 1 to 7.

9. A computer device, characterized in that: The computer device comprises a memory and a processor connected to the memory; the memory is used to store a computer program; the processor is used to run the computer program stored in the memory to execute the steps of the method as claimed in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: The storage medium stores a computer program, wherein the computer program includes program instructions, and when the program instructions are executed by a processor, the steps of the method according to any one of claims 1 to 7 can be implemented.

Images