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

Abstract

The application discloses a ubiquitous computing power sharing method and device, equipment and medium, wherein the ubiquitous computing power sharing method detects and configures the system of a target device through the built-in operating system of a non-intrusive ubiquitous computing power sharing hardware medium, uploads the hardware resource information of the device to a cloud platform, virtualizes idle disk sectors into virtual disks, and synchronizes the resource information of the virtual disks to the cloud; the cloud platform analyzes the resource condition of the target device, and allocates appropriate 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 returns the task result information 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. Efficient and safe computing power sharing of the device that can be connected to the non-intrusive ubiquitous computing power sharing hardware medium is realized.

Description

Technical Field

[0001] This invention relates to the field of computing power sharing, and specifically to a ubiquitous computing power sharing method, apparatus, device, and storage medium. Background Technology

[0002] With the rapid development of emerging technologies such as artificial intelligence (AI), big data, blockchain, and metaverse, the global demand for distributed computing power from GPUs is growing rapidly. However, the construction and maintenance costs of computing resources are high, deterring many enterprises and individuals from investing heavily. Meanwhile, personal computers, data centers, and enterprise servers often have a large amount of idle computing power during daily use. Effective utilization of these wasted resources would greatly improve the overall efficiency of global computing resources. However, installing and configuring computing power sharing software for personal computers, data centers, and enterprise servers presents a certain technical barrier for users and is somewhat intrusive to the equipment. Extensive software work is required to maintain security while sharing computing power, hindering the enthusiasm of users who can provide computing power to share ubiquitous computing power. Therefore, a ubiquitous computing power sharing method is urgently needed to address the problem of the inconvenience of sharing ubiquitous computing power for devices not connected to ubiquitous computing power sharing networks under current technology. Summary of the Invention

[0003] The embodiments of the present invention provide a ubiquitous computing power sharing method, apparatus, device and storage medium, which aims 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 prior art.

[0004] In a first aspect, embodiments of the present invention provide a ubiquitous computing power sharing method, applied to a non-intrusive ubiquitous computing power sharing hardware medium, wherein 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-swappably connected to a target device via an interface, the method comprising:

[0005] The built-in operating system is used to perform resource detection and system configuration on the target device, and the hardware resource information of the target device is uploaded to the cloud platform.

[0006] The built-in operating system virtualizes continuous and idle sectors into virtual disks, and uploads the resource information of the virtual disks to the cloud platform.

[0007] The cloud platform analyzes the resource information of the virtual disk and the hardware resource information of the target device 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, obtains the result information, and uploads the result information to the cloud platform;

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

[0010] Secondly, embodiments of the present invention also provide a ubiquitous computing power sharing device, including a unit for executing the ubiquitous computing power sharing method described above.

[0011] Thirdly, embodiments of the present invention also provide a computer device, the computer device including 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 perform the steps of the above-described ubiquitous computing power sharing method.

[0012] Fourthly, embodiments of the present invention also provide a computer-readable storage medium storing a computer program, the computer program including program instructions, which, when executed by a processor, can implement the steps of the above-described ubiquitous computing power sharing method.

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

[0014] In the technical solution of this invention, the built-in operating system of a non-intrusive ubiquitous computing power sharing hardware medium performs resource detection and system configuration on the target device, and uploads the device's hardware resource information to the cloud platform; idle disk sectors are virtualized into virtual disks, and the resource information of the virtual disks is synchronized to the cloud; after analyzing the resource status of the target device, the cloud platform allocates 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 sends the task result information back to the cloud platform; after the cloud platform verifies the validity of the results, the built-in operating system automatically restores the original state of the target device. This achieves efficient and secure computing power sharing for devices that can interface with non-intrusive ubiquitous computing power sharing hardware media. Attached Figure Description

[0015] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the following description of the embodiments will be briefly introduced. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

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

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

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

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

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

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

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

[0023] Figure 8 A schematic block diagram of a computer device provided for an embodiment of the present invention. Detailed Implementation

[0024] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection 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, integrals, steps, operations, elements and / or components, but do not exclude the presence or addition of one or more other features, integrals, steps, operations, elements, components and / or collections thereof.

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

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

[0028] To address the inconvenience of sharing computing power among devices not connected to a computing power sharing network in existing technologies, this invention proposes a ubiquitous computing power sharing method. This method applies to a non-intrusive ubiquitous computing power sharing hardware medium. This hardware medium carries a built-in operating system and hot-swappably connects to the target device via an interface. (Refer to...) Figures 1 to 6 The method includes:

[0029] S110. The target device is subjected to resource detection and system configuration through the built-in operating system, and the hardware resource information of the target device is uploaded to the cloud platform;

[0030] The architecture of ubiquitous computing power sharing hardware mainly includes storage media, embedded systems, and interfaces. It supports hot-swapping, meaning it comes pre-installed with a hot-swapping driver protocol stack, allowing seamless integration with target devices without requiring a restart when inserting or removing the device. The storage media is a high-performance solid-state drive (SSD) or a high-capacity USB flash drive, supporting fast read and write operations. The embedded system, in practice, uses a built-in lightweight Linux operating system for compatibility and convenience. It is based on a customized Linux kernel, optimized for resource consumption, and supports multitasking. For interfaces, to ensure compatibility with various devices such as personal computers and servers, it uses a connection scheme supporting common interfaces such as USB 3.0 / 3.1 and PCIe. Furthermore, in practical implementations, the ubiquitous computing power sharing hardware also integrates an ARM / x86 processor module.

[0031] The ubiquitous computing power sharing hardware medium connects to the target device via a hot-swappable interface. After successful connection, the ubiquitous computing power sharing hardware medium boots its built-in operating system. The built-in operating system first performs a comprehensive check of the target device's hardware resources, specifically the status and capacity of resources such as CPU, memory, and storage, to ensure resource availability. This check is implemented through the hardware interface and communicates with the target device's hardware via a connection protocol. After the check is complete, the built-in operating system uploads the target device's hardware resource information, 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] Furthermore, referring to Figure 2 Step S110 includes:

[0033] S111. Boot the built-in operating system via UEFI / MBR to configure the working environment and load drivers;

[0034] S112. Perform a status check on the hardware resources of the target device and read the overall parameters to integrate them into the hardware resource information.

[0035] S113. Securely connect to the cloud platform through an encrypted channel, register the hardware resource information, and complete identity verification and authorization.

[0036] In one embodiment of the present invention, after the ubiquitous computing power sharing hardware medium is hot-swapped with the target device, the boot process of the built-in operating system is completed by a UEFI or MBR bootloader. Booting via UEFI / MBR during the computer boot process ensures that the built-in operating system is correctly loaded on the target device. During the boot process, the UEFI / MBR bootloader first loads the core 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, laying the 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 target device's storage devices, network interfaces, display devices, etc., the built-in operating system ensures that their drivers are correctly installed so that device resources can be reasonably utilized in subsequent task execution. At this time, the system ensures that all functions of the device are working normally, and the device enters a state where computing power contribution is available.

[0037] Once the working environment is configured, the built-in operating system performs a comprehensive check of the target device's hardware resources. At this point, the operating system reads the status information of the target device's CPU, memory, hard drive, network interface, and other hardware, and combines this information with the device's hardware specifications and performance parameters to create a complete hardware resource information table. This table includes the target device's resource type, resource capacity, and performance status, such as CPU load, memory usage, and remaining storage capacity, providing a basis for subsequent computing power allocation.

[0038] To ensure data transmission security, the built-in operating system connects to the cloud platform via an encrypted channel. Specifically, the built-in operating system employs 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 target device's hardware resource information to the cloud platform for registration. During the upload process, the system performs identity verification and authorization to ensure the device's legitimacy and prevent unauthorized devices from accessing shared resources. This process typically includes steps such as device key authentication and user credential verification, ensuring that only legitimately authorized devices can upload hardware resource information and participate in computing power sharing. After successful identity verification, the built-in operating system sends an authorization request to the cloud platform, which then decides whether to allow the device to join the computing power sharing network based on the target device's authorization information. This identity verification and authorization process ensures security and prevents malicious devices from accessing the network and abusing resources.

[0039] S120. The built-in operating system virtualizes continuous and idle sectors into virtual disks, and uploads the resource information of the virtual disks to the cloud platform.

[0040] After completing the target device resource detection, the built-in operating system scans the target device's hard drive, identifying contiguous and unused free disk sectors. Based on the availability of free resources, the built-in operating system virtualizes these free sectors into virtual disks and generates corresponding virtual disk resource information. Essentially, a virtual disk is a portion of the physical disk divided into a logical storage unit for subsequent use by virtual machines. The built-in operating system uploads the relevant information of the virtual disks to the cloud platform and records it in the target device's resource information for analysis by the cloud platform.

[0041] Furthermore, referring to Figure 3 Step S120 includes:

[0042] S121. The built-in operating system is used to detect the disk sectors of the target device and mark consecutive and free sectors.

[0043] S122. The contiguous and idle sectors are virtualized into independent virtual disks using KVM, and the resource information of the virtual disks is uploaded to the cloud platform through the encrypted channel.

[0044] In one embodiment of the present invention, after the built-in operating system has started and been configured, the system performs a full scan of the target device's hard drive to identify each sector on the disk. The disk includes the ubiquitous computing power sharing hardware medium of the present invention and other disks of storage devices accessed in a non-intrusive manner. During this process, the built-in operating system checks 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 performed by accessing the hard drive's file system structure; the operating system marks all contiguous and free sectors as available resources, ready for virtualization processing.

[0045] After the built-in operating system identifies contiguous and free disk sectors, the next step is to virtualize these free sectors into independent virtual disks using KVM (Kernel-based Virtual Machine) virtualization technology. Through KVM, the built-in operating system can aggregate and virtualize contiguous free disk sectors into a single logical storage unit, i.e., a virtual disk. The size, performance, and other attributes of the virtual disk are dynamically configured based on the actual space and I / O performance of the virtualized disk sectors. During virtualization, the built-in operating system creates a virtual disk device using KVM and mounts it to the system, ensuring that the virtual disk can be accessed and managed like a regular disk. At this point, the virtual disk's storage space is ready for use by subsequent virtual machines or for storing data generated during the execution of computing tasks.

[0046] After the virtual disk is created, the built-in operating system collects and organizes relevant resource information, such as capacity, I / O performance, and usage status, and securely connects to the cloud platform via an encrypted channel. The built-in operating system uploads the virtual disk's resource information to the cloud platform through this encrypted channel. Upon receiving this information, the cloud platform merges it with the device's hardware resource information and stores and manages it in its cloud database. The uploaded virtual disk resource information also includes the disk's availability and expected load capacity, enabling the cloud platform to allocate computing tasks appropriately based on the target device's resource status. Through the upload of the virtual disk, the cloud platform can monitor the virtualization resource status of the target device in real time, thereby optimizing resource scheduling and ensuring that computing tasks are 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 to assess its computing power and storage resources, determining the types and scale of computing tasks it can handle. The cloud platform also considers factors such as the target device's network bandwidth and computing load, selecting suitable computing tasks and scheduling them to the target device. Task scheduling not only allocates tasks based on device hardware resources but also considers the device's current state, ensuring that task allocation maximizes the utilization of device resources and avoids overloading.

[0049] Furthermore, referring to Figure 4 Step S130 includes:

[0050] S131. Based on the hardware resource information and the virtual disk resource information, the computing power provided by the target device is evaluated through the cloud platform to obtain the evaluation result;

[0051] S132. The cloud platform allocates computing power tasks to the target device based on the evaluation results;

[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 one embodiment of the present invention, after the hardware resource information and virtual disk resource information of the target device are uploaded to the cloud platform, the cloud platform first performs a comprehensive analysis of this information. The information to be comprehensively analyzed includes hardware resource information and virtual disk resource information. Hardware resource information includes the target device's CPU model, number of cores, memory size, storage space, network bandwidth, etc., while virtual disk resource information includes the virtual disk's capacity, I / O performance, current load, etc. 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-intrusive manner. Based on this information, the cloud platform evaluates the overall computing power of the target device using a preset evaluation algorithm. The goal of the evaluation is to determine whether the device currently has the ability to handle certain computing tasks, and its optimal performance parameters for handling these tasks. For example, if the target device has strong CPU performance but weak storage I / O performance, the cloud platform may prioritize allocating compute-intensive tasks rather than storage-intensive tasks, and vice versa. Through a comprehensive evaluation of hardware and virtual disk resources, the cloud platform can accurately understand the computing power and bottlenecks of each device, thereby providing data support for subsequent task allocation. In particular, when the target device owner continues to use the target device, the built-in operating system will continuously upload updated information that needs to be comprehensively analyzed in real time to ensure that both the computing power provider and the computing power demander can complete their respective work requirements normally when the target device is used.

[0054] After the assessment is completed, the cloud platform allocates computing power tasks to the target device based on the assessment results. The cloud platform can dynamically assign suitable tasks based on the resource status of the target device. The type, number, and complexity of the tasks are adjusted according to the available resources of the device. The cloud platform also considers other factors, such as task priority, task computational requirements, the device's current load, and communication latency between the device and the cloud platform. Through the cloud platform's scheduling, the efficiency of device resource utilization can be maximized, and tasks can be prevented from exceeding the device's processing capacity, thereby improving the overall performance of the computing power sharing system. After task allocation, the cloud platform encapsulates the multiple computing power tasks assigned to the target device into data packets and transmits them to the target device's built-in operating system through an encrypted channel. Upon 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. Using the built-in operating system, multiple virtual machines are built on the target device according to the computing power task to execute the computing power task and obtain result information, and the result information is uploaded to the cloud platform;

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

[0057] Furthermore, 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. Based on the partitioning results, multiple execution containers are set up using Docker through the built-in operating system.

[0060] S143. Multiple execution virtual machines are obtained by injecting a sub-operating system into each execution container through the built-in operating system.

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

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

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

[0064] After allocating hardware and virtual disk resources, the built-in operating system uses Docker containerization technology to create corresponding execution containers for each computing task. The operating system allocates specific resources to each container, such as the number of CPU cores, memory size, and storage space, and assigns tasks to the appropriate containers for execution. These containers share the host machine's operating system kernel, but each container is isolated from the others, thus ensuring the security and stability of task execution.

[0065] Furthermore, Cgroups technology is used to limit the CPU, memory, and I / O resources of each container to avoid resource contention. In actual use, LUKS encryption technology is also employed to encrypt the container's file system, ensuring data security during storage and transmission. Linux-based AppArmor or SELinux technologies are also used to restrict container access to the target device's file system, thereby guaranteeing the information security of the computing power provider's devices when sharing computing power.

[0066] To further enhance the independence and flexibility of task execution, the built-in operating system injects a sub-operating system, such as a lightweight virtual operating system or a custom operating system, into each Docker container. This allows each container to not only have its own resource environment but also an independent operating system runtime environment, enabling it to run tasks completely independently, like a virtual machine. In this way, each execution virtual machine created within the container by the built-in operating system can simulate the behavior of a physical machine, possessing full operating system functionality and independently executing the computing tasks allocated to it. The combination of containerization and virtualization makes the execution environment of each task more flexible and controllable, while also simplifying resource allocation and management.

[0067] To ensure that network communication between multiple virtual machines does not interfere with each other, the built-in operating system configures an independent virtual network interface card (NIC) for each virtual machine. Each virtual NIC corresponds to an independent network interface, enabling secure network communication with other virtual machines, the host machine, and cloud platforms. By assigning an independent virtual NIC to each virtual machine, the built-in operating system ensures network traffic isolation between virtual machines, preventing data leaks or unnecessary interference. These virtual NICs can be connected to the host machine's physical network interface via a virtual switch, thereby enabling communication with cloud platforms or other devices.

[0068] After allocating resources, injecting the operating system, and configuring the network for each execution virtual machine, multiple execution virtual machines begin to execute their assigned computing tasks in parallel. Each virtual machine runs independently in an isolated execution environment, processing computing tasks and generating results, according to the requirements of the task. Because each virtual machine has its own independent resources and network environment, they can efficiently process multiple computing tasks in parallel, thus significantly improving task processing efficiency. After the task is completed, the virtual machine summarizes the calculation results through the task management module of its built-in operating system, preparing them for uploading to the cloud platform.

[0069] After all computing tasks are completed, the built-in operating system packages the results from each virtual machine into a unified result data package. This result information typically includes the task's execution status, computation results, and log data generated during execution. To ensure data security and integrity, the packaged data is transmitted to the cloud platform via an encrypted channel.

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

[0071] After receiving the results uploaded by the target device, the cloud platform first verifies the task results to ensure that no errors or data leaks occurred during execution. Once verification is successful, the cloud platform archives the task results and updates the corresponding resource usage records. At this point, the built-in operating system automatically restores the target device to its original state based on the verification results. The restoration process includes stopping the virtual machine, releasing virtual disk resources, and clearing temporary data on the device, ensuring that the device returns to a normal working state without affecting its subsequent use.

[0072] Furthermore, 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 the task result as valid, it sends a release command to the built-in operating system.

[0075] S153. After receiving the release command through the built-in operating system, automatically clear all temporary data and cache, and restore the target device to its original state.

[0076] S154. The device exit information, including the result information and device exit status, is reported to the cloud platform through the encrypted channel via the built-in operating system.

[0077] In one embodiment of the present invention, after executing multiple computing tasks and uploading the task results to the cloud platform via an 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 first decrypts the received data packet using a preset encryption key. After decryption, the cloud platform can recover the original result information, including the task execution status, calculation results, and log data that may have been generated during task execution. After decryption, the cloud platform performs data verification. The verification typically includes checking the integrity of the task execution, verifying the correctness of the results, and investigating errors or anomalies during task execution. Specifically, the cloud platform may compare the task results with the expected results, or use verification, digital signatures, or other technical means to ensure the integrity and accuracy of the data. If the task results have not been tampered with and meet expectations, the cloud platform considers the task execution valid.

[0078] Once the cloud platform confirms the task execution result is valid, it sends a release command to the target device's built-in operating system. This command notifies the operating system that the task has been completed and the result has been verified, allowing for the next step of resource release and cleanup. The release command typically includes restoring resources, clearing temporary data, and restoring the device's state. Specifically, the release command instructs the operating system to release the computing resources allocated to the task back to the device's resource pool and to clear all temporary data and cached data related to the task execution, ensuring that the target device's resources are fully released and preventing any useless data from occupying the device's storage space. It also instructs the built-in operating system to restore the target device to its original state before the task execution, ensuring that the device can continue to perform other tasks or enter standby mode.

[0079] After the release command is executed, 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 via an encrypted channel. The report includes task result information and the device 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, and execution status. The built-in operating system organizes this information into a standard format and uploads it to the cloud platform via an encrypted channel. The device exit status refers to the state of the device recorded by the built-in operating system after task execution, reporting whether the device is currently idle, whether it has successfully restored to its original configuration, and whether the device is ready to accept new tasks or enter standby mode. If an anomaly or error occurs during task execution, the exit status report will also include anomaly information, such as whether resources have not been fully released, cache has not been cleared, or whether the device has crashed or restarted. This status information helps the cloud platform understand the actual situation of the device in a timely manner, ensuring healthy management of computing resources.

[0080] In addition, after receiving the exit information from the built-in operating system, the cloud platform further processes the report. First, the cloud platform decrypts the received task result information and verifies its integrity to ensure the data has not been tampered with or corrupted. The platform checks whether the task results match the expected output; if an anomaly is found, necessary auditing and processing are performed. The cloud platform also determines whether the device can continue to accept new tasks or whether further checks are needed based on the device's exit status. If the report indicates an abnormal device status, the platform may mark the device as unavailable until repair or maintenance is performed. The cloud platform also records transaction records between the computing power provider and the requester for cost calculation. Furthermore, the cloud platform needs to update the device's resource availability status based on the exit report and mark the device in the resource pool as either "idle" or "recovered," ensuring efficient and accurate task allocation in the cloud.

[0081] Figure 7 This is a schematic block diagram of a ubiquitous computing power sharing device 600 provided in an embodiment of the present invention. Figure 7 As shown, corresponding to the above ubiquitous computing power sharing method, the present invention also provides a ubiquitous computing power sharing device 600. This ubiquitous computing power sharing device includes a unit for executing the above-described ubiquitous computing power sharing method, and the device can be configured in a desktop computer, tablet computer, smartphone, or other terminal. Specifically, please refer to... Figure 7 The ubiquitous computing power sharing device includes:

[0082] The resource detection and system configuration unit 610 is used 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] The virtual disk construction unit 620 is used to virtualize contiguous 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.

[0084] The task allocation unit 630 is used 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] The virtual machine construction unit 640 is used to construct multiple virtual machines on the target device according to the computing power task through the built-in operating system, execute the computing power task, obtain result information, and upload the result information to the cloud platform;

[0086] The closing unit 650 is used 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] Furthermore, the resource detection and system configuration unit 610 includes:

[0088] The boot unit is used to boot the built-in operating system via UEFI / MBR, and to configure the working environment and load drivers.

[0089] The hardware resource status checking unit is used to check the status of the hardware resources of the target device and read the overall parameters to integrate them into the hardware resource information.

[0090] The node registration unit is used to securely connect to the cloud platform through an encrypted channel, register the hardware resource information, and complete identity verification and authorization.

[0091] Furthermore, the virtual disk building unit 620 includes:

[0092] The disk detection unit is used to detect the disk sectors of the target device through the built-in operating system and mark consecutive and free sectors.

[0093] The KVM virtualization unit is used to virtualize the contiguous 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.

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

[0095] The computing power evaluation unit is used to evaluate the computing power provided by the target device through the cloud platform based on the hardware resource information and the virtual disk resource information to obtain the evaluation result;

[0096] A task matching unit is used by the cloud platform to allocate computing power tasks to the target device based on the evaluation results;

[0097] The downlink transmission unit is used by 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] Furthermore, the virtual machine building unit 640 includes:

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

[0100] The container generation unit is used to set up multiple execution containers using Docker based on the partitioning results through the built-in operating system.

[0101] The subroutine injection unit is used to inject a sub-operating system into each execution container through the built-in operating system to obtain multiple execution virtual machines.

[0102] A virtual network interface card (NIC) allocation unit is used to allocate an independent virtual NIC to each running virtual machine through the built-in operating system.

[0103] It is used to execute multiple 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.

[0104] Furthermore, the finishing unit 650 includes:

[0105] The result verification unit is used by the cloud platform to verify the result information by decryption and data verification.

[0106] The release command issuing unit is used to send a release command to the built-in operating system after the cloud platform verifies that the task result is valid.

[0107] The resource release unit is used to automatically clean up all temporary data and cache after the built-in operating system receives the release command, and restore the original state of the target device.

[0108] The exit information confirmation unit is used by the built-in operating system to report the device's exit information to the cloud platform through the encrypted channel, including the result information and the device's exit status.

[0109] The aforementioned ubiquitous computing power sharing device 600 can be implemented as a computer program, which can be used in, for example... Figure 8 It runs on the computer device shown.

[0110] Please see Figure 8 , Figure 8This is a schematic block diagram of a computer device 500 provided in an embodiment of this application. The computer device 500 can be a terminal or a server. The terminal can be an electronic device with communication functions, such as a desktop computer, tablet computer, or smartphone. The server can be a standalone server or a server cluster composed of multiple servers.

[0111] See Figure 8 The computer device 500 includes a processor 502, a memory, and a network interface 505 connected via a system bus 501. The memory may include a non-volatile storage medium 503 and internal memory 504.

[0112] The non-volatile storage medium 503 may store an operating system 5031 and a computer program 5032. The computer program 5032 includes program instructions that, when executed, cause the processor 502 to perform a ubiquitous computing power sharing method.

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

[0114] The internal memory 504 provides an environment for the execution 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 execute a ubiquitous computing power sharing method.

[0115] This network interface 505 is used for network communication with other devices. Those skilled in the art will understand that... Figure 7 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device 500 to which 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.

[0116] The processor 502 is used to run a computer program 5032 stored in a memory to implement the steps of the above method.

[0117] It should be understood that in the embodiments of this application, the processor 502 may be a central processing unit (CPU), or it may 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. The general-purpose processor may be a microprocessor or any conventional processor.

[0118] It will be understood by those skilled in the art that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program includes program instructions and can be stored in a storage medium, which 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 embodiments of the above methods.

[0119] Therefore, the present invention also provides a storage medium. This storage medium can be a computer-readable storage medium. The storage medium stores a computer program, wherein the computer program includes program instructions. When executed by a processor, the program instructions cause the processor to perform the steps of the above-described method.

[0120] The storage medium can be any computer-readable storage medium capable of storing program code, such as a USB flash drive, portable hard drive, read-only memory (ROM), magnetic disk, or optical disk.

[0121] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of both. To clearly illustrate the interchangeability of hardware and software, the components and steps of the various examples have been generally described in terms of functionality in the foregoing description. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementations should not be considered beyond the scope of this invention.

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

[0123] The steps in the method of this invention can be adjusted, merged, or reduced in order according to actual needs. The units in the device of this invention can be merged, divided, or reduced according to actual needs. Furthermore, the functional units in the various embodiments of this invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0124] If the integrated unit is implemented as 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. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, a terminal, or a network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention.

[0125] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any person skilled in the art can easily conceive of various equivalent modifications or substitutions within the technical scope disclosed in the present invention, and these modifications or substitutions should all be covered within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A ubiquitous computing power sharing method, characterized in that, The application is applied to non-invasive 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 connected to a target device through an interface, and the method comprises the following steps: The built-in operating system detects the resources of the target device and configures the system, and uploads the hardware resource information of the target device to a cloud platform; The built-in operating system virtualizes continuous and idle sectors into a virtual disk, and uploads the resource information of the virtual disk to the cloud platform; The cloud platform analyzes the resource information of the virtual disk and the hardware resource information of the target device to allocate appropriate computing power tasks to the target device; The built-in operating system constructs multiple execution virtual machines on the target device according to the computing power tasks to execute the computing power tasks, obtains result information, wherein the execution virtual machine is formed by injecting a sub-operating system based on a Docker container, and network isolation is realized by allocating an independent virtual network card. 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 of claim 1, wherein, The step of detecting the resources of the target device and configuring the system by the built-in operating system, and uploading the hardware resource information of the target device to the cloud platform comprises the following steps: The built-in operating system is started by UEFI / MBR booting, and the working environment is configured and the driver is loaded; The state of the hardware resources of the target device is checked, and the overall parameters are read and integrated into the hardware resource information; The hardware resource information is registered through a secure connection with the cloud platform through an encryption channel, and identity verification and authorization are completed.

3. The ubiquitous computing power sharing method of claim 2, wherein, The step of virtualizing continuous and idle sectors into a virtual disk by the built-in operating system, and uploading the resource information of the virtual disk to the cloud platform comprises the following steps: The built-in operating system detects the disk sectors of the target device, and marks the continuous and idle sectors; The continuous and idle sectors are virtualized into independent virtual disks by KVM, and the resource information of the virtual disk is uploaded to the cloud platform through the encryption channel.

4. The ubiquitous computing power sharing method of claim 3, wherein, The step of 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 comprises the following steps: According to the hardware resource information and the resource information of the virtual disk, the cloud platform evaluates the computing power provided by the target device to obtain an evaluation result; The cloud platform allocates computing power tasks to the target device according to the evaluation result; The cloud platform transmits the multiple computing power task data packets allocated to the target device to the built-in operating system through the encryption channel.

5. The ubiquitous computing power sharing method of claim 4, wherein, The step of constructing multiple virtual machines on the target device by the built-in operating system according to the computing power tasks to execute the computing power tasks and obtaining result information, and uploading the result information to a cloud platform includes: According to the computing power tasks, the virtual disk resources and the hardware resources are divided; Through the built-in operating system, multiple execution containers are set through Docker according to the division result; Through the built-in operating system, a sub-operating system is injected into each execution container to obtain multiple execution virtual machines; Through the built-in operating system, an independent virtual network card is allocated to each execution virtual machine; Through the multiple execution virtual machines, the multiple computing power tasks are executed to obtain result information, which is packaged and transmitted to the cloud platform through the encryption channel.

6. The ubiquitous computing power sharing method of claim 5, wherein, The step of the built-in operating system restoring the original state of the target device when the cloud platform verifies that the result information is valid includes: Through the cloud platform, the result information is decrypted and data verified; When the cloud platform verifies that the task result is valid, a release instruction is sent to the built-in operating system; After the built-in operating system receives the release instruction, all temporary data and cache are automatically cleaned up, and the original state of the target device is restored.

7. The ubiquitous computing power sharing method of claim 6, wherein, The step of automatically cleaning up all temporary data and cache and restoring the original state of the target device by the built-in operating system after receiving the release instruction further includes: Through the built-in operating system, exit information of the device is reported to the cloud platform through the encryption channel, including the result information and the device exit state.

8. A ubiquitous computing power sharing apparatus, characterized by, A method for performing the ubiquitous computing power sharing method according to any one of claims 1 to 7.

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

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

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