CN112394882A - Data storage method and device, storage medium and electronic device - Google Patents
Data storage method and device, storage medium and electronic device Download PDFInfo
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- CN112394882A CN112394882A CN202011288120.8A CN202011288120A CN112394882A CN 112394882 A CN112394882 A CN 112394882A CN 202011288120 A CN202011288120 A CN 202011288120A CN 112394882 A CN112394882 A CN 112394882A
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- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F3/00—Input arrangements for transferring data to be processed into a form capable of being handled by the computer; Output arrangements for transferring data from processing unit to output unit, e.g. interface arrangements
- G06F3/06—Digital input from, or digital output to, record carriers, e.g. RAID, emulated record carriers or networked record carriers
- G06F3/0601—Interfaces specially adapted for storage systems
- G06F3/0602—Interfaces specially adapted for storage systems specifically adapted to achieve a particular effect
- G06F3/0604—Improving or facilitating administration, e.g. storage management
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F3/00—Input arrangements for transferring data to be processed into a form capable of being handled by the computer; Output arrangements for transferring data from processing unit to output unit, e.g. interface arrangements
- G06F3/06—Digital input from, or digital output to, record carriers, e.g. RAID, emulated record carriers or networked record carriers
- G06F3/0601—Interfaces specially adapted for storage systems
- G06F3/0628—Interfaces specially adapted for storage systems making use of a particular technique
- G06F3/0629—Configuration or reconfiguration of storage systems
- G06F3/0631—Configuration or reconfiguration of storage systems by allocating resources to storage systems
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F3/00—Input arrangements for transferring data to be processed into a form capable of being handled by the computer; Output arrangements for transferring data from processing unit to output unit, e.g. interface arrangements
- G06F3/06—Digital input from, or digital output to, record carriers, e.g. RAID, emulated record carriers or networked record carriers
- G06F3/0601—Interfaces specially adapted for storage systems
- G06F3/0668—Interfaces specially adapted for storage systems adopting a particular infrastructure
- G06F3/067—Distributed or networked storage systems, e.g. storage area networks [SAN], network attached storage [NAS]
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F3/00—Input arrangements for transferring data to be processed into a form capable of being handled by the computer; Output arrangements for transferring data from processing unit to output unit, e.g. interface arrangements
- G06F3/06—Digital input from, or digital output to, record carriers, e.g. RAID, emulated record carriers or networked record carriers
- G06F3/0601—Interfaces specially adapted for storage systems
- G06F3/0668—Interfaces specially adapted for storage systems adopting a particular infrastructure
- G06F3/0671—In-line storage system
- G06F3/0683—Plurality of storage devices
- G06F3/0685—Hybrid storage combining heterogeneous device types, e.g. hierarchical storage, hybrid arrays
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Abstract
The embodiment of the invention provides a data storage method and device, a storage medium and an electronic device, wherein the method comprises the following steps: determining the current storage capacity of the N storage modules and the current computing capacity of the M computing modules based on the determined data to be processed; adjusting the M computing modules based on the current storage capacity and the current computing capacity so that K computing modules in the M computing modules process data to be processed to obtain target data; and storing the target data into the N storage modules. The invention solves the problem of cooperative work of the storage service and the computing service, and achieves the effect of improving the data storage performance.
Description
Technical Field
The embodiment of the invention relates to the field of communication, in particular to a data storage method and device, a storage medium and an electronic device.
Background
The existing servers include storage servers with storage services as a core and computing servers with computing as a core, and along with the rapid development of artificial intelligence and big data, the existing servers also include an integrated server integrating storage and computing. For example, the existing adaptive mixed insertion technology of the hard disk and the smart card can be accessed to the place of the hard disk and also can be accessed to the smart card, and a client can configure storage capacity and computing capacity according to requirements.
In the prior art, storage and calculation services are independent from each other and have no cooperative work mechanism, regardless of a storage server taking storage as a core, a calculation server taking calculation as a core or an integrated server integrating storage and calculation.
In view of the above technical problems, the related art has not yet proposed an effective solution.
Disclosure of Invention
The embodiment of the invention provides a data storage method and device, a storage medium and an electronic device, which are used for at least solving the problem of cooperative work of storage service and computing service in the related technology.
According to an embodiment of the present invention, there is provided a data storage method including: determining the current storage capacity of N storage modules and the current computing capacity of M computing modules based on the determined data to be processed, wherein the N storage modules are used for storing the data to be processed, the M computing modules are used for processing the data to be processed, both N and M are natural numbers which are greater than or equal to 1, and the N storage modules and the M computing modules are arranged in the same device; adjusting the number of the M computing modules based on the current storage capacity and the current computing capacity so that K paths of analysis paths in the M computing modules analyze the data to be processed to obtain target data, wherein K is a natural number less than or equal to M; and storing the target data into the N storage modules.
According to another embodiment of the present invention, there is provided a data storage device including: the device comprises a first determination module, a second determination module and a third determination module, wherein the first determination module is used for determining the current storage capacity of N storage modules and the current computing capacity of M computing modules based on the determined data to be processed, the N storage modules are used for storing the data to be processed, the M computing modules are used for processing the data to be processed, the N and the M are natural numbers which are greater than or equal to 1, and the N storage modules and the M computing modules are arranged in the same device; a first adjusting module, configured to adjust the number of the M computing modules based on the current storage capacity and the current computing capacity, so that K paths in the M computing modules analyze the data to be processed to obtain target data, where K is a natural number less than or equal to M; and storing the target data into the N storage modules.
In one exemplary embodiment, the first determining module includes: a first determining unit, configured to determine a storage space required by the to-be-processed data; a second determining unit, configured to determine current storage capacities of the N storage modules based on the storage space; a third determining unit, configured to determine an attribute of the to-be-processed data; a fourth determining unit, configured to determine current computing capabilities of the M computing modules based on the attributes.
In an exemplary embodiment, the first adjusting module includes: a fifth determining unit, configured to determine, when the current storage capacity does not meet the storage space required by the to-be-processed data and the computing capacities of the M computing modules are greater than the computing capacity required by the to-be-processed data, the computing module corresponding to the K paths of analysis paths as a device for processing the to-be-processed data, so as to process the to-be-processed data by using the computing module corresponding to the K paths of analysis paths, and obtain the target data.
In an exemplary embodiment, the fifth determining unit includes: and the first determining subunit is configured to determine the K computing modules as a device for processing the to-be-processed data, so as to compress the to-be-processed data by using the K computing modules to obtain the target data.
In an exemplary embodiment, the storage module includes: and the storage unit is used for storing the target data into the N storage modules according to a preset period.
According to a further embodiment of the present invention, there is also provided a computer-readable storage medium having a computer program stored thereon, wherein the computer program is arranged to perform the steps of any of the above method embodiments when executed.
According to yet another embodiment of the present invention, there is also provided an electronic device, including a memory in which a computer program is stored and a processor configured to execute the computer program to perform the steps in any of the above method embodiments.
According to the invention, the current storage capacity of N storage modules and the current computing capacity of M computing modules are determined based on the determined data to be processed, wherein the N storage modules are used for storing the data to be processed, the M computing modules are used for processing the data to be processed, N and M are natural numbers which are greater than or equal to 1, and the N storage modules and the M computing modules are arranged in the same device; adjusting the number of M calculation modules based on the current storage capacity and the current calculation capacity so that K paths of analysis paths in the M calculation modules analyze data to be processed to obtain target data, wherein K is a natural number less than or equal to M; and storing the target data into the N storage modules. The purpose of cooperative work of the computing module and the target equipment is achieved. Therefore, the problem of cooperative work of the storage service and the computing service can be solved, and the effect of improving the data storage performance is achieved.
Drawings
Fig. 1 is a block diagram of a hardware structure of a mobile terminal of a data storage method according to an embodiment of the present invention;
FIG. 2 is a flow chart of a data storage method according to an embodiment of the present invention;
FIG. 3 is a schematic diagram of a hard disk slot, according to an embodiment of the invention;
FIG. 4 is a schematic diagram of an implementation structure according to an embodiment of the invention;
FIG. 5 is a schematic diagram of an implementation of an embodiment in accordance with the invention;
fig. 6 is a block diagram of a data storage device according to an embodiment of the present invention.
Detailed Description
Hereinafter, embodiments of the present invention will be described in detail with reference to the accompanying drawings in conjunction with the embodiments.
It should be noted that the terms "first," "second," and the like in the description and claims of the present invention and in the drawings described above are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order.
The method embodiments provided in the embodiments of the present application may be executed in a mobile terminal, a computer terminal, or a similar computing device. Taking an example of the operation on a mobile terminal, fig. 1 is a hardware structure block diagram of the mobile terminal of a data storage method according to an embodiment of the present invention. As shown in fig. 1, the mobile terminal may include one or more (only one shown in fig. 1) processors 102 (the processor 102 may include, but is not limited to, a processing device such as a microprocessor MCU or a programmable logic device FPGA), and a memory 104 for storing data, wherein the mobile terminal may further include a transmission device 106 for communication functions and an input-output device 108. It will be understood by those skilled in the art that the structure shown in fig. 1 is only an illustration, and does not limit the structure of the mobile terminal. For example, the mobile terminal may also include more or fewer components than shown in FIG. 1, or have a different configuration than shown in FIG. 1.
The memory 104 may be used to store computer programs, for example, software programs and modules of application software, such as computer programs corresponding to the data storage method in the embodiment of the present invention, and the processor 102 executes various functional applications and data processing by running the computer programs stored in the memory 104, so as to implement the above-mentioned method. The memory 104 may include high speed random access memory, and may also include non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some examples, the memory 104 may further include memory located remotely from the processor 102, which may be connected to the mobile terminal over a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.
The transmission device 106 is used for receiving or transmitting data via a network. Specific examples of the network described above may include a wireless network provided by a communication provider of the mobile terminal. In one example, the transmission device 106 includes a Network adapter (NIC), which can be connected to other Network devices through a base station so as to communicate with the internet. In one example, the transmission device 106 may be a Radio Frequency (RF) module, which is used for communicating with the internet in a wireless manner.
In the present embodiment, a data storage method is provided, and fig. 2 is a flowchart of a data storage method according to an embodiment of the present invention, where as shown in fig. 2, the flowchart includes the following steps:
step S202, determining the current storage capacity of N storage modules and the current computing capacity of M computing modules based on the determined data to be processed, wherein the N storage modules are used for storing the data to be processed, the M computing modules are used for processing the data to be processed, N and M are natural numbers which are larger than or equal to 1, and the N storage modules and the M computing modules are arranged in the same device;
step S204, adjusting the number of M calculation modules based on the current storage capacity and the current calculation capacity so that K paths of analysis paths in the M calculation modules analyze data to be processed to obtain target data, wherein K is a natural number less than or equal to M;
step S206, storing the target data into N storage modules.
The execution subject of the above steps may be a terminal, but is not limited thereto.
Optionally, in this embodiment, the computing module includes, but is not limited to, a smart card provided in the terminal. The storage module includes, but is not limited to, a storage hard disk provided in the terminal. For example, 5 storage hard disks and 10 smart cards are provided in the terminal device. As shown in fig. 3, a smart card storing a hard disk or hard disk cartridge is accessed in a hard disk slot. The hard disk and the smart card can be mixed and inserted compatibly, the hard disk exists as a storage pool, and the smart card exists as an intelligent pool.
Optionally, the data to be processed includes, but is not limited to, video data acquired by a camera device, for example, image data of a vehicle acquired in a violation monitoring scene. In this scenario, the image data of the vehicle is relatively large, and some of the calculation modules may be used to assist the storage of the storage module, for example, the calculation module compresses the acquired image data, and then stores the compressed image data in the storage module. The memory of the storage module can be reduced, and the service cycle is prolonged.
Through the steps, the current storage capacity of N storage modules and the current computing capacity of M computing modules are determined based on the determined data to be processed, wherein the N storage modules are used for storing the data to be processed, the M computing modules are used for processing the data to be processed, N and M are natural numbers which are larger than or equal to 1, and the N storage modules and the M computing modules are arranged in the same device; adjusting the number of M calculation modules based on the current storage capacity and the current calculation capacity so that K paths of analysis paths in the M calculation modules analyze data to be processed to obtain target data, wherein K is a natural number less than or equal to M; and storing the target data into the N storage modules. The purpose of cooperative work of the computing module and the target equipment is achieved. Therefore, the problem of cooperative work of the storage service and the computing service can be solved, and the effect of improving the data storage performance is achieved.
In one exemplary embodiment, determining the current storage capabilities of the N storage modules and the current computing capabilities of the M computing modules based on the determined data to be processed comprises:
s1, determining the storage space needed by the data to be processed;
s2, determining the current storage capacity of the N storage modules based on the storage space;
s3, determining the attribute of the data to be processed;
s4, determining the current computing power of the M computing modules based on the attributes.
Optionally, as shown in fig. 4, the present embodiment includes the following scenarios:
scene one: a Central Processing Unit (CPU) calculates the storage capacity required by the current data to be processed, if the storage capacity of the storage module meets the requirement of the current data to be processed, the current service configuration of the storage module is maintained, and all the calculation modules are responsible for Processing the intelligent analysis of videos or pictures.
Scene two: the CPU calculates the storage capacity required by the current data to be processed, and if the storage module does not meet the requirement of the current data to be processed, a part of calculation modules are configured for intelligent compression, so that the storage performance of the storage module is improved.
Scene three: the CPU calculates the computing power required by the current data to be processed, if the computing power is excessive, an excessive computing module is configured to carry out intelligent compression, and the storage performance of the storage module is improved.
In an exemplary embodiment, adjusting M calculation modules based on the current storage capacity and the current calculation capacity to enable the number of K paths of analysis paths in the M calculation modules to analyze the data to be processed to obtain target data includes:
and S1, determining the calculation module corresponding to the K-path analysis path number as the device for processing the data to be processed to obtain the target data by using the calculation module when the current storage capacity does not meet the storage space required by the data to be processed and the calculation capacity of the M calculation modules is greater than the calculation capacity required by the data to be processed.
Optionally, in this embodiment, the CPU calculates the calculation capacity required by the current data to be processed, and if the calculation capacity is excessive, an excessive calculation module is configured to perform intelligent compression, so as to improve the storage performance of the storage module.
In an exemplary embodiment, analyzing the data to be processed by K paths of analysis to obtain target data, includes:
and S1, determining the calculation module corresponding to the K paths of analysis paths as equipment for processing the data to be processed, and compressing the data to be processed by using the calculation module to obtain target data.
Optionally, in this embodiment, the computation module corresponding to the K paths for analysis is used to assist the storage module to store data, so as to improve the storage performance of the storage module.
In one exemplary embodiment, storing the target data into the N storage modules includes:
and S1, storing the target data into the N storage modules according to a preset period.
Alternatively, in this embodiment, the storage module may store the target data in a set period, for example, store video data for one week.
In an exemplary embodiment, as shown in fig. 5, in this embodiment, the storage module has a video recording function, and the video recording function is a core function of the storage module in the security product, and generally requires that video recordings with a certain number of channels are stored and cannot be lost.
The calculation module possesses intelligent function, and intelligent function carries out different intelligent analysis to the code stream promptly, and the analysis result generally can take target cutout and panorama, needs to save.
The video compression function of the calculation module is to carry out transcoding compression on the accessed video, and reduce the size of the code stream under the condition of ensuring definition.
The storage capacity of the storage module is fixed, the storage resource is fixed, and the storage capacity, namely the storage bandwidth, is basically stable.
The intelligence and the compression capability of the computing module need to use the coding and decoding capability of hardware, and the two have a competitive relationship.
In practical projects, it is required to have as much intelligence as possible without losing videos. However, because of the unique features of intelligent analysis, most intelligent analysis will generate more events and pictures during peak periods of target traffic. The amount of data stored at this time may exceed the overall storage capacity of the device.
In summary, the method for dynamically adjusting the ratio between the intelligent data and the compression transcoding in this embodiment improves the storage capacity of the intelligent data under the condition that the video is not lost. When the scene mentioned in the previous section appears, a dynamic adjusting function is triggered, the number of intelligent analysis paths is gradually reduced for video compression and storage, and finally the maximum storage utilization rate is achieved. If the final adjustment result is that 10 paths of intelligent analysis are stopped for compression storage, the video storage bandwidth is changed to 70M/S, and the intelligent analysis result is 30 MB/S. Compared with the original scheme, the intelligent result storage of 10MB/S can be increased under the condition of ensuring that the video is not lost. The storage capacity and the intelligent capacity are estimated in advance through the CPU, a combined cooperative working mode with optimal storage and intelligence is configured, the intelligent card is enabled to process main services of intelligent analysis of videos and pictures, meanwhile, the storage capacity of the equipment is improved through an intelligent compression technology, and then the overall working performance of the equipment is improved.
Through the above description of the embodiments, those skilled in the art can clearly understand that the method according to the above embodiments can be implemented by software plus a necessary general hardware platform, and certainly can also be implemented by hardware, but the former is a better implementation mode in many cases. Based on such understanding, the technical solutions of the present invention may be embodied in the form of a software product, which is stored in a storage medium (e.g., ROM/RAM, magnetic disk, optical disk) and includes instructions for enabling a terminal device (e.g., a mobile phone, a computer, a server, or a network device) to execute the method according to the embodiments of the present invention.
In this embodiment, a data storage device is further provided, and the data storage device is used to implement the foregoing embodiments and preferred embodiments, and the description of the data storage device is omitted. As used below, the term "module" may be a combination of software and/or hardware that implements a predetermined function. Although the means described in the embodiments below are preferably implemented in software, an implementation in hardware, or a combination of software and hardware is also possible and contemplated.
Fig. 6 is a block diagram of a data storage apparatus according to an embodiment of the present invention, as shown in fig. 6, the apparatus including:
a first determining module 62, configured to determine, based on the determined data to be processed, current storage capacities of N storage modules and current computing capacities of M computing modules, where the N storage modules are configured to store the data to be processed, the M computing modules are configured to process the data to be processed, and the N storage modules and the M computing modules, which are both natural numbers greater than or equal to 1, are disposed in the same device;
a first adjusting module 64, configured to adjust the number of the M computing modules based on the current storage capacity and the current computing capacity, so that the number of K paths of analysis among the M computing modules analyzes the data to be processed to obtain target data, where K is a natural number less than or equal to M;
and the storage module 66 is used for storing the target data into the N storage modules.
In one exemplary embodiment, the first determining module includes:
a first determining unit, configured to determine a storage space required by the to-be-processed data;
a second determining unit, configured to determine current storage capacities of the N storage modules based on the storage space;
a third determining unit, configured to determine an attribute of the to-be-processed data;
a fourth determining unit, configured to determine current computing capabilities of the M computing modules based on the attributes.
In an exemplary embodiment, the first adjusting module includes:
a fifth determining unit, configured to analyze the to-be-processed data through the K paths of analysis paths to obtain the target data when the current storage capacity does not meet the storage space required by the to-be-processed data and the computation capacities of the M computation modules are greater than the computation capacity required by the to-be-processed data.
In an exemplary embodiment, the fifth determining unit includes:
and the first determining subunit is configured to determine the calculation module corresponding to the K paths of analysis paths as a device for processing the to-be-processed data, so as to compress the to-be-processed data by using the calculation module corresponding to the K paths of analysis paths to obtain the target data.
In an exemplary embodiment, the storage module includes:
and the storage unit is used for storing the target data into the N storage modules according to a preset period.
It should be noted that, the above modules may be implemented by software or hardware, and for the latter, the following may be implemented, but not limited to: the modules are all positioned in the same processor; alternatively, the modules are respectively located in different processors in any combination.
Embodiments of the present invention also provide a computer-readable storage medium having a computer program stored thereon, wherein the computer program is arranged to perform the steps of any of the above-mentioned method embodiments when executed.
In an exemplary embodiment, the computer-readable storage medium may include, but is not limited to: various media capable of storing computer programs, such as a usb disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a removable hard disk, a magnetic disk, or an optical disk.
Embodiments of the present invention also provide an electronic device comprising a memory having a computer program stored therein and a processor arranged to run the computer program to perform the steps of any of the above method embodiments.
In an exemplary embodiment, the electronic apparatus may further include a transmission device and an input/output device, wherein the transmission device is connected to the processor, and the input/output device is connected to the processor.
For specific examples in this embodiment, reference may be made to the examples described in the above embodiments and exemplary embodiments, and details of this embodiment are not repeated herein.
It will be apparent to those skilled in the art that the various modules or steps of the invention described above may be implemented using a general purpose computing device, they may be centralized on a single computing device or distributed across a network of computing devices, and they may be implemented using program code executable by the computing devices, such that they may be stored in a memory device and executed by the computing device, and in some cases, the steps shown or described may be performed in an order different than that described herein, or they may be separately fabricated into various integrated circuit modules, or multiple ones of them may be fabricated into a single integrated circuit module. Thus, the present invention is not limited to any specific combination of hardware and software.
The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention, and various modifications and changes may be made by those skilled in the art. Any modification, equivalent replacement, or improvement made within the principle of the present invention should be included in the protection scope of the present invention.
Claims (8)
1. A method of storing data, comprising:
determining the current storage capacity of N storage modules and the current computing capacity of M computing modules based on the determined data to be processed, wherein the N storage modules are used for storing the data to be processed, the M computing modules are used for processing the data to be processed, both N and M are natural numbers which are greater than or equal to 1, and the N storage modules and the M computing modules are arranged in the same device;
adjusting the analysis path number of the M calculation modules based on the current storage capacity and the current calculation capacity so that the K path analysis path number of the M calculation modules analyzes the data to be processed to obtain target data, wherein K is a natural number less than or equal to M;
and storing the target data into the N storage modules.
2. The method of claim 1, wherein determining the current storage capabilities of the N storage modules and the current computing capabilities of the M computing modules based on the determined data to be processed comprises:
determining a storage space required by the data to be processed;
determining current storage capabilities of the N storage modules based on the storage space;
determining the attribute of the data to be processed;
determining current computing capabilities of the M computing modules based on the attributes.
3. The method of claim 1, wherein adjusting the M computation modules based on the current storage capacity and the current computation capacity to enable K paths of analysis paths in the M computation modules to analyze the data to be processed to obtain target data comprises:
and under the condition that the current storage capacity does not meet the storage space required by the data to be processed and the computing capacity of the M computing modules is greater than the computing capacity required by the data to be processed, analyzing the equipment of the data to be processed by the K paths of analysis paths to obtain the target data.
4. The method according to claim 3, wherein analyzing the data to be processed by the K-way analysis path number to obtain the target data comprises:
and determining the calculation module corresponding to the K paths of analysis paths as the equipment for processing the data to be processed, and compressing the data to be processed by using the calculation module corresponding to the K paths of analysis paths to obtain the target data.
5. The method of claim 1, wherein storing the target data into the N storage modules comprises:
and storing the target data into the N storage modules according to a preset period.
6. A data storage device, comprising:
the device comprises a first determination module, a second determination module and a third determination module, wherein the first determination module is used for determining the current storage capacity of N storage modules and the current computing capacity of M computing modules based on the determined data to be processed, the N storage modules are used for storing the data to be processed, the M computing modules are used for processing the data to be processed, the N and the M are natural numbers which are greater than or equal to 1, and the N storage modules and the M computing modules are arranged in the same device;
a first adjusting module, configured to adjust the number of the M computing modules based on the current storage capacity and the current computing capacity, so that K paths in the M computing modules analyze the data to be processed to obtain target data, where K is a natural number less than or equal to M;
and the storage module is used for storing the target data into the N storage modules.
7. A computer-readable storage medium, in which a computer program is stored, wherein the computer program is arranged to perform the method of any of claims 1 to 5 when executed.
8. An electronic device comprising a memory and a processor, wherein the memory has stored therein a computer program, and wherein the processor is arranged to execute the computer program to perform the method of any of claims 1 to 5.
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| Application Number | Priority Date | Filing Date | Title |
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| CN202011288120.8A CN112394882B (en) | 2020-11-17 | 2020-11-17 | Data storage method and device, storage medium and electronic device |
| EP21887859.3A EP4038486A4 (en) | 2020-11-17 | 2021-10-11 | Systems and methods for data storage and computing |
| PCT/CN2021/122992 WO2022105473A1 (en) | 2020-11-17 | 2021-10-11 | Systems and methods for data storage and computing |
| US17/662,228 US20220261175A1 (en) | 2020-11-17 | 2022-05-05 | Systems and methods for data storage and computing |
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| CN202011288120.8A CN112394882B (en) | 2020-11-17 | 2020-11-17 | Data storage method and device, storage medium and electronic device |
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| CN112394882B CN112394882B (en) | 2022-04-19 |
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| WO2022105473A1 (en) * | 2020-11-17 | 2022-05-27 | Zhejiang Dahua Technology Co., Ltd. | Systems and methods for data storage and computing |
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