CN113238646B - Energy-saving storage method and device for optical storage cluster - Google Patents
Energy-saving storage method and device for optical storage cluster Download PDFInfo
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- G06F1/26—Power supply means, e.g. regulation thereof
- G06F1/32—Means for saving power
- G06F1/3203—Power management, i.e. event-based initiation of a power-saving mode
- G06F1/3234—Power saving characterised by the action undertaken
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- 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
- G06F3/0607—Improving or facilitating administration, e.g. storage management by facilitating the process of upgrading existing storage systems, e.g. for improving compatibility between host and storage device
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- G—PHYSICS
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- G06F—ELECTRIC DIGITAL DATA PROCESSING
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- Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
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Abstract
The invention discloses an energy-saving storage method and device of an optical storage cluster, wherein the method comprises the following steps: when a file operation request is received, obtaining attribute information of a file to be operated corresponding to the file operation request according to the file operation request; inputting the attribute information of the file operation request into a first preset model to obtain a file association relation map of the file to be operated; storing the files to be stored meeting preset association conditions into the same storage space according to the file association relation map, wherein the files to be stored comprise: and the file to be operated. According to the method and the device, the relation among the files to be stored is learned when the user stores the files, and the files with strong association are stored in the same storage space, so that the storage physical distribution is optimized, the dispatching times of the mechanical arm and the starting frequency of the optical storage space are reduced, and further the electric energy consumption is reduced.
Description
Technical Field
The invention relates to the technical field of artificial intelligence, in particular to an energy-saving storage method and device of an optical storage cluster.
Background
With digital informatization, a large amount of file data, sound data, image data, etc. need to be stored, which has led to the development of information storage demands toward high density, large capacity, high speed, and low cost, and thus, optical storage applications have arisen.
In optical storage, devices in a blu-ray storage area (such as a blu-ray recorder, a heat dissipation device, and a disc cartridge grabbing and transporting device) consume more power, so it is highly desirable to provide an energy-saving storage method for an optical storage cluster to reduce the energy consumption of the optical storage cluster.
Disclosure of Invention
Therefore, the technical problem to be solved by the invention is to overcome the defect of high energy consumption of blue light storage in the prior art, thereby providing an energy-saving storage method and device of an optical storage cluster.
According to a first aspect, the invention discloses an energy-saving storage method of an optical storage cluster, comprising the following steps: when a file operation request is received, obtaining attribute information of a file to be operated corresponding to the file operation request according to the file operation request; inputting the attribute information of the file operation request into a first preset model to obtain a file association relation map of the file to be operated; storing the files to be stored meeting preset association conditions into the same storage space according to the file association relation map, wherein the files to be stored comprise: and the file to be operated.
Optionally, the storing the files to be stored that meet the preset association condition in the same storage space according to the file association relationship map includes: inputting the file association relation map into a second preset model to obtain a storage distribution strategy meeting the preset association conditions; and storing the file to be stored according to the storage distribution strategy.
Optionally, the inputting the file association relationship map into a second preset model to obtain a storage distribution policy meeting the preset association condition includes: inputting the file association relation graph into a second preset model to obtain a segmentation result of the file association relation graph; and determining the storage distribution strategy according to the segmentation result of the file association relation graph and the file access frequency of the file to be stored corresponding to the segmentation result.
Optionally, the second preset model includes: the first algorithm model and the second algorithm model input the file association relation graph into a second preset model to obtain a segmentation result of the file association relation graph, and the method comprises the following steps: and respectively inputting the file association relation map into the first algorithm model and the second algorithm model, and determining a segmentation result of the file association relation map according to an output result of the first algorithm model and an output result of the second algorithm model.
Optionally, the method further comprises: when the size of the target file set exceeds the storage capacity of the storage space, the target file set is stored into the new storage space.
Optionally, the first preset model is a GCN model.
Optionally, the first algorithm model is a neural network model, and the second algorithm model is a network flow model.
According to a second aspect, the present invention also discloses an energy-saving storage device of an optical storage cluster, comprising: the receiving module is used for obtaining attribute information of a file to be operated corresponding to the file operation request according to the file operation request when the file operation request is received; the input module is used for inputting the attribute information of the file operation request into a first preset model to obtain a file association relation map of the file to be operated; the storage module is used for storing the files to be stored meeting the preset association conditions into the same storage space according to the file association relation map, and the files to be stored comprise: and the file to be operated.
According to a third aspect, the invention also discloses a computer device comprising: at least one processor; and a memory communicatively coupled to the at least one processor; wherein the memory stores instructions executable by the at least one processor to cause the at least one processor to perform the steps of the method for energy efficient storage of an optical storage cluster according to the first aspect or any alternative implementation of the first aspect.
According to a fourth aspect, the present invention also discloses a computer readable storage medium, on which a computer program is stored, which computer program, when being executed by a processor, implements the steps of the energy saving storage method of an optical storage cluster according to the first aspect or any alternative implementation manner of the first aspect.
The technical scheme of the invention has the following advantages:
according to the energy-saving storage method and device for the optical storage cluster, when a file operation request is received, attribute information of a file to be operated corresponding to the file operation request is obtained according to the file operation request, the attribute information of the file operation request is input into a first preset model, a file association relation map of the file to be operated is obtained, the file to be stored meeting preset association conditions is stored in the same storage space according to the file association relation map, and the file to be stored comprises: and (5) waiting for operating the file. According to the method and the device, the relation among the files to be stored is learned when the user stores the files, and the files with strong association are stored in the same storage space, so that the storage physical distribution is optimized, the dispatching times of the mechanical arm and the starting frequency of the optical storage space are reduced, and further the electric energy consumption is reduced.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings that are needed in the description of the embodiments or the prior art will be briefly described, and it is obvious that the drawings in the description below are some embodiments of the present invention, and other drawings can be obtained according to the drawings without inventive effort for a person skilled in the art.
FIG. 1 is a flowchart of a specific example of an energy-efficient storage method of an optical storage cluster in an embodiment of the present invention;
FIG. 2 is a schematic block diagram of one specific example of an energy-efficient storage device of an optical storage cluster in an embodiment of the invention;
FIG. 3 is a diagram showing a computer device according to an embodiment of the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made apparent and fully in view of the accompanying drawings, in which some, but not all embodiments of the invention are shown. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
In the description of the present invention, it should be noted that the directions or positional relationships indicated by the terms "center", "upper", "lower", "left", "right", "vertical", "horizontal", "inner", "outer", etc. are based on the directions or positional relationships shown in the drawings, are merely for convenience of describing the present invention and simplifying the description, and do not indicate or imply that the devices or elements referred to must have a specific orientation, be configured and operated in a specific orientation, and thus should not be construed as limiting the present invention. Furthermore, the terms "first," "second," and "third" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance.
In the description of the present invention, it should be noted that, unless explicitly specified and limited otherwise, the terms "mounted," "connected," and "connected" are to be construed broadly, and may be either fixedly connected, detachably connected, or integrally connected, for example; can be mechanically or electrically connected; the two components can be directly connected or indirectly connected through an intermediate medium, or can be communicated inside the two components, or can be connected wirelessly or in a wired way. The specific meaning of the above terms in the present invention will be understood in specific cases by those of ordinary skill in the art.
In addition, the technical features of the different embodiments of the present invention described below may be combined with each other as long as they do not collide with each other.
The embodiment of the invention discloses an energy-saving storage method of an optical storage cluster, which is applied to an equalization server of the optical storage cluster, wherein the optical storage cluster can be only the optical storage cluster (such as an optical drive, a blue-ray recorder and the like) or can be a magneto-optical hybrid storage cluster, as shown in fig. 1, and comprises the following steps:
s11: when a file operation request is received, obtaining attribute information of a file to be operated corresponding to the file operation request according to the file operation request.
Illustratively, the file operation request may include: file read requests and file store requests. The file operation request may be sent by a client device or a server, and the sending method may be sent by a wireless network or by a wired network. The embodiment of the invention does not limit the file operation request, the sender of the file operation request and the sending method of the file operation request in particular, and can be determined by a person skilled in the art according to practical situations.
Extracting attribute information of a file to be operated corresponding to a file operation request according to the file operation request, where in an embodiment of the present invention, the attribute information of the file to be operated may include: meta information of the file to be operated, semantic information of the file to be operated, etc., the attribute information is not particularly limited in the embodiment of the present invention, and can be determined by those skilled in the art according to actual situations.
S12: and inputting the attribute information of the file operation request into a first preset model to obtain a file association relation map of the file to be operated.
For example, the first preset model may be a GCN model, which may be trained in advance according to a large amount of historical data.
The file association relation map can be composed of nodes and edges, wherein the nodes are the relation among the 2 files, and the association degree of the relation can be represented by a weight value.
In the embodiment of the invention, in order to reduce the file association relationship map, attribute information of a file operation request can be input into a first preset model, and the file association relationship map with association degree meeting preset conditions is output. The preset condition may be: the association degree is larger than a first preset value, wherein the first preset value can be customized according to actual conditions or determined according to a clustering algorithm. The method for determining the first preset value according to the embodiment of the present invention is not particularly limited, and those skilled in the art can determine the first preset value according to actual situations.
In the embodiment of the invention, the first preset model can be updated online in the process of using the first preset model, so that the parameters of the first preset model are continuously adjusted, and the algorithm performance of the first preset model is improved.
S13: storing the files to be stored meeting the preset association conditions into the same storage space according to the file association relation map, wherein the files to be stored comprise: and (5) waiting for operating the file.
Illustratively, the preset association condition may be: the file association degree is larger than a second preset value. The method for determining the second preset value is the same as the method for determining the first preset value, and will not be described herein. In the embodiment of the present invention, the second preset value may be greater than or equal to the first preset value. The storage space is an optical storage space, such as an optical disc drive, a blue-ray recorder, etc.
Specifically, when the file with large association with the file to be operated is not reached, the file with large association with the file to be operated and the file to be operated can be pre-stored in the storage space together as the file to be stored, and when the file with large association with the file to be operated arrives together with the file to be operated, the file with large association with the file to be operated and the file to be operated are directly stored in the storage space together as the file to be stored.
According to the energy-saving storage method of the optical storage cluster, when a file operation request is received, attribute information of a file to be operated corresponding to the file operation request is obtained according to the file operation request, the attribute information of the file operation request is input into a first preset model, a file association relation map of the file to be operated is obtained, the file to be stored meeting preset association conditions is stored in the same storage space according to the file association relation map, and the file to be stored comprises: and (5) waiting for operating the file. According to the method and the device, the relation among the files to be stored is learned when the user stores the files, and the files with strong association are stored in the same storage space, so that the storage physical distribution is optimized, the dispatching times of the mechanical arm and the starting frequency of the optical storage space are reduced, and further the electric energy consumption is reduced.
As an alternative implementation manner of the embodiment of the present invention, the step S13 includes:
firstly, inputting a file association relation map into a second preset model to obtain a storage distribution strategy meeting preset association conditions.
The second preset model may be a neural network model, a network flow-based algorithm model, or a combination of a neural network model and a network flow-based algorithm model, for example. The embodiment of the present invention does not specifically limit the second preset model, and those skilled in the art can determine the second preset model according to actual situations.
In the same way, in the process of obtaining the storage distribution strategy by using the second preset model, the second preset model can be updated and adjusted, so that the prediction result of the second preset model is more accurate.
In an embodiment of the present invention, the storage distribution policy may include: how files to be operated and files strongly related to the files to be operated are stored and placed. Specifically:
inputting the file association relation graph into a second preset model to obtain a segmentation result of the file association relation graph. Inputting the file association relation map into a second preset model, and obtaining a segmentation result of minimum cost segmentation of the file association relation through a neural network model and/or an algorithm model based on network flow. And then, determining a storage distribution strategy according to the segmentation result of the file association relation graph and the file access frequency (namely the number of file reading/fetching times) of the files to be stored corresponding to the segmentation result, and placing the files to be stored at the position where the mechanical arm is easy to grasp, wherein the file access frequency of the files to be stored is higher.
And secondly, storing the file to be stored according to the storage distribution strategy.
As an optional implementation manner of the embodiment of the present invention, the second preset model includes: the first algorithm model and the second algorithm model input the file association relation graph into a second preset model to obtain a segmentation result of the file association relation graph, and the method comprises the following steps:
and respectively inputting the file association relation graph into the first algorithm model and the second algorithm model, and determining a segmentation result of the file association relation graph according to an output result of the first algorithm model and an output result of the second algorithm model.
Illustratively, the first algorithm model may be a neural network model, and the second algorithm model is a network flow model. And respectively inputting the file association relation graph into the first algorithm model and the second algorithm model, and determining a segmentation result of the file association relation graph according to a union of an output result of the first algorithm model and an output result of the second algorithm model. According to the embodiment of the invention, the segmentation result of the file association relation map is determined through the output results of the two algorithm models, so that the obtained segmentation result is more accurate and reasonable.
As an optional implementation manner of the embodiment of the present invention, the energy-saving storage method of the optical storage cluster further includes:
when the size of the target file set exceeds the storage capacity of its storage space, the target file set is stored to the new storage space.
The target file set may be any one of a large-association file set stored in an optical storage cluster, and as service data increases, when the size of the target file set exceeds the capacity of the current storage space, all files in the target file set are stored together in the storage space with larger capacity.
The embodiment of the invention also discloses an energy-saving storage device of the optical storage cluster, as shown in fig. 2, comprising:
a receiving module 21, configured to obtain, when receiving a file operation request, attribute information of a file to be operated corresponding to the file operation request according to the file operation request; the specific implementation manner is described in the above embodiment in the related description of step S11, which is not repeated here.
The input module 22 is configured to input attribute information of a file operation request into a first preset model, and obtain a file association relationship map of a file to be operated; the specific implementation manner is described in the above embodiment in the related description of step S12, which is not repeated here.
The storage module 23 is configured to store, according to a file association relationship map, a file to be stored that satisfies a preset association condition into the same storage space, where the file to be stored includes: and (5) waiting for operating the file. The specific implementation manner is described in the above embodiment in the related description of step S13, which is not repeated here.
According to the energy-saving storage device of the optical storage cluster, when a file operation request is received, attribute information of a file to be operated corresponding to the file operation request is obtained according to the file operation request, the attribute information of the file operation request is input into a first preset model, a file association relation map of the file to be operated is obtained, the file to be stored meeting preset association conditions is stored in the same storage space according to the file association relation map, and the file to be stored comprises: and (5) waiting for operating the file. According to the method and the device, the relation among the files to be stored is learned when the user stores the files, and the files with strong association are stored in the same storage space, so that the storage physical distribution is optimized, the dispatching times of the mechanical arm and the starting frequency of the optical storage space are reduced, and further the electric energy consumption is reduced.
As an alternative implementation of the embodiment of the present invention, the storage module 23 includes:
the storage distribution strategy obtaining module is used for inputting the file association relation map into a second preset model to obtain a storage distribution strategy meeting preset association conditions; the specific implementation manner is described in the related description of the corresponding steps in the foregoing embodiments, which is not repeated herein.
And the storage sub-module is used for storing the files to be stored according to the storage distribution strategy. The specific implementation manner is described in the related description of the corresponding steps in the foregoing embodiments, which is not repeated herein.
As an optional implementation manner of the embodiment of the present invention, the storage distribution policy obtaining module includes:
the segmentation result obtaining module is used for inputting the file association relation graph into a second preset model to obtain a segmentation result of the file association relation graph; the specific implementation manner is described in the related description of the corresponding steps in the foregoing embodiments, which is not repeated herein.
And the storage distribution strategy obtaining sub-module is used for determining the storage distribution strategy according to the segmentation result of the file association relation graph and the file access frequency of the file to be stored corresponding to the segmentation result. The specific implementation manner is described in the related description of the corresponding steps in the foregoing embodiments, which is not repeated herein.
As an optional implementation manner of the embodiment of the present invention, the second preset model includes: the segmentation result obtaining module comprises a first algorithm model and a second algorithm model, wherein the segmentation result obtaining module comprises:
the segmentation result obtaining sub-module is used for inputting the file association relation graph into the first algorithm model and the second algorithm model respectively, and determining the segmentation result of the file association relation graph according to the output result of the first algorithm model and the output result of the second algorithm model. The specific implementation manner is described in the related description of the corresponding steps in the foregoing embodiments, which is not repeated herein.
As an optional implementation manner of the embodiment of the present invention, the energy-saving storage device of the optical storage cluster further includes:
and the transformation storage module is used for storing the target file set into the new storage space when the size of the target file set exceeds the storage capacity of the storage space. The specific implementation manner is described in the related description of the corresponding steps in the foregoing embodiments, which is not repeated herein.
As an alternative implementation of the embodiment of the present invention, the first preset model is a GCN model. The specific implementation manner is described in the related description of the corresponding steps in the foregoing embodiments, which is not repeated herein.
As an optional implementation manner of the embodiment of the invention, the first algorithm model is a neural network model, and the second algorithm model is a network flow model. The specific implementation manner is described in the related description of the corresponding steps in the foregoing embodiments, which is not repeated herein.
The embodiment of the present invention further provides a computer device, as shown in fig. 3, which may include a processor 31 and a memory 32, where the processor 31 and the memory 32 may be connected by a bus or other means, and in fig. 3, the connection is exemplified by a bus.
The processor 31 may be a central processing unit (Central Processing Unit, CPU). The processor 31 may also be other general purpose processors, digital signal processors (Digital Signal Processor, DSP), application specific integrated circuits (Application Specific Integrated Circuit, ASIC), field programmable gate arrays (Field-Programmable Gate Array, FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, or a combination thereof.
The memory 32 is used as a non-transitory computer readable storage medium for storing non-transitory software programs, non-transitory computer executable programs, and modules, such as program instructions/modules (e.g., the receiving module 21, the input module 22, and the storage module 23 shown in fig. 2) corresponding to the energy-saving storage method of the optical storage cluster in the embodiment of the present invention. The processor 31 executes various functional applications of the processor and data processing, i.e. implements the energy-efficient storage method of the optical storage clusters in the method embodiments described above, by running non-transitory software programs, instructions and modules stored in the memory 32.
The memory 32 may include a storage program area that may store an operating system, at least one application program required for functions, and a storage data area; the storage data area may store data created by the processor 31, etc. In addition, the memory 32 may include high-speed random access memory, and may also include non-transitory memory, such as at least one magnetic disk storage device, flash memory device, or other non-transitory solid state storage device. In some embodiments, memory 32 may optionally include memory located remotely from processor 31, which may be connected to processor 31 via 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 one or more modules are stored in the memory 32, which when executed by the processor 31, performs a power saving storage method of an optical storage cluster in the embodiment shown in fig. 1.
The details of the above computer device may be understood correspondingly with respect to the corresponding relevant descriptions and effects in the embodiment shown in fig. 1, which are not repeated here.
It will be appreciated by those skilled in the art that implementing all or part of the above-described embodiment method may be implemented by a computer program to instruct related hardware, where the program may be stored in a computer readable storage medium, and the program may include the above-described embodiment method when executed. Wherein the storage medium may be a magnetic Disk, an optical Disk, a Read-Only Memory (ROM), a random access Memory (RandomAccessMemory, RAM), a Flash Memory (Flash Memory), a Hard Disk (HDD), a Solid State Drive (SSD), or the like; the storage medium may also comprise a combination of memories of the kind described above.
Although embodiments of the present invention have been described in connection with the accompanying drawings, various modifications and variations may be made by those skilled in the art without departing from the spirit and scope of the invention, and such modifications and variations are within the scope of the invention as defined by the appended claims.
Claims (7)
1. An energy-saving storage method of an optical storage cluster is characterized by comprising the following steps:
when a file operation request is received, obtaining attribute information of a file to be operated corresponding to the file operation request according to the file operation request;
inputting the attribute information of the file operation request into a first preset model to obtain a file association relation map of the file to be operated;
storing the files to be stored meeting preset association conditions into the same storage space according to the file association relation map, wherein the files to be stored comprise: the file to be operated;
storing the files to be stored meeting the preset association conditions into the same storage space according to the file association relationship map, wherein the method comprises the following steps:
inputting the file association relation map into a second preset model to obtain a storage distribution strategy meeting the preset association conditions;
storing the file to be stored according to the storage distribution strategy;
inputting the file association relation map into a second preset model to obtain a storage distribution strategy meeting the preset association conditions, wherein the method comprises the following steps:
inputting the file association relation graph into a second preset model to obtain a segmentation result of the file association relation graph;
determining the storage distribution strategy according to the segmentation result of the file association relation map and the file access frequency of the file to be stored corresponding to the segmentation result;
the second preset model comprises: the first algorithm model and the second algorithm model input the file association relation graph into a second preset model to obtain a segmentation result of the file association relation graph, and the method comprises the following steps:
and respectively inputting the file association relation map into the first algorithm model and the second algorithm model, and determining a segmentation result of the file association relation map according to an output result of the first algorithm model and an output result of the second algorithm model.
2. The method according to claim 1, wherein the method further comprises:
when the size of the target file set exceeds the storage capacity of the storage space, the target file set is stored into the new storage space.
3. The method of claim 1, wherein the first predetermined model is a GCN model.
4. The method of claim 1, wherein the first algorithm model is a neural network model and the second algorithm model is a network flow model.
5. An energy-efficient storage device of an optical storage cluster, comprising:
the receiving module is used for obtaining attribute information of a file to be operated corresponding to the file operation request according to the file operation request when the file operation request is received;
the input module is used for inputting the attribute information of the file operation request into a first preset model to obtain a file association relation map of the file to be operated;
the storage module is used for storing the files to be stored meeting the preset association conditions into the same storage space according to the file association relation map, and the files to be stored comprise: the file to be operated;
storing the files to be stored meeting the preset association conditions into the same storage space according to the file association relationship map, wherein the method comprises the following steps:
inputting the file association relation map into a second preset model to obtain a storage distribution strategy meeting the preset association conditions;
storing the file to be stored according to the storage distribution strategy;
inputting the file association relation map into a second preset model to obtain a storage distribution strategy meeting the preset association conditions, wherein the method comprises the following steps:
inputting the file association relation graph into a second preset model to obtain a segmentation result of the file association relation graph;
determining the storage distribution strategy according to the segmentation result of the file association relation map and the file access frequency of the file to be stored corresponding to the segmentation result;
the second preset model comprises: the first algorithm model and the second algorithm model input the file association relation graph into a second preset model to obtain a segmentation result of the file association relation graph, and the method comprises the following steps:
and respectively inputting the file association relation map into the first algorithm model and the second algorithm model, and determining a segmentation result of the file association relation map according to an output result of the first algorithm model and an output result of the second algorithm model.
6. A computer device, comprising: at least one processor; and a memory communicatively coupled to the at least one processor; wherein the memory stores instructions executable by the at least one processor to cause the at least one processor to perform the steps of the energy-efficient storage method of an optical storage cluster according to any one of claims 1-4.
7. A computer readable storage medium, on which a computer program is stored, characterized in that the computer program, when being executed by a processor, carries out the steps of the energy saving storage method of an optical storage cluster according to any one of claims 1-4.
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