CN109960587A - The storage resource distribution method and device of super fusion cloud computing system - Google Patents
The storage resource distribution method and device of super fusion cloud computing system Download PDFInfo
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- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F9/00—Arrangements for program control, e.g. control units
- G06F9/06—Arrangements for program control, e.g. control units using stored programs, i.e. using an internal store of processing equipment to receive or retain programs
- G06F9/46—Multiprogramming arrangements
- G06F9/50—Allocation of resources, e.g. of the central processing unit [CPU]
- G06F9/5005—Allocation of resources, e.g. of the central processing unit [CPU] to service a request
- G06F9/5011—Allocation of resources, e.g. of the central processing unit [CPU] to service a request the resources being hardware resources other than CPUs, Servers and Terminals
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- G—PHYSICS
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- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F9/00—Arrangements for program control, e.g. control units
- G06F9/06—Arrangements for program control, e.g. control units using stored programs, i.e. using an internal store of processing equipment to receive or retain programs
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- G06F9/5061—Partitioning or combining of resources
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Abstract
The present invention relates to field of computer technology, provide storage resource distribution method, device, computer equipment and the computer readable storage medium of a kind of super fusion cloud computing system.Wherein, method includes: the storage information by obtaining data to be stored, and the storage demand of the data to be stored is determined according to the storage information；Obtain the resource service condition information of memory module in all cloud nodes in the cloud resource pond；The cloud node is screened based on the storage demand and the resource service condition information, obtains the candidate Yun Jiedian that can store the data to be stored；It is the distribution that the data to be stored carries out storage resource based on the candidate Yun Jiedian, can be realized the reasonable utilization of storage resource, improve the allocative efficiency of storage resource.
Description
Technical field
The invention belongs to field of computer technology more particularly to a kind of storage resource distribution sides of super fusion cloud computing system
Method, device, computer equipment and computer readable storage medium.
Background technique
With being constantly progressive for network technology, the continuous growth of data volume in network surpasses the data in fusion storage system
Amount is also incrementally increasing.Super fusion storage system is a kind of distributed memory system of object-oriented, the system aim at by
The integration of the resources such as calculating, network, storage and virtualized server in system is played multinode by network polymerization with reaching
Come, realization is modular seamless extending transversely, and forms the effect of unified resource pool.Sino-Japan in face of super fusion storage system
When the data volume that benefit increases, storage resource for storing data is often limited.Therefore, storage money how is reasonably distributed
Source is just particularly important the data storage in super fusion storage system.
Currently, the prior art is deposited when storing to the data in super fusion storage system for data to be stored distribution
The mode of storage resource is often to be randomly assigned.However, in practical applications, the mode being randomly assigned will appear depositing of being distributed
The case where storage resource is unable to satisfy storage demand, to need to redistribute storage resource, so the distribution of its storage resource is imitated
Rate is low, can not effectively realize the reasonable utilization of storage resource.Therefore, the prior art exists when distributing storage resource for data
The low problem of storage resource allocative efficiency.
Summary of the invention
In view of this, the embodiment of the invention provides a kind of storage resource distribution methods of super fusion cloud computing system, dress
It sets, computer equipment and readable, there are storage resource allocative efficiencies when solving to distribute storage resource in the prior art for data
Low problem.
The first aspect of the embodiment of the present invention provides a kind of storage resource distribution method of super fusion cloud computing system, institute
Stating super fusion cloud computing system includes multiple super aggregators and switch, and each super aggregators include storage
The memory module of module, multiple super aggregators is connected to the network by the switch to form cloud resource
Pond, at least two super aggregators constitute a cloud node, and the storage resource distribution method includes:
The storage information for obtaining data to be stored determines the storage need of the data to be stored according to the storage information
It asks；
Obtain the resource service condition information of memory module in all cloud nodes in the cloud resource pond；
The cloud node is screened based on the storage demand and the resource service condition information, obtains to deposit
Store up the candidate Yun Jiedian of the data to be stored；
It is the distribution that the data to be stored carries out storage resource based on the candidate Yun Jiedian.
The second aspect of the embodiment of the present invention provides a kind of storage resource distributor of super fusion cloud computing system, packet
It includes:
First obtain module, for obtaining the storage information of data to be stored, according to the storage information determine described in
The storage demand of storing data；
Second obtains module, for obtaining the resource service condition of memory module in all cloud nodes in the cloud resource pond
Information；
Screening module, for being sieved based on the storage demand and the resource service condition information to the cloud node
Choosing, obtains the candidate Yun Jiedian that can store the data to be stored；
Distribution module, for being the distribution of data to be stored progress storage resource based on the candidate Yun Jiedian.
The third aspect of the embodiment of the present invention provides a kind of computer equipment, including memory, processor and storage
In the memory and the computer program that can run on the processor, which is characterized in that the processor executes institute
It is performed the steps of when stating computer program
The storage information for obtaining data to be stored determines the storage need of the data to be stored according to the storage information
It asks；
Obtain the resource service condition information of memory module in all cloud nodes in the cloud resource pond；
The cloud node is screened based on the storage demand and the resource service condition information, obtains to deposit
Store up the candidate Yun Jiedian of the data to be stored；
It is the distribution that the data to be stored carries out storage resource based on the candidate Yun Jiedian.
The fourth aspect of the embodiment of the present invention provides a kind of computer readable storage medium, the computer-readable storage
Media storage has computer program, and the computer program performs the steps of when being executed by processor
The storage information for obtaining data to be stored determines the storage need of the data to be stored according to the storage information
It asks；
Obtain the resource service condition information of memory module in all cloud nodes in the cloud resource pond；
The cloud node is screened based on the storage demand and the resource service condition information, obtains to deposit
Store up the candidate Yun Jiedian of the data to be stored；
It is the distribution that the data to be stored carries out storage resource based on the candidate Yun Jiedian.
In the embodiment of the present invention, the storage information of data to be stored is obtained first, is calculated according to the storage information wait deposit
The storage demand of data is stored up, the resource service condition information of all cloud nodes in current cluster is obtained, is then based on the storage
Demand and the resource service condition information are filtered all cloud nodes according to pre-set filter condition, obtain
It is the number to be stored from the filtered cloud node finally, using free time degree according to resource to filtered cloud node
According to the distribution for carrying out resource, it can be realized the reasonable utilization of storage resource, improve the allocative efficiency of storage resource.
Detailed description of the invention
It to describe the technical solutions in the embodiments of the present invention more clearly, below will be to embodiment or description of the prior art
Needed in attached drawing be briefly described, it should be apparent that, the accompanying drawings in the following description is only of the invention some
Embodiment for those of ordinary skill in the art without any creative labor, can also be according to these
Attached drawing obtains other attached drawings.
Fig. 1 is the schematic diagram of super fusion cloud computing system provided in an embodiment of the present invention；
Fig. 2 is the implementation process of the storage resource distribution method for the super fusion cloud computing system that the embodiment of the present invention one provides
Schematic diagram；
Fig. 3 is the structural representation of the storage resource distributor of super fusion cloud computing system provided by Embodiment 2 of the present invention
Figure；
Fig. 4 is the structural schematic diagram of screening module provided in an embodiment of the present invention；
Fig. 5 is another structural schematic diagram of screening module provided in an embodiment of the present invention；
Fig. 6 is the structural schematic diagram of distribution module provided in an embodiment of the present invention；
Fig. 7 is the structural schematic diagram of the second storage unit provided in an embodiment of the present invention；
Fig. 8 is the schematic diagram for the computer equipment that the embodiment of the present invention three provides.
Specific embodiment
In being described below, for illustration and not for limitation, the tool of such as particular system structure, technology etc is proposed
Body details, to understand thoroughly the embodiment of the present invention.However, it will be clear to one skilled in the art that there is no these specific
The present invention also may be implemented in the other embodiments of details.In other situations, it omits to well-known system, device, electricity
The detailed description of road and method, in case unnecessary details interferes description of the invention.
In order to illustrate technical solutions according to the invention, the following is a description of specific embodiments.
Fig. 1 shows the schematic diagram of super fusion cloud computing system provided in an embodiment of the present invention.As shown in Figure 1, described super
Fusion cloud computing system includes multiple super aggregators and switch, and each super aggregators include storage mould
The memory module of block, multiple super aggregators is connected to the network by the switch to form cloud resource
Pond, at least two super aggregators constitute a cloud node (Yun Jiedian is not shown).
Embodiment one:
Fig. 2 shows the realizations of the storage resource distribution method of the super fusion cloud computing system of the offer of the embodiment of the present invention one
Flow diagram.As shown in Fig. 2, the storage resource distribution method of the super fusion cloud computing system specifically comprises the following steps 101
To step 104.
Step 101: obtaining the storage information of data to be stored, the data to be stored is determined according to the storage information
Storage demand.
Wherein, storage information can be the amount of capacity of data to be stored, or data type and every kind of data
The amount of capacity of type.It should be noted that the executing subject of this step can be server, for example, server is obtained wait deposit
The amount of capacity for storing up data, determines storage demand according to the amount of capacity.
Step 102: obtaining the resource service condition information of memory module in all cloud nodes in the cloud resource pond.
Wherein, the resource service condition information of memory module includes but is not limited to the resources occupation rate of memory module.Storage
The resources occupation rate of module can be according to the operation occupancy and the comprehensive determination of storage occupancy of memory module.
Further, corresponding weight can be set according to the needs of analysis, respectively operation occupancy and storage occupancy.
For example, the weight of operation occupancy is w1, occupancy w2 is stored, then resources occupation rate=operation occupancy * w1+ storage occupies
Rate * w2.For example, operation occupancy is 60% (i.e. 0.6), the weight of operation occupancy is w1=0.6, and storage occupancy is 70%
(i.e. 0.7) stores occupancy w2=0.4, then resources occupation rate=0.6*0.6+0.7*0.4=0.64
Step 103: the cloud node being screened based on the storage demand and the resource service condition information, is obtained
To the candidate Yun Jiedian that can store the data to be stored.
In step 103, resource service condition information in storage demand obtained in step 101 and step 102 is carried out
Matching, to screen to cloud node, obtains the candidate Yun Jiedian that can store the data to be stored.It can store described
The candidate Yun Jiedian of data to be stored can be one or more.
As a preferred embodiment of the present invention, step 103 specifically includes step 201, step 202, step 203, step
Rapid 204 and step 205, specific as follows:
Step 201: judging whether fully loaded early warning queue is empty according to the loading thresholds of cloud node, if fully loaded early warning queue is not
For sky, 202 are thened follow the steps.
Wherein, the loading thresholds of Yun Jiedian can be configured according to the hardware specification for surpassing fusion all-in-one machine in cloud node.
Further, in order to guarantee that cloud node is in preferably operating status, the loading thresholds, which may be configured as being less than in cloud node, to be surpassed
All-in-one machine capacity is merged, as set all super fusion all-in-one machine capacity in the cloud node for the loading thresholds of cloud node
80%.Judge whether fully loaded early warning queue is sky according to the loading thresholds of cloud node, if it is empty then illustrates that cloud node has been fully loaded with
?.If fully loaded early warning queue is not sky, 202 are thened follow the steps.
Step 202: whether being sky according to unloaded threshold decision zero load early warning queue, when the unloaded early warning queue is not empty
When, 203 are thened follow the steps, when unloaded early warning queue is empty, executes step 205.
Step 203: obtaining unloaded early warning cloud node from the unloaded early warning queue, and by the unloaded early warning cloud node
Cloud node is utilized as resource priority.
Step 204: judge the resource priority using in cloud node with the presence or absence of the cloud that matches with the storage demand
Node；The cloud node to match if it exists with the storage demand, then using the resource priority using cloud node as candidate cloud
Node.
Step 205: judge the request queue of cloud machine whether be it is empty, if the request queue of cloud machine be not it is empty, then follow the steps 206.
Step 206: the directory information of all cloud nodes in the cloud resource pond is obtained, according to cloud node and the storage need
The matching degree asked is filtered the cloud node in the directory information and is filtered as a result, being filtered out according to the filter result
Candidate Yun Jiedian.
Before judging whether fully loaded early warning queue is sky according to the loading thresholds of cloud node in above-mentioned steps 201, also wrap
Step 301 and step 302 are included, specific as follows:
Step 301: obtaining the every load attribute value and consumption rate of all cloud nodes.
Wherein, load attribute value refers to that the hardware specification for surpassing fusion all-in-one machine in cloud node, hardware specification include but not
It is limited to CPU, hard disk and memory, accordingly, consumption rate includes the consumption rate of hard disk and the utilization rate of memory.
Step 302: according to the load attribute value and consumption rate setting loading thresholds and unloaded threshold value.
Loading thresholds and unloaded threshold value are set separately in load attribute value and consumption rate according to obtained in step 301.
Step 104: being the distribution that the data to be stored carries out storage resource based on the candidate Yun Jiedian.
As an embodiment of the present invention, above-mentioned steps 104 include step 401, step 402 and step 403, specifically such as
Under:
Step 401: judging in the candidate Yun Jiedian with the presence or absence of the mesh that can disposably accommodate the data to be stored
Mark Yun Jiedian, and if it exists, then follow the steps 202, then follow the steps 203 if it does not exist.
Step 402: the data to be stored is stored in the target cloud node.
Step 403: if it does not exist, then the data to be stored being stored at least two candidate Yun Jiedian.
Further, step 403 specifically may include step 501, step 502 and step 503, specific as follows:
Step 501: obtaining the write-in end address information of the data to be stored.
Wherein, the address information of terminal where write-in end address information refers to data to be stored.
Step 502: according to said write end address information, being determined from the storage resource address information in the cloud resource pond
The nearest candidate Yun Jiedian with said write end address.
Step 503: being used according to backup quantity needed for the data to be stored and the resource of the candidate Yun Jiedian empty
Not busy degree, selects corresponding with backup quantity target storage resource in the candidate Yun Jiedian, and by the number to be stored
According to preservation into the target storage resource.
For step 502, specifically comprise the following steps:
Step 601: according to said write end address information, determining that candidate's Yun Jiedian mistake is written in the data to be stored
The length of migration path in journey will be write on the smallest at least two candidates Yun Jiedian of the length of the migration path as with described
Enter to hold the nearest candidate Yun Jiedian in address.
For example, the migration path for carrying out the candidate Yun Jiedian of write operation to data to be stored is L1 or L2.Calculate road
The length of diameter, if it is determined that the path of L1 is shorter, then using the corresponding cloud node of migration path L1 as with said write end address
Nearest candidate Yun Jiedian.
On the basis of step 601, step 503 is specific can include:
Step 701: candidate Yun Jiedian shortest to migration path is screened to obtain target cloud node, in the target
Target storage resource corresponding with the backup quantity is selected in cloud node, and the data to be stored is saved to the target
In storage resource.
Wherein, the condition that above-mentioned candidate Yun Jiedian shortest to migration path is screened are as follows: the storage of candidate Yun Jiedian
Utilization rate highest, and space utilisation is no more than default utilization threshold (such as 50%).For example, the shortest candidate cloud of migration path
Node is cloud node A, B, C；E, D, F or G, H, I.Cloud node A, B, C；E, D, F or G, H, I are after being written data to be stored
Space utilisation be followed successively by M1, M2 and M3, the space utilisation of the shortest candidate Yun Jiedian of migration path is compared, such as
Fruit comparison result are as follows: preset utilization threshold > M1 > M2 > M3, then the target cloud node in the shortest candidate Yun Jiedian of migration path
For cloud node A, B and C, target storage resource corresponding with the backup quantity is selected in described target cloud node A, B and C,
And the data to be stored is saved into the target storage resource.
As shown in the above, it in the shortest not unique situation of candidate Yun Jiedian of migration path, can quickly determine
Unique target cloud node improves the efficiency of storage so that target cloud node is more acurrate.
In the embodiment of the present invention, the storage information of data to be stored is obtained first, is calculated according to the storage information wait deposit
The storage demand of data is stored up, the resource service condition information of all cloud nodes in current cluster is obtained, is then based on the storage
Demand and the resource service condition information are filtered all cloud nodes according to pre-set filter condition, obtain
It is the number to be stored from the filtered cloud node finally, using free time degree according to resource to filtered cloud node
According to the distribution for carrying out resource, it can be realized the reasonable utilization of storage resource, improve the allocative efficiency of storage resource.
It should be understood that the size of the serial number of each step is not meant that the order of the execution order in above-described embodiment, each process
Execution sequence should be determined by its function and internal logic, the implementation process without coping with the embodiment of the present invention constitutes any limit
It is fixed.
Embodiment two:
Referring to FIG. 3, it illustrates the storage resource distribution of super fusion cloud computing system provided by Embodiment 2 of the present invention
The structural schematic diagram of device.The storage resource distributor 30 of super fusion cloud computing system includes: the first acquisition module 31, second
Obtain module 32, screening module 33 and distribution module 34.Wherein, the concrete function of each module is as follows:
First obtain module, for obtaining the storage information of data to be stored, according to the storage information determine described in
The storage demand of storing data；
Second obtains module, for obtaining the resource service condition of memory module in all cloud nodes in the cloud resource pond
Information；
Screening module, for being sieved based on the storage demand and the resource service condition information to the cloud node
Choosing, obtains the candidate Yun Jiedian that can store the data to be stored；
Distribution module, for being the distribution of data to be stored progress storage resource based on the candidate Yun Jiedian.
Optionally, as shown in figure 4, screening module 33 includes:
First judging unit 331, for judging whether fully loaded early warning queue is empty according to the loading thresholds of cloud node.
Second judgment unit 332, if not being sky for fully loaded early warning queue, according to the unloaded pre- police of unloaded threshold decision
Whether column are empty.
Selecting unit 333, for when the unloaded early warning queue is not sky, then being obtained from the unloaded early warning queue
Unloaded early warning cloud node, and cloud node is utilized using the unloaded early warning cloud node as resource priority.
Third judging unit 334, for judging that the resource priority is needed using in cloud node with the presence or absence of with the storage
Seek the cloud node to match；The resource priority is then utilized cloud section by the cloud node to match if it exists with the storage demand
Point is used as candidate Yun Jiedian.
4th judging unit 335, for when unloaded early warning queue is empty, judging whether the request queue of cloud machine is empty.
Filter element 336 obtains all cloud nodes in the cloud resource pond if not being sky for the request queue of cloud machine
Directory information is filtered to obtain according to cloud node and the matching degree of the storage demand to the cloud node in the directory information
Filter result filters out candidate Yun Jiedian according to the filter result.
Optionally, as shown in figure 5, screening module 33 further include:
Acquiring unit 337, for obtaining the every load attribute value and consumption rate of all cloud nodes.
Definition unit 338, for according to the load attribute value and consumption rate setting loading thresholds and unloaded threshold value.
Optionally, as shown in fig. 6, distribution module 34 includes:
4th judging unit 341, for judge in the candidate Yun Jiedian with the presence or absence of can disposably accommodate it is described to
The target cloud node of storing data.
First storage unit 342, for if it exists, then the data to be stored being stored in the target cloud node.
Second storage unit 343, for if it does not exist, then the data to be stored being stored at least two candidate Yun Jie
Point on.
Optionally, as shown in fig. 7, the second storage unit 343 includes:
Subelement 3431 is obtained, for obtaining the write-in end address information of the data to be stored.
Determine subelement 3432, for according to said write end address information, from the storage resource in the cloud resource pond
The determining candidate Yun Jiedian nearest with said write end address in the information of location.
Subelement 3433 is selected, for the backup quantity according to needed for the data to be stored and the candidate Yun Jiedian
Resource uses free time degree, corresponding with the backup quantity target storage resource of selection in the candidate Yun Jiedian, and by institute
Data to be stored is stated to save into the target storage resource.
In the embodiment of the present invention, the storage information of data to be stored is obtained first, is calculated according to the storage information wait deposit
The storage demand of data is stored up, the resource service condition information of all cloud nodes in current cluster is obtained, is then based on the storage
Demand and the resource service condition information are filtered all cloud nodes according to pre-set filter condition, obtain
It is the number to be stored from the filtered cloud node finally, using free time degree according to resource to filtered cloud node
According to the distribution for carrying out resource, it can be realized the reasonable utilization of storage resource, improve the allocative efficiency of storage resource.
Embodiment three:
Fig. 8 is the schematic diagram for the computer equipment that the embodiment of the present invention three provides.As shown in figure 8, the calculating of the embodiment
Machine equipment 8 includes: processor 80, memory 81 and is stored in the memory 81 and can run on the processor 80
Computer program 82, such as the storage resource distribution method program of super fusion cloud computing system.The processor 80 executes institute
The step in the storage resource distribution method embodiment of above-mentioned each super fusion cloud computing system is realized when stating computer program 82,
Such as step 101 shown in Fig. 2 is to 104.Alternatively, the processor 80 realizes above-mentioned each dress when executing the computer program 82
The function of each unit in embodiment is set, such as the function of module 31 to 34 shown in Fig. 3.
Illustratively, the computer program 82 can be divided into one or more module/units, it is one or
Multiple module/units are stored in the memory 81, and are executed by the processor 80, to complete the present invention.Described one
A or multiple module/units can be the series of computation machine program instruction section that can complete specific function, which is used for
The computer program 82 is described in the storage resource distributor 8 of the super fusion cloud computing system of the computer equipment
Implementation procedure.For example, the computer program 82 can be divided into the first acquisition module, the second acquisition module, screening module
And distribution module, the concrete function of each module are as follows:
First obtain module, for obtaining the storage information of data to be stored, according to the storage information determine described in
The storage demand of storing data.
Second obtains module, for obtaining the resource service condition of memory module in all cloud nodes in the cloud resource pond
Information.
Screening module, for being sieved based on the storage demand and the resource service condition information to the cloud node
Choosing, obtains the candidate Yun Jiedian that can store the data to be stored.
Distribution module, for being the distribution of data to be stored progress storage resource based on the candidate Yun Jiedian.
The computer equipment 8 can be the calculating such as desktop PC, notebook, palm PC and cloud server and set
It is standby.The computer equipment may include, but be not limited only to, processor 80, memory 81.It will be understood by those skilled in the art that
Fig. 8 is only the example of computer equipment, does not constitute the restriction to computer equipment, may include more more or less than illustrating
Component, perhaps combine certain components or different components, such as the computer equipment can also be set including input and output
Standby, network access equipment, bus etc..
Alleged processor 80 can be central processing unit (Central Processing Unit, CPU), can also be
Other general processors, digital signal processor (Digital Signal Processor, DSP), specific integrated circuit
(Application Specific Integrated Circuit, ASIC), ready-made programmable gate array (Field-
Programmable Gate Array, FPGA) either other programmable logic device, discrete gate or transistor logic,
Discrete hardware components etc..General processor can be microprocessor or the processor is also possible to any conventional processor
Deng.
The memory 81 can be the internal storage unit of the computer equipment 8, such as the hard disk of computer equipment 8
Or memory.The memory 81 is also possible to the External memory equipment of the computer equipment 8, such as the computer equipment 8
The plug-in type hard disk of upper outfit, intelligent memory card (Smart Media Card, SMC), secure digital (Secure Digital,
SD) block, flash card (Flash Card) etc..Further, the memory 81 can also both include the computer equipment 8
Internal storage unit also includes External memory equipment.The memory 81 is for storing the computer program and the calculating
Other programs and data needed for machine equipment.The memory 81, which can be also used for temporarily storing, have been exported or will be defeated
Data out.
It is apparent to those skilled in the art that for convenience of description and succinctly, only with above-mentioned each function
Can unit, module division progress for example, in practical application, can according to need and by above-mentioned function distribution by different
Functional unit, module are completed, i.e., the internal structure of described device is divided into different functional unit or module, more than completing
The all or part of function of description.Each functional unit in embodiment, module can integrate in one processing unit, can also
To be that each unit physically exists alone, can also be integrated in one unit with two or more units, it is above-mentioned integrated
Unit both can take the form of hardware realization, can also realize in the form of software functional units.In addition, each function list
Member, the specific name of module are also only for convenience of distinguishing each other, the protection scope being not intended to limit this application.Above system
The specific work process of middle unit, module, can refer to corresponding processes in the foregoing method embodiment, and details are not described herein.
In the above-described embodiments, it all emphasizes particularly on different fields to the description of each embodiment, is not described in detail or remembers in some embodiment
The part of load may refer to the associated description of other embodiments.
Those of ordinary skill in the art may be aware that list described in conjunction with the examples disclosed in the embodiments of the present disclosure
Member and algorithm steps can be realized with the combination of electronic hardware or computer software and electronic hardware.These functions are actually
It is implemented in hardware or software, the specific application and design constraint depending on technical solution.Professional technician
Each specific application can be used different methods to achieve the described function, but this realization is it is not considered that exceed
The scope of the present invention.
In embodiment provided by the present invention, it should be understood that disclosed device/terminal device and method, it can be with
It realizes by another way.For example, device described above/terminal device embodiment is only schematical, for example, institute
The division of module or unit is stated, only a kind of logical function partition, there may be another division manner in actual implementation, such as
Multiple units or components can be combined or can be integrated into another system, or some features can be ignored or not executed.Separately
A bit, shown or discussed mutual coupling or direct-coupling or communication connection can be through some interfaces, device
Or the INDIRECT COUPLING or communication connection of unit, it can be electrical property, mechanical or other forms.
The unit as illustrated by the separation member may or may not be physically separated, aobvious as unit
The component shown may or may not be physical unit, it can and it is in one place, or may be distributed over multiple
In network unit.It can select some or all of unit therein according to the actual needs to realize the mesh of this embodiment scheme
's.
It, can also be in addition, the functional units in various embodiments of the present invention may be integrated into one processing unit
It is that each unit physically exists alone, can also be integrated in one unit with two or more units.Above-mentioned integrated list
Member both can take the form of hardware realization, can also realize in the form of software functional units.
If the integrated module/unit be realized in the form of SFU software functional unit and as independent product sale or
In use, can store in a computer readable storage medium.Based on this understanding, the present invention realizes above-mentioned implementation
All or part of the process in example method, can also instruct relevant hardware to complete, the meter by computer program
Calculation machine program can be stored in a computer readable storage medium, the computer program when being executed by processor, it can be achieved that on
The step of stating each embodiment of the method.Wherein, the computer program includes computer program code, the computer program generation
Code can be source code form, object identification code form, executable file or certain intermediate forms etc..The computer-readable medium
It may include: any entity or device, recording medium, USB flash disk, mobile hard disk, magnetic that can carry the computer program code
Dish, CD, computer storage, read-only memory (ROM, Read-Only Memory), random access memory (RAM,
Random Access Memory), electric carrier signal, telecommunication signal and software distribution medium etc..It should be noted that described
The content that computer-readable medium includes can carry out increasing appropriate according to the requirement made laws in jurisdiction with patent practice
Subtract, such as does not include electric carrier signal and electricity according to legislation and patent practice, computer-readable medium in certain jurisdictions
Believe signal.
Embodiment described above is merely illustrative of the technical solution of the present invention, rather than its limitations；Although referring to aforementioned reality
Applying example, invention is explained in detail, those skilled in the art should understand that: it still can be to aforementioned each
Technical solution documented by embodiment is modified or equivalent replacement of some of the technical features；And these are modified
Or replacement, the spirit and scope for technical solution of various embodiments of the present invention that it does not separate the essence of the corresponding technical solution should all
It is included within protection scope of the present invention.
Claims (10)
1. a kind of storage resource distribution method of super fusion cloud computing system, which is characterized in that the super fusion cloud computing system
Including multiple super aggregators and switch, each super aggregators include memory module, multiple described super to melt
The memory module for closing node is connected to the network to form cloud resource pond by the switch, and at least two is described super
Aggregators constitute a cloud node, and the storage resource distribution method includes:
The storage information for obtaining data to be stored determines the storage demand of the data to be stored according to the storage information；
Obtain the resource service condition information of memory module in all cloud nodes in the cloud resource pond；
The cloud node is screened based on the storage demand and the resource service condition information, obtains that institute can be stored
State the candidate Yun Jiedian of data to be stored；
It is the distribution that the data to be stored carries out storage resource based on the candidate Yun Jiedian.
2. the storage resource distribution method of super fusion cloud computing system as described in claim 1, which is characterized in that described to be based on
The storage demand and the resource service condition information screen the cloud node, obtain to store described wait store
The candidate Yun Jiedian of data includes:
Judge whether fully loaded early warning queue is empty according to the loading thresholds of cloud node；
It whether is empty according to unloaded threshold decision zero load early warning queue if fully loaded early warning queue is not empty；
When the unloaded early warning queue is not sky, then unloaded early warning cloud node is obtained from the unloaded early warning queue, and will
The zero load early warning cloud node utilizes cloud node as resource priority；
Judge the resource priority using in cloud node with the presence or absence of the cloud node that matches with the storage demand；If it exists with
The cloud node that the storage demand matches, then using the resource priority using cloud node as candidate Yun Jiedian；
When unloaded early warning queue is empty, judge whether the request queue of cloud machine is empty；
If the request queue of cloud machine is not sky, the directory information of all cloud nodes in the cloud resource pond is obtained, according to cloud node
The cloud node in the directory information is filtered with the matching degree of the storage demand and is filtered as a result, according to the mistake
Filter result filters out candidate Yun Jiedian.
3. the storage resource distribution method of super fusion cloud computing system as claimed in claim 2, which is characterized in that at described
Before judging whether fully loaded early warning queue is sky according to the loading thresholds of cloud node, further includes:
Obtain the every load attribute value and consumption rate of all cloud nodes；
According to the load attribute value and consumption rate setting loading thresholds and unloaded threshold value.
4. storage resource distribution method as described in claim 1, which is characterized in that based on the candidate Yun Jiedian be described in
Storing data carry out storage resource distribution include:
Judge in the candidate Yun Jiedian with the presence or absence of the target cloud node that can disposably accommodate the data to be stored；
If it exists, then the data to be stored is stored in the target cloud node；
If it does not exist, then the data to be stored is stored at least two candidate Yun Jiedian.
5. the storage resource distribution method of fusion cloud computing system as claimed in claim 4 super, which is characterized in that will it is described to
Storing data is stored at least two candidate Yun Jiedian
Obtain the write-in end address information of the data to be stored；
According to said write end address information, the determining and said write end from the storage resource address information in the cloud resource pond
The nearest candidate Yun Jiedian in address；
Free time degree is used according to backup quantity needed for the data to be stored and the resource of the candidate Yun Jiedian, in the time
It selects and selects target storage resource corresponding with the backup quantity in cloud node, and the data to be stored is saved to the mesh
It marks in storage resource.
6. a kind of storage resource distributor of super fusion cloud computing system characterized by comprising
First obtains module, for obtaining the storage information of data to be stored, is determined according to the storage information described wait store
The storage demand of data；
Second obtains module, and the resource service condition for obtaining memory module in all cloud nodes in the cloud resource pond is believed
Breath；
Screening module, for being screened based on the storage demand and the resource service condition information to the cloud node,
Obtain to store the candidate Yun Jiedian of the data to be stored；
Distribution module, for being the distribution of data to be stored progress storage resource based on the candidate Yun Jiedian.
7. the storage resource distributor of super fusion cloud computing system as claimed in claim 6, which is characterized in that the screening
Module includes:
First judging unit, for judging whether fully loaded early warning queue is empty according to the loading thresholds of cloud node；
Second judgment unit, if for fully loaded early warning queue be not it is empty, according to unloaded threshold decision zero load early warning queue whether
For sky；
Selecting unit, for when the unloaded early warning queue is not sky, then being obtained from the unloaded early warning queue unloaded pre-
Alert cloud node, and cloud node is utilized using the unloaded early warning cloud node as resource priority；
Third judging unit, for judge the resource priority using in cloud node with the presence or absence of matching with the storage demand
Cloud node；The cloud node to match if it exists with the storage demand, then using the resource priority using cloud node as time
Select Yun Jiedian；
4th judging unit, for when unloaded early warning queue is empty, judging whether the request queue of cloud machine is empty；
Filter element obtains the catalogue letter of all cloud nodes in the cloud resource pond if not being sky for the request queue of cloud machine
Breath is filtered the cloud node in the directory information to obtain filtering knot according to cloud node and the matching degree of the storage demand
Fruit filters out candidate Yun Jiedian according to the filter result.
8. the storage resource distributor of super fusion cloud computing system as claimed in claim 7, which is characterized in that further include:
Acquiring unit, for obtaining the every load attribute value and consumption rate of all cloud nodes；
Definition unit, for according to the load attribute value and consumption rate setting loading thresholds and unloaded threshold value.
9. a kind of computer equipment, including memory, processor and storage are in the memory and can be in the processor
The computer program of upper operation, which is characterized in that the processor realized when executing the computer program as claim 1 to
The step of any one of 5 the method.
10. a kind of computer readable storage medium, the computer-readable recording medium storage has computer program, and feature exists
In when the computer program is executed by processor the step of any one of such as claim 1 to 5 of realization the method.
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