CN111443989B - Virtual machine placement method, device, equipment and storage medium based on harmony search - Google Patents
Virtual machine placement method, device, equipment and storage medium based on harmony search Download PDFInfo
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Abstract
The invention belongs to the technical field of cloud computing, and discloses a virtual machine placement method, device and equipment based on harmony search and a storage medium. The method comprises the following steps: acquiring a virtual machine set and a physical host set to be placed, and establishing a sound memory library according to the virtual machine set and the physical host set; generating a new harmony according to the preset harmony generation condition; performing fitness calculation on various harmony sounds and new harmony sounds in the harmony sound memory library, and updating harmony sounds in the harmony sound memory library according to a calculation result; determining a target harmony with the maximum fitness value according to the updating result, and taking the tone information of the target harmony as the optimal solution for placing the virtual machine; and placing the virtual machines in the virtual machine set into the physical hosts corresponding to the physical host set according to the optimal solution for placing the virtual machines. Under the condition that the resource utilization rate and the energy consumption of the physical host are both constrained, the low-energy optimization of virtual machine placement is formed by generating a new harmony, namely a new placement scheme.
Description
Technical Field
The invention relates to the technical field of cloud computing, in particular to a virtual machine placement method, device and equipment based on harmony search and a storage medium.
Background
The problem of high energy consumption within cloud computing data centers is becoming more and more pronounced, with energy consumption of the energy and cooling systems already making up a major portion of the operational costs of the data centers. The low utilization efficiency of the physical hosts increases the energy consumption cost of the data center. Through virtualization technology, a plurality of virtual machines can be virtualized on one physical host machine, and user application is executed by taking the virtual machines as units. How to place virtual machines on hosts becomes a key factor ultimately affecting power consumption. The virtual machine placement problem is the process of placing a set of virtual machines to a physical host. Different virtual machine placement policies will result in different host power consumption due to the heterogeneity of virtual machines across resource requests and the difference in host resource provisioning capabilities. Research shows that the idle physical hosts still consume more than half of the full power consumption. In order to reduce the overall energy consumption, the virtual machine placement should be performed using as few hosts as possible, thereby shutting down completely unused hosts and saving the energy consumption of the idle part.
The harmony search mechanism is a heuristic method with high efficiency, the method simulates the impulse music playing process, players adjust musical instrument tones in impulse, and the aim is to play the best harmony through different tone adjustment, so that the harmony search mechanism can be used for continuous space optimization problems and discrete space optimization problems. Based on the method, the implementation is simple, and the dependent parameters are less.
Disclosure of Invention
The invention mainly aims to provide a virtual machine placement method, device, equipment and storage medium based on harmony search, which aim to solve the technical problem of how to realize virtual machine placement with less dependent parameters and low energy consumption.
In order to achieve the above object, the present invention provides a virtual machine placement method based on harmony search, the method comprising:
acquiring a virtual machine set and a physical host set to be placed, and establishing a sound memory library according to the virtual machine set and the physical host set;
generating a new harmony according to the preset harmony generation condition;
performing fitness calculation on various harmony sounds in the harmony memory library and the new harmony sounds, and updating harmony sounds in the harmony memory library according to a calculation result;
determining a target harmony with the maximum fitness value according to the updating result, and taking the tone information of the target harmony as a virtual machine placement optimal solution;
And placing the virtual machines in the virtual machine set into the physical hosts corresponding to the physical host set according to the optimal placement solution of the virtual machines.
Preferably, the step of obtaining a set of virtual machines and a set of physical hosts to be placed, and establishing a sound memory bank according to the set of virtual machines and the set of physical hosts specifically includes:
acquiring the number of physical hosts corresponding to the physical host set and the number of virtual machines corresponding to the virtual machine set;
taking the virtual machine number as the tone information number corresponding to various sounds, and randomly setting the tone information corresponding to various sounds according to the physical host number;
and establishing a harmony memory library according to the preset sum sound seed number, the tone information number and the tone information.
Preferably, the step of generating a new harmony according to the preset harmony generation condition specifically includes:
randomly setting tone information with the number of the virtual machines according to the physical host machine number so as to obtain harmony to be processed;
and selecting the harmony memory bank and performing pitch fine tuning disturbance processing on the harmony to be processed so as to acquire a processed new harmony.
Preferably, the step of performing sum sound memory bank selection processing and pitch fine tuning disturbance processing on the sum sound to be processed to obtain a processed new sum sound specifically includes:
Generating a first random number pair corresponding to each tone information in the harmony to be processed, randomly selecting tone information from a harmony memory bank according to the first random number pair and a preset harmony memory bank selection probability, and replacing the tone information corresponding to the harmony to be processed with the tone information;
and generating a second random number pair corresponding to each tone information in the harmony to be processed, and carrying out tone fine tuning disturbance processing on the replaced tone information according to the second random number pair, the tone adjustment probability and the disturbance bandwidth so as to acquire a processed new harmony.
Preferably, before the step of generating the first random number pair corresponding to each tone information in the sound to be processed, randomly selecting the tone information from the sound memory bank according to the first random number pair and a preset sound memory bank selection probability, and replacing the tone information corresponding to the sound to be processed with the tone information, the method further includes:
acquiring the current iteration times of the harmony memory bank;
and updating the tone adjustment probability and the disturbance bandwidth according to the current iteration times.
Preferably, the step of adaptively calculating various harmony sounds in the harmony memory and the new harmony sounds and updating the harmony sounds in the harmony memory according to the calculation result specifically includes:
Performing fitness calculation on various harmony sounds and the new harmony sounds in the harmony sound memory library;
acquiring a to-be-selected harmony with the minimum current fitness value in the harmony memory library, and judging whether the fitness value of the new harmony is larger than the fitness value of the to-be-selected harmony;
and when the fitness value of the new harmony is larger than that of the harmony to be selected, replacing the harmony to be selected with the new harmony so as to update the harmony in the harmony memory bank.
Preferably, after the step of determining the target harmony with the largest fitness value according to the updated result and taking the pitch information of the target harmony as the optimal solution for placing the virtual machine, the method further includes:
detecting the current iteration number of a current harmony memory bank, and judging whether the current iteration number is smaller than a preset iteration number or not;
returning to the step of generating a new harmony according to a preset harmony generating condition when the current iteration number is smaller than the preset iteration number;
and outputting the optimal solution placed by the virtual machine when the current iteration number is equal to the preset iteration number.
In addition, in order to achieve the above object, the present invention also proposes a virtual machine placement device based on harmony search, the device comprising: the system comprises a sound library establishing module, an adaptability calculating module, an optimal solution obtaining module and a placing module, wherein the sound library establishing module is used for establishing a sound library;
The harmony library establishing module is used for acquiring a virtual machine set and a physical host set to be placed, and establishing a harmony memory library according to the virtual machine set and the physical host set;
the fitness computing module is used for generating a new harmony according to preset harmony generation conditions; the method is also used for carrying out adaptability calculation on various harmony sounds in the harmony memory library and the new harmony sounds, and updating harmony sounds in the harmony memory library according to a calculation result;
the optimal solution acquisition module is used for determining a target harmony with the maximum fitness value according to the updating result, and taking the tone information of the harmony as a virtual machine to place an optimal solution;
the placement module is configured to place the virtual machines in the virtual machine set into physical hosts corresponding to the physical host set according to the optimal placement solution of the virtual machines.
In addition, in order to achieve the above object, the present invention also proposes a virtual machine placement device based on harmony search, the device comprising: the system comprises a memory, a processor, and a harmony search-based virtual machine placement program stored on the memory and executable on the processor, the harmony search-based virtual machine placement program configured to implement the steps of the harmony search-based virtual machine placement method as described above.
In addition, in order to achieve the above object, the present invention also proposes a storage medium having stored thereon a harmony search-based virtual machine placement program which, when executed by a processor, implements the steps of the harmony search-based virtual machine placement method as described above.
The method comprises the steps of obtaining a virtual machine set and a physical host set to be placed, and establishing a sound memory library according to the virtual machine set and the physical host set; generating a new harmony according to the preset harmony generation condition; performing fitness calculation on various harmony sounds in the harmony memory library and the new harmony sounds, and updating harmony sounds in the harmony memory library according to a calculation result; determining a target harmony with the maximum fitness value according to the updating result, and taking the tone information of the target harmony as a virtual machine placement optimal solution; and placing the virtual machines in the virtual machine set into the physical hosts corresponding to the physical host set according to the optimal placement solution of the virtual machines. Under the condition that the resource utilization rate and the energy consumption of the physical host are both constrained, a new harmony, namely a new placement scheme is generated, so that low-energy optimization of virtual machine placement is formed, and the efficiency and the effect of virtual machine placement are improved.
Drawings
FIG. 1 is a schematic diagram of a virtual machine placement device based on harmony search for a hardware execution environment according to an embodiment of the present invention;
FIG. 2 is a flowchart of a first embodiment of a virtual machine placement method based on harmony search according to the present invention;
FIG. 3 is a flowchart of a second embodiment of a virtual machine placement method based on harmony search according to the present invention;
fig. 4 is a block diagram of a first embodiment of a virtual machine placement device based on harmony search according to the present invention.
The achievement of the objects, functional features and advantages of the present invention will be further described with reference to the accompanying drawings, in conjunction with the embodiments.
Detailed Description
It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the invention.
Referring to fig. 1, fig. 1 is a schematic structural diagram of a virtual machine placement device based on harmony search in a hardware running environment according to an embodiment of the present invention.
As shown in fig. 1, the harmony search-based virtual machine placement apparatus may include: a processor 1001, such as a central processing unit (Central Processing Unit, CPU), a communication bus 1002, a user interface 1003, a network interface 1004, a memory 1005. Wherein the communication bus 1002 is used to enable connected communication between these components. The user interface 1003 may include a Display, an input unit such as a Keyboard (Keyboard), and the optional user interface 1003 may further include a standard wired interface, a wireless interface. The network interface 1004 may optionally include a standard wired interface, a WIreless interface (e.g., a WIreless-FIdelity (WI-FI) interface). The Memory 1005 may be a high-speed random access Memory (Random Access Memory, RAM) Memory or a stable nonvolatile Memory (NVM), such as a disk Memory. The memory 1005 may also optionally be a storage device separate from the processor 1001 described above.
Those skilled in the art will appreciate that the structure shown in fig. 1 does not constitute a limitation of the harmony search based virtual machine placement apparatus, and may include more or fewer components than illustrated, or may combine certain components, or may be a different arrangement of components.
As shown in fig. 1, an operating system, a network communication module, a user interface module, and a harmony search-based virtual machine placement program may be included in the memory 1005 as one storage medium.
In the harmony search-based virtual machine placement device shown in fig. 1, the network interface 1004 is mainly used for data communication with a network server; the user interface 1003 is mainly used for data interaction with a user; the processor 1001 and the memory 1005 in the harmony search based virtual machine placement apparatus of the present invention may be disposed in the harmony search based virtual machine placement apparatus, which invokes the harmony search based virtual machine placement program stored in the memory 1005 through the processor 1001 and performs the harmony search based virtual machine placement method provided by the embodiment of the present invention.
The embodiment of the invention provides a virtual machine placement method based on harmony search, and referring to fig. 2, fig. 2 is a flow diagram of a first embodiment of the virtual machine placement method based on harmony search.
In the cloud computing environment, the energy consumption of the physical host mainly comes from the CPU, the RAM, the storage system, and the like. Typically, the power consumption of the CPU occupies a significant portion of the physical host power consumption. The single CPU power saving technique is most commonly used with dynamic voltage/frequency scaling (DVFS, dynamic voltage and frequency scaling). The technology mainly considers two states of the CPU: idle state and load state. In an idle state (i.e., without any execution load), internal components of the CPU may be switched to a shutdown mode, thereby reducing the clock frequency of the CPU, which may operate at a minimum operating frequency, thereby saving energy. In the load state, the energy consumption of the CPU depends on the amount of load performed on the CPU and the utilization of the CPU. Studies have shown that the power consumption of a physical host is linear with its CPU utilization.
Defining a host power consumption formula as follows:
wherein P is j，max Representing a physical host h j Maximum power consumption of (1), i.e. power consumption when the physical host is fully loaded, P j ， idle Representing a physical host h j I.e. the power consumption in the idle condition of the physical host, which is typically 70% of the full power consumption, u j，CPU Representing a physical host h j CPU utilization of (c).
It is easy to understand that, assuming that there is an existing virtual machine n-stage to be placed in the cloud computing environment, the virtual machine n-stage is represented as a set v= { V 1 ，v 2 ，...，v n Available physical hosts have m stations, denoted as set h= { H 1 ，h 2 ，...，h m }. The virtual machine placement problem is the process of mapping a set of virtual machines to a physical host. Consider a request for three resource types in a placement process, including: CPU, memory RAM and DISK storage DISK. Let r i，CPU 、r i，RAM And r i，DISK Respectively represent virtual machines v i Request amounts on CPU resources, memory RAM resources, and storage DISK resources, i=1, 2,..n, c j，CPU 、c j，RAM And c j，DISK Respectively represent physical hosts h j The provisioning capability on CPU resources, memory RAM resources, and storage DISK resources, j=1, 2. Let x i，j Representing placement factors, indicating virtual machine v i Whether or not to be placed on the physical host h j Above, as a binary variable, the expression of the placement factor is:
let z j Representing the utilization factor of the physical host, representing the physical host h in the virtual machine placement process j Whether or not utilized, as a binary variable, the expression of the utilization factor is:
in order to save the energy consumption of the physical host, the physical host in the complete idle state needs to be converted into the sleep mode, so that the energy consumption of the idle physical host is saved. Therefore, the energy consumption minimization formula is:
the corresponding constraint conditions are as follows: the virtual machine corresponds to constraint conditions, so that one virtual machine can be placed on one physical host only, and the corresponding formula is as follows:
The placement factor constraint condition indicates that the placement factor is a binary number which can only take the value of 0 or 1, and the corresponding formula is as follows:
the utilization factor constraint condition shows that the physical host utilization factor is a binary number which can only take the value of 0 or 1, and the corresponding formula is as follows:
the memory constraint condition indicates that the memory amount requested by the virtual machine cannot exceed the memory capacity of the host, and the corresponding formula is as follows:
the memory request constraint condition ensures that the memory resource requested by the virtual machine cannot exceed the memory capacity of the physical host, and the corresponding formula is as follows:
the constraint condition of the storage request ensures that the storage resource requested by the virtual machine cannot exceed the storage capacity of the physical host, and the corresponding formula is as follows:
in this embodiment, the virtual machine placement method based on harmony search includes the following steps:
step S10, a virtual machine set and a physical host set to be placed are obtained, and a sound memory library is built according to the virtual machine set and the physical host set.
The step S10 specifically includes: acquiring the number of physical hosts corresponding to the physical host set and the number of virtual machines corresponding to the virtual machine set; taking the virtual machine number as the tone information number corresponding to various sounds, and randomly setting the tone information corresponding to various sounds according to the physical host number; and establishing a harmony memory library according to the preset sum sound seed number, the tone information number and the tone information.
Let a harmony h be expressed as:
X h ＝[x h,1 ,x h,2 ,...,x h,n ]
wherein element x in the vector h，k Representing the tone played by the kth instrument in harmony h, the tone corresponding to the physical host number of the placed virtual machine k, the physical host number having a value of [1, m]In-interval integer, h=1, 2, …, HMS representation and sound noteThe memory library is of a size, HMS is a preset number and a sound number, the HMS can be set according to actual requirements of problems, k=1, 2, …, n and n represent the number of musical instruments, and the number corresponds to the total number of virtual machines to be placed, namely the number of corresponding tone information. In other words, a harmony representation of a virtual machine placement scheme may be defined within an n-dimensional search space. One harmony in the virtual machine placement problem and in the harmony search mechanism can only appear in the form of a discrete numerical sequence number between 1 and m, m representing the maximum number of physical hosts.
In this embodiment, for example, harmony h is X h ＝[2，1，5，4，2，3，2，1]A total of 8 instruments are shown to play 8 tones, which represent the meaning of a virtual machine placement scheme: virtual machine v 1 、v 5 And v 7 Put to physical host h 2 On virtual machine v 2 、v 8 Put to physical host h 1 On virtual machine v 3 Put to physical host h 5 On virtual machine v 4 Put to physical host h 4 On virtual machine v 6 Put to physical host h 3 。
All possible harmony sounds may form a matrix, defined as harmony memory store HM:
and step S20, generating a new harmony according to the preset harmony generation condition.
The step S20 specifically includes: randomly setting tone information with the number of the virtual machines according to the physical host machine number so as to obtain harmony to be processed; and selecting the harmony memory bank and performing pitch fine tuning disturbance processing on the harmony to be processed so as to acquire a processed new harmony.
The process of selecting the harmony memory bank specifically includes: and generating a first random number pair corresponding to each tone information in the harmony to be processed, randomly selecting the tone information from the harmony memory bank according to the first random number pair and the preset harmony memory bank selection probability, and replacing the tone information corresponding to the harmony to be processed with the tone information.
For each harmony X h Tone x in (a) h，k K=1, 2,..n, a pair of random numbers is randomly generated, i.e., a first random number pair including a random number r 1 And a random number r 2 Both random numbers in the random number pair are between (0, 1).
If r 1 Less than the harmony memory bank selection probability HMCR, randomly selecting a harmony HM [ a ] from the harmony memory bank HM ][b]Substitution x h，k A=1, 2, HMS, b=1, 2, n, i.e. tone x h，k The updating is as follows:
x h,k ＝HM[a][b]
otherwise, if r 1 >HMCR, then x h，k The updated value of the value is in interval [1, m ]]Generating an integer number randomly, namely:
wherein r is 2 The random numbers in the interval (0, 1) are represented.
Note that, the pitch fine tuning disturbance processing specifically includes: and generating a second random number pair corresponding to each tone information in the harmony to be processed, and carrying out tone fine tuning disturbance processing on the replaced tone information according to the second random number pair, the tone adjustment probability and the disturbance bandwidth so as to acquire a processed new harmony.
It will be readily appreciated that for each harmony X h Tone x in (a) h，k K=1, 2,..n, a pair of random numbers is again randomly generated, i.e., a second random number pair, the first random number pair comprising a random number r 3 And a random number r 4 Both random numbers in the random number pair are between (0, 1).
At the satisfaction of r 1 <While HMCR, if r 3 Smaller than the pitch adjustment probability PAR, the updated value HM [ a ] of the previous step is further updated][b]And performing fine tuning disturbance. The fine tuning disturbance formula is:
wherein r is 4 Representing random numbers within the interval (0, 1), BW represents the bandwidth of the perturbation.
Since the placement scheme is limited to [1, m ] ]Integer values within an interval, i.e. x h，k Must be in the value of [1, m ]]Within the interval, the updating mode according to the fine tuning disturbance formula may have a value out of the range. Thus, the optimized pitch trim perturbation formula is:
where mod represents the modulo operation,
representing a round down, m represents the total physical host, i.e., the maximum physical host number.
The step of generating the first random number pair corresponding to each tone information in the sound to be processed, randomly selecting tone information from the sound memory bank according to the first random number pair and a preset sound memory bank selection probability, and replacing the tone information corresponding to the sound to be processed with the tone information, and the step of further comprises: acquiring the current iteration times of the harmony memory bank; and updating the tone adjustment probability and the disturbance bandwidth according to the current iteration times.
In the traditional harmony search mechanism, the tone adjustment probability PAR and the disturbance bandwidth BW are fixed values, and the two parameters determine global exploration and local development balance in the harmony search process, and the fixed values do not consider the iterative evolution process of harmony search. The smaller PAR in the initial iteration stage can enable the harmony search to have stronger overall exploration capacity, and premature and too fast convergence of the algorithm are avoided; and the PAR with larger iterative later period can enable the harmony search to have stronger local development capability, promote the searching capability in a local space and accelerate the algorithm convergence. At the same time, the same considerations apply to BW, and as the iteration proceeds, corresponding changes should be made.
In this embodiment, the formula corresponding to the tone adjustment probability PAR is:
wherein PAR (t) represents the tone adjustment probability at iteration t, PAR min Representing tone adjustment probability minimum, PAR max Represents the maximum value of tone adjustment probability, T max Represents the maximum number of iterations of the harmony search, i.e., the maximum number of harmony plays.
In this embodiment, the formula corresponding to the disturbance bandwidth BW is:
where BW (t) represents the bandwidth of the disturbance at iteration t, BW min Representing the bandwidth minimum of the disturbance BW max Represents the maximum value of disturbance bandwidth, T max Represents the maximum number of iterations of the harmony search, i.e., the maximum number of harmony plays.
And step S30, performing fitness calculation on various harmony sounds in the harmony memory library and the new harmony sounds, and updating harmony sounds in the harmony memory library according to a calculation result.
The method is characterized in that the adaptability calculation is carried out on various harmony sounds and the new harmony sounds in the harmony sound memory library; acquiring a to-be-selected harmony with the minimum current fitness value in the harmony memory library, and judging whether the fitness value of the new harmony is larger than the fitness value of the to-be-selected harmony; and when the fitness value of the new harmony is larger than that of the harmony to be selected, replacing the harmony to be selected with the new harmony so as to update the harmony in the harmony memory bank. That is, if the new harmony measures are larger than the worst harmony measures in the current harmony store HM, replacing the worst harmony measures with the newly generated harmony measures; otherwise, the original sound memory bank HM is maintained unchanged.
According to the placement targets of the virtual machines, the smaller the target function value is, the larger the individual fitness is. The fitness function of the virtual machine placement scheme represented by the evaluation harmony can be set as follows:
where P represents the objective function in the energy consumption minimization formula, i.e., minimizing the physical host power consumption.
If the obtained placement scheme cannot meet the constraint provided by the physical host resource, the adaptability of the placement scheme can be set to 0. Thus, when evaluating the quality of the placement plan represented by harmony, the fitness function optimized is:
and step S40, determining a target harmony with the maximum fitness value according to the updating result, and taking the tone information of the target harmony as the optimal solution for virtual machine placement.
It is readily appreciated that the goal of virtual machine placement is to reduce the power consumption of the machine, and therefore the larger the fitness value, the better the placement solution that harmony represents.
And S50, placing the virtual machines in the virtual machine set into the physical hosts corresponding to the physical host set according to the optimal placement solution of the virtual machines.
It is easy to understand that after the optimal solution for placing the virtual machine is obtained, the virtual machine can be placed according to the optimal solution, so as to realize reasonable application of physical host resources and energy consumption.
According to the embodiment of the invention, through the method, under the condition that the resource utilization rate and the energy consumption of the physical host are both constrained, the low-energy-consumption optimization of virtual machine placement is formed by generating a new harmony, namely a new placement scheme, and the efficiency and the effect of virtual machine placement are improved.
Referring to fig. 3, fig. 3 is a flowchart illustrating a third embodiment of a virtual machine placement method based on harmony search according to the present invention. Based on the first embodiment, the virtual machine placement method based on harmony search according to the present embodiment further includes, after the step S40:
step S401, detecting the current iteration times of the current harmony memory bank, and judging whether the current iteration times are smaller than preset iteration times or not.
And step S402, returning to the step of generating a new harmony according to the preset harmony generating condition when the current iteration times are smaller than the preset iteration times.
It is easy to understand that the preset iteration number is the maximum iteration number of the harmony memory bank HM, and the preset iteration number is set according to the requirement of the virtual machine placement problem when the harmony memory bank HM is generated. And when the iteration times are insufficient, repeatedly generating a new harmony, namely a new virtual machine placement scheme, performing fitness calculation, performing corresponding judgment according to a calculation result, and updating the harmony memory bank HM until the maximum iteration times Tmax are reached. And finally, outputting the harmony with the maximum adaptability in the harmony memory library as a final optimal solution for virtual machine placement.
Step S403, outputting the optimal solution for virtual machine placement when the current iteration number is equal to the preset iteration number.
According to the embodiment of the invention, by the method, new harmony is iteratively generated, so that the harmony library is continuously updated, and a new placement scheme is continuously formed, so that an optimized placement scheme is obtained, and the placement precision and effect of the virtual machine are improved.
Referring to fig. 4, fig. 4 is a block diagram illustrating a first embodiment of a virtual machine placement apparatus based on harmony search according to the present invention. It should be noted that, the present embodiment is based on the cloud computing environment in the foregoing method embodiment, and will not be described herein in detail. The device comprises: the system comprises a sound library establishment module 10, an adaptability calculation module 20, an optimal solution acquisition module 30 and a placement module 40, wherein;
the harmony library establishment module 10 is configured to obtain a virtual machine set and a physical host set to be placed, and establish a harmony memory library according to the virtual machine set and the physical host set.
The harmony library establishment module 10 is specifically configured to: acquiring the number of physical hosts corresponding to the physical host set and the number of virtual machines corresponding to the virtual machine set; taking the virtual machine number as the tone information number corresponding to various sounds, and randomly setting the tone information corresponding to various sounds according to the physical host number; and establishing a harmony memory library according to the preset sum sound seed number, the tone information number and the tone information.
Let a harmony h be expressed as:
X h ＝[x h,1 ,x h,2 ,...,x h,n ]
wherein element x in the vector h，k Representing the tone played by the kth instrument in harmony h, the tone corresponding to the physical host number of the placed virtual machine k, the physical host number having a value of [1, m]The in-section integer value, h=1, 2, …, the HMS represents the size of the acoustic memory, the HMS is a preset acoustic number, and can be set according to the actual requirements of the problem, and k=1, 2, …, n, n represents the number of instruments, and corresponds to the total number of virtual machines to be placed, namely the corresponding tone information number. In other words, a harmony representation of a virtual machine placement scheme may be defined within an n-dimensional search space. One harmony in the virtual machine placement problem and in the harmony search mechanism can only appear in the form of a discrete numerical sequence number between 1 and m, m representing the maximum number of physical hosts.
In this embodiment, for example, harmony h is X h ＝[2，1，5，4，2，3，2，1]A total of 8 instruments are shown to play 8 tones, which represent the meaning of a virtual machine placement scheme: virtual machine v 1 、v 5 And v 7 Put to physical host h 2 On virtual machine v 2 、v 8 Put to physical host h 1 On virtual machine v 3 Put to physical host h 5 On virtual machine v 4 Put to physical host h 4 On virtual machine v 6 Put to physical host h 3 。
All possible harmony sounds may form a matrix, defined as harmony memory store HM:
and the fitness calculating module 20 is used for generating a new harmony according to the preset harmony generating conditions. The method is specifically used for randomly setting tone information with the number of the virtual machines according to the physical host machine number so as to obtain harmony to be processed; and selecting the harmony memory bank and performing pitch fine tuning disturbance processing on the harmony to be processed so as to acquire a processed new harmony.
The process of selecting the harmony memory bank specifically includes: and generating a first random number pair corresponding to each tone information in the harmony to be processed, randomly selecting the tone information from the harmony memory bank according to the first random number pair and the preset harmony memory bank selection probability, and replacing the tone information corresponding to the harmony to be processed with the tone information.
For each harmony X h Tone x in (a) h，k K=1, 2,..n, a pair of random numbers is randomly generated, i.e., a first random number pair including a random number r 1 And a random number r 2 Both random numbers in the random number pair are between (0, 1).
If r 1 Less than the harmony memory bank selection probability HMCR, randomly selecting a harmony HM [ a ] from the harmony memory bank HM ][b]Substitution x h，k A=1, 2, HMS, b=1, 2, n, i.e. tone x h，k The updating is as follows:
x h,k ＝HM[a][b]
otherwise, if r 1 >HMCR, then x h，k The updated value of the value is in interval [1, m ]]Generating an integer number randomly, namely:
wherein r is 2 The random numbers in the interval (0, 1) are represented.
Note that, the pitch fine tuning disturbance processing specifically includes: and generating a second random number pair corresponding to each tone information in the harmony to be processed, and carrying out tone fine tuning disturbance processing on the replaced tone information according to the second random number pair, the tone adjustment probability and the disturbance bandwidth so as to acquire a processed new harmony.
It will be readily appreciated that for each harmony X h Tone x in (a) h，k K=1, 2,..n, a pair of random numbers is again randomly generated, i.e., a second random number pair, the first random number pair comprising a random number r 3 And a random number r 4 Both random numbers in the random number pair are between (0, 1).
At the satisfaction of r 1 <While HMCR, if r 3 Smaller than the pitch adjustment probability PAR, the updated value HM [ a ] of the previous step is further updated][b]And performing fine tuning disturbance. The fine tuning disturbance formula is:
wherein r is 4 Representing random numbers within the interval (0, 1), BW represents the bandwidth of the perturbation.
Since the placement scheme is limited to [1, m ] ]Integer values within an interval, i.e. x h，k Must be in the value of [1, m ]]Within the interval, the updating mode according to the fine tuning disturbance formula may have a value out of the range. Thus, the optimized pitch trim perturbation formula is:
where mod represents the modulo operation,
representing a round down, m represents the total physical host, i.e., the maximum physical host number.
The step of generating the first random number pair corresponding to each tone information in the sound to be processed, randomly selecting tone information from the sound memory bank according to the first random number pair and a preset sound memory bank selection probability, and replacing the tone information corresponding to the sound to be processed with the tone information, and the step of further comprises: acquiring the current iteration times of the harmony memory bank; and updating the tone adjustment probability and the disturbance bandwidth according to the current iteration times.
In the traditional harmony search mechanism, the tone adjustment probability PAR and the disturbance bandwidth BW are fixed values, and the two parameters determine global exploration and local development balance in the harmony search process, and the fixed values do not consider the iterative evolution process of harmony search. The smaller PAR in the initial iteration stage can enable the harmony search to have stronger overall exploration capacity, and premature and too fast convergence of the algorithm are avoided; and the PAR with larger iterative later period can enable the harmony search to have stronger local development capability, promote the searching capability in a local space and accelerate the algorithm convergence. At the same time, the same considerations apply to BW, and as the iteration proceeds, corresponding changes should be made.
In this embodiment, the formula corresponding to the tone adjustment probability PAR is:
wherein PAR (t) represents the tone adjustment probability at iteration t, PAR min Representing tone adjustment probability minimum, PAR max Represents the maximum value of tone adjustment probability, T max Represents the maximum number of iterations of the harmony search, i.e., the maximum number of harmony plays.
In this embodiment, the formula corresponding to the disturbance bandwidth BW is:
where BW (t) represents the bandwidth of the disturbance at iteration t, BW min Representing the bandwidth minimum of the disturbance BW max Represents the maximum value of disturbance bandwidth, T max Representing the maximum number of iterations of the harmony search, i.e. harmony performanceIs the maximum number of times (1).
The fitness calculating module 20 is further configured to calculate fitness of various harmony sounds in the harmony memory library and the new harmony sounds, and update harmony sounds in the harmony memory library according to a calculation result.
The method is characterized in that the adaptability calculation is carried out on various harmony sounds and the new harmony sounds in the harmony sound memory library; acquiring a to-be-selected harmony with the minimum current fitness value in the harmony memory library, and judging whether the fitness value of the new harmony is larger than the fitness value of the to-be-selected harmony; and when the fitness value of the new harmony is larger than that of the harmony to be selected, replacing the harmony to be selected with the new harmony so as to update the harmony in the harmony memory bank. That is, if the new harmony measures are larger than the worst harmony measures in the current harmony store HM, replacing the worst harmony measures with the newly generated harmony measures; otherwise, the original sound memory bank HM is maintained unchanged.
According to the placement targets of the virtual machines, the smaller the target function value is, the larger the individual fitness is. The fitness function of the virtual machine placement scheme represented by the evaluation harmony can be set as follows:
where P represents the objective function in the energy consumption minimization formula, i.e., minimizing the physical host power consumption.
If the obtained placement scheme cannot meet the constraint provided by the physical host resource, the adaptability of the placement scheme can be set to 0. Thus, when evaluating the quality of the placement plan represented by harmony, the fitness function optimized is:
the optimal solution obtaining module 30 is configured to determine a target harmony with the largest fitness value according to the update result, and place the optimal solution by using the pitch information of the target harmony as the virtual machine.
It is readily appreciated that the goal of virtual machine placement is to reduce the power consumption of the machine, and therefore the larger the fitness value, the better the placement solution that harmony represents.
The placement module 40 is configured to place the virtual machines in the virtual machine set into physical hosts corresponding to the physical host set according to the optimal placement solution of the virtual machines.
It is easy to understand that after the optimal solution for placing the virtual machine is obtained, the virtual machine can be placed according to the optimal solution, so as to realize reasonable application of physical host resources and energy consumption.
According to the embodiment of the invention, through the device, under the condition that the resource utilization rate and the energy consumption of the physical host are both constrained, the low-energy-consumption optimization of virtual machine placement is formed by generating a new harmony, namely a new placement scheme, and the efficiency and the effect of virtual machine placement are improved.
In addition, the embodiment of the invention also provides a virtual machine placement device based on harmony search, which is an electronic device, and comprises: the system comprises a memory, a processor, and a harmony search-based virtual machine placement program stored on the memory and executable on the processor, the harmony search-based virtual machine placement program configured to implement the steps of the harmony search-based virtual machine placement method as described above.
The device adopts all the technical schemes of all the embodiments, so that the device has at least all the beneficial effects brought by the technical schemes of the embodiments, and the description is omitted here.
In addition, the embodiment of the invention also provides a storage medium, wherein the storage medium stores a harmony search-based virtual machine placement program, and the harmony search-based virtual machine placement program is used for executing the steps of the harmony search-based virtual machine placement method by a processor.
Because the storage medium adopts all the technical schemes of all the embodiments, the storage medium has at least all the beneficial effects brought by the technical schemes of the embodiments, and the description is omitted here.
It should be understood that the foregoing is illustrative only and is not limiting, and that in specific applications, those skilled in the art may set the invention as desired, and the invention is not limited thereto.
It should be noted that the above-described working procedure is merely illustrative, and does not limit the scope of the present invention, and in practical application, a person skilled in the art may select part or all of them according to actual needs to achieve the purpose of the embodiment, which is not limited herein.
In addition, technical details not described in detail in the present embodiment may refer to the harmony search-based virtual machine placement method provided in any embodiment of the present invention, which is not described herein.
Furthermore, it should be noted that, in this embodiment, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or system that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or system. Without further limitation, an element defined by the phrase "comprising one … …" does not exclude the presence of other like elements in a process, method, article, or system that comprises the element.
The foregoing embodiment numbers of the present invention are merely for the purpose of description, and do not represent the advantages or disadvantages of the embodiments.
From the above description of the embodiments, it will be clear to those skilled in the art that the above-described embodiment method may be implemented by means of software plus a necessary general hardware platform, but of course may also be implemented by means of hardware, but in many cases the former is a preferred embodiment. Based on such understanding, the technical solution of the present invention may be embodied essentially or in a part contributing to the prior art in the form of a software product stored in a storage medium (e.g. Read Only Memory)/RAM, magnetic disk, optical disk) and including several instructions for causing a terminal device (which may be a mobile phone, a computer, a server, or a network device, etc.) to perform the method according to the embodiments of the present invention.
The foregoing description is only of the preferred embodiments of the present invention, and is not intended to limit the scope of the invention, but rather is intended to cover any equivalents of the structures or equivalent processes disclosed herein or in the alternative, which may be employed directly or indirectly in other related arts.
Claims (5)
1. A harmony search-based virtual machine placement method, the method comprising:
acquiring a virtual machine set and a physical host set to be placed, and establishing a sound memory library according to the virtual machine set and the physical host set;
generating a new harmony according to the preset harmony generation condition;
performing fitness calculation on various harmony sounds in the harmony memory library and the new harmony sounds, and updating harmony sounds in the harmony memory library according to a calculation result;
determining a target harmony with the maximum fitness value according to the updating result, and taking the tone information of the target harmony as a virtual machine placement optimal solution;
placing the virtual machines in the virtual machine set into the physical hosts corresponding to the physical host set according to the optimal placement solution of the virtual machines;
the step of obtaining a virtual machine set and a physical host set to be placed, and establishing a sound memory bank according to the virtual machine set and the physical host set specifically comprises the following steps:
acquiring the number of physical hosts corresponding to the physical host set and the number of virtual machines corresponding to the virtual machine set;
taking the virtual machine number as the tone information number corresponding to various sounds, and randomly setting the tone information corresponding to various sounds according to the physical host number;
Establishing a harmony memory library according to the preset sum sound seed number, the tone information number and the tone information;
the step of generating a new harmony according to the preset harmony generation condition specifically comprises the following steps:
randomly setting tone information with the number of the virtual machines according to the physical host machine number so as to obtain harmony to be processed;
generating a first random number pair corresponding to each tone information in the harmony to be processed, randomly selecting tone information from a harmony memory bank according to the first random number pair and a preset harmony memory bank selection probability, and replacing the tone information corresponding to the harmony to be processed with the tone information;
generating a second random number pair corresponding to each tone information in the harmony to be processed, and carrying out tone fine tuning disturbance processing on the replaced tone information according to the second random number pair, the tone adjustment probability and the disturbance bandwidth so as to acquire a processed new harmony;
the step of adaptively calculating various harmony sounds in the harmony memory bank and the new harmony sounds and updating the harmony sounds in the harmony memory bank according to the calculation result specifically comprises the following steps:
performing fitness calculation on various harmony sounds and the new harmony sounds in the harmony sound memory library;
Acquiring a to-be-selected harmony with the minimum current fitness value in the harmony memory library, and judging whether the fitness value of the new harmony is larger than the fitness value of the to-be-selected harmony;
when the fitness value of the new harmony is larger than that of the harmony to be selected, replacing the harmony to be selected with the new harmony so as to update the harmony in the harmony memory bank;
after the step of determining the target harmony with the maximum fitness value according to the updating result and taking the tone information of the target harmony as the optimal solution for placing the virtual machine, the method further comprises the following steps:
detecting the current iteration number of a current harmony memory bank, and judging whether the current iteration number is smaller than a preset iteration number or not;
returning to the step of generating a new harmony according to a preset harmony generating condition when the current iteration number is smaller than the preset iteration number;
and outputting the optimal solution placed by the virtual machine when the current iteration number is equal to the preset iteration number.
2. The harmony search-based virtual machine placement method of claim 1, wherein the step of generating a first random number pair corresponding to each tone information in the harmony to be processed, randomly selecting tone information from the harmony memory according to the first random number pair and a preset harmony memory selection probability, and replacing the tone information corresponding to the harmony to be processed with the tone information, further comprises:
Acquiring the current iteration times of the harmony memory bank;
and updating the tone adjustment probability and the disturbance bandwidth according to the current iteration times.
3. A harmony search-based virtual machine placement apparatus, the apparatus comprising: the system comprises a sound library establishing module, an adaptability calculating module, an optimal solution obtaining module and a placing module, wherein the sound library establishing module is used for establishing a sound library;
the harmony library establishing module is used for acquiring a virtual machine set and a physical host set to be placed, and establishing a harmony memory library according to the virtual machine set and the physical host set;
the fitness computing module is used for generating a new harmony according to preset harmony generation conditions; the method is also used for carrying out adaptability calculation on various harmony sounds in the harmony memory library and the new harmony sounds, and updating harmony sounds in the harmony memory library according to a calculation result;
the optimal solution acquisition module is used for determining a target harmony with the maximum fitness value according to the updating result, and taking the tone information of the harmony as a virtual machine to place an optimal solution;
the placement module is used for placing the virtual machines in the virtual machine set into the physical hosts corresponding to the physical host set according to the optimal placement solution of the virtual machines;
The harmony library establishment module is further used for acquiring the physical host number corresponding to the physical host set and the virtual machine number corresponding to the virtual machine set; taking the virtual machine number as the tone information number corresponding to various sounds, and randomly setting the tone information corresponding to various sounds according to the physical host number; establishing a harmony memory library according to the preset sum sound seed number, the tone information number and the tone information;
the fitness computing module is further used for randomly setting tone information with the number of the virtual machines according to the physical host numbers so as to obtain harmony to be processed; generating a first random number pair corresponding to each tone information in the harmony to be processed, randomly selecting tone information from a harmony memory bank according to the first random number pair and a preset harmony memory bank selection probability, and replacing the tone information corresponding to the harmony to be processed with the tone information; generating a second random number pair corresponding to each tone information in the harmony to be processed, and carrying out tone fine tuning disturbance processing on the replaced tone information according to the second random number pair, the tone adjustment probability and the disturbance bandwidth so as to acquire a processed new harmony; performing fitness calculation on various harmony sounds and the new harmony sounds in the harmony sound memory library; acquiring a to-be-selected harmony with the minimum current fitness value in the harmony memory library, and judging whether the fitness value of the new harmony is larger than the fitness value of the to-be-selected harmony; when the fitness value of the new harmony is larger than that of the harmony to be selected, replacing the harmony to be selected with the new harmony so as to update the harmony in the harmony memory bank;
The optimal solution acquisition module is further used for detecting the current iteration times of the current harmony memory bank and judging whether the current iteration times are smaller than preset iteration times or not; returning to the step of generating a new harmony according to a preset harmony generating condition when the current iteration number is smaller than the preset iteration number; and outputting the optimal solution placed by the virtual machine when the current iteration number is equal to the preset iteration number.
4. A harmony search-based virtual machine placement apparatus, the apparatus comprising: memory, a processor, and a harmony search based virtual machine placement program stored on the memory and executable on the processor, the harmony search based virtual machine placement program configured to implement the steps of the harmony search based virtual machine placement method as defined in any one of claims 1 to 2.
5. A storage medium, wherein a harmony search based virtual machine placement program is stored on the storage medium, which when executed by a processor implements the steps of the harmony search based virtual machine placement method as defined in any one of claims 1 to 2.
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