This application is based upon and claims the benefit of priority of the prior Japanese Patent Application No. 2020-045049 filed on Mar. 16, 2020, the entire contents of which are incorporated herein by reference.
A certain aspect of the embodiments is related to a non-transitory computer-readable recording medium and a charge calculation method.
With the development of virtualization technology, a cloud that provides various services to a user by using virtual machines running in a data center is widespread. In the cloud, since data and programs required for the service are managed by the virtual machine, it is not necessary for the user to manage the data and the programs, and it is possible to improve the efficiency of user's business and reduce a cost.
In recent years, a new service that combines clouds from different cloud providers is also proposed. In this service, each of a plurality of virtual machines is realized by the clouds of a plurality of different cloud providers. Thereby, even if a failure occurs in any of the cloud providers, the virtual machines can continue to operate in the cloud of the remaining cloud providers, so that the virtual machines can be made redundant.
In such a service, some cloud providers may reduce the charge of their own virtual machine. In that case, a usage charge of the service becomes cheaper than a current charge by using the virtual machine after the charge reduction. Therefore, it is preferable to encourage the users of the service to migrate their virtual machine to the virtual machines of the cloud provider that reduce the charge. Note that the technique related to the present disclosure is disclosed in Japanese Patent Application Publication No. 2017-142673.
According to an aspect of the present disclosure, there is provided a charge calculation method executed by a processor included in a computer to execute a process, the process including: determining a degree of possibility that a virtual machine having redundant configuration exists in a plurality of virtual machines that provide a service; calculating a difference of charges for using the service before and after a first virtual machine among the plurality of virtual machines is migrated to an another location different from a location where the first virtual machine is located; and displaying the degree of possibility and the difference with respect to the service.
The object and advantages of the invention will be realized and attained by means of the elements and combinations particularly pointed out in the claims.
It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory and are not restrictive of the invention, as claimed.
For example, if respective redundant virtual machines are migrated to the same cloud provider, the respective virtual machines cannot be used in the case where the failure occurs in the cloud provider. Therefore, it makes no sense to make the virtual machines redundant. Moreover, when the user of the service voluntarily makes the virtual machines redundant, it is difficult for an administrator of the service to determine that each of the virtual machines has redundant configuration. When providing candidates for the virtual machines to be migrated to the user of the service, if the above-mentioned virtual machines that are unlikely to be migrated by the user of the service are also included in the candidates, this might prevent the user of the service from selecting the virtual machine to be migrated.
Prior to the description of the present embodiment, matters studied by an inventor will be described.
As described above, in the service that combines the plurality of cloud services, it is preferable to encourage the user to migrate a virtual machine in use to the virtual machine of the cloud provider whose usage charge is reduced, and to propose reduction in a usage charge of the service to the user.
As illustrated in
Hereinafter, the combination of each of cloud providers X, Y, Z and the region is referred to as a cloud location. The cloud locations can be expressed as (X, Japan), (Y, UK), (Z, USA) or the like, for example. Furthermore, even if the cloud provider is the same, as indicated by (X, Japan) and (X, UK), the cloud locations may be different from each other.
These services A, B, C and D are managed by a same administrator M. The administrator M appropriately selects a plurality of virtual machines VM from at least two of the cloud locations P, Q, and R, connects the plurality of virtual machines by a network suitable for the service, and provides it to the user of the service.
When providing a service A to a user, for example, the administrator M selects three virtual machines VM in the cloud location P, and selects one virtual machine VM from each of the cloud locations Q and R. Then, the administrator M connects these virtual machines VM by an appropriate network.
For example, it is assumed a case where the cloud provider of the cloud location R reduces the usage charge of a virtual machine VM0. In this case, it is preferable to migrate a virtual machine having the same specifications as the virtual machine VM0 among the three virtual machines VM of the cloud location P in the service A to the virtual machine VM0 from a viewpoint of charge reduction. Here, the specifications of the virtual machine VM that serves as the reference for migration include the number of virtual CPUs, a capacity of a virtual memory and so on, in the virtual machine VM. This allows the administrator M to reduce the usage charge to the user of service A, and the cost of the service A can be reduced. The same applies to the services B, C, and D.
How much cost reduction is possible depends on a ratio of virtual machines VM having the same specifications as the virtual machine VM0 of the cloud location R whose usage charge is reduced, to the virtual machines VM included in each of the current services A, B, C, and D.
Therefore, significant charge reduction can be realized by migrating a virtual machine having the same specifications as the virtual machine VM0 in the cloud location R among the virtual machines VM of service A, to the cloud location R.
However, when the service A includes a redundant virtual machine VM, it may be difficult to migrate the virtual machine VM as follows.
When the charge of the virtual machine VM in the cloud location R is reduced, the usage charge of the service A can be reduced by migrating the virtual machine VM in this way. Therefore, it is also considered that the administrator M of the service A calculates the charge of the service A after the charge reduction and presents it to the user of the service A.
However, in this case, both of the two virtual machines VM having the redundant configuration are deployed in the same cloud location R. Therefore, when the failure occurs in the cloud location R, the user cannot use the service A and the availability of service A is reduced.
Whether the two virtual machines VM have the redundant configuration is determined by application programs that the user of the service A runs on respective virtual machines VM. When the respective virtual machines VM run the same application programs, for example, the functions of the respective virtual machines VM are the same, and these virtual machines VMs have the redundant configuration.
However, although the administrator M of the service A knows the network configuration that connects the virtual machines VM to each other, the application programs that run on the respective virtual machines VM are not included in a category managed by the administrator M. The user of the service A can voluntarily make the virtual machines VM redundant by running the same application programs on the respective virtual machines VM. Therefore, the administrator M of the service A cannot directly determine whether each virtual machine VM has the redundant configuration.
Therefore, even if the user of the service A is encouraged to migrate the virtual machine VM to the cloud location R, it is unlikely that the user of the service A accepts it, and the calculation of a new usage charge becomes useless.
Hereinafter, each embodiment capable of eliminating such uselessness is described.
The information processing device 12 is a computer such as a server or a PC (Personal Computer), and accesses charge information 15 of the cloud providers X, Y, and Z via the network 11. The charge information 15 is a web page in which charge tables of the virtual machine VM in the respective cloud locations P, Q, and R are described. The information processing device 12 can detect whether the usage charge of the virtual machine VM in each of the cloud locations P, Q, and R is reduced, by referring to the charge information 15.
The administrator N of the system 10 described above manages the cloud locations where the respective virtual machines VM in the services A, B, C, and D are deployed and the network for connecting the respective virtual machines VM.
However, the administrator N does not manage whether each virtual machine VM has the redundant configuration. Furthermore, each user of the services A, B, C, and D can freely run the application programs on the virtual machines VM, and the administrator N does not have an authority to manage the application programs. Therefore, even if the user runs the same application programs on the two virtual machines VM and makes these virtual machines VM redundant, the administrator N cannot directly know the redundant configuration.
Therefore, in the present embodiment, the information processing device 12 determines a possibility that the virtual machine VM has the redundant configuration as follows. The determination method of the redundant configuration includes the following first to fifth examples.
In this example, when there are two virtual machines VM1 and VM2 under the control of a single virtual machine VM3, the information processing device 12 monitors traffic volumes tr1 and tr2 input to these virtual machines VM1 and VM2, respectively. Note that the traffic volumes tr1 is an example of a first traffic volume, and the traffic volumes tr2 is an example of a second traffic volume.
If the virtual machines VM1 and VM2 have the redundant configuration, the virtual machine VM3 has a high possibility to function as a load balancer that distributes traffic to the virtual machines VM1 and VM2. Therefore, there should be no large difference between the traffic volumes tr1 and tr2.
Therefore, in this example, the information processing device 12 monitors the traffic volumes tr1 and tr2 to determine a degree of possibility that the virtual machines VM1 and VM2 have the redundant configuration.
In this example, total volumes (bits) of traffic in one minute are set as the traffic volumes tr1 and tr2, and the information processing device 12 calculates a difference Δtra between them. Then, the information processing device 12 determines the degree of possibility of the redundant configuration based on a ratio Pt(=Δtra/tr1) occupied by the difference Δtra to the traffic amount tr1.
In the determination rule R1, the information processing device 12 determines the degree of possibility depending on which of the conditions “R1-1”, “R1-2”, and “R1-3” is satisfied, as illustrated in
Here, the information processing device 12 measures the traffic volumes tr1 and tr2 5 times. When the ratio Pt is less than 10% in 4 out of 5 times, the condition “R1-1” is satisfied, and the information processing device 12 determines that there is a high possibility of the redundant configuration.
When the ratio Pt is less than 30% in 4 out of 5 times, or the ratio Pt is less than 10% in 2 out of 5 times, the condition “R1-2” is satisfied, and the information processing device 12 determines that there is a medium possibility of the redundant configuration.
In any other cases, the condition “R1-3” is satisfied, and the information processing device 12 determines that there is a low possibility of the redundant configuration.
If the virtual machines VM1 and VM2 have the redundant configuration, the virtual machine VM3 has the high possibility to function as the load balancer that distributes traffic to the virtual machines VM1 and VM2. In this case, virtual machine VM3 distributes input data to its own virtual machine to each virtual machine VM1 and VM2 at random in time. Therefore, a total value mot of the output traffic volumes tr1 and tr2 is equal to the input traffic volume tr3.
Therefore, in this example, the information processing device 12 monitors the traffic volumes tr1, tr2, and tr3 to determine the degree of possibility that the virtual machines VM1 and VM2 have the redundant configuration.
In this example, the total volumes (bits) of traffic in one minute are set as the traffic volumes tr1, tr2 and tr3. The information processing device 12 calculates a difference Δtrb between the total value trtot of the output traffic volumes tr1 and tr2 and the input traffic volume tr3. Further, the information processing device 12 determines the degree of possibility of the redundant configuration based on a ratio Pb(=Δtrb/tr3) occupied by the difference Δtrb to the input traffic volume tr3.
In the determination rule R2, the information processing device 12 determines the degree of possibility depending on which of the conditions “R2-1”, “R2-2”, and “R2-3” is satisfied, as illustrated in
Here, the information processing device 12 measures the traffic volumes tr1, tr2 and tr3 5 times. When the ratio Pb is less than 10% in 4 out of 5 times, the condition “R2-1” is satisfied, and the information processing device 12 determines that there is the high possibility of the redundant configuration.
When the ratio Pb is less than 30% in 4 out of 5 times, or the ratio Pb is less than 10% in 2 out of 5 times, the condition “R2-2” is satisfied, and the information processing device 12 determines that there is the medium possibility of the redundant configuration.
In any other cases, the condition “R2-1” is satisfied, and the information processing device 12 determines that there is the low possibility of the redundant configuration.
In order to confirm this, the information processing device 12 monitors a traffic volume tr4 flowing between the virtual machine VM1 and the virtual machine VM4 and a traffic volume tr5 flowing between the virtual machine VM2 and the virtual machine VM5. If the virtual machines VM4 and VM5 have the redundant configuration, there should be no large difference between the traffic volumes tr4 and tr5.
Therefore, in this example, the information processing device 12 monitors the traffic volumes tr4 and tr5 to determine the degree of possibility that the virtual machines VM4 and VM5 have the redundant configuration.
In this example, the total volumes (bits) of traffic in one minute are set as the traffic volumes tr4 and tr5, and the information processing device 12 calculates a difference Δtrc between them. Then, the information processing device 12 determines the degree of possibility of the redundant configuration based on a ratio Pc(=Δtrc/tr4) occupied by the difference Δtrc to the traffic volume tr4.
In the determination rule R3, the information processing device 12 determines the degree of possibility depending on which of the conditions “R3-1”, “R3-2”, and “R3-3” is satisfied, as illustrated in
Here, the information processing device 12 measures the traffic volumes tr4 and tr5 5 times. When the ratio Pc is less than 10% in 4 out of 5 times, the condition “R3-1” is satisfied, and the information processing device 12 determines that there is the high possibility of the redundant configuration.
When the ratio Pc is less than 30% in 4 out of 5 times, or the ratio Pc is less than 10% in 2 out of 5 times, the condition “R3-2” is satisfied, and the information processing device 12 determines that there is the medium possibility of the redundant configuration.
In any other cases, the condition “R3-3” is satisfied, and the information processing device 12 determines that there is the low possibility of the redundant configuration.
When the virtual machines VM1 and VM2 are the redundant databases, a content F of a disk D1 in the virtual machine VM1 is copied to a disk D2 in the virtual machine VM2 after a certain period of time ΔT elapsed. In this case, the virtual machine VM2 operates in the same manner as the virtual machine VM1 after the certain period of time ΔT. Therefore, a resource usage rate U2 of the virtual machine VM2 should be the same as a resource usage rate U1 of the virtual machine VM1 at the time going back by the certain period of time ΔT.
Therefore, in this example, the information processing device 12 monitors the resource usage rates U1 and U2 to determine the degree of possibility that the virtual machines VM1 and VM2 have the redundant configuration. Examples of such resource usage rates U1 and U2 include a CPU usage rate (%) or a memory usage rate (%) of each of the virtual machines VM1 and VM2.
When the virtual machines VM1 and VM2 have the redundant configuration, the graphs of the resource usage rates U1 and U2 have similar shapes as illustrated in
In this example, the information processing device 12 calculates a difference ΔU between a value of the resource usage rate U1 at a time t1 and a value of the resource usage rate U2 at a time t2. Then, the information processing device 12 determines the degree of possibility of the redundant configuration based on a ratio Pu(=ΔU/U1) occupied by the difference ΔU to the resource usage rate U1.
In the determination rule R4, the information processing device 12 determines the degree of possibility depending on which of the conditions “R4-1”, “R4-2”, and “R4-3” is satisfied, as illustrated in
In this example, the information processing device 12 measures the difference ΔU 5 times at different times. In this case, in the n-th measurement, the information processing device 12 measures the difference ΔU between the resource usage rate U1 at a time tn and the resource usage rate U2 at a time tn+1. A value of “tn−tn+1” is the same for all n, and “tn−tn+1” is expressed as ΔT (tn−tn+1−ΔT).
When the ratio Pu is less than 10% in 4 or more out of 5 times, the condition “R4-1” is satisfied, and the information processing device 12 determines that there is the high possibility that the virtual machines VM1 and VM2 have the redundant configuration.
When the ratio Pu is less than 30% in 4 or more out of 5 times, or the ratio Pu is less than 10% in 2 or more out of 5 times, the condition “R4-2” is satisfied, and the information processing device 12 determines that there is the medium possibility of the redundant configuration.
In any other cases, the condition “R4-3” is satisfied, and the information processing device 12 determines that there is the low possibility of the redundant configuration.
In order to confirm this, the information processing device 12 monitors the traffic volume tr4 flowing between the virtual machine VM1 and the virtual machine VM4 and the traffic volume tr5 flowing between the virtual machine VM2 and the virtual machine VM5. If the virtual machines VM4 and VM5 have the redundant configuration, there should be no large difference between the traffic volumes tr4 and tr5.
Therefore, in this example, the information processing device 12 monitors the traffic volumes tr4 and tr5 to determine the degree of possibility that the virtual machines VM4 and VM5 have the redundant configuration.
In this example, the total volumes (bits) of traffic in one minute are set as the traffic volumes tr4 and t5, and the information processing device 12 calculates a difference Δtrd between them. Then, the information processing device 12 determines the degree of possibility of the redundant configuration based on a ratio Pd(=Δtrd/tr4) occupied by the difference Δtrd to the traffic volume tr4.
In the determination rule R5, the information processing device 12 determines the degree of possibility depending on which of the conditions “R5-1”, “R5-2”, and “R5-3” is satisfied, as illustrated in
Here, the information processing device 12 measures the traffic volumes tr4 and tr5 5 times. When the ratio Pd is less than 10% in 4 out of 5 times, the condition “R5-1” is satisfied, and the information processing device 12 determines that there is the high possibility of the redundant configuration.
When the ratio Pd is less than 30% in 4 out of 5 times, or the ratio Pd is less than 10% in 2 out of 5 times, the condition “R5-2” is satisfied, and the information processing device 12 determines that there is the medium possibility of the redundant configuration.
In any other cases, the condition “R5-3” is satisfied, and the information processing device 12 determines that there is the low possibility of the redundant configuration.
Next, a description is given of the functional configuration of the information processing device 12.
The communication unit 21 is a communication interface for connecting its own device to the network 11 (see
The storage unit 23 is a processing unit realized by, for example, an HDD (Hard Disk Drive), a memory or the like, and stores the above-mentioned determination rules R1 to R5.
The control unit 24 is a processing unit that controls its own device, and includes a detection unit 25, an extraction unit 26, a determination unit 27, a calculation unit 28, a display processing unit 29, a traffic monitoring unit 30 and a resource monitoring unit 31.
The detection unit 25 is a processing unit that detects that the usage charge of each of the virtual machines VM provided by the cloud providers is reduced by periodically referring to the charge information 15 (
Further, the detection unit 25 stores virtual machine information related to the virtual machine VM whose usage charge is reduced, in the storage unit 23.
In this case, the detection unit 25 stores the information related to the virtual machines VM of the cloud locations R and V for which the usage charge is reduced, in the virtual machine information. For example, an item “status” indicating that the usage charge is updated stores “update”. An item “cloud provider” stores the cloud provider “Z” that reduced the usage charge. An item “type” stores “nano” which is a type of the virtual machine VM provided by the cloud provider “Z”. An item “region” stores the regions “USA” and “UK” where the virtual machines VM whose usage charges are reduced are deployed. An item “number of CPU” stores the number of virtual CPUs in the virtual machine whose usage charge is reduced.
An item “usage charge” stores the usage charge of the virtual machine VM after the charge reduction. Furthermore, an item “OS” stores a name of an OS to be run by the virtual machine VM after the charge reduction.
Referring to
The determination unit 27 is a processing unit that determines the degree of possibility that the virtual machine VM having the redundant configuration exists in the plurality of virtual machines VM that provide the services. As an example, the determination unit 27 determines the degree of possibility that each of the plurality of virtual machine VMs extracted by the extraction unit 26 has the redundant configuration, according to any of the above-mentioned determination rules R1 to R5. At the time of the determination, the determination unit 27 uses a monitoring result of either the traffic monitoring unit 30 or the resource monitoring unit 31 described later.
For example, it is assumed that the virtual machines extracted by the extraction unit 26 are the virtual machines VM1 and VM2 in the service A. In this case, the determination unit 27 identifies the virtual machine VM3 connected to each of the virtual machines VM1 and VM2 as illustrated in
The calculation unit 28 is a processing unit that calculates a difference between the usage charges before and after the migration when a first virtual machine among the plurality of virtual machines is migrated to another cloud location different from the cloud location where the first virtual machine is deployed.
Hereinafter, a description is given of a case of calculating the usage charges before and after the migration of the virtual machine VM for providing the service A as an example. In this case, it is assumed that the virtual machines extracted by the extraction unit 26 are the virtual machine VM1 in the cloud location P and the virtual machine VM2 in the cloud location Q. Further, it is assumed that the virtual machines whose usage charges are reduced are virtual machines VM6 and VM7 in the cloud location R. In this case, the calculation unit 28 calculates the usage charge of the service A when the virtual machine VM1 is migrated to the virtual machine VM6 and the virtual machine VM2 is migrated to the virtual machine VM7, and calculates a difference between calculated usage charge and the usage charge before the migration. This calculation is executed by the calculation unit 28 for each of the services A, B, C, and D.
Referring to
The traffic monitoring unit 30 is a processing unit that monitors each of the traffic volumes tr1, tr2, tr3, tr4 and tr5 in
Next, a description is given of a charge calculation method according to the present embodiment.
Next, the extraction unit 26 extracts the plurality of virtual machines VM having attributes similar to those of the virtual machines whose usage charges are reduced detected in step S11, from all the virtual machines VM that provide the service A (step S12).
For example, it is assumed that the virtual machines in which the reduction of the usage charge detected are the virtual machines VM6 and VM7 in the cloud location R (see
Next, the traffic monitoring unit 30 monitors the traffic volumes tr1, tr2, tr3, tr4 and tr5 (see
Further, the resource monitoring unit 31 monitors the resource usage rates U1 and U2 (see
Next, the determination unit 27 performs a determination process for determining the degree of possibility that the virtual machine having the redundant configuration exist in the plurality of virtual machines providing the service (step S15). Here, the determination unit 27 determines the degree of possibility that the respective extracted virtual machines VM have the redundant configuration based on any of the above-mentioned determination rules R1 to R5. The details of the determination process are described later.
Next, the calculation unit 28 sorts the plurality of services A, B, C, and D (step S16).
Before sorting, the service A has the highest ratio occupied by the virtual machine whose usage charge is reduced.
In this embodiment, each of the ratios ZA, ZB, ZC, and ZD is multiplied by a coefficient α corresponding to the degree of possibility that the plurality of virtual machines VM having similar attributes to the virtual machine whose usage charge is reduced have the redundant configuration. The coefficient α is a coefficient that decreases as the degree of possibility of the redundant configuration increases. Here, the coefficient α is set to 0.1 (α=0.1) when the possibility of the redundant configuration is high, and the coefficient α is set to 0.5 (α=0.5) when the possibility of the redundant configuration is medium. Moreover, the coefficient α is set to 1 (α=1) when the possibility of the redundant configuration is low.
Here, it is assumed that the service A has a high possibility of including the virtual machine VM having the redundant configuration and the coefficient α is set to 0.1 (α=0.1). It is assumed that each of the services C and D has a medium possibility of including the virtual machine VM having the redundant configuration and the coefficient α is set to 0.5 (α=0.5). Further, it is assumed that each of the services C and D has a low possibility of including the virtual machine VM having the redundant configuration and the coefficient α is set to 1 (α=1).
The calculation unit 28 multiplies each of the ratios ZA, ZB, ZC, and ZD by the coefficient α, and sorts the respective services in a descending order of the multiplication results. In this example, the service B has the largest multiplication result, and the services C, D, and A have smaller multiplication results in that order. The sorting method is not limited to this.
In this example, the services A, B, C, and D are sorted in an ascending order of the degree of possibility of the redundant configuration determined in step S15. For example, it is assumed that the possibility of redundant configuration is high in the services A and C, medium in the service D, and low in the service B, as illustrated in
In this case, when the calculation unit 28 sorts the services, the services B, D, A and C are arranged in this order (B→D→A→C).
In case of
Referring to
At this time, the calculation unit 28 calculates the difference between the usage charges in order from the beginning of the services sorted as illustrated in
The calculation process of step S17 terminates without calculating the difference between the usage charges for subsequent services when a difference between the calculated usage charge and the current usage charge is not equal to or less than a predetermined charge. For example, the calculation unit 28 terminates the calculation when it is determined that a migration cost required to migrate the respective virtual machines VM to the virtual machines whose usage charges are reduced is larger than the difference. This avoids a situation where the charge reduction for the respective virtual machines VM is offset by the migration cost, resulting in a higher charge for the service.
In the present embodiment, as a result of the sorting as illustrated in
On the other hand, with respect to the service where there are few virtual machines VM having attributes similar to those of the virtual machines whose usage charges are reduced and the charge reduction cannot be expected so much, the calculation is likely to be terminated, and unnecessary calculation can be avoided. Similarly, with respect to the service where there is a high possibility that the respective virtual machines VM have the redundant configuration and it is expected that the user of the service hardly accepts the migration of the virtual machines VM, the calculation is terminated and the unnecessary calculation can be avoided.
Similarly, also when the sorting is performed based on the degree of possibility of the redundant configuration as illustrated in
When the sorting is performed based on the total number of resources as illustrated in
Then, the display processing unit 29 performs a process of displaying the degree of possibility that the virtual machine having the redundant configuration determined in step S15 exists and the calculation result of the difference between the usage charges in step S17 on the display unit 22 (step S18). This completes basic steps in the charge calculation method according to the present embodiment.
In this example, the display processing unit 29 causes the display unit 22 to display a rate of the charge reduction from the usage charge before the migration in an identifiable manner, as the difference between the usage charges of the service before and after the migration of the virtual machines. The display processing unit 29 may display the usage charge after the charge reduction on the display unit 22 instead of the difference between the usage charges.
The display processing unit 29 causes characters “high”, “medium” and “low” to be displayed on the display unit 22 in the identifiable manner as the degree of the possibility that the virtual machines having the redundant configuration exist in the current respective virtual machines VM.
Thereby, the administrator N of the services A, B, C, and D can confirm the degree of possibility that the virtual machines VM having the redundant configuration exist in each service, and the difference between the usage charges. As a result, the administrator N can predict whether the user of the service accepts the migration to another virtual machine whose usage charge is reduced, and then determine whether to present the usage charge after the charge reduction to the user.
For example, the service A has a maximum charge reduction rate compared to other services, but on the other hand, there is a high possibility that the current virtual machine VM having the attribute similar to that of other virtual machine whose usage charge is reduced has the redundant configuration. If the virtual machine VM is migrated to the other virtual machine whose usage charge is reduced in the same cloud location, the virtual machines VM having the redundant configuration are deployed in the same cloud location. In this case, each virtual machine VM cannot be used when the failure occurs in the above-mentioned cloud location, and hence there is no sense in making each virtual machine VM redundant. Therefore, the administrator N can predict that the user of the service A prevents the migration of the virtual machine, and can refrain from proposing the migration of the virtual machine to the user of service A.
Moreover, since it is possible to prevent the administrator N from accidentally migrating the virtual machine VM having the redundant configuration to the same cloud location, it is also possible to obtain a technical improvement that the availability of service A can be prevented from decreasing.
On the contrary, the service B has a small price reduction rate, but there is a low possibility that the virtual machine VM having the attribute similar to that of the virtual machine whose usage charge is reduced has the redundant configuration. Therefore, even if the virtual machine VM is migrated to the same cloud location where the usage charge is reduced, it is unlikely that the user of the service B is concerned about the redundant configuration of the virtual machine VM to prevent the migration. As a result, the administrator N can positively propose to the user of the service B to migrate the virtual machine.
Next, a description is given of the determination process in step S15. This determination process can be performed by any one of the following first to fifth examples.
First, the determination unit 27 calculates the difference Δtra between the traffic volumes tr1 and tr2 monitored by the traffic monitoring unit 30 (step S21), and further calculates the ratio Pt(=Δtra/tr1).
Next, the determination unit 27 determines whether the ratio Pt satisfies the condition “R1-1” of the determination rule R1 (see
When the ratio Pt does not satisfy the condition “R1-1” (step S22: NO), the process proceeds to step S24. The determination unit 27 determines whether the ratio Pt satisfies the condition “R1-2” of the determination rule R1 (step S24). When the ratio Pt satisfies the condition “R1-2” (step S24: YES), the process proceeds to step S25, and the determination unit 27 determines that the degree of possibility of the redundant configuration is “medium”.
When the ratio Pt does not satisfy the condition “R1-2” (step S24: NO), the process proceeds to step S26. In step S26, the determination unit 27 determines that the degree of possibility of the redundant configuration is “low”. After this, the process returns to S16 of
First, the determination unit 27 calculates the difference Δtrb between the total value trtot, of the output traffic volumes tr1 and tr2 and the input traffic amount tr3 which are monitored by the traffic monitoring unit 30 (step S31), and further calculates the ratio Pb(=Δtrb/tr3).
Next, the determination unit 27 determines whether the ratio Pb satisfies the condition “R2-1” of the determination rule R2 (see
When the ratio Pb does not satisfy the condition “R2-1” (step S32: NO), the process proceeds to step S34. The determination unit 27 determines whether the ratio Pb satisfies the condition “R2-2” of the determination rule R2 (step S34). When the ratio Pb satisfies the condition “R2-2” (step S34: YES), the process proceeds to step S35, and the determination unit 27 determines that the degree of possibility of the redundant configuration is “medium”.
When the ratio Pb does not satisfy the condition “R2-2” (step S34: NO), the process proceeds to step S36. In step S36, the determination unit 27 determines that the degree of possibility of the redundant configuration is “low”. After this, the process returns to S16 of
First, the determination unit 27 calculates the difference Δtrc between the traffic volumes tr4 and tr5 monitored by the traffic monitoring unit 30 (step S41), and further calculates the ratio Pc(=Δtrc/tr4).
Next, the determination unit 27 determines whether the ratio Pc satisfies the condition “R3-1” of the determination rule R3 (see
When the ratio Pc does not satisfy the condition “R3-1” (step S42: NO), the process proceeds to step S44. The determination unit 27 determines whether the ratio Pc satisfies the condition “R3-2” of the determination rule R3 (step S44). When the ratio Pc satisfies the condition “R3-2” (step S24: YES), the process proceeds to step S45, and the determination unit 27 determines that the degree of possibility of the redundant configuration is “medium”.
When the ratio Pc does not satisfy the condition “R3-2” (step S44: NO), the process proceeds to step S46. In step S46, the determination unit 27 determines that the degree of possibility of the redundant configuration is “low”. After this, the process returns to S16 of
First, the determination unit 27 calculates the difference ΔU between the resource usage rate U1 and the resource usage rate U2 monitored by the resource monitoring unit 31 (step S51), and further calculates the ratio Pu(=ΔU/U1). In the difference ΔU, the resource usage rate U1 is a value at the time t1, and the resource usage rate U2 is a value at the time t2.
Next, the determination unit 27 determines whether the ratio Pu satisfies the condition “R4-1” of the determination rule R4 (see
When the ratio Pu does not satisfy the condition “R4-1” (step S52: NO), the process proceeds to step S54. The determination unit 27 determines whether the ratio Pu satisfies the condition “R4-2” of the determination rule R4 (step S54). When the ratio Pu satisfies the condition “R4-2” (step S54: YES), the process proceeds to step S55, and the determination unit 27 determines that the degree of possibility of the redundant configuration is “medium”.
When the ratio Pu does not satisfy the condition “R4-2” (step S54: NO), the process proceeds to step S56. In step S56, the determination unit 27 determines that the degree of possibility of the redundant configuration is “low”. After this, the process returns to S16 of
First, the determination unit 27 calculates the difference Δtrd between the traffic volumes tr4 and tr5 monitored by the traffic monitoring unit 30 (step S61), and further calculates the ratio Pd(=Δtrd/tr4).
Next, the determination unit 27 determines whether the ratio Pd satisfies the condition “R5-1” of the determination rule R5 (see
When the ratio Pd does not satisfy the condition “R5-1” (step S62: NO), the process proceeds to step S64. The determination unit 27 determines whether the ratio Pd satisfies the condition “R5-2” of the determination rule R5 (step S64). When the ratio Pd satisfies the condition “R5-2” (step S64: YES), the process proceeds to step S65, and the determination unit 27 determines that the degree of possibility of the redundant configuration is “medium”.
When the ratio Pd does not satisfy the condition “R5-2” (step S64: NO), the process proceeds to step S66. In step S66, the determination unit 27 determines that the degree of possibility of the redundant configuration is “low”. After this, the process returns to S16 of
Next, a description is given of hardware configuration of the information processing device 12 according to the present embodiment.
As illustrated in
The storage device 12a is a non-volatile storage such as an HDD (Hard Disk Drive) or an SSD (Solid State Drive), and stores a charge calculation program 40 according to the present embodiment.
The charge calculation program 40 may be recorded on a computer-readable recording medium 12h, and the processor 12c may read the charge calculation program 40 from the recording medium 12h.
Examples of such a recording medium 12h include physically portable recording media such as a CD-ROM (Compact Disc-Read Only Memory), a DVD (Digital Versatile Disc), and a USB (Universal Serial Bus) memory. Further, a semiconductor memory such as a flash memory, or a hard disk drive may be used as the recording medium 12h. The recording medium 12h is not a temporary medium such as a carrier wave having no physical form.
Further, the charge calculation program 40 may be stored in a device connected to a public line, an Internet, a LAN (Local Area Network), or the like. In this case, the processor 12c may read and execute the charge calculation program 40.
Meanwhile, the memory 12b is hardware that temporarily stores data, such as a DRAM, and the charge calculation program 40 is deployed on the memory 12b.
The processor 12c is hardware such as a CPU (Central Processing Unit) and a GPU (Graphical Processing Unit) that control each part of the information processing device 12. Further, the processor 12c executes the charge calculation program 40 in cooperation with the memory 12b.
In this way, the control unit 24 of
Further, the communication interface 12d is a communication interface such as a NIC (Network Interface Card) for connecting the information processing device 12 to the network 11. The communication unit 21 of
The display device 12e is hardware such as a liquid crystal display device for realizing the display unit 22 of
All examples and conditional language recited herein are intended for pedagogical purposes to aid the reader in understanding the invention and the concepts contributed by the inventor to furthering the art, and are to be construed as being without limitation to such specifically recited examples and conditions, nor does the organization of such examples in the specification relate to a showing of the superiority and inferiority of the invention. Although the embodiments of the present invention have been described in detail, it should be understood that the various change, substitutions, and alterations could be made hereto without departing from the spirit and scope of the invention.
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