Resource determination device, method, and program

Abstract

A resource determination device according to one embodiment of the present invention has: a model storage device in which is stored a model that indicates the relationships between the processing load allocated to a virtual machine, the resource allocation of the virtual machine, and the predicted value of quality when the processing load is allocated to the virtual machine; an assessment unit for assessing whether or not the predicted value of quality when it is assumed that a new processing load is allocated to the virtual machine in the model satisfies suitable quality requirements; and a control unit for controlling alteration of the resource allocation of the virtual machine such that the predicted value satisfies the suitable quality requirements when it is assessed by the assessment unit that the predicted value does not satisfy the suitable quality requirements.

Description

[Technical Field]

[0001] FIELD Embodiments of the present invention relate to a resource determination device, method, and program. [Background technology]

[0002] Auto-scaling is relatively commonly used to control the resources of server computers (see, for example, Non-Patent Documents 1 and 2). This auto-scaling determines resource adjustment based on the real-time state of a VM (Virtual Machine), which is an instance, such as the CPU (Central Processing Unit) usage rate. [Prior art documents] [Non-patent literature]

[0003] [Non-Patent Document 1] Lorido-Botran, et, al. A Review of Auto-scaling Techniques for Elastic Applications in Cloud Environments. J Grid Computing 12, 559-592 (2014). [Non-patent document 2] M. Mao, et al. Auto-scaling to minimize cost and meet application deadlines in cloud workflows, International Conference for High Performance Computing, Networking, Storage and Analysis, 2011, pp. 1-12. Summary of the Invention [Problem to be solved by the invention]

[0004] The above-mentioned existing auto-scaling techniques determine resource adjustment based on the real-time state of the VM as described above, and therefore cannot proactively control resources. Furthermore, while there are many autoscaling technologies that take deadlines and budgets into account, they do not take into account the requirements for user quality of experience.

[0005] Therefore, when applying auto-scaling to a web conferencing service, if multiple web conferences occur simultaneously, resources cannot be proactively allocated, which may result in resource depletion due to sudden high processing loads, resulting in a deterioration in the user experience.

[0006] The present invention has been made in light of the above-mentioned circumstances, and its purpose is to provide a resource determination device, method, and program that can appropriately determine resources according to the state of an instance. [Means for solving the problem]

[0007] A resource determination device according to one aspect of the present invention comprises: A service requested by a user Deployed to a virtual machine services and services assumed to be deployed on said virtual machines processing load, resource allocation of the virtual machine, and Requested Service was deployed on the virtual machine. It was assumed that When Related to the requested service a model storage device in which a model indicating the relationship between the quality prediction values ​​is stored; service and a control unit that, when the determination unit determines that the predicted value does not satisfy the appropriate quality requirements, controls a change in resource allocation of the virtual machine so that the predicted value satisfies the appropriate quality requirements.

[0008] A resource determination method according to one aspect of the present invention includes: A service requested by a user Deployed to a virtual machine services and services assumed to be deployed on said virtual machines processing load, resource allocation of the virtual machine, and Requested Service was deployed on the virtual machine. It was assumed that When Related to the requested service A model showing the relationship between quality prediction values ​​is Store will be Store The resource determination device is provided with a circle a determination unit of the resource determination device assigns a new resource to the virtual machine in the model, service determining whether the predicted value of the quality when it is assumed that the virtual machine is allocated satisfies the requirement of appropriate quality; and when the determination unit determines that the predicted value does not satisfy the requirement of appropriate quality, a control unit of the resource determination device controls a change in the resource allocation of the virtual machine so that the predicted value satisfies the requirement of appropriate quality. [Effects of the Invention]

[0009] According to the present invention, resources can be appropriately determined depending on the state of an instance. [Brief explanation of the drawings]

[0010] [Figure 1] FIG. 1 is a diagram showing an application example of a resource determination system according to an embodiment of the present invention. [Figure 2] FIG. 2 is a diagram showing an example of input and output data of a Web conference quality model. [Figure 3] FIG. 3 is a sequence diagram showing an example of a procedure related to vertical scaling by a resource determination device according to an embodiment of the present invention. [Figure 4] FIG. 4 is a sequence diagram showing an example of a procedure related to horizontal scaling by a resource determination device according to an embodiment of the present invention. [Figure 5] FIG. 5 is a diagram showing a specific example of a vertical scale according to the quality of a Web conference. [Figure 6] FIG. 6 is a diagram showing a specific example of a vertical scale according to the quality of a Web conference. [Figure 7] FIG. 7 is a diagram showing a specific example of a vertical scale according to the quality of a Web conference. [Figure 8] FIG. 8 is a diagram showing a specific example of a horizontal scale according to the quality of a Web conference. [Figure 9] FIG. 9 is a diagram showing a specific example of a horizontal scale according to the quality of a Web conference. [Figure 10] FIG. 10 is a diagram showing a specific example of a horizontal scale according to the quality of a Web conference. [Figure 11] FIG. 11 is a diagram showing a specific example of a horizontal scale according to the quality of a Web conference. [Figure 12] FIG. 12 is a diagram showing a specific example of a horizontal scale according to the quality of a Web conference. [Figure 13] FIG. 13 is a block diagram showing an example of the hardware configuration of a resource determination device according to one embodiment of the present invention. DETAILED DESCRIPTION OF THE INVENTION

[0011] An embodiment of the present invention will be described below with reference to the drawings. FIG. 1 is a diagram showing an application example of a resource determination system according to an embodiment of the present invention. As shown in FIG. 1, the resource determination system according to an embodiment of the present invention includes a Web conference scheduling device 100, which is a resource determination device, and a cloud resource controller 200.

[0012] The Web conference scheduling device 100 includes a Web conference scheduler 10, a Web conference reservation storage unit 20, and a Web conference arrangement unit 30. The Web conference scheduler 10 also includes a controller 11, an instance (VM) state monitoring unit 12, and a Web conference quality model DB (database) 13.

[0013] A database (not shown) in the Web conference reservation storage unit 20 stores reservation information indicating the reservation details of reserved but unfinished Web conferences, i.e., new Web conferences, i.e., reservation information for new processing loads. This reservation information includes, for example, identification information (ID (IDentifier)) assigned to each reservation, the number of participants planned for the reserved Web conference, and information about the time period during which the Web conference is scheduled to be held. Information related to completed Web conferences is deleted from the Web conference reservation storage unit 20.

[0014] A user who wishes to reserve a new Web conference can send a request for reservation of a Web conference to the Web conference scheduler 10 using an interface (not shown) that can be connected to the Web conference scheduler 10 .

[0015] When the Web conference scheduler 10 receives this reservation request, it saves the reservation information related to this request in the Web conference reservation storage unit 20 ((1-1) in FIG. 1), and then acquires reservation information indicating the reservation details of the Web conference that has been booked and is not yet finished, including the saved reservation information ((1-2) in FIG. 1). This reservation information indicates the processing load related to the Web conference allocated to the VM (hereinafter sometimes referred to as the Web conference load), such as the number of participants in the Web conference, and the scheduled time period for the conference.

[0016] When the controller 11 of the Web conference scheduler 10 acquires the reservation information, it inquires of the instance status monitor 12 about the status of each VM, which is an instance used for the Web conference, such as the resource setting status of the VM where the Web conference is placed, such as the number of CPU cores and memory capacity, and acquires the inquired information. Here, it is assumed that each VM is a virtual machine operated on the cloud.

[0017] The controller 11 inputs the information acquired from the instance state monitor 12 into the Web conference quality model in the Web conference quality model DB 13. The Web conference quality model inputs information indicating the resource configuration status of the VM on which the Web conference is placed, and the processing load related to the Web conference placed in the VM and the Web conference assumed to be placed in the VM, and can output a predicted value of the user's quality of experience related to the Web conference placed in the VM, and the input / output relationship can be learned in advance.

[0018] When the predicted value of the user experience quality output from the Web conference quality model does not satisfy the specified conditions for the user experience quality, the controller 11 recommends to the system administrator how to adjust the resources of the VM where the Web conference is placed so that the user experience quality satisfies the above conditions ((2) in Figure 1). In addition, the controller 11 instructs the Web conference placement unit 30 to place the Web conference in the VM where the Web conference is to be placed so that the user quality of experience satisfies the above conditions ((4-1) in FIG. 1).

[0019] The system administrator issues instructions relating to resource adjustment by operating the cloud resource controller 200 ((3-1) in FIG. 1). According to this instruction, the cloud resource controller 200 can start a new VM (see symbol a in FIG. 1) in which the Web conference is placed, or change the resources of this VM ((3-2) in FIG. 1). The Web conference arrangement unit 30 arranges the Web conference in the VM according to the above instruction, so that the Web conference can be started ((4-2) in FIG. 1).

[0020] Next, we explain the construction of the web conference quality model and its learning process. The controller 11 of the Web conference scheduler 10 acquires from the instance status monitoring unit 12 (1) the Web conference load, which is the processing load related to the Web conference placed in the VM and the Web conference assumed to be placed in the VM, and (2) the cloud resource setting, which is the resource setting status in the VM where the Web conference is placed, and inputs the acquired results as explanatory variables into the Web conference quality model.

[0021] The processing load related to the above-mentioned Web conferences is, for example, the number of Web conferences, the number of participants in the Web conferences, the number of publishers participating in the Web conferences, the number of subscribers, and so on. The resource setting status is, for example, the number of CPUs and memory capacity provided in a VM that is an instance.

[0022] Based on the results of the above inputs, the web conference quality model can output an index representing the quality of the web conference (user experience quality) as the objective variable, i.e., a predicted value of the quality of the web conference. The parameters of this model can be trained using regression analysis methods such as neural-network regression, linear regression, and random forest regression so that the relationship between the input and output is appropriate, i.e., so that the predicted value of the web conference quality approaches the correct information.

[0023] For example, indicators that represent the quality of a web conference (user experience quality) include predicted CPU usage in the VM, which is the instance where the web conference is deployed, jitter, throughput, and MOS (Mean Opinion Score).

[0024] Next, we will explain how to calculate indicators related to web conference quality using the web conference quality model trained as described above. Figure 2 shows an example of input and output data of the web conference quality model. This shows that the user's quality of experience is calculated in response to a new web conference reservation. In the example shown in Figure 2, the Web conference load indicated by the information input to the Web conference model includes (1) the Web conference load related to the currently ongoing Web conference, and (2) the Web conference load related to a Web conference reservation for 10 minutes in the future, which is a reservation for a Web conference that starts 10 minutes from the current time, based on a new Web conference request (see symbol a in Figure 2). The 10 minutes from the current time to the scheduled start time of this 10-minute future Web conference reservation can be customized according to the actual operating status of the instance.

[0025] The above-mentioned web conference load for a currently ongoing web conference may include an identification (ID) that uniquely identifies the web conference, the number of participants in the web conference, and the time period from the start time to the end time of the web conference.

[0026] The above-mentioned web conference load for a web conference reservation for 10 minutes in the future may include identification information that uniquely identifies the web conference, the number of participants expected to attend the web conference, and the time period from the scheduled start time to the scheduled end time of the web conference. The cloud resource settings input to the Web conference model may include the number of CPUs installed in one VM, which is an instance. The currently ongoing Web conference is placed on the one VM.

[0027] The indicators related to the quality of the Web conference output from the above Web conference model include identification information that uniquely identifies the Web conference in question, a predicted value of the CPU usage rate of the above one VM due to the currently ongoing Web conference, a predicted value of the CPU usage rate of the above one VM due to the Web conference to be held in response to a new conference request, and the time period from the start to the end of each Web conference.

[0028] In the example shown in FIG. 2, when "Web conference p" with the identification information "p" is placed on the one VM, the predicted value of the CPU usage rate of the VM is 50%. In the example shown in Figure 2, if a new "Web Conference a" with the identification information "a" is deployed to the VM, the predicted CPU usage rate of the VM is 10%.

[0029] This "Web conference a" is a newly requested Web conference to be held in a time period that partially overlaps with the time period of "Web conference p."

[0030] If the CPU usage threshold for the VM is set to 80%, and it is assumed that "Web Conference A" is newly placed on the VM in addition to "Web Conference P," the total predicted CPU usage will be 60%, which does not exceed the threshold of 80%. Therefore, "Web Conference A" can be placed on the VM where "Web Conference P" is currently placed.

[0031] On the other hand, if the predicted CPU usage rate of the VM when "Web Conference A" is newly deployed exceeds, for example, 30%, the sum of the above predicted values ​​will exceed the threshold, and adjustment of the resources related to the VM where it is deployed will be necessary.

[0032] FIG. 3 is a sequence diagram showing an example of a procedure related to vertical scaling by a resource determination device according to an embodiment of the present invention. In the example shown in FIG. 3, the flow of each process when vertical scaling is performed by a Web conference scheduler is shown.

[0033] First, the controller 11 of the Web conference scheduler 10 acquires, from the Web conference reservation storage unit 20, reservation information on Web conferences currently being held and conferences for which new holding has been requested, as the Web conference load (S11).

[0034] The controller 11 inquires of the instance state monitor 12 about the cloud resource settings, which are the states of each existing VM in which a Web conference has already been placed, and acquires them (S12).

[0035] The controller 11 inputs the results obtained in S11 and S12 into the Web conference quality model to inquire about the predicted value of the change in user experience quality when the requested Web conference is newly placed in one of the existing VMs, and obtains the output result from the Web conference quality model as the predicted value (S13).

[0036] The controller 11 compares this predicted value with the scale-up user experience threshold, and if the predicted value does not exceed the threshold, determines that the requested Web conference can be placed on the corresponding existing instance (VM). In this case, no resource adjustment is performed to place the requested Web conference.

[0037] On the other hand, if the predicted value exceeds the threshold, it is determined that vertical scaling, which is an adjustment of the instance resources, is necessary to place the requested Web conference in an existing instance and hold it. In this case, the controller 11 recommends scale-up as vertical scaling to the system administrator (S14, S15), and instructs the Web conference placement unit 30 to set a VM as a placement destination for the requested Web conference from each existing VM and place the requested Web conference in the set VM (S16). In other words, when it is determined that the predicted value does not satisfy the appropriate quality requirements, the controller 11 controls changes to the virtual machine resource placement so that the predicted value satisfies the appropriate quality requirements.

[0038] The system administrator instructs the cloud resource controller 200 to scale up the resources of each VM according to the recommendation from the controller 11 (S17). In accordance with this instruction, the cloud resource controller 200 executes the control required to implement the scale-up. This scale-up expands the resources of the VM, for example, by increasing the number of CPU cores.

[0039] Furthermore, after the above-mentioned scale-up is implemented, a predicted value of the change in the user quality of experience is obtained, for example, at regular time intervals, and when this obtained predicted value is equal to or less than a scale-down threshold that is smaller than the user quality of experience threshold for the scale-up, the controller 11 recommends scaling down the instance to the system administrator (S18).

[0040] The system administrator instructs the cloud resource controller 200 to scale down the resources of each VM (S19) in accordance with the recommendation from the controller 11. In accordance with this instruction, the cloud resource controller 200 executes the control required to implement the scale-down.

[0041] FIG. 4 is a sequence diagram showing an example of a procedure related to horizontal scaling by a resource determination device according to an embodiment of the present invention. The example shown in FIG. 4 shows the flow of each process when horizontal scaling is performed by a Web conference scheduler.

[0042] First, the controller 11 of the Web conference scheduler 10 acquires, from the Web conference reservation storage unit 20, reservation information on Web conferences currently being held and conferences for which new holding has been requested, as the Web conference load (S31).

[0043] The controller 11 inquires of the instance state monitor 12 about the cloud resource settings, which are the states of each existing VM in which a Web conference has already been placed, and acquires them (S32).

[0044] The controller 11 inputs the results obtained in S31 and S32 into the Web conference quality model to inquire about the predicted value of the user's quality of experience when the requested Web conference is newly placed in one of the existing VMs, and obtains the output result from the Web conference quality model as the predicted value (S33).

[0045] The controller 11 compares this predicted value with the scale-up user experience threshold, and if the predicted value does not exceed the threshold, determines that the requested Web conference can be placed on the corresponding existing instance (VM). In this case, no resource adjustment is performed to place the requested Web conference.

[0046] On the other hand, if the predicted value exceeds the threshold, it is determined that horizontal scaling, which is an adjustment of the instance resources, is necessary to place the requested Web conference on an existing instance and hold it.

[0047] In this case, the controller 11 recommends a scale-out as a vertical scale to the system administrator (S34, S35), sets a new VM to which the requested Web conference will be placed that is different from each existing VM, and instructs the Web conference placement unit 30 to place the requested Web conference in this set VM (S36).

[0048] The system administrator follows the recommendation from the controller 11 and instructs the cloud resource controller 200 to scale out the VM resources (S37). According to this instruction, the cloud resource controller 200 executes the control necessary to implement the scale-out. This scale-up adds resources to the VM, for example, adding a new VM to the existing VMs.

[0049] After the scale-out is performed, the controller 11 accesses the Web conference placement unit 30 to check whether or not a Web conference is to be placed in the added VM. If a Web conference is not placed in the added VM for a certain period of time, the controller 11 accesses the Web conference placement unit 30 to check whether or not a Web conference is to be placed in the added VM. of The scale-in to be suspended is recommended to the system administrator (S38).

[0050] The system administrator instructs the cloud resource controller 200 to scale in the resources of the VM in question (S39) in accordance with the recommendation from the controller 11. In accordance with this instruction, the cloud resource controller 200 executes the control required to implement the scale-in.

[0051] 5 to 7 are diagrams showing specific examples of vertical scales according to the quality of a Web conference. First, in the example shown in Figure 5, an existing instance, "Instance A," is a VM with two CPU cores, and the current predicted CPU usage for "Meeting X," an existing web conference that has been running on this VM since 8:55, is 75%, and the upper limit of CPU usage for this VM is 80%. This upper limit is the CPU usage rate required to satisfy the user quality of experience.

[0052] In the example shown in Figure 5, a request is made to place a new web conference "Meeting A" starting at 9:00 a.m., and the predicted increase in CPU usage when "Meeting A" is newly placed on "Instance A" is 35%.

[0053] In this case, assuming that "Meeting A" is newly placed on "Instance A," the overall CPU usage will be 110%, exceeding the upper limit of 80%, so vertical scaling of "Instance A," in this case an increase in the number of CPU cores, is required, and the above-mentioned scale-up is required.

[0054] In the example shown in Figure 6, it is assumed that the number of CPU cores of "Instance A" has been increased from 2 to 4 by the above scale-up. In this configuration, the predicted current CPU usage due to the web conference currently placed on the VM corresponding to "Instance A" has decreased from the above 75% to 40%, and the predicted increase in CPU usage when "Conference A" is newly placed on "Instance A" has decreased from the above 35% to 18%.

[0055] In this case, assuming that "Meeting A" is newly placed on "Instance A," the overall CPU usage will decrease from the above 110% to 58%, and will not exceed the upper limit of 80%. Therefore, "Meeting A" will be newly placed on "Instance A," and this "Meeting A" will be able to be held together with the above-mentioned existing web conference "Meeting X."

[0056] Then, assuming that "Meeting A" is newly placed on "Instance A" due to the above scale-up, if the overall CPU usage decreases so that it does not exceed the upper limit, further new web conferences can be placed on "Instance A".

[0057] For example, in the example shown in Figure 7, if "Meeting B" is newly placed in "Instance A" in addition to "Meeting A," the predicted increase in CPU usage is 5%, and the overall CPU usage is 63%, which does not exceed the upper limit.Therefore, "Meeting B" is newly placed in "Instance A," and this "Meeting B" can be held together with the existing Web conference "Meeting X" and the previously placed "Meeting A."

[0058] 8 to 12 are diagrams showing specific examples of horizontal scales according to the Web conference quality. First, in the example shown in Figure 8, the current predicted CPU usage for an existing web conference "Meeting X" that has been placed on a VM called "Instance A" since 8:55 is 75%, and the upper limit of CPU usage for this VM is 80%.

[0059] In the example shown in Figure 8, a request is made to place a new web conference "Meeting A" starting at 9:00 a.m., and the predicted increase in CPU usage when "Meeting A" is newly placed on "Instance A" is 35%.

[0060] In this case, assuming that "Meeting A" is newly placed on "Instance A," the overall CPU usage will be 110%, exceeding the upper limit of 80%, so horizontal scaling of "Instance A," in this case an increase in the number of CPU cores, is required, and the scale-out described above is required.

[0061] In the example shown in FIG. 9, it is assumed that a new "instance B" is added by the above scale-out. In this configuration, the above "Meeting A" is newly placed on a VM corresponding to the new "Instance B" rather than the existing "Instance A," and the predicted CPU usage when this "Meeting A" is newly placed on "Instance B" is assumed to be 35% as mentioned above.

[0062] In this case, assuming that "Meeting A" is newly placed, the overall CPU usage of "Instance A" will remain at the above 75% and will not exceed the upper limit of 80%, so "Meeting A" will be newly placed on "Instance B" and this "Meeting A" will be able to be held together with the existing web conference "Meeting X" placed on "Instance A".

[0063] Then, as a result of the above scale-out, a new "Instance B" is created, and assuming that a new "Conference A" is placed on this instance, the CPU usage of "Instance A" and "Instance B" will have room for more than the upper limit, so further new web conferences can be placed on each instance.

[0064] For example, in the example shown in Figure 10, assuming that "Meeting B" is newly placed in addition to "Meeting A" on the new "Instance B," the predicted CPU usage is 10%, and the overall CPU usage is 45%, which does not exceed the upper limit.Therefore, "Meeting B" is newly placed on "Instance B," and this "Meeting B" can be held together with the existing Web conference "Meeting X" and the previously placed Web conference "Meeting A."

[0065] 11 shows that, assuming that "Meeting B" is newly placed on "Instance B" as shown in FIG. 10, if a new Web conference "Meeting C" is placed on "Instance A," the predicted increase in CPU usage is 75%, and if "Meeting A" is newly placed on "Instance A," the overall CPU usage is 150%, exceeding the upper limit of 80%. Also, assuming that "Meeting C" is newly placed on "Instance B," the predicted increase in CPU usage is 75%, and if "Meeting C" is newly placed on "Instance B," the overall CPU usage is 120%, exceeding the upper limit of 80%. In this case, further scaling out is required to implement "Meeting C."

[0066] In the example shown in Figure 12, if we assume that a new "Instance C" is added as a result of the further scale-out and that the above-mentioned "Meeting C" is newly placed on this instance, the overall CPU usage in "Instance A" to "Instance C" will not exceed the upper limit of 80%, so "Meeting C" will be able to be held together with the above-mentioned existing Web conference "Meeting X" and the previously placed Web conferences "Meeting A" and "Meeting B."

[0067] FIG. 13 is a block diagram showing an example of the hardware configuration of a resource determination device according to an embodiment of the present invention. 13, the Web conference scheduling device 100 according to the embodiment is configured, for example, by a server computer or a personal computer, and has a hardware processor 111A such as a CPU. A program memory 111B, a data memory 112, an input / output interface 113, and a communication interface 114 are connected to this hardware processor 111A via a bus 115. The same applies to the cloud resource controller 200.

[0068] The communication interface 114 includes, for example, one or more wireless communication interface units, and enables transmission and reception of information to and from a communication network NW. As the wireless interface, for example, an interface that adopts a low-power wireless data communication standard such as a wireless LAN (Local Area Network) is used.

[0069] The input / output interface 113 is connected to an input device 500 and an output device 600 that are attached to the Web conference scheduling device 100 and used by users, etc. The input / output interface 113 takes in operation data input by a user or the like via an input device 500 such as a keyboard, touch panel, touchpad, or mouse, and outputs and displays output data to an output device 600 including a display device using liquid crystal or organic EL (Electro Luminescence). The input device 500 and the output device 600 may be devices built into the Web conference scheduling device 100, or may be input devices and output devices of other information terminals that can communicate with the Web conference scheduling device 100 via the network NW.

[0070] The program memory 111B is a non-transitory tangible storage medium that is a combination of a non-volatile memory that can be written to and read from at any time, such as a hard disk drive (HDD) or a solid state drive (SSD), and a non-volatile memory such as a read only memory (ROM), and stores programs necessary to execute various control processes, etc., according to one embodiment.

[0071] The data memory 112 is a tangible storage medium that is a combination of, for example, the above-mentioned nonvolatile memory and a volatile memory such as RAM (Random Access Memory), and is used to store various data acquired and created during various processing steps.

[0072] A Web conference scheduling device 100 according to one embodiment of the present invention can be configured as a data processing device having a Web conference scheduler 10, a Web conference reservation storage unit 20, and a Web conference arrangement unit 30 shown in FIG. 1 as software processing function units.

[0073] Each information storage unit used as a working memory by each unit of the Web conference scheduling device 100 can be configured using the data memory 112 shown in Fig. 13. However, these configured storage areas are not essential components within the Web conference scheduling device 100, and may be areas provided in an external storage medium such as a USB (Universal Serial Bus) memory, or in a storage device such as a database server located in the cloud.

[0074] The processing function units in the Web conference scheduler 10, Web conference reservation storage unit 20, and Web conference arrangement unit 30 can all be realized by having the hardware processor 111A read and execute programs stored in the program memory 111B. Note that some or all of these processing function units may be realized in various other forms, including integrated circuits such as an application specific integrated circuit (ASIC) or a field-programmable gate array (FPGA).

[0075] In the embodiment described above, for example, a model is constructed that represents the relationship between cloud resources, the processing load of a Web conference service, and user experience quality. When allocating a reserved Web conference to a VM, it is determined whether the user experience index is satisfied. If not, resources are controlled by a horizontal or vertical scale to satisfy the index. Thus, optimal resources can be determined taking user experience quality into consideration.

[0076] The methods described in each embodiment may be stored as a program (software means) that can be executed by a computer on a recording medium such as a magnetic disk (e.g., a floppy disk, a hard disk, etc.), an optical disk (e.g., a CD-ROM, a DVD, an MO, etc.), or a semiconductor memory (e.g., a ROM, a RAM, a flash memory, etc.), or may be transmitted and distributed via a communication medium. The program stored on the medium also includes a configuration program that configures the software means (including not only execution programs but also tables and data structures) that the computer executes. The computer that realizes this device reads the program stored on the recording medium and, in some cases, configures the software means using the configuration program, and executes the above-described processing by having the operation controlled by this software means. The term "recording medium" as used herein is not limited to a storage medium for distribution, but also includes a storage medium such as a magnetic disk or semiconductor memory installed inside the computer or in a device connected via a network.

[0077] The present invention is not limited to the above-described embodiments, and various modifications can be made in the implementation stage without departing from the spirit of the invention. Furthermore, the embodiments may be implemented in appropriate combinations, in which case the combined effects can be obtained. Furthermore, the above-described embodiments include various inventions, and various inventions can be extracted by combining selected elements from the disclosed elements. For example, if the problem can be solved and the desired effect can be obtained even if some elements are deleted from all elements shown in the embodiments, the configuration from which these elements are deleted can be extracted as an invention. [Explanation of symbols]

[0078] 100...Web conference scheduling device 200: Cloud resource controller 10. Web conference scheduler 11...Controller 12...Instance status monitoring unit 13…Web conference quality model DB 20…Web conference reservation storage section 30…Web Conference Configuration Department

Claims

1. A model storage device that stores a model showing the relationship between a service requested by a user that is to be deployed on a virtual machine and the processing load associated with the service assumed to be deployed on the virtual machine, the resource allocation of the virtual machine, and a predicted value of the quality associated with the requested service when it is assumed that the requested service is deployed on the virtual machine; a determination unit that determines whether the predicted value of quality when a new service is assumed to be allocated to the virtual machine in the model satisfies an appropriate quality requirement; a control unit that controls a change in resource allocation of the virtual machine so that the predicted value satisfies the requirement of appropriate quality when the determination unit determines that the predicted value does not satisfy the requirement of appropriate quality; A resource determination device comprising:

2. The model is a model in which a service to be deployed on the virtual machine, a processing load related to the service assumed to be deployed on the virtual machine, and information indicating resource allocation of the virtual machine are input as explanatory variables, and a predicted value of the quality when the service is assumed to be deployed on the virtual machine is output as a response variable, The parameters of the model are updated so that the predicted value of quality approaches the correct information. The resource determination device according to claim 1 .

3. The control unit when the determination unit determines that the predicted value does not satisfy the requirement for appropriate quality, controlling the change in the resource allocation to enhance performance without changing the number of virtual machines so that the predicted value satisfies the requirement for appropriate quality. The resource determination device according to claim 1 .

4. The control unit When the determination unit determines that the predicted value does not satisfy the requirement for appropriate quality, the change in resource allocation is controlled so that the number of virtual machines on which the service is allocated is increased so that the predicted value satisfies the requirement for appropriate quality. The resource determination device according to claim 1 .

5. a reservation information storage device for storing reservation information of a new service requested to be allocated to the virtual machine; The determination unit determining whether the predicted value of quality when the service indicated by the reservation information stored in the reservation information storage device is assumed to be deployed on the virtual machine satisfies an appropriate quality requirement; The resource determination device according to claim 1 .

6. A method performed by a resource determination device having a storage device in which a model is stored showing the relationship between a service requested by a user that is to be deployed on a virtual machine and a processing load associated with the service assumed to be deployed on the virtual machine, resource allocation of the virtual machine, and a predicted value of quality associated with the requested service when it is assumed that the requested service is deployed on the virtual machine, comprising: determining, by a determination unit of the resource determination device, whether or not the predicted value of quality when a new service is assumed to be allocated to the virtual machine in the model satisfies an appropriate quality requirement; a control unit of the resource determination device controlling a change in resource allocation of the virtual machine so that the predicted value satisfies the requirement of appropriate quality when the determination unit determines that the predicted value does not satisfy the requirement of appropriate quality; A resource determination method comprising:

7. The model is a model in which a service to be deployed on the virtual machine, a processing load related to the service assumed to be deployed on the virtual machine, and information indicating resource allocation of the virtual machine are input as explanatory variables, and a predicted value of the quality when the service is assumed to be deployed on the virtual machine is output as a response variable, The parameters of the model are updated so that the predicted value of quality approaches the correct information. The resource determination method according to claim 6 .

8. A resource determination processing program that causes a processor to function as each unit of the resource determination device according to any one of claims 1 to 5.

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