This application is based upon and claims the benefit of priority of the prior Japanese Patent Application No. 2014-044420, filed on Mar. 6, 2014, the entire contents of which are incorporated herein by reference.
The embodiment discussed herein is related to a setting support program, a setting support device, and a setting support method.
Recently, cloud systems each being capable of using a plurality of computing resources present on a network as user's computing resources using a technology for virtualizing a server or a network are used. Such cloud systems are increased in scale and are complicated and, for example, parameters relating to additional installation of devices or designs of the systems are added or changed.
A system is designed in accordance with a change in the system. In the design of a system, for example, a designer creates a setting rule for setting parameters relating to the design. The setting rule is created, for example, based on settings of parameters that are performed in a plurality of systems in the past.
In addition, there is a technology for automatically creating a setting rule. According to such a technology, an information processing apparatus receives configuration data relating to a plurality of computers, analyzes the configuration data, and creates a configuration rule based on a result of the analysis. In the configuration rule, a variable parameter setting rule is included (for example, see Japanese Laid-open Patent Publication No. 2009-048611 and Japanese Laid-open Patent Publication No. 10-097413).
However, there is a problem in that it is difficult to acquire the degree of certainty of a setting rule of parameters for a designer. In other words, in a case where there are many errors in the settings of parameters performed in the past, a setting rule that is created based on the settings of parameters performed in the past is not accurate. In a case where an erroneous setting of parameters can be removed when a setting rule is created, an accurate setting rule can be created. However, since there is no information representing whether or not a setting of parameters is erroneous, an erroneous setting of parameters is removed. Thus, it is difficult to acquire whether or not a setting rule of parameters is accurate for the designer.
According to an aspect of an embodiment, a non-transitory computer-readable recording medium stores a setting support program. The setting support program causes a computer to execute a process. The process includes generating a setting of parameters common to a plurality of devices and a condition used for the setting as a first rule based on information relating to settings of the parameters performed for the plurality of devices in the past. The process includes generating a setting of parameters common to the plurality of devices and a condition used for the setting as a second rule for each generation based on information of each generation that relates to settings of the parameters performed for the plurality of devices in the past. The process includes comparing the first rule and the second rule with each other in relation to the setting of the parameters that is common, specifying a different rule and calculating an index representing a degree of certainty of the specified different rule.
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.
Preferred Embodiments of the Present Invention will be explained with reference to accompanying drawings. However, the embodiments are not limited thereto.
Here, the problem of the setting rule not being accurate in a case where there are many errors in settings of parameters will be described with reference to
Thus, the setting support device 1 according to the embodiment generates a setting rule used for setting parameters for each generation by using setting information (teacher data 11) of parameters for each generation of an existing data center. Then, the setting support device 1 calculates the degrees of reliability of setting rules for which common parameters are different from each other and supports the generation of an appropriate setting rule.
Here, a generation, for example, represents a time division. In other words, a generation represents a time point determined in advance as a time point when the setting information of parameters of a plurality of systems installed to the data center is acquired. The time division, for example, may be one hour, two hours, or 24 hours. In other words, the time division may be a time point that is determined in advance. In addition, as another example, a generation represents a division according to a change in the configuration of systems and the like inside a data center. In other words, a generation represents a time point when the configuration of systems and the like is changed as a time point when the setting information of parameters of a plurality of systems installed to a data center is acquired. A division according to a configuration change, for example, may be a time point when a system is added or a time point when a parameter is changed. In other words, the division according to a configuration change may be a time point when a certain configuration is changed. As the generation, for example, “1” represents the current time point, and, as the number representing a generation is smaller, the generation is a newer generation. Here, while a generation has been described as a time division or a division according to a configuration change, the generation is not limited thereto, but the generation may be a division combining the time division and the division according to a configuration change.
Hereinafter, description will be presented as a generation being a time division.
Referring back to
The storage unit 10 corresponds to a storage device such as a nonvolatile semiconductor memory element, for example, a flash memory or a ferroelectric random access memory (FRAM) (registered trademark). The storage unit 10 includes a parameter setting history 12 as the teacher data 11. The parameter setting history 12 stores setting information of parameters of a plurality of systems installed to an existing data center. The parameter setting history 12 stores setting information of parameters for each generation.
Here, an example of the parameter setting history 12 will be described with reference to
The parameters are parameters used for the design of the system. Here, the parameters include “IPADDR”, “nameserver”, “LANG”, “UTC”, and “IP”. “IPADDR” represents an IP address of a server. In addition, “nameserver” represents an IP address of a domain name service (DNS). “LANG” represents a use language of a server. “UTC” represents whether or not the coordinate universal time is used. For example, in a case where “UTC” is “TRUE”, it represents that the coordinate universal time is used, and, in a case where “UTC” is “FALSE”, it represents that the coordinate universal time is not used. “IP” represents whether the allocation of an IP address is dynamic or static. For example, in a case where “IP” is “dhcp”, it represents dynamic allocation, and, in a case where “IP” is “static”, it represents static allocation.
In each server, values of such parameters are set. As an example, in the case of the server A1, “10.0.0.1” is set to the parameter “IPADDR”, and “192.168.1.1” is set to the parameter “nameserver”. In addition, “jp” is set to the parameter “LANG”, “FALSE” is set to the parameter “UTC”, and “static” is set to the parameter “IP”. Also for the systems B and C illustrated in
Referring back to
The overall generation rule extracting unit 21 extracts a setting rule of parameters common to a plurality of systems by using the parameter setting histories 12 of all the generations. For example, the overall generation rule extracting unit 21 specifies a common portion in units of systems from the parameter setting histories 12 of a plurality of systems belonging to all the generations by using a clustering technique. Then, the overall generation rule extracting unit 21 extracts a setting rule from a result of the clustering. Here, as the clustering technique, any kind of clustering technique may be used.
The individual generation rule extracting unit 22 extracts a setting rule of parameters common to a plurality of systems by using the parameter setting history 12 of each generation for each generation. For example, the individual generation rule extracting unit 22 specifies a common portion in units of systems from the parameter setting histories 12 of the plurality of systems belonging to each generation for each generation by using a clustering technique. Then, the individual generation rule extracting unit 22 extracts a setting rule from a result of the clustering. Here, the clustering technique used by the individual generation rule extracting unit 22 is assumed to be the same as the clustering technique used by the overall generation rule extracting unit 21.
Here, an example of the rule extraction process will be described with reference to
In addition, within a system or between systems, in a case where the value of a parameter changes in an incremental manner, in a setting rule of this parameter, “*” will be used as a portion to be changed. Here, the individual generation rule extracting unit 22 specifies the value of the parameter “IPADDR” set for each server as a common portion. In other words, in Generation 1, the parameter “IPADDR” is represented as “10.0.*.*”. In addition, the individual generation rule extracting unit 22 specifies the value of the parameter “nameserver” set for each server as a common portion. In other words, in Generation 1, the parameter “nameserver” is represented as “192.168.*.1”. Such common portions are specified as a result of the clustering.
Then, the individual generation rule extracting unit 22 extracts a setting rule of Generation 1 from the result of the clustering. Here, the individual generation rule extracting unit 22 extracts a setting rule of “IF ALL THEN IPADDR=10.0.*.*”. In addition, the individual generation rule extracting unit 22 extracts a setting rule of “IF ALL THEN nameserver=192.168.*.1”. The individual generation rule extracting unit 22 extracts a setting rule of “IF ALL THEN IP=static”. In addition, the individual generation rule extracting unit 22 extracts a setting rule of “IF UTC=FALSE THEN LANG=jp”. The individual generation rule extracting unit 22 extracts a setting rule of “IF UTC=TRUE THEN LANG=en”. In addition, the individual generation rule extracting unit 22 extracts a setting rule of “IF LANG=jp THEN UTC=FALSE”. The individual generation rule extracting unit 22 extracts a setting rule of “IF LANG=en THEN UTC=TRUE”.
Here, the individual generation rule extracting unit 22 specifies the value of the parameter “LANG” and the value of the parameter “UTC” set in the systems A and B as common portions. The individual generation rule extracting unit 22 specifies the value of the parameter “LANG” and the value of the parameter “UTC” set in the systems C as a common portion. In other words, in Generation 3, in the systems A and B, in a case where the parameter “UTC” is “FALSE”, the parameter “LANG” is “jp”. In the system C, in a case where the parameter “UTC” is “FALSE”, the parameter “LANG” is “en”. For the parameter “LANG”, such common portions are specified as a result of the clustering.
Then, the individual generation rule extracting unit 22 extracts a setting rule of Generation 3 from the result of the clustering. Here, the individual generation rule extracting unit 22 extracts the following setting rules for the parameter “LANG”. The individual generation rule extracting unit 22 extracts a setting rule of “IF nameserver=192.168.3.1 & UTC=FALSE THEN LANG=en”. In addition, the individual generation rule extracting unit 22 extracts a setting rule of “IF UTC=TRUE THEN LANG=en”. Furthermore, the individual generation rule extracting unit 22 extracts a setting rule of “IF nameserver!=192.168.3.1 & UTC=FALSE THEN LANG=jp”.
Here, in a case where the parameter setting information of Generation 2 is the same as that of Generation 1, the individual generation rule extracting unit 22 extracts the same setting rule as the setting rule of Generation 1 that is illustrated in
Referring back
Here, the process of specifying different rules that is performed by the different rule specifying unit 23 will be described with reference to
On the first and second stages illustrated in
On the third and fourth stages illustrated in
Referring back to
In Equation (1), a part of “Trange(R)/N×log Trange(R)/N” represents entropy (information amount), and, as the generation is continuous, the information amount increases. In addition, a part of “1/t” represents a weighting factor for a generation, and, as the generation is newer, the information amount increases. In other words, based on Equation (1), as the generation is continuous and is newer, the degree of reliability of a setting rule has a higher value. In other words, the degree of certainty of the setting rule has a larger value.
For example, the reliability calculating unit 24 calculates a degree of reliability based on Equation (1) for the different setting rules represented in
A degree of reliability of “IF nameserver=192.168.3.1 & UTC=FALSE THEN LANG=en” of <2> specified as the different setting rules is calculated as in the following Equation (3) by applying Equation (1). A latest generation of this setting rule is “3”, and an oldest generation thereof is “6”. In addition, N is the number of all the generations and thus, is “6”.
A degree of reliability of “IF nameserver!=192.168.3.1 & UTC=FALSE THEN LANG=jp” of <3> specified as the different setting rule is calculated as in the following Equation (4) by applying Equation (1). A latest generation of this setting rule is “3”, and an oldest generation thereof is “6”. In addition, N is the number of all the generations and thus, is “6”.
According to this, the degree of reliability of the setting rule of <1> is higher than the degrees of reliability of the setting rules of <2> and <3>. In other words, it can be understood that the degrees of reliability of the setting rules of Generations 1 and 2 are higher than those of the setting rules of Generations 3 to 6.
The reliability output unit 25 outputs the degrees of reliability of the different setting rules that are calculated by the reliability calculating unit 24. As an example, the reliability output unit 25 outputs the degrees of reliability of the different setting rules in a table form together with the setting rules and the generations. As another example, the reliability output unit 25 outputs the degrees of reliability of the different setting rules in a graph form together with the generations.
Here, an example of the output of the degrees of reliability that is performed by the reliability output unit 25 will be described with reference to
As illustrated in
As illustrated in
Referring back to
For example, the setting rule “IF UTC=FALSE THEN LANG=jp” illustrated in
Next, the sequence of the setting support process will be described with reference to
First, the overall generation rule extracting unit 21 determines whether or not a setting support request is present in Step S11. In a case where the setting support request is determined not to be present (No in Step S11), the overall generation rule extracting unit 21 repeats the determination process until a setting support request is present. On the other hand, in a case where a setting support request is determined to be present (Yes in Step S11), the overall generation rule extracting unit 21 extracts setting rules (overall rules) of parameters common to the plurality of systems by using all the data (parameter setting histories 12) of all the generations in Step S12. Here, the setting rules are extracted using the clustering technique.
Then, the individual generation rule extracting unit 22 extracts setting rules for each generation of parameters common to the plurality of systems by using the data (the parameter setting history 12) of each generation in Step S13. In addition, the setting rules are extracted using the same technique as the clustering technique used by the overall generation rule extracting unit 21.
Subsequently, the different rule specifying unit 23 compares the overall rules with setting rules extracted for each generation in Step S14. Then, the different rule specifying unit 23 specifies different setting rules relating to the setting of common parameters in Step S15.
Subsequently, the reliability calculating unit 24 calculates the degrees of reliability of the different setting rules based on a rule relating to a generation having the different setting rules in Step S16. For example, the reliability calculating unit 24 calculates the degrees of reliability of the different setting rules based on Equation (1).
Then, the reliability output unit 25 outputs the degrees of reliability of the different setting rules in Step S17. For example, the reliability output unit 25 outputs the degrees of reliability of the different setting rules in a table form to a monitor of the setting support device 1 together with the setting rule and the generation.
Subsequently, the optimization unit 26 determines whether or not any one setting rule is selected from among the different setting rules output by the reliability output unit 25 in Step S18. In a case where any one setting rule is determined not to have been selected (No in Step S18), the setting support process ends.
On the other hand, in a case where any one setting rule is determined to have been selected (Yes in Step S18), when the degree of reliability of the selected setting rule is higher than the degrees of reliability of the other setting rules, the optimization unit 26 reflects the selected setting rule on the teacher data 11 in Step S19. For example, in a case where the degree of reliability of the selected setting rule is higher than the degrees of reliability of the other setting rules, the optimization unit 26 applies the selected setting rule to generations different from the generations having the selected setting rule. Then, the optimization unit 26 rewrites the parameter setting history 12 of the generation to which the selected setting rule has been applied. Then, the setting support process ends.
According to the above-described embodiment, the setting support device 1 generates settings of parameters common to a plurality of systems and conditions used for the settings as a first rule based on the parameter setting information relating to the settings of parameters performed for the plurality of systems in the past. Then, the setting support device 1 generates settings of parameters common to the plurality of systems and conditions used for the settings as a second rule for each generation based on the parameter setting information of each generation relating to the settings of parameters performed in the past for the plurality of systems. Then, the setting support device 1 compares the first rule with the second rule of each generation in relation with the setting of common parameters, specifies different rules, and calculates indexes representing the degrees of certainty of the specified different rules. According to such a configuration, in a case where there is a difference in the setting rules of common parameters, the setting support device 1 can present the degree of certainty of the different setting rules to the designer and allow the designer to acquire the degree of certainty of the different setting rules.
In addition, according to the embodiment described above, the setting support device 1, based on a rule relating to generations having a different rule therebetween, calculates indexes representing the degree of certainty of the different rules. According to such a configuration, the setting support device 1 calculates an index representing the degree of certainty of a different rule in consideration of the generation, thereby calculating an index having high accuracy.
In addition, according to the embodiment described above, the setting support device 1 calculates an index representing the degree of certainty to be higher as a generation having the different rule is newer and is continuous. According to such a configuration, the setting support device 1 calculates the index representing the degree of certainty of the different rule in consideration of the generation, thereby calculating an index having high accuracy.
In addition, the setting support device 1 can be realized by implementing the functions of the different rule specifying unit 23, the reliability calculating unit 24, and the like in an information processing apparatus such as an existing personal computer or a workstation.
In the embodiment described above, the reliability calculating unit 24 calculates the degree of reliability of a different setting rule specified by the different rule specifying unit 23 based on the rule relating to the generation having the different setting rule. At this time, an example of the rule relating to the generation has been described as a rule that as a generation having a different setting rule is newer and is continuous, the reliability increases. However, the rule relating to the generation is not limited thereto, but in a case where a different setting rule is included only in a latest generation, the degree of reliability may be configured to decrease. The reason for this is that, in the case where the setting rule is included only in the latest generation, the result is still insufficient. For example, the reliability calculating unit 24 may be configured to decrease the degree of reliability calculated using Equation (1) by a predetermined adjustment value.
In addition, each constituent element of the device illustrated in each figure does not necessarily need to be physically configured as illustrated in the figure. In other words, a specific embodiment of division/integration of the device is not limited to that illustrated in the figure, but the whole or a part thereof may be configured to be integrated/divided functionally or physically in an arbitrary unit based on various loads, use statuses, and the like. For example, the overall generation rule extracting unit 21 and the individual generation rule extracting unit 22 may be integrated as one unit. On the other hand, the overall generation rule extracting unit 21 may be divided into a storing unit that receives the teacher data 11 from an existing data center and stores the teacher data 11 in the storage unit 10 and an extraction unit that extracts the overall generation rule. In addition, the storage unit 10 may be stored in an external device of the setting support device 1, or an external device storing the storage unit 10 may be configured to be connected to the setting support device 1 through a network.
In addition, various processes described in the embodiment described above may be realized by executing a program prepared in advance by using a computer such as a personal computer or a workstation. Thus, hereinafter, an example of a computer that executes a setting support program realizing the same function as that of the setting support device 1 illustrated in
As illustrated in
The drive device 213, for example, is a device for a removable disk 211. The HDD 205 stores a setting support program 205a and setting support related information 205b.
The CPU 203 reads the setting support program 205a, expands the setting support program in the memory 201, and executes the setting support program as processes. The processes correspond to the functional units of the setting support device 1 respectively. The setting support related information 205b corresponds to the teacher data 11. For example, the removable disk 211 stores various kinds of information such as the teacher data 11.
In addition, the setting support program 205a may be configured not to be necessarily stored in the HDD 205 from the start. For example, the program is stored in a “portable physical medium” such as a flexible disk (FD), a CD-ROM, a DVD disc, a magneto-optical disk, or an IC card inserted into the computer 200. Then, the computer 200 may be configured to read the setting support program 205a therefrom and executes the setting support program 205a.
The degree of certainty of a setting rule of parameters can be acquired.
All examples and conditional language recited herein are intended for pedagogical purposes of aiding the reader in understanding the invention and the concepts contributed by the inventor to further the art, and are not to be construed as limitations 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 embodiment of the present invention has been described in detail, it should be understood that the various changes, substitutions, and alterations could be made hereto without departing from the spirit and scope of the invention.
Number | Date | Country | Kind |
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2014-044420 | Mar 2014 | JP | national |