Abstract:
A method and system for migrating source data from one or more databases to a destination database, wherein the destination database is selected based on power consumption of the destination database. A data migration server determines which destination database should be selected by selecting a number of candidates and comparing the power consumed, the available space and the maximum monthly power consumption limit. A user intervention policy is created to evaluate which data should be moved to a destination database. A “payback period” is calculated to determine the amount of time that will elapse before savings are realized.

Description:
BACKGROUND OF THE INVENTION 
       [0001]    The present invention relates generally to energy efficiency across the data center, and more particularly to the migration of data based on power consumption. 
         [0002]    Energy efficiency across the entire data center is becoming a top concern for corporations around the world. This problem requires consideration of all energy efficiency components of the data center, from component levels through server and system levels, and concluding with the complete data center. At the system level, storage devices are an extremely important part of the equation, which needs to be analyzed. Disk systems can require substantial amounts of power to operate and cool, and in many cases, can require more power than the server itself. 
         [0003]    Data migration is the process of transferring data between storage types, formats or computer systems. Data migration is usually performed programmatically to achieve an automated migration, freeing up human resources from tedious tasks. It is required when organizations or individuals change computer systems or upgrade to new systems, or when systems merge (such as when the organizations that use them undergo a merger/takeover). 
         [0004]    To achieve an effective data migration procedure, data on the old system is mapped to the new system providing a design for data extraction and data loading. The design relates old data formats to the new system&#39;s formats and requirements. Programmatic data migration may involve many phases but it minimally includes data extraction where data is read from the old system and data loading where data is written to the new system. 
         [0005]    After loading into the new system, results are subjected to data verification to determine that data was accurately translated, is complete, and supports processes in the new system. During verification, there may be a need for a parallel run of both systems to identify areas of disparity and forestall erroneous data loss. Automated and manual data cleansing is commonly performed in migration to improve data quality, eliminate redundant or obsolete information, and match the requirements of the new system. Data migration phases (design, extraction, cleansing, load, verification) for applications of moderate to high complexity are commonly repeated several times before the new system is activated. 
         [0006]    Traditional data migration involves business decisions from application owners and IT administrators to predefine a destination database that usually resides physically on another disk for each given source database. Very often, such migration is a one to one relationship where a source database is mapped to a predefined destination database This migration process is done at a database level that involves no concerns on how data is being used by applications and how it relates to power consumption. 
         [0007]    Reference is made to  FIG. 1 , which illustrates a traditional database migration process  10 . Database A at  12  and Database B at  14  are source databases containing data that can be migrated to another storage database. Migration routines, cleansing routines and indexing strategies are created by application owners. IT administrators then determine the physical location of the destination database. The source data from Database A is moved to Staging Cleansing scripts are applied to the data on Staging Database A and to the data on Staging Database B. An index is then created for the data on Staging Database A and for the data on Staging Database B. Each set of data from Staging Database A and Staging Database B is migrated to a destination database  20 , which is Database  1  in the Figure. The data from Staging Database A and Staging Database B must be merged with each other and with any existing data on Database  1 . In these prior art methods, the destination database is predefined for each source database, not taking into account the amount of power that may used in the destination database. 
         [0008]    It is a primary object of the invention to provide a method and system for migrating data based on power conservation. It is another object of the invention to provide a method and system for selecting the destination database based on energy efficiency. It is a further object of the invention to provide a method and system for determining the length of time for realizing cost savings after migration of data has been performed. 
       SUMMARY OF THE INVENTION 
       [0009]    These and other objects and advantages are accomplished by a method for migrating source data from one or more databases to a destination database, wherein the destination database is selected based on power consumption of the destination database. Specifically, the method of the present invention determines which destination database should be selected by selecting a number of candidates and comparing the power consumed, the available space and the maximum monthly power consumption limit. In one aspect of the method of the invention, a user intervention policy is created to evaluate which data should be moved to a destination database that is more energy efficient than the source database. In another aspect of the method of the invention, a “payback period” is calculated to determine the amount of time that will elapse before savings are realized. 
         [0010]    In accordance with another embodiment, a system is provided for migrating source data from one or more databases to a destination database, wherein the destination database is selected based on power consumption of the destination database. Specifically, the system of the present invention determines which destination database should be selected by selecting a number of candidates and comparing the power consumed, the available space and the maximum monthly power consumption limit. In one aspect of the system of the invention, the system includes a data migration server to control the decision process and manage the data migration based on energy efficiency characteristics. In another aspect of the system of the invention, the data migration server handles the mapping of the data. In yet another aspect of the invention, the data migration server maintains the user intervention policy table, which is critical to the destination database decision. 
     
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
         [0011]    The present invention will be more fully understood and appreciated by reading the following Detailed Description in conjunction with the accompanying drawings, in which: 
           [0012]      FIG. 1  is a schematic view of a prior art data migration system; 
           [0013]      FIG. 2  is a schematic view of the data migration system of the present invention; and 
           [0014]      FIG. 3  is a flow chart showing the logic for the data migration system of the present invention. 
       
    
    
     DETAILED DESCRIPTION 
       [0015]    As will be appreciated, the present invention provides an effective method for reducing energy consumption of certain types of computer systems. The data migration process is enhanced by using power consumption as a guiding factor in determining how data in the source database can be assigned real time to a destination database to maintain a desirable power consumption level. Reference is made to  FIG. 2 , which illustrates the method of the present invention. Database A at  20  and Database B at  22  are source databases containing data that may be moved to an alternate storage location. It should be mentioned that the method and system of the present invention may be used for i) data that must be moved and ii) data that may be moved or may stay in its current location. Migration is ultimately an economic decision that is based on the fixed cost of the migration versus the variable costs for an organization. 
         [0016]    Data from Database A is sent to a Staging Server  24  and data from Database B is sent to a Staging Server  26  to test and check the data. The data migration server  28  looks at a number of databases and determines the best destination database to send the data from Database A and Database B.  FIG. 2  shows three potential candidates for destination databases, Database  1  at  30 , Database  2  at  32  and Database  3  at  34 . 
         [0017]    Data migration server  28  also handles the mapping of data from staging server  26  to the destination database. Scripts can be written to handle the migration process or existing database migration tools may be used to assist administrators in the migration process. Existing tools include a graphical user interface (GUI), which can interface with the data migration server  28 . 
         [0018]    In order to determine the best possible candidate for the destination database, the data migration server monitors the power consumption level of each destination database candidate. The monitoring may be accomplished by using an internal or external power meter device and other devices known for measuring power usage. In addition to monitoring power consumption, the data migration server executes migration policies and performs a predictive data migration decision-making process. Migration policies can include, but are not limited to, control of reference data, schema configurations, and merges of data. 
         [0019]    Examples of types of databases useful herein as a destination database are set forth in Table 1 below. The parameters set forth in the Table are accessed in order to determine the best possible candidate for the destination database. The type of source data, the frequency of use of the source data, and the amount of source data to be moved are factors that are also taken into consideration when determining the best destination candidate for migration of data. For example, if the source data is not frequently accessed, the best candidate for the destination database may be Database  2  or  3 , which use more power for each operation than Database  1  because the data will not be accessed on a regular basis. In comparison, if source data is frequently used, it may be more advantageous to move it to a database such as Database  1 , which uses less power per operation. 
         [0000]    
       
         
               
             
               
               
               
               
               
               
               
               
             
               
               
               
               
               
               
               
               
             
           
               
                 TABLE 1 
               
             
             
               
                   
               
               
                 Destination Databases 
               
             
          
           
               
                   
                   
                   
                   
                   
                   
                   
                 Max. Power 
               
               
                   
                   
                   
                   
                   
                   
                   
                 consumption 
               
               
                   
                   
                   
                   
                   
                 Power 
                 Power 
                 limit (e.g. 
               
               
                 Data 
                   
                 Storage 
                 Vendor/ 
                 Space 
                 (watt)/ 
                 used so far 
                 kilowatts per 
               
               
                 base 
                 Location 
                 Type 
                 Model 
                 Available 
                 operation 
                 (kilowatts) 
                 month) 
               
               
                   
               
             
          
           
               
                 1 
                 Denver 
                 NAS 
                 Net 
                 1,300 
                 425 
                 4000 
                 10000 
               
               
                   
                   
                   
                 Apps 
               
               
                 2 
                 San Jose 
                 DASD 
                 XYZ 
                 4,600 
                 600 
                 7000 
                 8000 
               
               
                 3 
                 Denver 
                 Tape 
                 ABC 
                 3,900 
                 760 
                 3500 
                 6000 
               
               
                   
               
             
          
         
       
     
         [0020]    Reference is made to  FIG. 3 , which shows the logic  40  used by the data migration server to determine the best candidate for the destination database. The first step involves polling for potential candidates for destination databases and/or receiving the status of potential candidates for destination databases as shown in step  42 . Data migration server  28  maps the parameters of each of the candidates as set forth in Table 1 above. The data migration server  28  executes the migration task in accordance with the migration policy. For each migration task, source data is sent from the source database to the data migration server, as shown in steps  44  and  46 . The data migration server  28  calculates the number of operations based on the transaction type and size of the source data. The data migration server  28  then compares the size of the source data and the number of operations of the write requests with potential destinations specified in the Destination Database Table. The data migration server  28  then determines which destination database is optimal for the source data and selects the destination database as shown in step  48 . The data migration server writes data to the destination database in step  50  and records and maintains the data as shown in step  52 . The data migration server continues to survey the destination databases after data has been migrated to a destination database to determine if energy efficiency characteristics have changed as set forth in step  54 . If thrashing occurs, the data migration server must determine if the data should be relocated to a different destination database by repeating steps  48  through  54 . 
         [0021]    As mentioned above, the data migration server not only evaluates candidates for the destination database, but also must manage and assess the source data to determine when and where to move the data. Examples of source databases and parameters to be evaluated are set forth in Table 2, a User Intervention Policy Table. The source databases are reviewed by the data migration server. 
         [0000]    
       
         
               
             
               
               
               
               
               
             
           
               
                 TABLE 2 
               
             
             
               
                   
               
               
                 User Intervention Policy 
               
             
          
           
               
                   
                 Archive 
                 Criticality of 
                 Application 
                   
               
               
                 Database 
                 Status 
                 Data 
                 Priority 
                 Time 
               
               
                   
               
               
                 Database A 
                 New 
                 High 
                 Payroll = High 
                 Weekly 
               
               
                 Database B 
                 New 
                 Low 
                 HR = Medium 
                 Daily 
               
               
                 Database C 
                 New 
                 High 
                 Finance = Low 
                 Weekly 
               
               
                 Database D 
                 Archived 
                 Medium 
                 HR = Medium 
                 Monthly 
               
               
                   
               
             
          
         
       
     
         [0022]    In addition to the parameters set forth in Table 2, others may include the age of the data, the seasonality of the data and peak issues related to the data. Moreover, the values in Table 2 above are weighted to assist in further assessment of the data. Table 3 provides examples of weighted numbers to be applied to the parameters in Table 2. 
         [0000]    
       
         
               
             
               
               
               
             
               
               
               
             
           
               
                 TABLE 3 
               
             
             
               
                   
               
               
                 User Intervention Policy Weighting Table 
               
             
          
           
               
                   
                 Policy 
                 Weight (must add to 1) 
               
               
                   
                   
               
             
          
           
               
                   
                 Archive Status 
                 .20 
               
               
                   
                 Criticality of Data 
                 .40 
               
               
                   
                 Application 
                 .25 
               
               
                   
                 Time 
                 .15 
               
               
                   
                   
               
             
          
         
       
     
         [0023]    The policies from the User Intervention Policy Table along with the weightings from the User Intervention Policy Weighting Table are then applied to the destination. The destination is updated as appropriate. For example, data that is less critical, older, and used less often by an application that is deemed of lower importance may be moved to a destination that is not as power efficient as a newer and more critical database used every day since a relatively idle storage device may use somewhat less power than a very busy one. Once the data migration server has selected the most efficient destination database according to the Destination Database Table for any given transaction, the power consumption can be predicted to reflect how much power has been used up to this point. 
         [0024]    In circumstances where the data does not have to be moved, a determination can be made regarding potential cost savings. A calculation is provided to compute the “payback period,” which is the time period that it will take to realize savings. The time period may be measured in minutes, hours, days, months, or years. The formula is as follows: 
         [0000]      ( T   0   +E   0 ) x=M   i   +E   i ) x.    
         [0025]    whereby
       x=the time period measured in months;   T 0 =estimated total cost per month of ownership of the source database;   E 0 =estimated cost per month of the energy consumption of the source database;   M i =estimated cost of migrating the source data to the destination database;   T i =estimated cost per month of ownership of the destination database; and   E i =estimated cost per month of the energy consumption of the destination database.       
 
         [0032]    The following example illustrates the use of the formula. 
       EXAMPLE 
       [0033]    The current system&#39;s total cost of ownership of the source database is $10.00 per month. The energy consumption for the current system is $20.00 per month. The total cost of ownership of the destination database is $20.00 per month and the energy consumption for the destination database is $5.00 per month. The migration cost to move the data is $50.00. The amount of time that must be expended before savings can be realized is calculated as follows: 
         [0000]      (10+20) x =50+(20+5) x    
         [0000]      30 x= 50+25 x    
         [0000]      5x=50 
         [0000]      x=10 
         [0034]    Therefore, the “payback period” or the break-even point for migration in this example is ten months. Total costs are the same for ten months. Thereafter, savings will be realized. 
         [0035]    Another embodiment of the invention is directed to a medium that is readable by a computer or other device, which includes an executable instruction for initializing data migration. In an aspect, the executable instruction involves the process steps  42 - 54  shown in  FIG. 3 , as described in detail above. In various aspects, the executable instruction may be in the form of a database utility application, a script-type program, a compiled program, or other suitable forms known in the art. 
         [0036]    The term computer-readable medium as used herein refers to any medium that participates in providing an instruction to a computer processor for execution. Such a medium may take many forms, including but not limited to non-volatile media, volatile media, and transmission media. Non-volatile media include, for example, optical or magnetic disks. Volatile media include dynamic memory. Transmission media include coaxial cables, copper wire and fiber optics. Transmission media can also take the form of acoustic, optical, or electromagnetic waves, such as those generated during radio frequency (RF) and infrared (IR) data communications. Common forms of computer-readable media include, for example, a hard disc, any magnetic medium, a CD-ROM, CDRW, DVD, any other optical medium, optical mark sheets, and any other physical medium with patterns of holes or other optically recognizable indicia, a RAM, a PROM, an EPROM, a FLASH-EPROM, any other memory chip or cartridge, a carrier wave, or any other medium from which a computer can read. 
         [0037]    The invention has been described with reference to exemplary embodiments, it will be understood by those skilled in the art that various changes may be made and equivalents may be substituted for elements thereof without departing from the scope of the invention. In addition, many modifications may be made to adapt a particular situation or material to the teachings of the invention without departing from the essential scope thereof. Therefore, it is intended that the invention not be limited to the particular embodiment disclosed as the best mode contemplated for carrying out this invention, but that the invention will include all embodiments falling within the scope of the appended embodiments.