AUTONOMIC WORKLOAD PLANNING

• US 20090313631A1
• Filed: 06/11/2008
• Published: 12/17/2009
• Est. Priority Date: 06/11/2008
• Status: Abandoned Application

• Current Assignee: International Business Machines Corporation
• Original Assignee: International Business Machines Corporation
• Inventors: De Marzo, Fabio, Di Cocco, Antonio, Di Giulio, Domenico, Mossotto, Franco
• Application Number:
  US12/136,813
• Publication Number:
  US 20090313631A1
• Time in Patent Office: Days
• US Class Current: 718/103
• CPC Class Codes: G06F 9/5038 considering the execution order of a plurality of tasks, e.g. taking priority or time dependency constraints into consideration scheduling strategies G06F9/4881 and subgroups

Abstract

A method of automatically optimizing workload scheduling. Target values for workload characteristics and constraint specifications are received. Generation of a first execution plan is initiated. Initial constraint values conforming to the constraint specifications are selected. Each constraint value constrains tasks included in the workload. The first execution plan is executed, thereby determining measurements of workload characteristics. Contributions indicating differences between workload characteristic measurements and target values are determined and stored. Generation of a next execution plan is initiated. Modified constraint values conforming to the constraint specifications are selected. Changes in the workload characteristics based on the modified constraint values are evaluated. An optimal or acceptable sub-optimal solution in a space of solutions defined by the constraint specifications is determined, resulting in new values for the constraints. After replacing the initial values with the new values, the next execution plan is generated and executed.

Claims

1. A computer-implemented method of automatically optimizing workload scheduling, comprising:

receiving, by a computing system, a plurality of target values for a plurality of workload characteristics, wherein said target values are user-defined and are characteristics of a workload in an information technology infrastructure;

receiving, by said computing system, a plurality of constraint specifications, wherein each constraint specification is user-defined and includes a range of values or a set of values;

initiating, by said computing system, subsequent to said receiving said plurality of constraint specifications and subsequent to said receiving said plurality of target values for said plurality of workload characteristics, a generation of a first execution plan;

selecting, by said computing system and subsequent to said initiating said generation of said first execution plan, a plurality of initial values for a plurality of constraints, wherein each constraint of said plurality of constraints is specified by a constraint specification of said plurality of constraint specifications, and wherein each constraint of said plurality of constraints constrains a plurality of tasks included in said workload;

generating, by said computing system and subsequent to said selecting said plurality of initial values, said first execution plan;

executing, by said computing system and subsequent to said generating said first execution plan, said first execution plan, wherein said executing said first execution plan includes determining a plurality of measurements of said plurality of workload characteristics;

determining, by said computing system and subsequent to said executing said first execution plan, a plurality of contributions, wherein said plurality of contributions indicates a plurality of differences between said plurality of measurements of said plurality of workload characteristics and said plurality of target values;

storing, by said computing system, in a computer data storage unit and subsequent to said determining said plurality of contributions, said plurality of contributions;

initiating, by said computing system and subsequent to said determining said plurality of contributions, a generation of a next execution plan;

modifying, by said computing system and subsequent to said initiating said generation of said next execution plan, said plurality of constraints, wherein a result of said modifying is a plurality of modified values of said plurality of constraints, and wherein each modified value is specified by a constraint specification of said plurality of constraint specifications;

evaluating, by said computing system and subsequent to said modifying said plurality of constraints, a plurality of changes of said plurality of workload characteristics, wherein said plurality of changes is based on said plurality of modified values of said plurality of constraints for each time period of a plurality of predefined time periods in a duration of said next execution plan;

determining, by said computing system and subsequent to said evaluating said plurality of changes, a solution in a space of solutions defined by said plurality of constraint specifications, wherein said solution is selected from the group consisting of;

an optimal solution and an acceptable sub-optimal solution, wherein a result of said determining said solution is a plurality of new values for said plurality of constraints;

storing, by said computing system, in a computer data storage medium and subsequent to said determining said solution, said plurality of new values for said plurality of constraints;

replacing, by said computing system and subsequent to said determining said solution, said plurality of initial values with said plurality of new values;

generating, by said computing system and subsequent to said replacing said plurality of initial values, said next execution plan, wherein said next execution plan includes said plurality of new values as said plurality of constraints; and

executing, by said computing system and subsequent to said generating said next execution plan, said next execution plan.

2. The method of claim 1, further comprising iteratively repeating, in a loop, said determining said plurality of contributions, said storing said plurality of contributions, said initiating said generation of said next execution plan, said modifying said plurality of constraints, said evaluating said plurality of changes of said plurality of workload characteristics, said determining said optimal solution or said acceptable sub-optimal solution, said storing said plurality of new values, said replacing said plurality of initial values with said plurality of new values, said generating said next execution plan, and said executing said next execution plan until said solution satisfies predefined criteria for being said optimal solution or said acceptable sub-optimal solution.

3. The method of claim 2, wherein said determining said plurality of contributions is performed prior to said iteratively repeating, wherein said determining said plurality of contributions includes determining multiple sets of contributions included in said plurality of contributions, and wherein each set of contributions is based on a corresponding time period of a plurality of predefined time periods in a duration of said first execution plan.

4. The method of claim 2, wherein said determining said plurality of contributions is performed in a current iteration of said loop, wherein said determining said plurality of contributions includes determining multiple sets of contributions included in said plurality of contributions, wherein each set of contributions is based on a corresponding time period of a plurality of predefined time periods in a duration of a prior execution plan, and wherein said prior execution plan was executed prior to said current iteration of said loop.

5. The method of claim 1, wherein said generating said next execution plan includes generating an optimized execution plan at scheduling time and not during an execution of said plurality of tasks.

6. The method of claim 1, wherein each workload characteristic of said plurality of workload characteristics is selected from the group consisting of:

an average number of tasks executed per unit of time,

central processing unit usage,

memory consumption,

input/output (I/O) read rate, and

I/O write rate.

7. The method of claim 1, wherein each constraint specification of said plurality of constraint specifications is selected from the group consisting of:

a range of dates for a date on which a task of said plurality of tasks is expected to run,

a range of times for a time at which said task is expected to run,

a range of frequency rates for a frequency rate for repeating an execution of said task,

a maximum value of a priority of said task, and

a minimum value of said priority of said task.

8. A computing system comprising a processor coupled to a computer-readable memory unit, said memory unit comprising a software application, said software application comprising instructions that when executed by said processor implement the method of claim 1.

9. A computer program product, comprising a computer-usable medium having a computer-readable program code embodied therein, said computer-readable program code comprising an algorithm adapted to implement the method of claim 1.