System and method for predictive idle-time task initiation

• US 20060190938A1
• Filed: 02/22/2005
• Published: 08/24/2006
• Est. Priority Date: 02/22/2005
• Status: Abandoned Application

• Current Assignee: Lenovo Singapore Pte Limited (Lenovo Group Ltd.)
• Original Assignee: Lenovo Singapore Pte Limited (Lenovo Group Ltd.)
• Inventors: Cheston, Richard Wayne, Pickover, Clifford Alan, Locker, Howard Jeffrey, Capek, Peter George
• Application Number:
  US11/061,481
• Publication Number:
  US 20060190938A1
• Time in Patent Office: Days
• US Class Current: 717/161
• CPC Class Codes: G06F 11/1461 Backup scheduling policy
• CPC Class Codes: G06F 9/46 Multiprogramming arrangements

Abstract

A system automatically determines probable idle times for a computing system and performs maintenance tasks, such as virus scanning, during these times. A prediction of probable idle times is based on an assessment of a user'"'"'s past use or by an aggregate of information from several users if a company wishes to determine optimal times for running such tasks or pushing software patches to employees. A policy table set by the user or a company determines the priority of maintenance tasks to be run during the predicted idle time.

Claims

1. A maintenance system comprising:

maintenance task means for maintaining and improving operation of a computing system; and

automatic means for determining scheduling of the implementation of individual tasks of said maintenance means based on a history of computing resource use and a priority of said individual tasks.

2. The system of claim 1, wherein individual tasks are client management tasks.

3. The system of claim 2, wherein the client management tasks of the individual tasks includes one or more of the disk defragmentation, anti-virus scan, anti-spam scan, anti-adware scan, database compaction, downloading/applying corrective patches, encryption, application upgrades, and indexing.

4. The system of claim 1, wherein history includes a user'"'"'s history of letting his or her machine be relatively idle.

5. The system of claim 4, wherein idle time is measured by one or more of a screensaver use and duration, central processing unit (CPU) level below a threshold for a given time duration, and input/output (I/O) below a threshold for a given time duration.

6. The system of claim 4, wherein idle time has an associated confidence.

7. The system of claim 1, wherein said automatic means determines scheduling based on a probability of idle time above a threshold for a given time duration.

8. The system of claim 1, wherein a history of computing resource use is determined for one or more of a history of a user'"'"'s use, a history of a group'"'"'s use, a history of a company'"'"'s use.

9. The system of claim 1, wherein the maintenance task means is installed on a client in a client/server system.

10. The system of claim 9, wherein a server in the client/server system implements the automatic means for determining scheduling.

11. The system of claim 9, wherein said automatic means for scheduling is implemented as a service by a third party.

12. The system of claim 1, wherein said history includes a record of any of the times a user has stopped a maintenance program and the times a user has competed with a maintenance program by trying to perform other tasks at the same time.

13. The system of claim 1, wherein a history of computing resource use is presented graphically, along with maintenance tasks use.

14. The system of claim 1, wherein an autocorrelation function is applied to history of computing resource use so that periodicities in use can be determined, in order to help select when maintenance tasks will run.

15. The system of claim 1, wherein a prediction of probable idle times is based on an assessment of a user'"'"'s past use or by an aggregate of information from several users if a company wishes to determine optimal times for running such tasks or pushing software patches to employees.

16. The system of claim 1, wherein the automatic means is responsive to a user input indicating when the user will be absent for a period of time.

17. A method of automatic maintenance of a computing system comprising the steps of:

measuring system busy and idle states;

processing a database to determine idle and off times;

establishing priorities for running maintenance tasks; and

running maintenance tasks during idle times according to established priorities.

18. The method of claim 17, wherein the maintenance tasks are run on a client of a client/server system.

19. The method of claim 18, wherein the database is processed on a server of the client/server system.

20. The method of claim 18, wherein the database is processed by a third party service provider.