Client / server application task allocation based upon client resources

• US 20060184626A1
• Filed: 02/11/2005
• Published: 08/17/2006
• Est. Priority Date: 02/11/2005
• Status: Active Grant

• Current Assignee: Microsoft Technology Licensing LLC (Microsoft Corporation)
• Original Assignee: International Business Machines Corporation
• Inventors: Patel, Paritosh D., Cross, Charles W. Jr., Agapi, Ciprian, Metianu, Nicolae D.
• Granted Patent: US 7,548,977 B2
• Time in Patent Office: Days
• US Class Current: 709/205
• CPC Class Codes: G06F 9/505 considering the load
• CPC Class Codes: G06F 9/5055 considering software capabilities, i.e. software resources associated or available to the machine

Abstract

A software method for allocating application tasks between a client and a server can include the step of detecting client-based computing resources for executing at least one application task. At least one indicator of the detected client-based computing resources can be conveyed to a remotely located application server, the application server can determine whether to allocate at least one application task to the client or to a server component based upon at least one indicator.

Claims

1. A software method for allocating application tasks between a client and a server comprising the steps of:

detecting client-based computing resources capable of executing at least one application task;

conveying at least one indicator of the detected client-based computing resources to a remotely located application server; and

the application server determining whether to allocate at least one application task to a client or to a server component based upon the at least one indicator.

2. The method of claim 1, wherein the detecting step further comprises dynamically detecting currently available client-based resources, wherein the method further comprises the step of:

repeating the dynamically detecting and conveying steps as the application server operates so that the determining step is based upon intermittently updated information.

3. The method of claim 1, wherein the determining step further comprises the step of:

comparing the client-based computing resources indicated by the at least one indicator against at least one previously determined resource threshold associated with the application task; and

when the client-based computing resources favorably compare to the previously determined resource threshold, allocating the at least one application task to the client, otherwise allocating the at least one application task to the server component.

4. The method of claim 1, further comprising the steps of:

establishing a lower resource limit for application server tasks;

allocating all application server tasks that are associated with a resource requirement that is less than the lower resource limit to the client.

5. The method of claim 1, further comprising the steps of:

establishing an upper resource limit for application server tasks;

allocating all application server tasks that are associated with a resource requirement that is greater than the upper resource limit to the server component.

6. The method of claim 2, further comprising the steps of:

establishing a lower resource limit for application server tasks;

allocating all application server tasks that are associated with a resource requirement that is less than the lower resource limit to the client;

establishing an upper resource limit for application server tasks;

allocating all application server tasks that are associated with a resource requirement that is greater than the upper resource limit to the server component; and

performing the determining step to selectively allocate all application server tasks with a resource requirement between the lower resource limit and the upper resource limit.

7. The method of claim 1, wherein the at least one application server task comprises a speech recognition task, and wherein the determining step is based at least in part upon a size of grammar used in the speech recognition task.

8. The method of claim 7, further comprising the step of:

establishing a lower grammar size, wherein all speech recognition tasks using a grammar having an associated size below said lower grammar size are allocated to the client.

9. The method of claim 7, further comprising the step of:

establishing an upper grammar size, wherein all speech recognition tasks using a grammar having an associated size above said upper grammar size are allocated to the server component.

10. The method of claim 1, wherein the at least one application server task comprises a text-to-speech conversion task, and wherein the determining step is based at least in part upon a complexity of the text-to-speech conversion task.

11. The method of claim 10, wherein the complexity is determined based upon at least one of a length of text to be text-to-speech converted and a quality of sound required for resulting text-converted speech.

12. The method of claim 10, wherein the complexity is determined based upon a number of languages required to generate the text-to-speech result.

13. An application serving system comprising:

a server engine located within an application server configured to selectively execute at least one application task for the application server;

a client engine located within a client remotely located from said application server configured to selectively execute said at least one application task for the application server;

a load analyzer configured to detect computing resources of said client and to convey an indicator of these detected computing resource to a load distributor; and

a load distributor configured to selectively allocate application tasks between the server engine and the client engine based upon the indicators received from the load analyzer.

14. The system of claim 13, wherein the load analyzer is configured to dynamically determine currently available resources for said client, and where the load distributor allocates application tasks to the client based upon current resource availability.

15. The system of claim 13, wherein the load analyzer is located within the client, and wherein the client is a handheld computing device.

16. The system of claim 13, wherein the computing resources detected by the load analyzer include at least two of a memory capacity of the client, a CPU capability of the client, and a communication throughput level for exchanging data with the client.

17. The system of claim 14, said load distributor further comprising:

a lower resource limit, wherein application tasks having resource requirements below the lower resource limit are always allocated to the client engine; and

an upper resource limit where tasks, wherein application tasks having resource requirements above the upper resource limit are always allocated to the server engine.

18. The system of claim 13, wherein the application task comprises at least one speech recognition task, and wherein the load distributor selectively allocates the speech recognition task based at least in part upon a size of grammar used in the speech recognition task.

19. The system of claim 13, wherein the application task comprises at least one text-to-speech conversion task and wherein the load distributor selectively allocates the text-to-speech conversion task based at least in part upon a complexity of the text-to-speech conversion task, wherein complexity is based upon at least one factor selected from the group consisting of a text length to be converted, a sound quality of resulting speech, and a number of languages needed for the text-to-speech conversion task.

20. A machine-readable storage having stored thereon, a computer program having a plurality of code sections, said code sections executable by a machine for causing the machine to perform the steps of:

detecting client-based computing resources capable of executing at least one application task;

conveying at least one indicator of the detected client-based computing resources to a remotely located application server; and

the application server determining whether to allocate at least one application task to a client or to a server component based upon the at least one indicator.