Dynamic resource scheduling to optimize location of meeting participants

• US 7,027,995 B2
• Filed: 06/01/2001
• Issued: 04/11/2006
• Est. Priority Date: 06/01/2001
• Status: Expired due to Fees

• Current Assignee: International Business Machines Corporation
• Original Assignee: International Business Machines Corporation
• Inventors: Kaufman, James H., Ruvolo, Joann
• Primary Examiner(s): Hafiz, Tariq R.
• Assistant Examiner(s): Heck, Michael C.
• Application Number:
  US09/870,656
• Publication Number:
  US 20020184063A1
• Time in Patent Office: 1,775 Days
• Field of Search: 705/8
• US Class Current: 705/7.12
• CPC Class Codes: G06Q 10/0631 Resource planning, allocation, distributing or scheduling for enterprises or organisations
• CPC Class Codes: G06Q 10/109 Time management, e.g. calendars, reminders, meetings or time accounting

Abstract

A global positioning system (GPS) is used to detect locations (dynamic locations) associated with meeting participants and the proximity between participants is used to create one or more location clusters. Next, the availability of suitable meeting locations (static locations) are identified and an optimum meeting location, given the participant clusters and their proximity to the available meeting locations, is determined. Additionally, the center of mass associated with each of the clusters is also used to determine optimal meeting locations. Lastly, participants are notified regarding the optimized location for the meeting.

Claims

1. A system for determining optimal resources based upon client location and resource locations, said system comprising:

a. one or more databases containing dynamic client location data and static resource location data;

b. a cluster detector retrieving dynamic client location data from one or more databases to determine one or more client locations and creating one or more client clusters, each of said client clusters having one or more weights associated with them;

c. a cluster rater receiving said one or more client clusters and outputting one or more weighted clusters;

d. a locator determining one or more resources and retrieving static resource location data from said one or more databases;

e. an optimizer computing at least one optimized resource based upon said weighted clusters and said static resource location data, and

f. a scheduler dynamically scheduling said at least one optimized resource, wherein said system further includes a positioning interface receiving, from one or more remote electronic devices associated with one or more clients, dynamic client location information and saving said dynamic client location information onto said location database.

2. A system for determining optimal resources based upon client location and resource locations, as per claim 1, wherein said optimizer further calculates a center of mass associated with each of said weighted clusters and utilizes said calculated center of mass in said computation of at least one optimized resource.

3. A system for determining optimal resources based upon client location and resource locations, as per claim 2, wherein said center of mass calculation is done using:

${\stackrel{\to <br><br>}{V}}_{c<br><br><br><br>m}=\left(\frac{\underset{i=1}{\overset{N}{\sum <br><br>}}<br><br>w_i<br><br>x_i}{N<br><br>\underset{i=1}{\overset{N}{\sum <br><br>}}<br><br>w_i},\frac{\underset{i=1}{\overset{N}{\sum <br><br>}}<br><br>w_i<br><br>y_i}{N<br><br>\underset{i=1}{\overset{N}{\sum <br><br>}}<br><br>w_i},\frac{\underset{i=1}{\overset{N}{\sum <br><br>}}<br><br>w_i<br><br>z_i}{N<br><br>\underset{i=1}{\overset{N}{\sum <br><br>}}<br><br>w_i}\right),$

where w is the weight associated with each client in a client cluster, N is the total number of clients in said client cluster, and x, y, and z are coordinate locations associated with each client in said client cluster.

4. A system for determining optimal resources based upon client location and resource locations, as per claim 1, wherein said system further comprises a center of mass calculation engine, said engine calculating a center of mass associated with each of said weighted clusters and passing said calculated center of mass to said optimizer for computing said at least one optimized resource.

5. A system for determining optimal resources based upon client location and resource locations, as per claim 4, wherein said center of mass calculation is done using:

${\stackrel{\to <br><br>}{V}}_{c<br><br><br><br>m}=\left(\frac{\underset{i=1}{\overset{N}{\sum <br><br>}}<br><br>w_i<br><br>x_i}{N<br><br>\underset{i=1}{\overset{N}{\sum <br><br>}}<br><br>w_i},\frac{\underset{i=1}{\overset{N}{\sum <br><br>}}<br><br>w_i<br><br>y_i}{N<br><br>\underset{i=1}{\overset{N}{\sum <br><br>}}<br><br>w_i},\frac{\underset{i=1}{\overset{N}{\sum <br><br>}}<br><br>w_i<br><br>z_i}{N<br><br>\underset{i=1}{\overset{N}{\sum <br><br>}}<br><br>w_i}\right),$

where w is the weight associated with each client in a client cluster, N is the total number of clients in said client cluster, and x, y, and z are coordinate locations associated with each client in said client cluster.

6. A system for determining optimal resources based upon client location and resource locations, as per claim 1, wherein said weights associated with said clients are equal in value.

7. A system for determining optimal resources based upon client location and resource locations, as per claim 1, wherein said resources are any of the following:

meeting location, airfare, flight availability, or airline.

8. A system for determining optimal resources based upon client location and resource locations, as per claim 1, wherein said system further comprises a filter manager passing said one or more clusters through one or more filters, said filters modifying at least one weight associated with each of said client clusters.

9. A system for determining optimal resources based upon client location and resource locations, as per claim 1, wherein said retrieved dynamic client location data is a set of coordinate data, said coordinate data comprising longitude, latitude, and altitude information.

10. A system for determining optimal resources based upon client location and resource locations, as per claim 1, wherein said one or more databases comprises a plurality of the following databases:

a location database containing records of locations, a client database containing records regarding said one or more clients, an event database containing information regarding events associated with one or more clients, or a resource database containing records of said one or more resources.

11. A system for determining optimal resources based upon client location and resource locations, as per claim 1, wherein said system further comprises a notification manager updating said one or more databases and notifying one or more clients regarding said scheduled at least one resource.

12. A system for determining optimal resources based upon client location and resource locations, as per claim 11, wherein said notification is done via an electronic mail message.

13. A computer-based method for optimizing resources and dynamically scheduling said resources, said method comprising the steps of:

a. identifying dynamic location coordinates associated with one or more participants, each of said participants associated with a rating;

b. detecting one or more location clusters from said identified dynamic location coordinates, based on proximity of said participants;

c. creating a rated cluster from each of said location clusters, based on said ratings associated with participants within each of said location clusters;

d. calculating a center of mass associated with each of said rated clusters;

e. identifying available resources and retrieving static resource location data from one or more databases;

f. optimizing at least one resource based on said identified resource and said calculated center of mass, and

g. dynamically scheduling said optimized at least one resource.

14. A computer-based method for optimizing resources and dynamically scheduling said resources, as per claim 13, wherein said method further comprises the step of filtering said location clusters to modify said ratings.

15. A computer-based method for optimizing resources and dynamically scheduling said resources, as per claim 13, wherein said center of mass calculation is done using:

${\stackrel{\to <br><br>}{V}}_{c<br><br><br><br>m}=\left(\frac{\underset{i=1}{\overset{N}{\sum <br><br>}}<br><br>w_i<br><br>x_i}{N<br><br>\underset{i=1}{\overset{N}{\sum <br><br>}}<br><br>w_i},\frac{\underset{i=1}{\overset{N}{\sum <br><br>}}<br><br>w_i<br><br>y_i}{N<br><br>\underset{i=1}{\overset{N}{\sum <br><br>}}<br><br>w_i},\frac{\underset{i=1}{\overset{N}{\sum <br><br>}}<br><br>w_i<br><br>z_i}{N<br><br>\underset{i=1}{\overset{N}{\sum <br><br>}}<br><br>w_i}\right),$

where w is the weight associated with each client in a client cluster, N is the total number of clients in said client cluster, and x, y, and z are coordinate locations associated with each client in said client cluster.

16. A computer-based method for optimizing resources and dynamically scheduling said resources, as per claim 15, wherein said weights associated with said clients are equal in value.

17. A computer-based method for optimizing resources and dynamically scheduling said resources, as per claim 13, wherein said method further comprises notifying said one or more participants regarding said optimized at least one resource.

18. A computer-based method for optimizing resources and dynamically scheduling said resources, as per claim 13, wherein said resources are any of the following:

meeting location, airfare, flight availability, or airline.

19. A computer-based method for optimizing resources and dynamically scheduling said resources, as per claim 13, wherein said notification is done via an email message.

20. An article of manufacture comprising a computer usable medium having computer readable program code embodied therein which optimizes resources and dynamically scheduling said optimized resources, said medium further comprising:

a. computer readable program code identifying dynamic location coordinates associated with one or more participants, each of said participants associated with a rating;

b. computer readable program code detecting one or more location clusters from said identified dynamic location coordinates, based on proximity of said participants;

c. computer readable program code creating a rated cluster from each of said location clusters, based on said ratings associated with participants within each of said location clusters;

d. computer readable program code identifying available resources and retrieving static resource location data from one or more databases;

e. computer readable program code optimizing at least one resource based on said identified resource and said rated clusters, and

f. computer readable program code dynamically scheduling said optimized at least one resource.

21. An article of manufacture comprising a computer usable medium having computer readable program code embodied therein which optimizes resources and dynamically scheduling said optimized resources, as per claim 20, said medium further comprising computer readable program code filtering said location clusters to modify said ratings.

22. An article of manufacture comprising a computer usable medium having computer readable program code embodied therein which optimizes resources and dynamically scheduling said optimized resources, as per claim 20, wherein said resources are any of the following:

meeting location, airfare, flight availability, or airline.