Method and system for pro-active desktop resume operation based on historical data
A system and method for resuming a remote desktop for a networked client device. An access control system accepts login data from a user input to a networked client device, and/or user activity data collected by an agent running on the desktop. The networked client device may include a client application. A data center allows access to an activated desktop to the networked client device. The access control system suspends the desktop when the user is inactive in operating the client device. The access control system resumes the desktop on the networked client device in relation to a predicted start time. The predicted start time is based on login data from past logins by the user on networked client devices.
1. A system resuming a remote desktop accessed by a networked client device comprising:
a control system accepting login data from a user input to a networked client device;
a remote server that allows a stored desktop to be accessed by the networked client device when the control system validates the login data from the user input; and
wherein the control system suspends the desktop when the user is inactive in operating the client device;
wherein the control system is operable to activate the desktop for the networked client device a predetermined time period before a predicted start time, wherein the predicted start time is based on login data from past logins by the user on one or more client devices; and
wherein the control system is operative to suspend the desktop after a logoff from the client device outside of a normal active time window, wherein the normal active time window is determined based on past logins.
2. The system of claim 1 , wherein the control system accepts login data from an agent running on the desktop.
3. The system of claim 1 , wherein the predicted start time is determined by machine learning.
4. The system of claim 1 , wherein the control system builds a desktop use profile for the user based on past logins.
5. The system of claim 1 , wherein the computer system includes a plurality of users and a plurality of client devices, and wherein the control system predicts a start time for each of the plurality of users.
6. The system of claim 1 , wherein the control system is operative to keep the desktop activated if the logoff is within the normal active time window.
7. The system of claim 1 , wherein the control system updates the predicted start on a periodic basis based on times of logins.
8. The system of claim 1 , wherein the control system and the remote server are executed on one of a cloud hosting system or a data center.
9. The system of claim 1 , wherein the desktop is one of a persistent desktop or a non-persistent desktop.
10. The system of claim 1 , wherein the networked client device includes a client application to access the desktop.
11. The system of claim 1 , wherein the desktop is a Remote Desktop Session Host (RDSH) session.
12. The system of claim 11 , wherein the activation includes activating another remote server based on the predicted start time.
13. A method of activating a desktop on an idle client device operating a client application in a network system, the method comprising:
accepting login data from a user input to the client device via a control system;
validating the login data from the user;
allowing access to a desktop on a remote server to the networked client device from over the network;
suspending the desktop when the user is inactive in operating the client device;
activating the desktop for the networked client device a predetermined time period before a predicted start time, wherein the predicted start time is based on login data from past logins by the user on one or more client devices; and
suspending the desktop after a logoff from the client device outside of a normal active time window, wherein the normal active time window is determined based on past logins.
14. The method of claim 13 , wherein the predicted start time is determined by machine learning.
15. The method of claim 13 , further comprising building a desktop use profile for the user via the control system.
16. The method of claim 13 , wherein the network system includes a plurality of users and a plurality of client devices, and wherein a start time is predicted for each of the plurality of users.
17. The method of claim 13 , further comprising keeping the desktop activated if the logoff is within the normal active time window.
18. The method of claim 13 , wherein the desktop includes a data collection agent that collects the times of the login of the user.
19. The method of claim 13 , further comprising updating the predicted start time on a periodic basis based on times of logins.
20. The method of claim 13 , wherein the desktop is one of a persistent desktop or a non-persistent desktop.
21. The method of claim 13 , wherein the desktop is a Remote Desktop Session Host (RDSH) session.
22. The method of claim 21 , further comprising activating another remote server based on the predicted start time.
23. A system that determines a time to activate a desktop for a networked client device, the system comprising:
an access control system accepting login data from a user input to the networked client device;
a remote server storing a desktop that is accessed by the networked client device when the control system validates the login data from the user input;
wherein the control system is operable to determine a predicted start time associated with the user, wherein the predicted start time is based on login data from past logins by the user on networked client devices, and
wherein the control system is operable to determine a time to suspend the desktop after a logoff from the client device outside of a normal active time window, wherein the normal active time window is determined based on past login.