Patent №
US 9,952,953
Granted
2018-04-24
Filed 2015
Owner
MICROSOFT TECHNOLOGY LICENSING LLC
Lab
AI components
1
hardware
Assignment
Recorded
Dataset
AIPD
2023_r1 edition
Application
14982306
Technologies are provided for non-monotonic eventual convergence for desired state configuration. One class of problem in DSC is that, in some situations, DSC cannot move forward toward a desired state without first moving further from the desired state. For example, an executable file providing a service that needs to be replaced with a newer version, but that is currently executing (i.e., in the desired state of “operating”), cannot be replaced with the newer version without first being stopped. But stopping the service moves in the wrong direction relative to the desired state, which is to have the service operating. This moving away from the desired state so as to be able to move closer to the desired state is a problem for conventional DSC systems that results in failures. The solution to this problem is herein referred to as “non-monotonic eventual convergence” or “NMEC”. Such NMEC enables a DSC system to configure a target system for a desired state by moving further away from that state if such is needed to eventually reach the desired state.
AI classification
Ownership
MICROSOFT TECHNOLOGY LICENSING LLC
assignment · 373740932
Assignors
PAYETTE, BRUCE GORDON, MAHAWAR, HEMANT, HANSEN, KENNETH M., GRAY, MARK, LAKSHMANAN, NARAYANAN
On an employer assignment, the assignors are typically the inventors.