Abstract: The present technology pertains to a method to balance the performance of an application with the device health and the application runtime health statistics utilizing a hybrid approach. In the hybrid approach, the static performance control is a robust machine learning algorithm trained on data from many client devices and applications. The dynamic performance control is local to the client device and the application and reacts to the real-time device performance and application performance. Additionally, a user can provide their preferences for the performance and resource optimization of the application.

Abstract: An approach to supplying a data stream, for e.g., an internet-based video conference, to multiple client devices in a network, including attempting, at a first client device, to join an Internet Protocol (IP) multicast session in a network in which the first client device is operating and, if unsuccessful to attempt to join a unicast transmission of the data stream from a network node other than the meeting server and that is in a same subnet as the first client device, and if the unicast join within the same subnet is unsuccessful, registering the first client device with the meeting server to obtain at least one candidate node from which to receive the data stream.

Abstract: An approach to supplying a data stream, for e.g., an internet-based video conference, to multiple client devices in a network, including attempting, at a first client device, to join an Internet Protocol (IP) multicast session in a network in which the first client device is operating and, if unsuccessful to attempt to join a unicast transmission of the data stream from a network node other than the meeting server and that is in a same subnet as the first client device, and if the unicast join within the same subnet is unsuccessful, registering the first client device with the meeting server to obtain at least one candidate node from which to receive the data stream.