Abstract: A system and method for orchestrating artificial intelligence (AI) and media processing workflows in a distributed computing environment. The method involves modeling processing nodes as a directed acyclic graph (DAG) where each node represents a discrete processing entity and each edge represents a communication path. A central controller dynamically discovers processing nodes, determines their capabilities, and constructs an optimal execution pipeline using graph traversal algorithms such as Dijkstra's algorithm or the A* search algorithm. The system assigns AI and media processing tasks to selected nodes based on network latency, computational load, and resource availability. Execution pipelines are dynamically adjusted in response to real-time network conditions, server availability, or processing demands, ensuring optimized resource allocation.

Abstract: A method for managing media streams including at least video data and audio data in a multi-party video conference involving one or more groups of one or more nodes respectively receiving a media stream from each of a plurality of associated endpoints is provided. In each of the one or more nodes of each of the one or more groups, the loudest audio of the media streams received from the respective plurality of associated endpoints is determined. An indication of the volume of the determined loudest audio and an identification of the node is transmitted to a decision maker. The highest received volume and the associated identification is determined. The node of the identification is instructed to transmit the received media stream of the endpoint to one of: all nodes in the one or more groups and to a proxy.

Abstract: A method for managing media streams including at least video data and audio data in a multi-party video conference involving one or more groups of one or more nodes respectively receiving a media stream from each of a plurality of associated endpoints is provided. In each of the one or more nodes of each of the one or more groups, the loudest audio of the media streams received from the respective plurality of associated endpoints is determined. An indication of the volume of the determined loudest audio and an identification of the node is transmitted to a decision maker. The highest received volume and the associated identification is determined. The node of the identification is instructed to transmit the received media stream of the endpoint to one of: all nodes in the one or more groups and to a proxy.