Systems and methods for managing a Network Based Media Processing (NBMP) workflow are provided. A method includes obtaining, by a workflow manager, a network based media processing (NBMP) workflow including a plurality of workflow tasks and a plurality of proximity parameters which indicate a plurality of desired distances between the plurality of workflow tasks and at least one of a media source and a media sink; assigning the plurality of workflow tasks to the media sink, the media source, and at least one cloud element or network element, based on the plurality of desired distances; and managing the NBMP workflow according to the assigned plurality of workflow tasks.

A system and method are provided to support a scenario where a cluster of HTTP – Hypertext Transfer Protocol – servers has to accept and maintain permanently open HTTP connections with a large number of client devices. The proposed system relies on HTTP/2 and Server-sent Events – SSE – in order to keep connections open and to allow bidirectional message exchange between client and server. It is comprised by following computational entities: at least one connection redirector entity, at least two connection handler entities, a location registry entity and an execution server entity configured to support an API implementation adapted to provide an interface for external systems. The connection between the system and the client device is performed through an internet connection.

A network device may include a processor. The processor is configured to: receive a network address of a load balancer device from a management device; send a test request to the load balancer device based on the received network address; obtain a network address of a data collector device from the load balancer device; and perform a test with the data collector device. The data collector device is configured to: obtain a result of the test; and send the result to a data lake.

An information transmission method includes: receiving, by a network element selector from a user equipment (UE), a first message including identification information of the UE; determining, based on the identification information of the UE, a user group to which the UE belongs; determining a controller corresponding to the user group; and receiving and sending a further message to the controller.

A system for data recording across a network includes a session border controller connecting incoming data from the network to an endpoint recorder. A load balancer is connected to the network between the session border controller and the endpoint and receives the incoming data from the session border controller, wherein the load balancer comprises computer memory and a processor configured to parse the incoming data into video data and audio data according to identification protocols accessible by the processor from the computer memory. A recording apparatus includes recording memory that receives the incoming data from the load balancer, stores a duplicate version of the incoming data in the recording memory, and connects the incoming data to the endpoint.

A multi-cloud service mesh orchestration platform can receive a request to deploy an application as a service mesh application. The platform can tag the application with governance information (e.g., TCO, SLA, provisioning, deployment, and operational criteria). The platform can partition the application into its constituent components, and tag each component with individual governance information. For first time steps, the platform can select and perform a first set of actions for deploying each component to obtain individual rewards, state transitions, and expected returns. The platform can determine a reinforcement learning policy for each component that maximizes a total reward for the application based on the individual rewards, state transitions, and expected returns of each first set of actions selected and performed for each component. For second time steps, the platform can select and perform a second set of actions for each component based on the reinforcement learning policy for the component.

A method includes receiving a plurality of inputs comprising data corresponding to a plurality of network elements, confirming presence of a given network element of the plurality of network elements on at least one network, and adding the given network element to a network element database. The method also includes interfacing with one or more network integration services of a plurality of network integration services to receive data corresponding to the given network element. The network element database is automatically updated with the received data, and the interfacing is performed via a message bus.

A method and system that perform cluster node work assignments for tenants in a multi-tenant system. The method includes selecting a partition of a cluster tenant tracking structure having a hierarchical namespace and virtual nodes representing each tenant by a cluster node foreman controller, searching the selected partition for a tenant that is unlocked in the cluster tenant tracking structure, and initiating work for the tenant by the cluster node.

The invention is based, in part, on a system and method designed to be able to easily and automatically scale up to millions of cameras and users. To do this, this discourse teaches use of modern cloud computing technology, including automated service provisioning, automated virtual machine migration services, RESTful API, and various firewall traversing methods to facilitate the scaling process. Moreover, the system and method described herein teaches scalable cloud solutions providing for higher though-put camera provisioning and event recognition. The network may segregate the retrieval server from the storage server, and by doing so, minimizing the load on any one server and improving network efficiency and scalability.

The invention is based, in part, on a system and method designed to be able to easily and automatically scale up to millions of cameras and users. To do this, this discourse teaches use of modern cloud computing technology, including automated service provisioning, automated virtual machine migration services, RESTful API, and various firewall traversing methods to facilitate the scaling process. Moreover, the system and method described herein teaches scalable cloud solutions providing for higher though-put camera provisioning and event recognition. The network may segregate the retrieval server from the storage server, and by doing so, minimizing the load on any one server and improving network efficiency and scalability.