An embodiment may involve: transmitting a first graphical user interface (GUI) that allows selection of a plurality of item streams for a mobile user interface; receiving a selection of a first item stream; transmitting a second GUI, where the first item stream is populated from a first database table and the second GUI allows selection of a first field from the first database table; receiving a selection of a second item stream; transmitting the second GUI, where the second item stream is populated from a second database table and the second GUI allows selection of a second field from the second database table, where the first and second fields are of a common type; and transmitting, to a mobile device, the mobile user interface with items from the first and second item streams sorted according to values in the first and second fields.

A system to distribute an Aircraft Operations Communication (AOC) application is provided. The system includes communication components in a vehicle, and an AOC database. The communication components include one of: a Communication Management Unit (CMU); or a Communication Management Function (CMF); and at least one of: at least one electronic flight bag (EFB); and at least one cabin terminal. The AOC database includes an operational configuration for aircraft operations communication for the communication components in the vehicle. The AOC database is loaded into at least one of: the CMU, the CMF, the at least one EFB; the at least one cabin terminal; and a database device. The AOC database configures the operation of the communication components in the vehicle.

Embodiments may be generally direct to apparatuses, systems, method, and techniques to determine a configuration for a plurality of connectors, the configuration to associate a first interconnect protocol with a first subset of the plurality of connectors and a second interconnect protocol with a second subset of the plurality of connectors, the first interconnect protocol and the second interconnect protocol are different interconnect protocols and each comprising one of a serial link protocol, a coherent link protocol, and an accelerator link protocol, cause processing of data for communication via the first subset of the plurality of connectors in accordance with the first interconnect protocol, and cause processing of data for communication via the second subset of the plurality of connector in accordance with the second interconnect protocol.

Methods and systems for a topology service providing an interface for specifying a topology and answering queries regarding the topology. Further, the topology service may create, from a specified topology, a directed acyclic graph and corresponding closure table. The topology service may also provide an interface for receiving metadata regarding the topology. In this way, the topology service, based at least in part on connections between nodes in the entries of the closure table and based at least in part on the metadata regarding the topology, may answer queries in regard to the specified topology.

A novel machine learning-based network analytics, troubleshoot, and self-healing system identifies and locates sources of data network problems autonomously within an entire end-to-end network topology of a network operator, while not necessitating human diagnosis of the data network problems. This system uniquely embeds a smart universal telemetry (SUT) as a quality-of-experience (QoE) parameter collection agent in intermediary transport-level network equipment and each end-user modem, which in turn enables on-demand collection of robust diagnostic data from all end-user modems and intermediary transport level nodes in a data network. By executing a machine learning (ML)-based artificial intelligence (AI) analytical module in a cloud-computing resource, the system then achieves autonomous identification and source pinpointing of network problems, and even self-repairs some machine-identified data network problems autonomously through remote software updates performed intelligently by the ML-based AI analytical module, if physical replacement of a network equipment is unnecessary to resolve such problems.

A novel machine learning-based network analytics, troubleshoot, and self-healing system identifies and locates sources of data network problems autonomously within an entire end-to-end network topology of a network operator, while not necessitating human diagnosis of the data network problems. This system uniquely embeds a smart universal telemetry (SUT) as a quality-of-experience (QoE) parameter collection agent in intermediary transport-level network equipment and each end-user modem, which in turn enables on-demand collection of robust diagnostic data from all end-user modems and intermediary transport level nodes in a data network. By executing a machine learning (ML)-based artificial intelligence (AI) analytical module in a cloud-computing resource, the system then achieves autonomous identification and source pinpointing of network problems, and even self-repairs some machine-identified data network problems autonomously through remote software updates performed intelligently by the ML-based AI analytical module, if physical replacement of a network equipment is unnecessary to resolve such problems.

A service distribution obtaining method, a network side device, and a terminal are provided in this disclosure. The method includes: obtaining, by a network side device, measurement information of multiple terminals in a serving cell and an average service volume of each of the multiple terminals, and determining service distribution, where the measurement information includes first channel state values of channels between the multiple terminals and a primary cell, the primary cell refers to the serving cell or one of neighboring cells of the serving cell, the service distribution includes a first typical channel state value of each type of the first channel state values and a first service volume between a terminal set corresponding to each type of the first channel state values and the primary cell, and the first service volume is determined according to the average service volume of each terminal.

A method at a server system includes: receiving a user request to enter a first information exchange hall; detecting a lock status of information of an information exchange operation associated with the user and with a second information exchange hall, where the information exchange operation is associated with a second information exchange hall; when the lock status is an unlocked state, processing entry of the user into the first information exchange hall; when the lock status is a locked state, determining an operation state of the information of the information exchange operation; when the operation state is an inactive operation state, changing the lock status of the information from the locked state to the unlocked state, and processing entry of the user into the first information exchange hall; and when the operation state is an active operation state, restoring entry of the user into the second information exchange hall.

A Yet Another Next Generation (YANG) module management method includes that a first network device determines a target YANG package in a second network device. The target YANG package includes at least two service-related YANG modules. The first network device generates a processing instruction for the target YANG package, and sends the processing instruction to the second network device. The processing instruction includes an identifier of the target YANG package. The identifier of the target YANG package includes a name of the target YANG package or the name and version information of the target YANG package.

A computer program product, system, and method for accessing an application from different locations to gather geo-location specific data via pre-provisioned network endpoints in the different locations, the method includes receiving a request from a client application to access an application via a particular geographical location to collect geo-location specific data via a pre-provisioned network endpoint in the particular location, selecting a route to send traffic via the particular geographical location using the pre-provisioned network endpoint, establishing a virtual circuit to route the request via a network endpoint, sending the request for execution to the network endpoint, collecting responses received from the network endpoint from accessing the application, and sending the responses to the client application.