Amdocs Development Limited

Nir Fattal

Shmuel Ur

Sarit Chehanowitz

Eran Yosef Paran

Gad Yitzhak Weissman

As described herein, a system, method, and computer program are provided for network experience optimization using a residential network router. In use, an electronic calendar is accessed by a residential network router. Additionally, the residential network router determines a plurality of events saved to the electronic calendar, wherein the plurality of events require, at least in part, simultaneous network resource (e.g. bandwidth) usage. Further, the plurality of events are prioritized, using the residential network router. Still yet, available network resources are assigned among the plurality of events, using the residential network router, based on the prioritization.

System, method, and computer program for network experience optimization using a home network router

As described herein, a machine learning system, method, and computer program are provided to predict which resident of a residential space is watching television for content targeting purposes. In use, a login to a television service on a television device in a residential space is detected. Additionally, information defining a plurality of residents of the residential space is identified. Further, a profile determined for the login is identified, where the profile is associated with a particular resident of the plurality of residents or a particular resident group of the plurality of residents. Still yet, the profile and the information defining the plurality of residents of the residential space is input to a machine learning model to predict one or more residents of the plurality of residents that is consuming the television service on the television device.

Machine learning system, method, and computer program to predict which resident of a residential space is watching television for content targeting purposes

As described herein, a system, method, and computer program are provided for using in-video annotations to select relevant advertisements for distribution to users. In use, one or more in-video annotations are automatically created for a video content, using video analysis of the video content. Also, the one or more in-video annotations included within the video content is identified. Additionally, real-time bidding is used to select an advertisement relevant to the video content, wherein the real-time bidding is performed based on the one or more in-video annotations. Further, the advertisement is presented in association with the video content.

Real-time bidding based system, method, and computer program for using in-video annotations to select relevant advertisements for distribution

Systems and methods transfer execution of tasks executed on behalf of client devices between edge nodes operated by different operators. A request is received at a destination edge node deployed at a network edge to provide computing services to a client device currently served by an origin edge node. The origina edge node and the destination edge node are operated by different operators. An edge identifier of the origin edge node and task identifier(s) of task(s) executed by the origin edge node for the client device are received. The origin edge node is communicated with to obtain task information relating to the task(s) in one or more registries shared by the first and second operators to map task identifier(s) to respective tasks. A connection is made to the client device the task(s) are executed for the client device using the task information.

Handshake of application execution between edge nodes

A system, method, and computer program product are provided for implementing various device decisions regarding edges/towers. The method comprises one or more of: choosing a single best edge or tower for a device; splitting workloads between multiple edges or towers; and controlling multiple smart devices and deciding how to split a workload between them.

Growing community of inventors

Yehud-Monosson, Israel

Nir Fattal