Abstract: The described technology is generally directed towards creation of shared overlay maps to support automated, real-time, cross-platform sharing of map information among groups of digital navigational map users, including but not limited to unmanned ground vehicles (UGVs). A central map authority (or other collaborative/federated organizational entity) can receive map overlay information from a mobile subscriber device, such as a UGV. The central map authority can promulgate the map overlay information to a group of multiple mobile subscriber devices according to the techniques described herein. Individual mobile subscriber devices can use received map overlay information, along with their individual digital navigational maps (DNMs) and navigation systems, to plan their individual routes.

Abstract: Methods, systems, and apparatuses, for real-time operation control, among other things. There may be adjustments to a first device in which a first network service operates. The adjustment to the device may include moving a second network service of the first device to a second device. The first network service and the second network service may be associated with virtual machines.

Abstract: Methods, systems, and apparatuses, for real-time operation control, among other things. There may be adjustments to a first device in which a first network service operates. The adjustment to the device may include moving a second network service of the first device to a second device. The first network service and the second network service may be associated with virtual machines.

Abstract: The described technology is generally directed towards proactive content placement for low latency mobile access. Digital content requested by a mobile device can be sent to network nodes proactively, so that the network nodes have the digital content before it is requested by the mobile device. Mobile device travel predictions can be made to predict future locations of the mobile device. The future locations can be used to determine network nodes for proactive digital content delivery. The digital content for delivery to a network node can also be predicted based on current digital content in use at the mobile device and estimated arrival times of the mobile device into service areas of next network nodes.

Abstract: The described technology is generally directed towards digital map truth maintenance. Map inputs shared among multiple users of a shared overlay map service can have a range of credibility, from not credible to highly credible. The disclosed digital map truth maintenance technologies can be used to enhance credibility of shared map inputs. Credibility values can be calculated for map inputs, based on any of multiple factors. Map inputs having sufficiently high credibility, such as a credibility value determined to be above a threshold value, can be shared among multiple mobile devices.

Abstract: The autonomous cloud design system may determine a design that may appropriately mix emerging technologies and operations to provide a versatile and cost-effective or efficient solution for a given cloud site.

Abstract: An example method performed by a processing system includes receiving a request from a first user to render an extended reality environment, wherein the request includes a definition of a first policy that governs user behavior within the extended reality environment, rendering the extended reality environment by presenting content contributed by at least one user in the extended reality environment, monitoring the extended reality environment to ensure that the rendering results in a compliance of the extended reality environment with the first policy, detecting that a portion of the content contributed by at least one other user of the extended reality environment results in the extended reality environment failing to comply with the first policy, and modifying a presentation of the portion of content in the extended reality environment in response to the detecting, wherein the modifying results in the compliance of the extended reality environment with the first policy.

Abstract: Concepts and technologies disclosed herein are directed to visualization for network virtualization platforms (“NVPs”) enhanced with non-visual sensory interactivity. A computer system can obtain data associated with an NVP. The computer system can generate a non-visual feedback environment representative of at least a portion of the network virtualization platform. The non-visual feedback environment can include non-visual sensory feedback to be presented to a user. The computer system also can receive one or more rules associated with the data. The rule(s) can be associated with one or more service elements of the NVP. The rule(s) alternatively or additionally can be associated with one or more events. The computer system can provide the non-visual sensory feedback via a non-visual sensory feedback device that outputs the non-visual sensory feedback to be sensed by the user. The non-visual sensory feedback can include audio feedback, haptic feedback, olfactory feedback, or some combination thereof.

Abstract: An example method performed by a processing system includes retrieving a digital model of a media element from a database storing a plurality of media elements, wherein the media element is to be inserted into a scene of an audiovisual media, rendering the media element in the scene of the audiovisual media, based on the digital model of the media element and on metadata associated with the digital model to produce a rendered media element, wherein the metadata describes a characteristic of the media element and a limit on the characteristic, and inserting the rendered media element into the scene of the audiovisual media.

Abstract: In one example, a method includes presenting an extended reality (XR) experience to a plurality of user devices, wherein the presenting includes presenting a time control along with an XR stream, receiving a first signal from a first user device of the plurality of user devices via the time control, wherein the first signal indicates that a user of the first user device wishes to shift the XR stream to a first point in time that is different from a time that is currently being rendered in the XR stream, and presenting a personal XR environment to the first user device in response to the first signal, wherein the personal XR environment presents the first point in time in the XR stream to the first user device without changing a time point of the XR stream that is currently being presented to other user devices of the plurality of user devices.

Abstract: Cloud infrastructure planning systems and methods can utilize artificial intelligence/machine learning agents for developing a plan of demand, plan of record, plan of execution, and plan of availability for developing cloud infrastructure plans that are more precise and accurate, and that learn from previous planning and deployments. Some agents include one or more of supervised, unsupervised, and reinforcement machine learning to develop accurate predictions and perform self-tuning alone or in conjunction with other agents.

Abstract: The described technology is generally directed towards policy-based navigation control. Map inputs including, e.g., information about blocked routes or other map information, can be collected from mobile devices. Policies can be applied to the map inputs in order to generate navigation advisories that synthesize information from multiple map inputs. For example, a size and shape of a route blockage zone can be determined from multiple discrete map inputs. In some embodiments, the techniques disclosed herein can be applied in connection with shared overlay maps to support automated, real-time, cross-platform sharing of map information, including navigation advisories, among digital navigational map users, including but not limited to unmanned ground vehicles.

Abstract: The described technology is generally directed towards proactive content placement for low latency mobile access. Digital content requested by a mobile device can be sent to network nodes proactively, so that the network nodes have the digital content before it is requested by the mobile device. Mobile device travel predictions can be made to predict future locations of the mobile device. The future locations can be used to determine network nodes for proactive digital content delivery. The digital content for delivery to a network node can also be predicted based on current digital content in use at the mobile device and estimated arrival times of the mobile device into service areas of next network nodes.

Abstract: The described technology is generally directed towards digital map truth maintenance. Map inputs shared among multiple users of a shared overlay map service can have a range of credibility, from not credible to highly credible. The disclosed digital map truth maintenance technologies can be used to enhance credibility of shared map inputs. Credibility values can be calculated for map inputs, based on any of multiple factors. Map inputs having sufficiently high credibility, such as a credibility value determined to be above a threshold value, can be shared among multiple mobile devices.

Abstract: The autonomous cloud design system may determine a design that may appropriately mix emerging technologies and operations to provide a versatile and cost-effective or efficient solution for a given cloud site.

Abstract: Augmented/mixed reality virtual venue pipeline optimization is provided. A method can include acquiring, by a device comprising a processor, information relating to a group of augmented reality applications operating in an area; designating, by the device, an augmented reality application of the group of augmented reality applications as a priority application based on the information relating to the group of augmented reality applications; and granting, by the device, prioritized access to edge network resources in a sub-area comprising at least a portion of the area to the priority application relative to at least one non-priority application of the group of augmented reality applications.

Abstract: Cloud infrastructure planning systems and methods can utilize artificial intelligence/machine learning agents for developing a plan of demand, plan of record, plan of execution, and plan of availability for developing cloud infrastructure plans that are more precise and accurate, and that learn from previous planning and deployments. Some agents include one or more of supervised, unsupervised, and reinforcement machine learning to develop accurate predictions and perform self-tuning alone or in conjunction with other agents.

Abstract: An example method includes obtaining a profile of a user using a user device to present an immersive experience, wherein the profile specifies a user reaction indicator and a value that represents a baseline for the user reaction indicator, presenting the immersive experience on the user device, receiving user state data including a current value of the user reaction indicator, determining that the current value of the user reaction indicator deviates from the value that represents the baseline by more than a threshold, in response to the determining, selecting, from among a plurality of variants for a segment of the immersive experience, a variant that is expected to cause the current value of the user reaction indicator to adjust to a value that does not deviate from the value that represents the baseline by more than the threshold, and presenting the variant that is selected on the user device.

Abstract: An example method performed by a processing system includes receiving a request from a first user to render an extended reality environment, wherein the request includes a definition of a first policy that governs user behavior within the extended reality environment, rendering the extended reality environment by presenting content contributed by at least one user in the extended reality environment, monitoring the extended reality environment to ensure that the rendering results in a compliance of the extended reality environment with the first policy, detecting that a portion of the content contributed by at least one other user of the extended reality environment results in the extended reality environment failing to comply with the first policy, and modifying a presentation of the portion of content in the extended reality environment in response to the detecting, wherein the modifying results in the compliance of the extended reality environment with the first policy.

Abstract: The described technology is generally directed towards policy based navigation control. Map inputs including, e.g., information about blocked routes or other map information, can be collected from mobile devices. Policies can be applied to the map inputs in order to generate navigation advisories that synthesize information from multiple map inputs. For example, a size and shape of a route blockage zone can be determined from multiple discrete map inputs. In some embodiments, the techniques disclosed herein can be applied in connection with shared overlay maps to support automated, real-time, cross-platform sharing of map information, including navigation advisories, among digital navigational map users, including but not limited to unmanned ground vehicles.