Abstract: Methods, apparatus, systems and articles of manufacture (e.g., physical storage media) to implement license management solutions for software defined silicon (SDSi) products are disclosed. Example license management solutions disclosed herein include, but are not limited to, virtual resource migration using SDSi, resource configuration management using SDSi, hardware self-configuration using SDSi, reduced footprint agents using SDSi, performing SDSi usage evaluation and corresponding license transfer responsive to detected and/or predicted failures, transferring node locked SDSi licenses, transfer of SDSi licenses without a trusted license server, community license generation, expirable SDSi licenses via a reliable clock, non-node locked licenses via blockchain, and activating hardware features with a pre-generated hardware license.

Abstract: Methods, apparatus, systems and articles of manufacture (e.g., physical storage media) to implement software defined silicon feature configuration pay-as-you-go licensing are disclosed. A disclosed silicon semiconductor device includes a first counter that increments a first count when a timer expires and, responsive to expiration of the timer, a feature configuration sampler to sample a state of a configuration of a feature of the silicon semiconductor device. In addition, the silicon semiconductor device includes a second counter that increments a second count when the sampled state of the configuration of the feature indicates the feature is active. A feature up-time tracker is also included outputs a value representative of an amount of time the configuration has been active, where the amount of time is based on the first count and the second count.

Abstract: System and techniques for radio link quality prediction are described herein. A mobile device may receive a device registration. Motion data for the mobile device may then be obtained. A predicted path for the mobile device may be derived from the motion data. A set of predicted radio metrics for the mobile device along the predicted path mat be produced via a dynamic coverage map. The set of predicted radio metrics may then be transmitted.

Abstract: A compute system that includes an Internet of things (IoT) device is provided. The IoT device includes a common services interface (CSI) to create a self-managing network of devices with other nodes comprising the CSI.

Abstract: Technologies for context-aware dynamic bandwidth allocation include a network compute device configured to collect context inputs from a plurality of compute devices communicatively coupled to the network compute device. The network compute device is further configured to identify a context of each compute device based on the collected context inputs and determine a bandwidth priority for each compute device based on the identified context. Additionally, the network compute device is configure to determine an amount of bandwidth from a total available bandwidth to allocate to the compute device based on the determined bandwidth priority and update a moderated bandwidth allocation policy to reflect the determined amount of bandwidth allocated to the compute device. Other embodiments are described herein.

Abstract: Methods and apparatus to execute a workload in an edge environment are disclosed. An example apparatus includes a node scheduler to accept a task from a workload scheduler, the task including a description of a workload and tokens, a workload executor to execute the workload, the node scheduler to access a result of execution of the workload and provide the result to the workload scheduler, and a controller to access the tokens and distribute at least one of the tokens to at least one provider, the provider to provide a resource to the apparatus to execute the workload.

Abstract: Technologies for deploying virtual machines (VMs) in a virtual network function (VNF) infrastructure include a compute device configured to collect a plurality of performance metrics based on a set of key performance indicators, determine a key performance indicator value for each of the set of key performance indicators based on the collected plurality of performance metrics, and determine a service quality index for a virtual machine (VM) instance of a plurality of VM instances managed by the compute as a function each key performance indicator value. Additionally, the compute device is configured to determine whether the determined service quality index is acceptable and perform, in response to a determination that the determined service quality index is not acceptable, an optimization action to ensure the VM instance is deployed on an acceptable host of the compute device. Other embodiments are described herein.

Abstract: A compute system that includes an Internet of things (IoT) device is provided. The IoT device includes a common services interface (CSI) to create a self-managing network of devices with other nodes comprising the CSI.

Abstract: Methods, apparatus, systems, and articles of manufacture to translation between sign language and spoken language are disclosed. An example apparatus includes processor circuitry to at least one of instantiate or execute machine readable instructions to identify a plurality of candidate signs across different frames in video; associate a respective gloss to respective ones of the candidate signs; associate a respective confidence score with the respective glosses; identify overlapping frames of the candidate signs; select one or more of the candidate signs as performed signs based on the respective confidence scores and overlapping frames; and convert the performed signs to audio data.

Abstract: Systems, methods, and computer-readable media are provided for managing mutual and transitive trust relationships between resources, such as Fog/Edge nodes, autonomous devices (e.g., IoT devices), and/or analog/biological resources to provide collaborative, trusted communication over a network for service delivery. Disclosed embodiments include a subject resource configured to assign an observed resource to a trust zone based on situational and contextual information. The situational information may indicate a vector of the observed resource with respect to the subject resource. The contextual information may be based in part on whether a relationship exists between the subject resource and the observed resource. The subject resource is configured to determine a trust level of the observed resource based on the determined trust zone. Other embodiments are disclosed and/or claimed.

Abstract: Technologies for deploying virtual machines (VMs) in a virtual network function (VNF) infrastructure include a compute device configured to collect a plurality of performance metrics based on a set of key performance indicators, determine a key performance indicator value for each of the set of key performance indicators based on the collected plurality of performance metrics, and determine a service quality index for a virtual machine (VM) instance of a plurality of VM instances managed by the compute as a function each key performance indicator value. Additionally, the compute device is configured to determine whether the determined service quality index is acceptable and perform, in response to a determination that the determined service quality index is not acceptable, an optimization action to ensure the VM instance is deployed on an acceptable host of the compute device. Other embodiments are described herein.

Abstract: A compute system that includes an Internet of things (IoT) device is provided. The IoT device includes a common services interface (CSI) to create a self-managing network of devices with other nodes comprising the CSI.

Abstract: System and techniques for radio link quality prediction are described herein. A mobile device may receive a device registration. Motion data for the mobile device may then be obtained. A predicted path for the mobile device may be derived from the motion data. A set of predicted radio metrics for the mobile device along the predicted path mat be produced via a dynamic coverage map. The set of predicted radio metrics may then be transmitted.

Abstract: A compute system that includes an Internet of things (IoT) device is provided. The IoT device includes a common services interface (CSI) to create a self-managing network of devices with other nodes comprising the CSI.

Abstract: Systems, methods, and computer-readable media are provided for managing mutual and transitive trust relationships between resources, such as Fog/Edge nodes, autonomous devices (e.g., IoT devices), and/or analog/biological resources to provide collaborative, trusted communication over a network for service delivery. Disclosed embodiments include a subject resource configured to assign an observed resource to a trust zone based on situational and contextual information. The situational information may indicate a vector of the observed resource with respect to the subject resource. The contextual information may be based in part on whether a relationship exists between the subject resource and the observed resource. The subject resource is configured to determine a trust level of the observed resource based on the determined trust zone. Other embodiments are disclosed and/or claimed.

Abstract: System and techniques for radio link quality prediction are described herein. A mobile device may receive a device registration. Motion data for the mobile device may then be obtained. A predicted path for the mobile device may be derived from the motion data. A set of predicted radio metrics for the mobile device along the predicted path mat be produced via a dynamic coverage map. The set of predicted radio metrics may then be transmitted.

Abstract: Systems, methods, and computer-readable media are provided for managing mutual and transitive trust relationships between resources, such as Fog/Edge nodes, autonomous devices (e.g., IoT devices), and/or analog/biological resources to provide collaborative, trusted communication over a network for service delivery. Disclosed embodiments include a subject resource configured to assign an observed resource to a trust zone based on situational and contextual information. The situational information may indicate a vector of the observed resource with respect to the subject resource. The contextual information may be based in part on whether a relationship exists between the subject resource and the observed resource. The subject resource is configured to determine a trust level of the observed resource based on the determined trust zone. Other embodiments are disclosed and/or claimed.

Abstract: Technologies for context-aware dynamic bandwidth allocation include a network compute device configured to collect context inputs from a plurality of compute devices communicatively coupled to the network compute device. The network compute device is further configured to identify a context of each compute device based on the collected context inputs and determine a bandwidth priority for each compute device based on the identified context. Additionally, the network compute device is configure to determine an amount of bandwidth from a total available bandwidth to allocate to the compute device based on the determined bandwidth priority and update a moderated bandwidth allocation policy to reflect the determined amount of bandwidth allocated to the compute device. Other embodiments are described herein.

Abstract: Methods, apparatus, systems, and articles of manufacture to provide a distributed edge-based tracing framework system are disclosed. An example system includes an intermediary generator to generate an intermediary in response to a monitoring request, the intermediary to monitor execution of a service executing in an execution vehicle; an intermediary controller to gather data regarding the monitored execution of the service from the intermediary, and control the intermediary in response to the monitored execution; and a remediator to provide a remediation in response to an error identified in the monitored execution of the service.

Abstract: Embodiments include apparatuses, systems, and methods for a computer-aided or autonomous driving (CA/AD) system to transmit to a remote service scheduling server, a request message for a service slot at a service provider. In embodiments, the remote service scheduling server may assign the service slot for a semi-autonomous or autonomous driving (SA/AD) vehicle including the CA/AD system. In embodiments, the service scheduling server may perform analysis or machine learning on data received from the CA/AD system as well as from a plurality of service stations in order to assign the service provider and/or service slot to the SA/AD vehicle. In embodiments, the CA/AD system may receive an assignment message and control driving elements of the SA/AD vehicle to autonomously or semi-autonomously drive the SA/AD vehicle to the service provider to receive the service at the assigned service slot. Other embodiments may also be described and claimed.