Abstract: Methods, apparatus, systems and articles of manufacture are disclosed for managing compute resources in a hyperconverged infrastructure computing environment. An example apparatus includes a resource manager table populator to populate a resource management table with information identifying workloads and a workload categorizer to categorize the workloads identified in the resource management table as needy workloads or offering workloads. The disclosed apparatus further include a workload selector to select an offering workload to lend resources to a needy workload, and a resource configurer. The resource configurer to cause a host included in the workload to spin a virtual machine or create a container, and assign the virtual machine or container to support the needy workload.

Abstract: The disclosure provides an approach for processing frames of a virtualized desktop to improve accessibility for users, such as users with disabilities. The approach involves processing frames by an accessibility engine that is located on a client device of the user. The virtualized desktop runs on a virtual machine that is remote to the client device. The location of the accessibility engine on the client device allows advantages such as the ability to process frames that indicate a non-operational virtual machine.

Abstract: Embodiments of the present disclosure relate to techniques for providing an augmented reality experience. Certain embodiments involve receiving a request from an application to register a context for detection, wherein the context for detection comprises an artifact and a context identifier. Some embodiments involve sending the context for detection to a registration component. The registration component may register the context for detection. Certain embodiments involve receiving context detection information from a client device. Some embodiments involve sending a notification to the application that the context detection information was received. Certain embodiments involve receiving application content and a relative pose of the application content from the application. Some embodiments involve composing a scene based on the application content and the relative pose of the application content and transporting, by the computing device, the scene to the client device.

Abstract: Embodiments of the present disclosure relate to synthesizing a virtual stereo device. Embodiments include receiving a request from a user to synthesize the virtual stereo device based on a first camera and a second camera associated with a client device. Embodiments include calibrating the virtual stereo device by using images received from the first camera and the second camera to determine calibration parameters. Embodiments include storing the calibration parameters in a manifest file and transmitting the manifest file to the client device. Embodiments include receiving encoded frames associated with the virtual stereo device from the client device, each of the encoded frames including a stereo image that has been created by the client device, based on the calibration parameters in the manifest file, from image data captured using the first camera and the second camera. Embodiments include decoding the encoded frames for use by an application involving stereo vision.

Abstract: Described herein are systems, methods, and software to improve distribution of service information in a computing environment. In one implementation, a computing element identifies a modification to a locally maintained service data structure that maintains status information for services of a computing environment. In response to the modification, the computing element may identify a key-value pair and add the key-value pair to a gateway protocol packet. Once added to the packet, the computing element may communicate the packet to a second computing element.

Abstract: In a decentralized cloud computing system, a fog resource manager is utilized for management. The fog resource manager identifies nodes of the decentralized cloud computing system, and images a first one of the nodes so as to include a hypervisor. The fog resource manager further provisions one or more virtual machines on the first one of the nodes, and generates a resource pool from an inventory of the nodes. A payload is provisioned by the fog resource manager on the first one of the nodes based on a request from a virtual resource management module.

Abstract: Examples described herein include systems and methods for providing dynamic serviceability for a software-defined data center (“SDDC”). An example method can include collecting data-center metrics from a management service that monitors the SDDC, filtering the data-center information based on a predetermined list of metrics provided by a partner entity, and translating the filtered data-center information into a partner-specific format requested by the partner entity. The example method can also include generating metadata associated with the translated data-center information and transmitting the metadata and translated data-center information to a partner site associated with the partner entity. If the partner site is not available, the method can include transmitting the information to a partner-accessible storage location and, when the partner site becomes available, identifying the storage location and failed attempt to deliver the information.

Abstract: Methods, apparatus, systems and articles of manufacture to dynamically discover and host services in fog servers are disclosed. An example apparatus includes a service manager to determine that a received service request from an Internet of things (IoT) device is not able to be performed locally at a first fog server; a first interface to transmit the service request to a fog resource manager; and a second interface to transmit instructions to the IoT device to transmit the service request to a second fog server, a response from the fog resource manager including service data related to the second fog server.

Abstract: Embodiments disclosed herein relate to a method, system, and computer-readable medium for monitoring an application executing across a plurality of containers. A performance monitor requests a list of containers created on at least one computing system. The performance monitor retrieves information associated with a creation of each container in the list. The performance monitor parses the information associated with each container in the list to identify a cluster of related containers that are running the applications. The performance monitor displays a topology that relates the containers of the cluster to resources in the at least one computing system. The performance monitor identified a pair of containers that are negatively correlated based on the topology. The performance monitor adjusts the application to remove the negative correlation between the pair of containers.

Abstract: Embodiments of the present disclosure relate to techniques for providing an augmented reality experience. Certain embodiments involve receiving a request from an application to register a context for detection, wherein the context for detection comprises an artifact and a context identifier. Some embodiments involve sending the context for detection to a registration component. The registration component may register the context for detection. Certain embodiments involve receiving context detection information from a client device. Some embodiments involve sending a notification to the application that the context detection information was received. Certain embodiments involve receiving application content and a relative pose of the application content from the application. Some embodiments involve composing a scene based on the application content and the relative pose of the application content and transporting, by the computing device, the scene to the client device.

Abstract: Embodiments of the present disclosure relate to techniques for providing an augmented reality experience for virtual desktops. In particular, certain embodiments relate to acquiring, by a computing device one or more images from a client device and determining, by the computing device, that the one or more images contain an artifact to be augmented. Further, certain embodiments involve acquiring, by the computing device, a screen buffer from a virtual desktop or application running on it and applying, by the computing device, a geometric transformation to the screen buffer. Further, certain embodiments relate to augmenting, by the computing device, the one or more images by inserting the screen buffer onto the artifact, resulting in one or more augmented images. Further, certain embodiments relate to providing, by the computing device, the one or more augmented images to the client device in order to provide a user of the client device with the augmented reality experience.

Abstract: Methods, apparatus, systems and articles of manufacture are disclosed for managing compute resources in a hyperconverged infrastructure computing environment. An example apparatus includes a resource manager table populator to populate a resource management table with information identifying workloads and a workload categorizer to categorize the workloads identified in the resource management table as needy workloads or offering workloads. The disclosed apparatus further include a workload selector to select an offering workload to lend resources to a needy workload, and a resource configurer. The resource configurer to cause a host included in the workload to spin a virtual machine or create a container, and assign the virtual machine or container to support the needy workload.

Abstract: A method, predictive analytics system, and computer program product for performing online and offline learning is provided. The system obtains a first function used to generate a prediction, where the first function was generated from a first set of training data. The system sets a second function as being equal to the first function. The system further collects during an interval a second set of training data. At the end of the interval, the predictive analytics system updates the first function based on the second set of training data. While the first function is being updated, a third set of training data is collected. The system updates the second function while the first function is being updated. The updating of the second function is based on the third set of training data, where the third set of training data is more recent than the second set of training data.