Abstract: An adaptive virtual desktop architecture is provided. Application install or assignment is evaluated, such as by using heuristics to identify applications that may present compatibility problems. Upon determining that a newly installed application may have compatibility problems when associated with a non-persistent virtual desktop, a promotion to a persistent virtual desktop occurs.

Abstract: An adaptive virtual desktop architecture is provided. Application install or assignment is evaluated, such as by using heuristics to identify applications that may present compatibility problems. Upon determining that a newly installed application may have compatibility problems when associated with a non-persistent virtual desktop, a promotion to a persistent virtual desktop occurs.

Abstract: Documents or other files opened on a remote desktop are mirrored onto a mobile client device that allows a user to seamlessly work on such documents or files in either a stationary or mobile fashion. The mirrored files may be presented to the user on the mobile client device with the capacity for the user to sign his or her name—or otherwise mark—the mirrored document on the client device. Once signed, various techniques are executed that cause the signed version of the mirrored files to be communicated back to the remote desktop where the signed files are saved. Such techniques may operate transparent to a user, eliminating the need for the user to constantly have to save and transport signed files between multiple devices when working on the go.

Abstract: User interface virtualization describes a technique for providing a user with access to one computing device from another computing device, while translating the ergonomics of one computer's user interface style into the ergonomics of the other's. An agent running on a remote desktop exchanges metadata and input events with a corresponding client running on a client device that accepts a “touch and swipe” style input. The agent running on the remote desktop may use an interface interaction API or software framework to programmatically manipulate the user interface of the remote desktop and act as a proxy for the corresponding client. The client constructs and displays native graphical user interface elements at the client device that are virtual representations of a corresponding user interface element at the remote desktop, including file dialogs, clipboards, start menus, and task switchers.

Abstract: Methods, computer-readable storage medium, and systems described herein facilitate provisioning a virtual desktop infrastructure having virtual shared storage. A provisioning manager receives a desktop pool type and provisions virtual shared storage among a cluster of hosts. The provisioning manager configures the virtual shared storage based on the desktop pool type and provisions at least one virtual machine to each host in the cluster of hosts. The provisioning manager optimizes the virtual shared storage by receiving a storage performance benchmark from each host and performing an optimization on the cluster of hosts if the storage performance benchmark results do not meet a threshold within a pre-defined tolerance.

Abstract: Embodiments provision and customize virtual machines (VMs), such as desktop VMs, without rebooting the desktop VMs. In response to a request to provision the VMs, a computing device creates a clone VM from a parent VM template identified in the request. One or more customization that prompt rebooting of the clone VM are applied to the clone VM. The computing device instantiates a plurality of child VMs from the customized clone VM. A child VM configuration is applied to at least one of the instantiated child VMs without provoking a reboot of those child VMs.

Abstract: Aspects of the disclosure allocate shares of processing resources or other physical resources among virtual machines (VMs) operating as, for example, virtual desktops on a plurality of host computing devices. Allocations of resources are adjusted based on the user activity, VM activity, and/or application activity detected by an agent executing on each VM. Allocated shares may be boosted, unboosted, or normalized, depending on the type and duration of detected activity, by a resource allocation manager executing on a management server.

Abstract: Examples perform creation of a non-persistent virtual machine with a persistent machine identity associated with the user of the virtual machine, to provide consistent virtual desktop sessions to the user. Some examples contemplate that the machine identity is inserted into a virtual machine created through cloning, forking, or from a virtual machine pool.

Abstract: Examples quickly suspend and resume virtual desktops on demand or on schedule. Virtual desktops, or desktops as a service, are provided to users, where the virtual desktop is a forked VM, cloned VM, or otherwise at least a partial duplicate of an existing VM. The virtual desktop points to existing memory maintained by the existing VM, and the virtual desktop only writes to memory the pages that the virtual desktop creates or modifies.

Abstract: The current document is directed a resource-exchange system that facilitates resource exchange and sharing among computing facilities. The currently disclosed methods and systems employ efficient, distributed-search methods and subsystems within distributed computer systems that include large numbers of geographically distributed data centers to locate resource-provider computing facilities that match the resource needs of resource-consumer computing-facilities based on attribute values associated with the needed resources, the resource providers, and the resource consumers. Nested-hypervisor technology is employed, in disclosed implementations, to guarantee data security for, and prevent monitoring of operational states and characteristics of, resource-consumer virtual machines and virtual applications while they execute above leased computational resources in remote computing facilities.

Abstract: Aspects of the disclosure allocate shares of processing resources or other physical resources among virtual machines (VMs) operating as, for example, virtual desktops on a plurality of host computing devices. Allocations of resources are adjusted based on the user activity, VM activity, and/or application activity detected by an agent executing on each VM. Allocated shares may be boosted, unboosted, or normalized, depending on the type and duration of detected activity, by a resource allocation manager executing on a management server.

Abstract: Examples described herein enable memory state sharing among a plurality of virtual machines (VM) including a parent VM and a child VM. A request for memory state sharing between the parent VM and the child VM is received, and the parent VM is suspended. The child VM resumes execution of one or more suspended applications. In one example, the child FM is forked with pre-loaded, suspended applications from the parent VM. Aspects of the disclosure offer a high performance, resource efficient solution that outperforms traditional approaches in areas of software compatibility, stability, quality of service control, re-source utilization, and more.

Abstract: An adaptive virtual desktop architecture is provided. Application install or assignment is evaluated, such as by using heuristics to identify applications that may present compatibility problems. Upon determining that a newly installed application may have compatibility problems when associated with a non-persistent virtual desktop, a promotion to a persistent virtual desktop occurs.

Abstract: Embodiments of a system and method for identifying and prioritizing company prospects by training at least one classifier on client company win/loss metrics. One or more classifiers can be trained on a training database compiled from company win/loss database for a client and firmographic data from a robust business entity database. Once trained, the system can employ Artificial Intelligence powered by the trained classifiers to classify and output customized prospect lists of thousands of profiled and scored companies that the AI has determined are likely targets for specific marketing and sales. The AI can also ingest databases of client targets and classify and score them based on the custom-trained classifier.

Abstract: The current document is directed a resource-exchange system that facilitates resource exchange and sharing among computing facilities. The currently disclosed methods and systems employ efficient, distributed-search-based auction methods and subsystems within distributed computer systems that include large numbers of geographically distributed data centers to locate resource-provider computing facilities that match the resource needs of resource-consumer computing facilities. Multiple security methods and subsystems are employed to prevent unauthorized access to resource-exchange-system services, to secure resource-exchange-system-participant data from unauthorized access, and to prevent hosted virtual machines and other hosted computational entities from interfering with operation of native virtual machines and other native computational entities within hosting resource-provider computing facilities.

Abstract: The current document is directed a resource-exchange system that facilitates resource exchange and sharing among computing facilities. The currently disclosed methods and systems employ efficient, distributed-search-based auction methods and subsystems within distributed computer systems that include large numbers of geographically distributed data centers to locate resource-provider computing facilities that match the resource needs of resource-consumer computing facilities. In one implementation, the resource-exchange system continuously collects communications-latency data for pairs of resource-exchange participants, in order to support latency constraints associated with potential resource exchanges. The collected data facilitates efficient, rapid, automated candidate-resource-provider selection during auction-based matching of resource consumers to resource providers.

Abstract: The current document is directed a resource-exchange system that facilitates resource exchange and sharing among computing facilities. The currently disclosed methods and systems employ efficient, distributed-search methods and subsystems within distributed computer systems that include large numbers of geographically distributed data centers to locate resource-provider computing facilities that match the resource needs of resource-consumer computing-facilities based on attribute values associated with the needed resources, the resource providers, and the resource consumers. The resource-exchange system monitors and controls resource exchanges on behalf of participants in the resource-exchange system in order to optimize resource usage within participant data centers and computing facilities.

Abstract: The current document is directed a resource-exchange system that facilitates resource exchange and sharing among computing facilities. The currently disclosed methods and systems employ efficient, distributed-search methods and subsystems within distributed computer systems that include large numbers of geographically distributed data centers to locate resource-provider computing facilities that match the resource needs of resource-consumer computing-facilities based on attribute values associated with the needed resources, the resource providers, and the resource consumers. The resource-exchange system monitors and controls resource exchanges on behalf of participants in the resource-exchange system in order to optimize resource usage within participant data centers and computing facilities.

Abstract: The current document is directed to efficient, distributed-search methods and subsystems within distributed computer systems, including computer systems distributed over multiple sets of geographically distributed data centers, each comprising multiple discrete computer systems, such as multi-processor servers. In one implementation, the distributed-search methods and subsystems are implemented locally within participating entities as well as within one or more distributed-search engines. Each search is directed, by a participant, to identify attribute-associated entities within, provided by, connected to, or otherwise accessible to a distributed computing system having attribute values specified or indicated by the search query. Certain attribute values are continuously collected and centrally stored by the one or more centralized distributed-search engines while other attribute values are obtained through information requests distributed among participating entities.

Abstract: The current document is directed to efficient, distributed-search methods and subsystems within distributed computer systems, including computer systems distributed over multiple sets of geographically distributed data centers, each comprising multiple discrete computer systems, such as multi-processor servers. In one implementation, the distributed-search methods and subsystems are implemented locally within participating entities as well as within one or more distributed-search engines. Each search is directed, by a participant, to identify attribute-associated entities within, provided by, connected to, or otherwise accessible to a distributed computing system having attribute values specified or indicated by the search query. Certain attribute values are continuously collected and centrally stored by the one or more centralized distributed-search engines while other attribute values are obtained through information requests distributed among participating entities.