Microsoft Technology Licensing, LLC

Esaias Engelbertus Greeff

Narayanan Ganapathy

Randall Edward Aull

Doron J Holan

James George Cavalaris

Douglas Keith Brubacher

Justin Allen Hutchings

John Lawrence Miller

Samuel David Adams

David Walker Duhon

Arun Babu Nagarajan

Erik O Peterson

Niket Ashok Sanghvi

Robert Franz Hain

J Adrian Lannin

Kyle P Wojtaszek

David Allen Dion

Ajay Mani

Neil Sandlin

Shailesh Padmakar Joshi

Device information for each of multiple devices associated with a user account is maintained by a cloud service. The device information can include credential information allowing the device to be accessed by other ones of the multiple devices, remote access information indicating how the device can be accessed by other ones of the multiple devices on other networks, and property information including settings and/or device drivers for the device. The device information for each of the multiple devices is made available to other ones of the multiple devices, and can be used by the multiple devices to access one another and provide a consistent user experience across the multiple devices.

Cloud-based device information storage

Predicting capacity of shared virtual machine (VM) resources by generating estimated remaining capacities (ERCs) for computing clusters within a virtualization system rather than continuously monitoring actual remaining capacities (ARCs). Generating ERCs for a virtualization system's computing cluster(s) by using physical resource allocation flux data and/or VM type exchange probabilities provides benefits over continuously monitoring ARCs. The physical resource allocation flux data may correspond to commissioning and decommissioning VMs into the cluster and may be obtained during a blind period when current ARCs are unknown. For example, the physical resource allocation flux may be an indication of how many instances of each VM type are commissioned and/or decommissioned from the cluster over a time interval of interest. The VM type exchange probabilities may indicate a likelihood that commissioning or decommissioning a VM type into the computing cluster(s) will take up or free up computing resources available to other VM types, respectively.

Predicting capacity of shared virtual machine resources

According to examples, an apparatus may include a processor and a memory on which is stored machine readable instructions that are to cause the processor to receive an allocation request from an allocator client, determine a resource allocation for the received job allocation request, store a record of the determined resource allocation in a records store, and send the determined resource allocation to the allocator client, in which an acknowledgement to the sent determined resource allocation is to be received from the allocator client. The instructions may also cause the processor to manage a state of the determined resource allocation using the record stored in the records store based on whether the acknowledgement is received from the allocator client.

Resource allocation state management

A computer system that recognizes multi-function devices and associates functions with multi-function devices. Each multi-function device may be represented by a multi-function object, allowing tools, applications or other components within the computer to take actions relating to the entire device or relating to a function based on the association of that function with other functions in the same device. These actions include displaying information about devices, instead of or in addition to information about functions. Actions also include selecting functions based on proximity within a device. Functions may be associated with a multi-function device using a unique device identifier provided by the device or generated for the function based on a connection hierarchy between functions and the computer. Devices may be configured to provide the same identifier regardless of the transport over which the device is accessed.

Multi-function device ID with unique identifier

Device association data for peripheral devices, which is data used to connect to the peripheral devices, is maintained and synchronized across multiple computing devices associated with a user account on a service. When a new peripheral device is associated with a computing device, device association data for the new peripheral device is added to the computing device. The device association data for the new peripheral device is also sent to the service, which provides the device association to the other computing devices from which the user logs into his or her account, and those other computing devices in turn automatically associate themselves with the peripheral device. Device use data describing how a user desires to use the peripheral device on one computing device, as well as changes to the device association data on one computing device, can similarly be synchronized across the multiple computing devices.

Synchronizing device association data among computing devices

Multi-function devices expose multiple functions to device drivers or other lower-level software. Device function providers can interface with such drivers or lower-level software and can provide information, including device identifiers regarding such functions, to a device display object infrastructure. A device display object can then be created that encompasses one or more functions such that, in one embodiment, the device display object corresponds to a single, physical multi-function device. Alternatively, any combination of functionality from one or more physical devices can be combined into a single device display object representing a virtual multi-function device. Properties of the device display object can be set with reference to user-specified settings, remotely maintained metadata, locally available metadata, and information associated with each function. Functions can be ranked such that, if there is a conflict, information from more highly ranked functions is used to set the properties of the device display object.

Device display object infrastructure

Various embodiments utilize information contained in a message, such as addressing and other information, to derive a unique identifier. The unique identifier is then used as a means to route an associated message to an appropriate component for processing. In at least some embodiments, the unique identifier is derived using hash-based techniques which are applied to various portions of the message header. Once the hash-based techniques have been used to produce the unique identifier, the unique identifier can be used in a look up process to look for the appropriate component to which the message is to be routed.

Efficient dispatch of messages based on message headers

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Redmond, WA, United States of America

Esaias Engelbertus Greeff