Microsoft Technology Licensing, LLC

Microsoft Corporation

Efstathios Papaefstathiou

Jonathan C Hardwick

Pavel Anatolievich Dournov

John Morgan Oslake

Russell Irvin Sanchez

Nathaniel Terrell Clinton

Glenn R Peterson

Malek M Chalabi

Anthony Baron

Michael D Lubrecht

Kathryn A Pizzo

Andrew Savvides

Galen Clyde Hunt

Robert M Fries

Robert Victor Welland

Bassam Tabbara

Ashvinkumar J Sanghvi

Christopher Wellington Brumme

Aamer Hydrie

Rene Antonio Vega

Raymond W McCollum

Anders Bertil Vinberg

Geoffrey Hugh Outhred

Ashok Kuppusamy

Raymond Edward Endres

John M Parchem

Vij Rajarajan

Sean Edwin Trowbridge

Eric D Rudder

Jean Sebastien Fouillade

David Edward Guimbellot

Jinsong Yu

David C James

Rob M Mensching

Vitaly Voloshin

Michael Joseph Healy

Bruce Wayne Copeland

Eric Dean Tribble

Paul Barham

John H Wilson

Mazhar Naveed Mohammed

Rebecca Isaacs

Eric Joseph Winner

Rajagopalan Badri Narayanan

Anand Lakshminarayanan

Stanislav A Oks

Jeffrey A Woolsey

Edwin R Lassettre

Kevin D J Grealish

Zhengkai Kenneth Pan

Quanzhan Zheng

Ravi Pandya

Russel Sanchez

David Bartholomew Stewart

Glenn F LaVigne

Initial interaction between a mobile robot and at least one user is described herein. The mobile robot captures several images of its surroundings, and identifies existence of a user in at least one of the several images. The robot then orients itself to face the user, and outputs an instruction to the user with regard to the orientation of the user with respect to the mobile robot. The mobile robot captures images of the face of the user responsive to detecting that the user has followed the instruction. Information captured by the robot is uploaded to a cloud-storage system, where information is included in a profile of the user and is shareable with others.

Interactive robot initialization

There is provided a device such as a robot that includes a processor and a number of sensors. Each of the sensors provides respective sensor data to the processor. The sensor data from each sensor is indicative of corresponding characteristics of an environment of the device. A memory includes a security mode component that is executable by the processor and is configured to cause the device to autonomously navigate at least a portion of the environment. A detection component executable by the processor is configured to detect an unusual condition in the environment.

Nomadic security device with patrol alerts

There is provided a robot that includes a processor executing instructions that determine a desired image to be displayed. The processor issues control signals corresponding to the desired image to be displayed. The robot also comprises a display assembly including a visual projector, a mirror, and a display surface. The visual projector and mirror are disposed within the robot. The visual projector projects light corresponding to the desired image onto the mirror. The mirror receives the light from the projector, and reflects the light onto the display surface. The display surface receives the light. The image is visible on the display surface from outside the robot.

Illuminated skin robot display

A mobile image processing manager may include an image data receiving engine configured to obtain a first set of three-dimensional (3-D) image data associated with an observation environment. The mobile image processing manager may also include a navigational plan engine configured to determine a navigational plan based on the first set. A navigation manager may be configured to initiate a navigation event based on the navigational plan. A scene determination engine may be configured to determine a first group of one or more graphical images. An image projection engine may be configured to initiate a display of the first group on a first surface, the display based on a light source.

Mobile platform for augmented reality

The subject disclosure is directed towards a robot device including a computational intelligence system that can be coupled to/decoupled from different interchangeable mobility mechanisms at different times. The robot may operate with its intelligence portion detached from the mobility portion, whereby the intelligence portion may be easily to interact therewith out lifting the (typically dirty) mobility mechanism. The robot may operate according to a coupled state, a decoupled state, or in a transition state when being moved for purposes of coupling or decoupling.

Robotic drive system modularity

The present invention extends to methods, systems, and computer program products for protected mode scheduling of operations. Protected mode (e.g., user mode) scheduling can facilitate the development of programming frameworks that better reflect the requirements of the workloads through the use of workload-specific execution abstractions. In addition, the ability to define scheduling policies tuned to the characteristics of the hardware resources available and the workload requirements has the potential of better system scaling characteristics. Further, protected mode scheduling decentralizes the scheduling responsibility by moving significant portions of scheduling functionality from supervisor mode (e.g., kernel mode) to an application.

Protected mode scheduling of operations

Simulating an application. A method that may be practiced in a computing environment configured for simulating an application modeled by an application model deployed in a performance scenario of a computing system by deploying service models of the application model to device models modeling devices. The method includes referencing a performance scenario to obtain a transaction being modeled as originating from a first device model. The transaction invokes of a first service model. The first service model specifies hardware actions for simulation. The first service model is referenced to determine the hardware actions for simulation and the next referenced service. The next referenced service specifies hardware actions to be added to the transaction and may specify invocation of other service models. A chain of hardware actions is generated by following the invocation path of the service models. The hardware actions are applied to device models to simulate the transaction.

Dynamic software performance models

A prescribed system architecture is recommended to an entity that desires to implement a system supporting distributed applications. A performance scenario is created based on anticipated usage, devices employed by servers running the distributed applications, and topology of locations using the servers. An optimized scenario may be provided by determining device optimization, different use load, and if possible consolidation of distributed applications on servers.

Prescriptive architecture recommendations

A computing system for determining performance factors for using in performance modeling of a deployed subject system, is presented. The computing system includes a plurality of software components comprising the subject system. Each of the components is susceptible to event tracing while executing on the computing system. The computing system includes a tracing component. The tracing component is configured to trace events of the components of the subject system as they execute. The computing system includes a transaction identification table. The transaction identification table comprises starting and ending actions for transactions performed by the subject system. The computing system also includes a transaction identification component that identifies actions from traced events, identifies related actions corresponding to a transaction according to the starting and ending actions in the transaction identification table, and stores the related actions in the transaction workflow data store.

Generating static performance modeling factors in a deployed system

In one aspect, a method of instructing at least one operator in a best practices implementation of a process for managing resource capacity in an information technology (IT) environment is provided. The method comprising providing instructions to the at least one operator to perform acts of: (A) creating at least one model of at least some aspects of the IT environment; (B) analyzing the at least one model to determine cost information relating to the modeled IT environment; (C) applying at least one simulated use condition to the at least one model; (D) analyzing performance of the at least one model under the at least one simulated use condition to determine information relating to at least a utilization of resources in the modeled IT environment and to determine resources in the modeled IT environment that create performance bottlenecks in the modeled IT environment; and (E) modifying at least one aspect of the at least one model impacting resource capacity based on the information determined in (B) and/or (D).

Methods for capacity management

In accordance with certain aspects of the model-based policy application, each of a plurality of policies is associated with appropriate parts of a model of a heterogeneous system. A deployment agent is invoked to apply each of the plurality of policies to components associated with the parts of the model. An identification of a change to one of the plurality of policies is received, and the deployment agent is also invoked to apply the changed policy to selected ones of the components associated with the parts of the model.

Model-based policy application

A performance prediction simulator gives effect to the resource contention among multiple resources in a simulated system by adjusting event durations appropriately. A resource topology tree defining the resource configuration of the system is input to the simulator. The simulator includes an evaluation engine that determines the amount of resource used during each simulation interval of the simulation and records the resource usage in a resource contention timeline, which can be displayed to a user. The amount of resource used during a simulation is also used to adjust the event duration calculations of the hardware models associated with each event.

Evaluating hardware models having resource contention

Simulating device interactions. A method may be practiced in a computing system for simulating interconnected devices. The method of simulating device interactions may be done in performing an overall transaction to obtain an output of system performance characteristics including measurement of latencies and/or device loads for actions performed by devices in performing the overall transaction. The method includes dividing a transaction into individual actions. The actions are applied to appropriate device models to produce latencies and/or device utilizations for the action as applied to the appropriate device model. This may be done by including an indication of an action type and optionally an action subservice. Memory resources may be conserved by ending the simulation when latencies and/or device utilizations have settled. Device utilization and latency may be aggregated and averaged over time. When changes in the latencies and/or device utilizations are within a predetermined range, the simulation can be ended.

Simulation of connected devices

Methods for managing capacity

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Redmond, WA, United States of America

Efstathios Papaefstathiou