Microsoft Technology Licensing, LLC

Webtv Networks, Inc.

Webtv Newtorks, Inc.

Digital Equipment Company

John M Parchem

Robert M Fries

Galen Clyde Hunt

Robert Victor Welland

Michael Richard Fortin

Jun Liu

Bassam Tabbara

Rene Antonio Vega

Aamer Hydrie

Anders Bertil Vinberg

Geoffrey Hugh Outhred

Clark David Nicholson

Soemin Tjong

Rob M Mensching

Eric Joseph Winner

Dean L DeWhitt

Jeffrey A Woolsey

William Jefferson Westerinen

Cenk Ergan

Michael James Zwilling

Mark Joseph Zbikowski

Hanumantha Rao Kodavalla

Nathan Steven Obr

Kevin Grealish

Daniel J Shoff

Patrick L Stemen

Rajeev Y Nagar

Therron Powell

Edwin R Lassettre

Surenda Verma

Dan Teodosiu

Emily Nicole Hill

Sean McGrane

Sureshkumar Natarajan

Carl Melvin Ellison

Stephen Berard

Ashvinkumar J Sanghvi

Raymond W McCollum

Charles Patrick Thacker

David N Cutler

Vij Rajarajan

David C James

Efstathios Papaefstathiou

Emily Nicole Wilson

Vitaly Voloshin

Darrel D Donaldson

Bruce Wayne Copeland

Michael Joseph Healy

David A Orbits

Douglas D Williams

Robert T Short

John H Wilson

Mazhar Naveed Mohammed

Jonathan C Hardwick

Matthew H Holle

Rajagopalan Badri Narayanan

Anand Lakshminarayanan

Vladimir Rovinsky

Zhengkai Kenneth Pan

Kevin D J Grealish

W Jeff Westerinen

Mark N Howard

Przemek Pardyak

Daniel Teodosiu

David M Robinson

Dean L Dewhitt

Model-based virtual system provisioning includes accessing a model of a workload to be installed on a virtual machine of a system as well as a model of the system. A workload refers to some computing that is to be performed, and includes an application to be executed to perform the computing, and optionally includes the operating system on which the application is to be installed. The workload model identifies a source of the application and operating system of the workload, as well as constraints of the workload, such as resources and/or other capabilities that the virtual machine(s) on which the workload is to be installed must have. An installation specification for the application is also generated, the installation specification being derived at least in part from the model of the workload and the model of the virtual system.

Model-based virtual system provisioning

In order to provide a more efficient persistent storage device, one or more long-term storage media are included along with a non-volatile memory. In one embodiment, one portion of the non-volatile memory is used as a write buffer and a read cache for writes and reads to the long-term storage media. Interfaces are provided for controlling the use of the non-volatile memory as a write buffer and a read cache. Additionally, a portion of the non-volatile memory is used to provide a direct mapping for specified sectors of the long-term storage media. Descriptive data regarding the persistent storage device is stored in another portion of the non-volatile memory.

Non-volatile memory cache performance improvement

Messages, including messages in conformance with various protocols, can be hashed and the hash values added to an event log and provided to a Trusted Platform Module (TPM), which can extend one or more Platform Configuration Registers (PCRs) with the hash value, much as it would with the hash of a component that was installed or executed on the computing device with the TPM. Subsequently, the TPM can sign one or more of the PCRs and the signed PCRs can be transmitted, together with the event log and a copy of the messages. The recipient can verify the sender based on the signed PCRs, can confirm that the signed PCRs match the event log, and can verify the hash of the message in the event log by independently hashing it. In another embodiment, an intermediate hashing of the message can avoid transmission of potentially malicious executable instructions within a message.

Protocol-Independent remote attestation and sealing

Computer-executable instructions can implement a software-based Trusted Platform Module (TPM) that can have more computational power than the hardware TPM. The software TPM can be protected from modification, or other unauthorized access, via a memory partitioning scheme that enables other computer-executable instructions to access the software TPM in a predefined manner, but yet prohibits other access. A tri-partied partitioning scheme can be used wherein the computer executable instructions of the software TPM reside in a first region, a jump table to appropriate ones of those instructions resides in a second region, and everything else resides in the third region. The storage key of the software TPM can be sealed by the hardware TPM to be released only if the software TPM, and the computing device, are in a known good state, as determined by the Platform Configuration Registers of the hardware TPM, thereby further protecting the software TPM from tampering.

Software enhanced trusted platform module

A plurality of power budgets are sent to a corresponding plurality of power consumers by a power management point, wherein a total power budget managed by the power management point includes a sum of the plurality of power budgets and an available power budget not assigned to the plurality of power consumers. An additional power request having a power increase amount is received from a first power consumer of the plurality of power consumers. The additional power request is approved when the power increase amount does not exceed the available power budget. The available power budget is decreased by the power increase amount. An approval of the additional power request is sent to the first power consumer.

Collaborative power sharing between computing devices

Model-based provisioning of test environments includes accessing a model of an application to be installed in a test environment of a system and further accessing a model of the system and a model of the test environment. An installation specification for the application is also generated, the installation specification being derived at least in part from the model of the application, the model of the system, and the model of the test environment.

Model-based provisioning of test environments

Aspects of the subject matter described herein relate to a data structure for budgeting power for multiple devices. In aspects, devices are allotted a power budget. The devices are each capable of operating at one or more power levels. A console queries the devices to obtain the power capabilities of the devices. The console stores the power capabilities in a data structure. The data structure together with the power budget may then be used to instruct each device to operate at a particular power level. The data structure includes fields for storing power levels for the devices as well as fields that associate the power levels with the devices. In addition, the data structure includes a group field that associates the devices with the power budget.

Data structure for budgeting power for multiple devices

Aspects of the subject matter described herein relate to using priorities and power usage to allocate power budget to devices. In aspects, a console that maintains power usage, priorities, and other power data regarding a set of devices may receive a notification that a device has exceeded its budgeted power. In response, using priorities and power usage associated with the devices, the console determines one or more devices to instruct to use less power. A device that exceeded its budgeted power may be instructed to operate at a lower power level or another device (e.g., a lower priority device that is underutilizing its budgeted power) may be instructed to reduce its power to remain below a power budget for the set of devices.

Using priorities and power usage to allocate power budget

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

Growing community of inventors

Seattle, WA, United States of America

John M Parchem