International Business Machines Corporation

Lenovo (singapore) Pte. Ltd.

Trend Micro Inc.

Ian N Whalley

David Michael Chess

Alla Segal

Malgorzata Steinder

Steve Richard White

William Carlisle Arnold

John Frederick Morar

James Edwin Hanson

Claris Castillo

Murthy V Devarakonda

Jeffrey Owen Kephart

Asser Nasreldin Tantawi

Diana Jeanne Arroyo

Rohith Kottamangalam Ashok

Rajarshi Das

Michael Joseph Spreitzer

Edward Charles Snible

Jian Yin

Gerald James Tesauro

Morton Gregory Swimmer

Rajashi Das

Matthew R Hogstrom

Arun Kwangil Iyengar

Hidayatullah Habeebullah Shaikh

Brian Lee White Eagle

Hoi Yeung Chan

Steven Duane Clay

Sophia Krasikov

Michael Masin

David W Levine

Steve Harris Weingart

Edward John Pring

Sean Leo Dague

Wolfgang Segmuller

Ronald T Goering

Zohar Feldman

Edwin Richie Lassettre

Mike Joseph Spreitzer

Amol P Nayate

Isci Canturk

A system, method and computer program product for detecting data omissions between intermittently-connected devices. An example system includes physical computing resources available for utilization. A placement server communicates with a client. The client seeks to use a portion of the computer resources to execute the software product instances. The placement server receives resource utilization parameters from the client and assigns the portion of the computer resources to the software product instances based on the resource utilization parameters and the physical computing resources available for utilization. The resource utilization parameters include specification of a hierarchal arrangement of the software product instances.

Software product instance placement

Systems and methods for managing a system of heterogeneous workloads are provided. Work that enters the system is separated into a plurality of heterogeneous workloads. A plurality of high-level quality of service goals is gathered. At least one of the plurality of high-level quality of service goals corresponds to each of the plurality of heterogeneous workloads. A plurality of control functions are determined that are provided by virtualizations on one or more containers in which one or more of the plurality of heterogeneous workloads run. An expected utility of a plurality of settings of at least one of the plurality of control functions is determined in response to the plurality of high-level quality of service goals. At least one of the plurality of control functions is exercised in response to the expected utility to effect changes in the behavior of the system.

Management of heterogeneous workloads

Techniques for managing a system of heterogeneous applications are provided. A plurality of applications is classified into a plurality of application types. One or more of the plurality of applications in each of the plurality of application types are classified into one or more collections. A utility function of possible resource allocations is computed for each of the one or more collections. An application placement is computed that optimizes a global utility of the plurality of applications in accordance with the one or more utility functions. Placement and resource allocation of the plurality of applications are modified in the system in accordance with the application placement.

Dynamic placement of heterogeneous workloads

Systems and methods for admission control to a physical host system are provided herein. One aspect provides for receiving at least one resource request at an admission control component of a distributed computing system, the at least one resource request comprised of at least one system type; processing the at least one resource request utilizing at least one physical host accessible to the distributed computing system; specifying a number of resource request slots to be reserved for at least one system type based on at least one future reservation threshold accessible to the admission control component; and blocking resource requests from entering the system through the admission control component based on a number of available resource request slots and the at least one future reservation threshold. Other embodiments and aspects are also described herein.

Host system admission control

A technique is provided for creating virtual units in a computing environment. A virtual system definition is received by a processor that is utilized to create the virtual units for a virtual system. Relationship constraints between the virtual units in the virtual system are received by the processor. The relationship constraints between the virtual units include a communication link requirement between the virtual units and/or a location requirement between the virtual units. The virtual units in the virtual system are deployed by the processor according to the relationship constraints between virtual units.

Integrated virtual infrastructure system

A method for use in a system in which computational entities are distributed across physical computing resources to place the entities on the resources includes estimating actual resource demand for each entity on each resource based on application resource usage data collected from a data source external from the entity, computing a best allocation of the resources to the entities from the estimated actual resource demand for each entity and distributing the resources to the entities in accordance with the computed best allocation.

Virtual machine demand estimation

An exemplary method of allocating a workload among a set of computing devices includes obtaining at least one efficiency model for each device. The method also includes, for each of a set of allocations of the workload among the devices, determining, for each device, the power consumption for the device to perform the workload allocated to the device by the allocation, the power consumption being determined based on the at least one efficiency model for each device; and determining a total power consumption of the devices. The method also includes selecting an allocation of the workload among the devices based at least in part on the total power consumption of the devices for each allocation. The method also includes implementing the selected allocation of the workload among the devices.

Power-aware workload allocation in performance-managed computing environments

Methods and systems are provided for autonomic control and optimization of computing systems. A plurality of component models for one or more components in an autonomic computing system are maintained in a system level database. These component models are obtained from a source external to the management server including the components associated with the models. Component models are added or removed from the database or updated as need. A system level management server in communication with the database utilizes the component models maintained in the system level database and generic component models as needed to compute an optimum state of the autonomic computing system. The autonomic computing system is managed in accordance with the computed optimum state.

Autonomic computing system with model transfer

A method, system and computer program product for storing data in memory. An example system includes at least one multistage application configured to generate intermediate data in a generating stage of the application and consume the intermediate data in a subsequent consuming stage of the application. A runtime profiler is configured to monitor the application's execution and dynamically allocate memory to the application from an in-memory data grid.

Execution of dataflow jobs

Embodiments of the present invention provide a method, data processing system and computer program product for secure distribution of virtualized storage. In an embodiment of the invention, a method for secure distribution of virtualized storage in a host in a cloud computing can include composing at least one virtual machine (VM) disk in a secure container and configured to deploy VM images into a cloud computing environment, encrypting the composed at least one VM disk, transmitting the encrypted VM disk to a hypervisor in the cloud computing environment receiving a request to activate a VM instance and generating a bootloader in the secure container, transmitting the bootloader to the hypervisor in the cloud computing environment and providing a key to the bootloader to unlock the at least one VM disk.

System for securing virtual machine disks on a remote shared storage subsystem

A method, information processing system, and computer readable medium for managing virtual machine imaging. The method includes receiving a request for an imaging operation associated with at least one virtual machine. A notification is sent to at least one operating system associated with the at least one virtual machine of the request for the imaging operation. The operating system is determined to be in a state for the virtual machine to be imaged. The request for the imaging operation is granting in response to determining.

Hypervisor with cloning-awareness notifications

A system, computer program and method for inspection of a system under inspection. The system may include an inspection program configured to access information available at the system under inspection and generate inspection data for the system under inspection. A runtime platform independent from the inspection program at the system under inspection is configured to limit the limit the contents of the inspection data to a maximum information content. A trusted third-party computer system may assist in selecting the inspection program and transferring the resulting inspection data.

Computer system evaluation

Systems and methods are provided for dynamically controlling application placement and server resource allocation in a distributed system wherein a performance manager and power manager collaborate during run-time execution of data processing tasks to coordinate management and control of workload placement and server usage and dynamically determine a tradeoff between performance level and power usage that meets power and performance objectives.

Systems and methods for coordinated management of power usage and runtime performance in performance-managed computing environments

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Pawling, NY, United States of America

Ian N Whalley