International Business Machines Corporation

James Edwin Hanson

Jeffrey Owen Kephart

Ian N Whalley

Malgorzata Steinder

David Michael Chess

Rajarshi Das

Canturk Isci

Steve Richard White

Hoi Yeung Chan

David W Levine

Hidayatullah Habeebullah Shaikh

Alla Segal

Jian Yin

Gerald James Tesauro

Rajashi Das

Asser Nasreldin Tantawi

Daniel Manuel Dias

Alberto Giammaria

Giovanni Pacifici

Michael Joseph Spreitzer

John Frederick Morar

Sophia Krasikov

Diana Jeanne Arroyo

Wolfgang Segmuller

Claris Castillo

Robert L Orr

Isci Canturk

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

A system method and computer program product for managing readiness states of a plurality of computing devices. In response to a request, a computer system operates to either: provide one or more computing devices from an inactive pool to an active pool, or accept one or more active computing devices into the inactive pool. An Inactive Pool Manager proactively manages the inactive states of each computing device by: determining the desired number (and identities) of computing devices to be placed in each inactive state of readiness by solving a constraint optimization problem that describes a user-specified trade-off between expected readiness (estimated time to be able to activate computing devices when they are needed next) and conserving energy; generating a plan for changing the current set of inactive states to the desired set; and, executing the plan. Multiple alternative ways of quantifying the desired responsiveness to surges in demand are provided.

Saving power by managing the state of inactive computing devices according to specific constraints

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

Managing readiness states of a plurality of computing devices. A programmed processor unit operates, upon receipt of a request, to: provide one or more computing devices from an inactive pool to an active pool, or accept one or more active computing devices into the inactive pool. The system proactively manages the inactive states of each computing device by: determining the desired number (and identities) of computing devices to be placed in each inactive state of readiness by solving a constraint optimization problem that describes a user-specified trade-off between expected readiness (estimated time to be able to activate computing devices when they are needed next) and conserving energy; generating a plan for changing the current set of inactive states to the desired set; and, executing the plan. Multiple alternative ways of quantifying the desired responsiveness to surges in demand are provided.

Method for saving power in a system by placing inactive computing devices in optimized configuration corresponding to a specific constraint

A system method and computer program product for managing readiness states of a plurality of computing devices. A programmed processor unit operates, upon receipt of a request, to either: provide one or more computing devices from an inactive pool to an active pool, or accept one or more active computing devices into the inactive pool. An Inactive Pool Manager proactively manages the inactive states of each computing device by: determining the desired number (and identities) of computing devices to be placed in each inactive state of readiness by solving a constraint optimization problem that describes a user-specified trade-off between expected readiness (estimated time to be able to activate computing devices when they are needed next) and conserving energy; generating a plan for changing the current set of inactive states to the desired set; and, executing the plan. Multiple alternative ways of quantifying the desired responsiveness to surges in demand are provided, and, in each case, the tradeoff between responsiveness and power savings is formulated as an objective function with constraints, and the desired number of devices in each inactive state emerges as the solution to a constraint optimization problem.

Saving power by placing inactive computing devices in optimized configuration corresponding to a specific constraint

Upgrading a multi-tiered application is provided. In response to receiving a request to upgrade a multi-tiered application, wherein components of the multi-tiered application are deployed across a plurality of virtual machines, an appropriate integrated patch is selected for the upgrade. The selected integrated patch includes an integrated set of patches for the components of the multi-tiered application, state update data, and order constraints. The components of the multi-tiered application specified in the selected integrated patch are upgraded by using the integrated set of patches and order constraints. In addition, the state of the components of the multi-tiered application are updated by using the state update data. Then, the updated state of the multi-tiered application is saved to storage.

Upgrading virtual resources

A computer implemented method, data processing system, and computer usable program code are provided for creating a set of virtual machine image for software. A virtual software resource template is retrieved. Metadata associated with the virtual software resource template is copied and the copy of the metadata is modified to generate personalized metadata for each virtual machine image in the set of virtual machine images. Then, the set of virtual machine images is deployed using the personalized metadata.

Virtual resource templates

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

In one aspect this invention provides a data processing system () that includes a plurality of self-organizing software agents () capable of autonomously establishing relationships between themselves, where the totality of the relationships can be represented by a topological structure having nodes that each contain one of the plurality of software agents and links between the nodes that are the established relationships. The data processing system further includes a topology tuning function that obtains information that is descriptive of the topology and, based at least in part on the obtained information and on at least one criterion, that makes a recommendation to at least one of the plurality of software agents that is intended to modify the topology. In one embodiment the topology tuning function is performed by a topology tuner software agent (), while in another embodiment the topology tuning function forms a part of a system hosting function, such as a part of the operating system of the system ().

Dynamically tuning networks of relationships in self-organizing multi-agent systems

An apparatus, system and method for automatically making operation selling decisions are provided. The apparatus, system and method make use of selling policy rules established by human operators associated with a firm to guide the making of decisions to sell products and/or services. The actual decisions to sell are made automatically by the system without requiring human intervention. The decisions to sell are made by negotiating terms of sale with a customer using history information, exogenous preference information, information obtained from third parties, and the like. An initial offer of sale is provided to a customer who may then elect to modify the terms of sale of the product or service. If the customer elects to modify the terms of sale of the product or service, a negotiation engine of the present invention may automatically provide counteroffers to offers made by the customer until acceptable terms of sale are agreed upon. The negotiation with the customer occurs within the framework established by the selling policy rules established by the human operators. Because the actual decisions are performed automatically without human intervention, the decisions may be made much more quickly than would have been done by a human being.

Apparatus, system and method for automatically making operational selling decisions

A method, computer program product, and data processing system for circumventing profiling and targeting of World Wide Web users is disclosed. A number of fictitious web 'personae' are established. A user wishing to perform a particular web transaction assumes a persona that best fits the user's current needs. The user's actions are then attributed to the persona, rather than the user. When the user wishes to perform another transaction, a different persona may be assumed, depending upon the circumstances, so that any disadvantage attributable to performing the same web transaction multiple times may be eliminated. This has the dual advantage of both protecting the user's privacy and taking advantage of special offers and incentives that may be targeted to first-time customers.

Strategic internet persona assumption

A method and system for searching for software agents or directory service agents in a distributed environment. The system employs a plurality of host computers that include software agents and/or directory service agents and that are connected to a network. The method as invoked at one of the host computers searches for other agents with a recursive search that enables one agent to locate other agents that match a given criteria. The recursive search may use cross-listed directory services, negotiated cross-listings and economic considerations.

Growing community of inventors

Yorktown Heights, NY, United States of America

James Edwin Hanson