Hewlett-packard Development Company, L.p.

Cipriano A Santos

Dirk Manfred Beyer

Arif Abdulhusein Merchant

Xiaoyun Zhu

Kimberly Keeton

Alex Xin Zhang

Shailendra K Jain

John Wilkes

Sharad Singhal

Xin Zhang

Jeffrey Scott Chase

Maria Teresa Gonzalez Diaz

Ernesto Brau

Evan Randy Kirshenbaum

Robert E Tarjan

Jerry Zhaolin Shan

Hsiu-Khuern Tang

Terence Patrick Kelly

Mathias Salle

Akhil Sahai

Fereydoon Safai

Yunhong Zhou

Kay-Yut Chen

Pankaj K Garg

Hsiu-Khuem Tang

Qi Feng

Lyle H Ramshaw

Harlan Crowder

Ivan Adrian Lopez Sanchez

Andrei Fuciec

Joachim Resch

Bilal Iqbal

Marcos Cesar Vargas-Magana

Carlos Valencia

Ivan Lopez-Sanchez

Glenn W Herrick

Mark D Raper

A report indicating a user-reported probability of a successful outcome is received. A behavior and information model is estimated based on the report. The behavior and information model includes a behavior model component having a bias parameter and a consistency parameter. The behavior and information model includes an information model component having a first user-believed probability of a successful outcome and a second user-believed probability of a successful outcome. The behavior and information model is used to yield a model-determined probability of a successful outcome that more accurately reflects a probability of a successful outcome than the user-reported probability of a successful outcome does.

Behavior and information model to yield more accurate probability of successful outcome

A tool receives parameters relating to target enterprise objective of an enterprise, the cost of an enterprise resource associated with the enterprise, and an enterprise resource capacity. The tool calculates an amount of an enterprise resource to be assigned in an enterprise based on the received parameters relating to the target enterprise objective, the enterprise resource cost, and the enterprise resource capacity.

Calculating an amount of enterprise resource to be assigned based on received parameters

A method and system for selection of a task in proportion to a desired distribution. Specifically, in one embodiment, the present invention discloses a method and system for selecting a task associated with a visiting customer to a web site over a communication network. The customer is assigned to a segment of a target customer base that most closely resembles the customer's characteristics. A plurality of tasks is associated with the segment and can be expressed as a distribution of tasks performed. A current distribution of tasks is determined. The task which provides a new distribution that is closest to a desired distribution of the plurality of tasks is selected to be performed. In one embodiment, the task to be performed is the offering of an advertising promotion to the customer over the communication network.

Method and system for deterministic sampling with a specific distribution

A method for cost entity matching can include constructing a first graph including a number of first entities and a number of second entities, and assigning a number of first cost values to each of a number of first edges connecting one of the number of first entities to one of the number of second entities in the first graph; adding a second graph to the first graph, wherein the second graph includes the number of first entities and the number of second entities, and assigning a second cost value to each of a number of second edges connecting one of the number of first entities in the first graph to the corresponding first entity in the second graph; and, matching each one of the number of second entities to one of the number of first entities based on the number of first cost values and the second cost values.

Cost entity matching

A method and system of workforce related resource planning is disclosed. The method includes receiving workforce related resource data wherein the workforce related resource data includes demand data and supply data, disaggregating the demand data and the supply data and creating a probability distribution of a workforce gap between the demand data and supply data to quantify risk associated with workforce related resource planning.

Method and system for workforce related resource planning

A method includes receiving flight leg data and dispatcher position data for a planning horizon and identifying cycle flight legs and extraordinary flight legs based on the flight leg data. The method includes allocating each cycle flight leg to at least one dispatcher position while minimizing workload deviations between the dispatcher positions. The method includes allocating, after allocating each cycle flight leg, each extraordinary flight leg to at least one dispatcher position while minimizing workload deviations between the dispatcher positions.

Allocation of flight legs to dispatcher positions

A method of managing product end of life over an end of life horizon includes the step of selecting an objective of either maximizing gross profit or minimizing writeoff costs for a selected plurality of products being discontinued. The products may have parts in common. A subset of all possible combinations of product demand levels is selected. Each combination is associated with a probability. A procurement plan that optimizes the selected objective is generated based on the selected subset of demand levels given a non-zero pre-existing inventory of at least some parts of the selected products.

Method and apparatus for managing product end of life

An embodiment of a method of scheduling computer processing begins with a first step of receiving job properties for a plurality of jobs to be processed in a multi-processor computing environment. At least some of the jobs each comprise a plurality of stages, one or more tasks for each stage, and precedence constraints among the stages. The method continues with a second step of determining a schedule for processing at least a subset of the plurality of jobs on processors within the multi-processor computing environment from a solution of a mathematical program that provides a near maximal completion reward. The schedule comprises a sequence of tasks for each processor. In a third step, the computer processing jobs are processed on the processors according to the sequence of tasks for each processor.

Scheduling computer processing jobs that have stages and precedence constraints among the stages

A method is disclosed for evaluating the performance of a website. An agent interacts with the website using a behavior model of an exemplary website customer. The agent interacts with the website according to the behavior model and gathers website performance data related to the interaction. The performance data is compared to a utility function for the behavior model. A rating is assigned to the website based on the comparison, and the rating is made available to potential website customers seeking information related to the website's performance.

Method and system for evaluating performance of a website using a customer segment agent to interact with the website according to a behavior model

In at least some embodiments, a method comprises computing an initial schedule of jobs to be run on a computing system using a mathematical program and monitoring the computing system. The method also comprises, based on the monitoring, determining, using the mathematical program used to compute the initial schedule, whether the initial schedule should be re-computed.

Job scheduling system and method

Embodiments of the present invention relate to a system and method for allocating resources to applications. One embodiment of the present invention may include identifying a plurality of applications and a plurality of application components, and determining available resources of a networked computing system for potentially storing the applications and application components. Additionally, the embodiment may include determining required resources for each application component, assigning a subset of available resources for each application component based on the required resources of the application component and the available resources. The embodiment may also include associating the application components with the subsets of available resources and storing more than one application component of the plurality of application components on a single available resource.

System and method for assigning an application component to a computing resource

Embodiments of the present invention relate to a system and method for assigning resources to an application component. One embodiment of the present invention includes identifying an application component, and determining available resources of a networked computing system for running the application component. Additionally, the embodiment includes determining required resources for the application component, assigning a subset of available resources for the application component taking into account the required resources of the application component, the available resources, and one or more operator policies. These operator policies generally include preferences of operators, administrators, users, or the like, and could also include business rules. Additionally, the embodiment includes associating the application component with the subset of available resources.

Assigning resources to an application component by taking into account an objective function with hard and soft constraints

A method for resource allocation in a data center is disclosed which employs modeling techniques that enable resource allocation in large-scale data centers. A method for resource allocation according to the present techniques includes providing a model for resource allocation which is adapted to a resource topology of a data center and an architecture of an application to be deployed in the data center. A set of resources in the data center are allocated to the application using the model in response to a set of resource requirements of the application and a set of attributes of the resources in the data center such that communication delay among the resources allocated to the application is minimized. Techniques are disclosed for decomposing the model into a set of more tractable programming models which may be solved using available mathematical programming solvers.

Resource allocation in data centers using models

A configuration method includes selecting a design configuration, and modeling the solution configuration having a failure event for the selected solution configuration to determine an amount of down time associated with the failure event. A first penalty cost function is applied the amount of down time to determine a first penalty cost associated with the failure event of the selected solution configuration.

Configuration system and method

An embodiment of a method of designing a storage system begins with a step of assigning decision variables to a range of candidate storage systems. Each of the decision variables identifies a single candidate storage system. The method concludes with a step of employing the decision variables in a mathematical program to determine which of the candidate storage systems meets availability and reliability criteria and incurs a near minimal projected cost.

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Modesto, CA, United States of America

Cipriano A Santos