Hewlett-packard Development Company, L.p.

Hewlett Packard Enterprise Development LP

Amip J Shah

Cullen Edwin Bash

Chandrakant D Patel

Ratnesh Kumar Sharma

Manish Marwah

Martin Arlitt

Thomas W Christian

Geoff M Lyon

Chih C Shih

Zhikui Wang

Parthasarathy Ranganathan

Jichuan Chang

Henri Jacques Suermondt

Jerome Alexander Rolia

Yuan Chen

Daniel Juergen Gmach

Gowtham Bellala

Justin James Meza

Paulo Maciel

Christopher Gregory Malone

Bernardo A Huberman

Abdlmonem H Beitelmal

Alan Andrew McReynolds

Chris Deon Hyser

Henry W Sang, Jr

Debprakash Patnaik

Naren Ramakrishnan

Rongliang Zhou

Niru Kumari

Henry Sang

Allison Littman

Naren Sundaravaradan

Abdimonem Beitelal

Daniel Jurgen Gmach

Henry W Sang

Abdlmonem Beitelal

Examples relate to throttling data access using a data porch. In some examples, an analysis engine is used to access memory and prepare a data response for a data request that is obtained from the data porch via a throttled data buffer. The data response is sent to the data porch via the throttled data buffer, where the throttled data buffer has a throttled data bandwidth that limits a data flow of data requests and data responses between the analysis engine and the data porch. In response to receiving the data response from the analysis engine via the throttled data buffer, the data porch is used to provide the data response to a networked device.

Data porch for throttling data access

Techniques for secure linking of attributes between a first node and a plurality of nodes are provided. In one aspect, the first node and the plurality of nodes maintain a distributed data set. The techniques may include encoding the attributes as integer values at the first node. The nodes of the plurality of nodes that include matching attributes may be determined using a secure list matching protocol.

Attribute determination using secure list matching protocol

Examples relate to providing throttled data memory access. In some examples, a locking mechanism is used to activate a corresponding memory lock after receiving a first read access cycle. While the corresponding memory lock is active, responses to subsequent read access cycles are prevented. After the corresponding memory lock deactivates, a second read access cycle is responded to with access to the memory.

Throttled data memory access

According to an example, a method for area occupancy information extraction may include receiving a signal from a sensor, and determining a number of occupants moving within a first area based on the signal. The method may further include determining when an occupant is moving and a direction of motion of the occupant based on the signal, and determining a most likely trajectory based on the direction of motion of the occupant. The method may also include controlling, by a processor, a service in the first area based on the determination of the number of occupants, the determination of when the occupant is moving and the direction of motion of the occupant, and/or the determination of the most likely trajectory.

Area occupancy information extraction

Detecting fraud in resource distribution systems includes determining a meter of a resource in a resource distribution system exhibits a characteristic indicative of fraud and increasing a collection frequency of measurements of a usage of the resource of the meter per unit of time.

Detecting fraud in resource distribution systems

Systems and methods of determining sub-tree similarity for component substitution. A method includes assigning a similarity metric to a plurality of trees stored in computer-readable media. The method also includes constructing a distance matrix in computer-readable media, the distance being between sub-trees. The method also includes correlating sub-trees in the computer-readable media based on the distance matrix.

Sub-tree similarity for component substitution

A system and method for determining installation locations for meters are disclosed herein. The method includes generating, via a computing device, a resource map for a site, wherein the resource map includes inflow locations and corresponding outflow locations for a resource. The method also includes identifying a number of tiers within the resource map based on the inflow locations and the corresponding outflow locations for the resource. The method further includes determining a number of recommended installation locations for meters based on the tiers.

Determining installation locations for meters

A method is provided for system deconstruction for component substitution. The method includes a system tree which is deconstructed in a computer-readable medium, the system tree deconstructing into constituent nodes. Each node in the system tree represents a characteristic of a component of a system under consideration. A database of trees is searched for trees containing similar attributes to the system tree. Trees are qualified based on a frequency of nodes that are similar to certain highly ranked nodes in the system tree. The most relevant nodes from the qualified trees are selected. Searching the database is terminated when the most relevant nodes account for a fraction, less than a whole, of an environmental footprint of the system tree.

System deconstruction for component substitution

Examples of meter data management testing are disclosed. In one example implementation according to aspects of the present disclosure, a computing device may include one or more processors, a memory for storing machine readable instructions, and a data store. The computing device may further include a meter data management testing module stored in the memory and executing on at least one of the one or more processors to test a meter data management system using a data set of representative metering data and a user-generated test scenario specifying a plurality of metering parameters.

Meter data management testing

According to an example, synthetic time series data generation may include receiving time series data for a plurality of users, and applying dimensionality reduction to transform the time series data from a high dimensional space n of the time series data to a low dimensional space m, where m&#x3c;n. The transformed time series data may be used to estimate a time series data density in the low dimensional space m by generating a density function. The density function may be sampled for data, and the sampled data may be transformed back to the high dimensional space n to generate the synthetic time series data.

Synthetic time series data generation

Example computer racks to improve environmental sustainability in data centers are disclosed. An example computer rack includes a spine (); a first set of support structures () and a second set of support structures () extending from the spine (). Each of the support structures () is positioned to receive a respective blade. A first communication port is carried by the spine () and associated with the first set of support structures (). A second communication port is carried by the spine () and associated with the second set of support structures ().

Computer racks

In an implementation, a method for managing an entity may include establishing of a framework for characterization of the entity, in which the framework abstracts operation of the entity to a state machine. In addition, each state in the state machine may be characterized in terms of distributions of a performance metric associated with the entity. The method may also include implementing of the framework for characterization of the entity to manage the entity.

Managing an entity using a state machine abstract

Determining a sustainability impact for available data center architectures. A data center is accessed by a computer. Two or more functional parameters of the data center are then evaluated by the computer. Then, the computer combines the two or more evaluated functional parameters into a quantified judgment to determine a sustainability impact of available architectures of the data center.

Determining sustainability of a data center

A virtual power infrastructure for managing distribution of power to a plurality of power demanding units from a plurality of power generators includes a demand manager having logical descriptions of the power demanding units, in which the demand manager is configured to determine power load demands of the power demanding units using the logical descriptions of the power demanding units, and a capacity manager having logical descriptions of the power generators. The capacity manager is configured to determine allocation of power capacity supplied to the power generators from one or more of the power generators to meet the power load demands of the power demanding units, while satisfying one or more predetermined constraints associated with at least one of the power demanding units and the power generators.

Management of a virtual power infrastructure

In a method of determining cooling resource capacity allocations for resource units in a shared environment for optimized operations, cost parameters associated with operating the resource units in at least one of delivering and receiving cooling resources are identified, one or more constraints associated with operating the resource units are identified, in which at least one of the one or more constraints comprises meeting at least a total cooling demand of components in the shared environment, a cost function that correlates the plurality of identified cost parameters is developed, a minimized cost function is solved for through application of a Lagrange multiplier subject to the identified one or more constraints, and cooling resource capacity allocations for the resource units that result in optimized operations in the shared environment based upon the minimized cost function solution are determined.

Growing community of inventors

Santa Clara, CA, United States of America

Amip J Shah