Intel Corporation

Virtual Power Systems, Inc.

Other

Cato

Ravi S Subramaniam

Ned M Smith

Karimulla Raja Shaikh

Shankar Ramamurthy

David W Grawrock

Nikhil Sharma

Martin P Leslie

Jesse R Walker

Mats Gustav Agerstam

Gregory Burns

Denis Kouroussis

Ryan Kennedy

Eduardo Cabre

Erich Karl Nachbar

George W Clement

Pranthik Samal

Rajaram Soundararajan

Clark A Jeria Frias

Andrew Sy

Rajeev P Huralikoppi

Dhanaraja Kasinathan

In one embodiment, a domain controller (a) quarantines unknown devices at a first quarantine point at a first layer of a multi-layer communication model; (b) communicates with a domain name system (DNS) service to self-allocate and register a domain name with the DNS service; (c) receives a provisioning request for a first device via an access point, wherein the access point comprises a second quarantine point at a second layer of the multi-level communication model; (d) verifies a device type of the first device with the DNS service; and (e) responsive to that verification, provisions the first device into the domain. The domain controller may also send a provisioning response to the access point to enable the first device to be removed from the second quarantine point, to enable the first device to communicate with the domain controller. Other embodiments are described and claimed.

System, apparatus and method for scalable internet of things (IOT) device on-boarding with quarantine capabilities

In one embodiment, a domain controller includes a quarantine logic to quarantine unknown devices from unrestricted network access. The quarantine logic comprises a first quarantine point at a first layer of a multi-layer communication model. The domain controller also includes: a first logic to communicate with a domain name system (DNS) service to self-allocate and register a domain name with the DNS service, the domain name associated with a domain to be managed by the domain controller; a second logic to manage a group of devices of the domain; and a third logic to receive a provisioning request for a first device via an access point that comprises a second quarantine point at a second layer of the multi-level communication model. The second layer is a lower layer than the first layer, and the second quarantine point is more restrictive than the first. Other embodiments are described and claimed.

System, apparatus and method for scalable internet of things (IoT) device on-boarding with quarantine capabilities

In disclosed techniques, simulations are performed to determine data center performance under certain conditions. The simulations are dynamic and allow for changes in power demand due to temporal data center activities. In order to accommodate predicted and unpredicted fluctuations in power demand of a data center, one or more power caches are configured to supply additional power during periods of peak demand. Power caches provide supplemental power during periods of peak demand. The simulations are used for a variety of purposes, including determining the effects of power caches going offline under various conditions. Disclosed techniques can simulate the cycling of a power cache and can determine if additional configuration changes to the data center are warranted to maintain optimal health of the power caches. Thus, power scenario simulation of a data center can provide information vital to efficient operation of the data center.

Data center power scenario simulation

Embodiments provide techniques for datacenter power management using variable power sources. Power from the variable power sources is stored in a power cache. An optimization engine receives input criteria such as power availability from non-variable and variable power sources, as well as one or more power management goals. The optimization engine implements a dispatch strategy that dispatches stored energy from the power cache and feeds it to the datacenter, resulting in a mixture of non-variable and variable power sources used to achieve the power management goals, such as reduced power cost, increased power availability, and lowered carbon footprint for the datacenter.

Datacenter power management using variable power sources

In disclosed techniques, augmented power control within a datacenter uses predictive modeling. A power usage by a first data rack within a datacenter is measured, using one or more processors, over a first period of time. A predicted power usage by the first data rack over a second period of time is generated on a computing device, wherein the second period of time is subsequent to the first period of time. A power correlation model is calculated that correlates a power prediction to an actual power usage. The predicted power usage for the second period of time is refined, based on the predicted power usage and the power correlation model. The refining is accomplished using a power prediction model comprising the predicted power usage and the power correlation model. Datacenter power structure is configured, based on the refined power usage prediction.

Augmented power control within a datacenter using predictive modeling

In disclosed techniques, secure communication initiation and execution is used for datacenter power control. Information relating to power control is encrypted for inclusion in a first data payload. The first data payload is used for datacenter power infrastructure control. The first data payload is sent from a first component within a datacenter to a second component within the datacenter. The first component and the second component enable power infrastructure power control of the datacenter. The datacenter power infrastructure control is modified based on decryption of the first data payload by the second component within the datacenter. The first data payload provides for intelligent power control within the datacenter. Modifying the datacenter power infrastructure control dynamically changes power control within the datacenter. The changing power control changes power policies within the datacenter. The first component is authenticated using the first data payload. Encryption includes obscurity. The decryption ignores the obscurity.

Secure communication initiation and execution for datacenter power control

A communications device, such as an Internet-of-Things device, includes an entity resource to originate or consume data, and core resources to facilitate stateless messaging with a remote device, with the messaging being associated with the entity resource. Transaction resources are provided to manage a transaction with the remote device. The transaction includes a sequence of messages associated with the entity resource. The transaction resources include a transaction state machine to represent a current intra-transactional ephemeral state from among a plurality of intra-transactional ephemeral states representing progression of the transaction, a commit handler to institute a persistent state change related to the entity resource in response to a successful completion of the transaction, and a transaction communicator to conduct intra-transaction communications via the core resources directed to corresponding transactional resources of the remote device.

Transaction resources for stateless message protocol

In one embodiment, a domain controller includes: a quarantine logic to quarantine unknown devices from unrestricted network access, the quarantine logic comprising a first quarantine point at a first layer of a multi-layer communication model; a first logic to communicate with a domain name system (DNS) service to self-allocate and register a domain name with the DNS service, the domain name associated with a domain to be managed by the domain controller; a second logic to manage a group of devices of the domain; and a third logic to receive a provisioning request for a first device via an access point, wherein the access point comprises a second quarantine point at a second layer of the multi-level communication model. Other embodiments are described and claimed.

Multi-level data center using consolidated power control is disclosed. One or more controllers communicate with one or more power supplies and sensors to adapt to dynamic load requirements and to distribute DC-power efficiently across multiple IT racks. The distributed DC-power includes one or more DC-voltages. Batteries can be temporarily switched into a power supply circuit to supplement the power supply during spikes in power load demand while a controller reconfigures power supplies to meet the new demand. One or more DC-to-AC converters handle legacy power loads. The DC-to-AC converters are modular and are paralleled for redundancy. The DC-to-AC converters are sourced from the one or more AC-to-DC converters. The AC power is synchronized for correct power flow control. The one or more controllers communicate with the one or more AC-power supplies to dynamically allocate AC-power from the DC-to-AC converters to the multiple legacy IT racks.

Multi-level data center using consolidated power control

Technologies for trusted device on-boarding include a first computing device to generate a first public Diffie-Hellman key based on a private Diffie-Hellman key and a first unique identifier of the first computing device. The first unique identifier is retrieved from secure memory of the first computing device. The first computing device transmits the first public Diffie-Hellman key to a second computing device and receives, from the second computing device, a second public Diffie-Hellman key of the second computing device. The second public Diffie-Hellman key incorporates a second unique identifier of the second computing device. Further, the first computing device removes a contribution of the second unique identifier from the second public Diffie-Hellman key to generate a modified public Diffie-Hellman key and generates a shared Diffie-Hellman key based on the modified public Diffie-Hellman key and the private Diffie-Hellman key of the first computing device.

Technologies for trusted device on-boarding

Systems and methods utilize directory services snap-ins to create, maintain, and interpret policies for controlling the execution of grid applications.

Growing community of inventors

San Jose, CA, United States of America

Ravi S Subramaniam