U.S. patent application number 14/591572 was filed with the patent office on 2017-08-03 for data center infrastructure management (dcim) system comprising predictive analytics.
The applicant listed for this patent is Nautilus Data Technologies, Inc.. Invention is credited to Daniel Kekai, Arnold C. Magcale.
Application Number | 20170219241 14/591572 |
Document ID | / |
Family ID | 53524345 |
Filed Date | 2017-08-03 |
United States Patent
Application |
20170219241 |
Kind Code |
A1 |
Magcale; Arnold C. ; et
al. |
August 3, 2017 |
Data Center Infrastructure Management (DCIM) system comprising
predictive analytics
Abstract
A Data Center Infrastructure Management (DCIM) system comprising
predictive analytics and methods for collecting data, analyzing
data, optimizing infrastructure efficiency and automating
management of data center infrastructure systems and components is
disclosed. The DCIM system comprising predictive analytics may
generally comprise a DCIM appliance or server, data collection
hardware, database hardware, software for collecting data from a
plurality of infrastructure systems, infrastructure components and
wireless sensors, presentation client software, reporting software
and an intelligent predictive analytics engine. The intelligent
predictive analytics engine may be employed to identify
infrastructure optimization actions enabling the DCIM system
software or DCIM element controller to enact changes to the
operational state of data center infrastructure systems or
components to sustain optimal data center infrastructure
efficiency. The DCIM system comprising predictive analytics may
continuously collect and analyze infrastructure system,
infrastructure components and environmental data.
Inventors: |
Magcale; Arnold C.; (San
Ramon, CA) ; Kekai; Daniel; (San Ramon, CA) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
Nautilus Data Technologies, Inc. |
San Ramon |
CA |
US |
|
|
Family ID: |
53524345 |
Appl. No.: |
14/591572 |
Filed: |
January 7, 2015 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
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61925531 |
Jan 9, 2014 |
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Current U.S.
Class: |
1/1 |
Current CPC
Class: |
F24F 11/30 20180101;
H05K 7/20836 20130101; G06F 2009/45591 20130101 |
International
Class: |
F24F 11/00 20060101
F24F011/00 |
Claims
1. A computer system for data center infrastructure management
(DCIM) comprising: a processor unit; a memory element coupled to
the processor unit; a connection to and means for communicating
over a wired and wireless network: wherein the system is configured
to: determine an optimum placement of a single or plurality of
servers, which further comprises, estimating a power, a cooling and
a network data resource requirement for each rack in a plurality of
racks; based on the determined optimum placement, enforce a
pre-defined process for operating the data center; based on the
pre-defined process, determine an operational requirement from
collected operational data, which comprises collected
environmental, power, cooling, and information technology (IT)
data; via a predictive analytics engine configured to communicate
over the network, analyze and store the collected operational data;
based on the collected and analyzed operational data, automatically
make zero or more adjustments to the, environmental condition,
power condition, cooling condition and IT condition; wherein the
predictive analytics engine is further configured to analyze a
single or plurality of virtual machines, an instance or instances
over a cloud computing network, and to estimate based on the
analyzed virtual machines and instances, a demand for the said
virtual machines and cloud instances; and wherein the analytics for
demand comprises: estimating a baseline of virtual machine or cloud
demands based on collected real-time and historical demand data;
estimating a baseline of virtual machine or cloud status based on
collected real-time and historical demand data; predicting future
status and demand based on predictive modeling which further
comprises the collected real-time estimations; and based on the
predictive modeling and analytics, and via a planning engine
configured to communicate over the network, dynamically
implementing an action or actions.
2. The computer system of claim 1, wherein the predictive analytics
engine is further configured to analyze a future infrastructure
system condition, a future environment condition, and a future
component or components' condition.
3. The computer system of claim 1 wherein the collection of
operational data further comprises collecting environmental data
from a plurality of wireless sensors and collecting infrastructure
system and component data from infrastructure and component
elements, wherein said infrastructure system and component data
comprise collecting air temperature data, air flow data, water
temperature data and water flow data.
4. The computer system of claim 1 further comprises a data center
infrastructure management (DCIM) element controller, wherein the
DCIM element controller is caused to employ the analyzed data, and
based on the analyzed data, configure the infrastructure system and
components' operational states for optimal efficiency.
5. The system of claim 4 wherein the DCIM element controller is
further caused to configure based on whether an analyzed ambient
air temperature is within a defined range.
6. The system of claim 5 wherein based on the analyzed air
temperature, the DCIM element controller is caused to make zero or
more adjustments to at least one of a computer room air-conditioner
(CRAC), a rear door heat exchanger (RDHX), a coolant distribution
unit (CDU), and a single or plurality of automated, adjustable flow
control valves, to bring the ambient air temperature to within the
defined range.
7. The system of claim 4 wherein the DCIM element controller is
further caused to configure based on whether an analyzed water
temperature and water flow is within a defined range.
8. The system of claim 7 wherein based on the analyzed water
temperature and water flow, the DCIM element controller is caused
to make zero or more adjustments to at least one of a coolant
distribution unit (CDU), a rear door heat exchanger (RDHX), a
single or plurality of automated, adjustable flow control valves,
and a single or plurality of variable frequency drive (VFD) pumps
to bring the water flow and the water temperature to within a
defined range.
9. The system of claim 4 wherein the DCIM element controller is
further caused to configure based on whether an analyzed, measured
air flow is within a defined range.
10. The system of claim 9 wherein based on the analyzed, measured
air flow, the DCIM element controller is caused to make zero or
more adjustments to a single or plurality of variable frequency
drive (VFD) fans to bring the said air flow to within the defined
range.
11. The system of claim 1 wherein the system is further caused to,
via a presentation software module, display the collected and
analyzed data to a single or plurality of users.
12. The system of claim 1 wherein the system further caused to
allow access to the system over a secure network.
13. In a system for data center infrastructure management (DCIM)
comprising a processing unit coupled to a memory element, and
having instructions encoded thereon, a method comprising:
determining an optimum placement of a single or plurality of
servers, which further comprises, estimating a power, cooling and
network data resource requirement for each rack in a plurality of
racks; based on the determined optimum placement, enforcing a
pre-defined process for operating the data center; based on the
pre-defined process for operating the data center, determining
operational requirements from collected operational data, which
comprises collected environmental data, power data, cooling data,
and information technology (IT) data; via a predictive analytics
engine configured to communicate over the network, collecting,
analyzing and storing data of the said operational requirements;
based on the collected and analyzed data, automatically making zero
or more adjustments to the environmental condition, power
condition, cooling condition and IT condition; wherein the
predictive analytics engine is further configured to analyze a
single or plurality of virtual machines, an instance or instances
over a cloud computing network, and to estimate based on the
analyzed virtual machines and instances, a demand for the said
virtual machines and cloud instances; and wherein the analytics for
demand comprises: estimating a baseline of virtual machine or cloud
demands based on collected real-time and historical demand data;
estimating a baseline of virtual machine or cloud status based on
collected real-time and historical demand data; predicting future
status and demand based on predictive modeling which further
comprises the collected real-time estimations; and based on the
predictive modeling and analytics, and via a planning engine
configured to communicate over the network, dynamically
implementing an action or actions.
14. The method of claim 13, further comprising, based on collected
and analyzed data, predictively analyzing a future infrastructure
system condition, a future environment condition, and a future
component or components' condition.
15. The method of claim 13 wherein the said collecting further
comprises collecting environmental data from a plurality of
wireless sensors and collecting infrastructure system and component
data from infrastructure and component elements wherein said
infrastructure system and component data comprise collecting air
temperature data, air flow data, water temperature data and water
flow data.
16. The method of claim 13 further comprising: employing the
analyzed data via a data center infrastructure management (DCIM)
element controller; and configuring the infrastructure system and
components' operational states for optimal efficiency via the DCIM
controller.
17. The method of claim 16 wherein the said configuring further
comprises configuring based on analyzing if ambient air temperature
is within a defined range.
18. The method of claim 17 wherein the said configuring further
comprises making zero or more adjustments to at least one of a
computer room air-conditioner (CRAC), a rear door heat exchanger
(RDHX), a coolant distribution unit (CDU), and a single or
plurality of automated, adjustable flow control valves, to bring
the ambient air temperature to within the defined range.
19. The method of claim 16 wherein the said configuring further
comprises configuring based on analyzing if the water temperature
and water flow is within a defined range.
20. The method of claim 19 wherein the said configuring further
comprises making zero or more adjustments to at least one of a
coolant distribution unit (CDU), a rear door heat exchanger (RDHX),
a single or plurality of automated, adjustable flow control valves,
and a single or plurality of variable frequency drive (VFD) pumps
to bring the water flow and the water temperature to within a
defined range.
21. The method of claim 16 wherein the said configuring further
comprises measuring ambient air flow data, and analyzing if the
measured air flow is within a defined range.
22. The method of claim 21 wherein the said configuring further
comprises making zero or more adjustments to a single or plurality
of VFD fans to bring the said air flow within the defined
range.
23. The method of claim 13 further comprising, via a presentation
software module, displaying of the collected and analyzed data to a
single or plurality of users.
24. The method of claim 13 further comprising allowing access to
the system over a secure network.
25. A system for data center infrastructure management (DCIM)
comprising a processing unit coupled to a memory element, and
having instructions encoded thereon, wherein the encoded
instructions cause the system to: collect and store data center
infrastructure system condition data, environmental condition data
and component condition data; analyze the collected infrastructure
system, environmental and component condition data; and based on
the collected and analyzed data, automatically make zero or more
adjustments to data center infrastructure system condition,
environmental condition and component condition; wherein the said
zero or more adjustments are based on a predictive analytics
functionality configured to continuously collect and analyze data,
and wherein the predictive analytics functionality is further
configured to implement predictive analytics of a single or
plurality of virtual machines, an instance or instances over a
cloud computing network, and to estimate demand for the said
virtual machines and cloud instances; and wherein the analytics for
demand comprises: estimating a baseline of virtual machine or cloud
demands based on collected real-time and historical demand data;
estimating a baseline of virtual machine or cloud status based on
collected real-time and historical demand data; predicting future
status and demand based on predictive modeling which further
comprises the collected real-time estimations; and based on the
predictive modeling and analytics, dynamically implementing an
action or actions.
26. In a system for data center infrastructure management (DCIM)
comprising a processing unit coupled to a memory element, and
having instructions encoded thereon, a method comprising:
collecting and storing data center infrastructure system condition
data, environmental condition data and component condition data;
analyzing the collected infrastructure system, environmental and
component condition data; and based on the collected and analyzed
data, automatically making zero or more adjustments to data center
infrastructure system condition, environmental condition and
component condition; wherein the said zero or more adjustments are
based on a predictive analytics functionality configured for
continuously collecting and analyzing data, and wherein the
predictive analytics functionality is further configured to
implement predictive analytics of a single or plurality of virtual
machines, an instance or instances over a cloud computing network,
and to estimate demand for the said virtual machines and cloud
instances; and wherein the analytics for demand comprises:
estimating a baseline of virtual machine or cloud demands based on
collected real-time and historical demand data; estimating a
baseline of virtual machine or cloud status based on collected
real-time and historical demand data; predicting future status and
demand based on predictive modeling which further comprises the
collected real-time estimations; and based on the predictive
modeling and analytics, dynamically implementing an action or
actions.
Description
CROSS REFERENCE TO RELATED APPLICATIONS
[0001] This application claims reference to Provisional Patent
application No. 61/925,531 filed on Jan. 9, 2014, entitled "A Data
Center Infrastructure Management (DCIM) system with predictive
analytics."
FIELD
[0002] The present invention relates to infrastructure management
systems, especially with respect to data center facilities, but not
restricted to the said data center facilities.
BACKGROUND OF THE INVENTION
[0003] Data centers and co-location providers in particular
struggle with both supplying requisite power as well as cooling. As
data center density continues to increase there is a growing demand
for more energy efficient and cost effective data centers and co
location solutions.
[0004] A data center is designed to maintain interior ambient
conditions suitable for proper operation of the computer systems
therein. Typical data centers may consume more than twice the power
needed to support the plurality of computer systems housed therein.
This is a result of the inefficient air conditioning units that may
account for half of the total power consumed in the data center to
cool the plurality of computer systems therein. This inefficiency
prohibits support of high density computing systems in today's data
centers.
[0005] Embodiments disclose a data center infrastructure management
(DCIM) system and method for monitoring, controlling and analyzing
infrastructure and environmental conditions and managing resources
according to the monitored and analyzed conditions.
[0006] Traditional data centers face challenges with technical
innovation, operational efficiency and modern design principles.
With increasingly complex environments such challenges with energy
efficiency and resource utilization management have become vital to
long term sustainment of data center facilities. Current data
center providers struggle to monitor infrastructure systems,
collect data from infrastructure systems and manage infrastructure
systems to allow optimal efficiency of the data center
facility.
[0007] Traditional data centers are built with physical
infrastructure that is static in nature. When this constrained
static infrastructure is placed under dynamic workloads, it can
expose significant infrastructure inefficiencies. These
inefficiencies may only be addressed through continuous collection
and analysis of data center infrastructure and environmental
data.
[0008] The described DCIM system comprising predictive analytics
may be employed to continuously collect and analyze infrastructure
system, component, and environmental data. The DCIM system
comprising predictive analytics may identify inefficiencies or
previously unknown interdependencies. The continuous collection and
analysis of infrastructure and environmental data enables automated
management of infrastructure systems and components to sustain
optimal infrastructure efficiencies.
SUMMARY
[0009] A system for data center infrastructure management
comprising a processing unit coupled to a memory element, and
having instructions encoded thereon, wherein the encoded
instructions cause the system to: collect and store data center
infrastructure system condition data, environmental condition data
and component condition data; analyze the collected infrastructure
system, environmental and component condition data; and based on
the collected and analyzed data, automatically make zero or more
adjustments to data center infrastructure system condition,
environmental condition and component condition.
[0010] In a system for data center infrastructure management
comprising a processing unit coupled to a memory element, and
having instructions encoded thereon, a method comprising:
collecting and storing data center infrastructure system condition
data, environmental condition data and component condition data;
analyzing the collected infrastructure system, environmental and
component condition data; and based on the collected and analyzed
data, automatically making zero or more adjustments to data center
infrastructure system condition, environmental condition and
component condition.
[0011] A system for data center infrastructure management
comprising a processing unit coupled to a memory element, and
having instructions encoded thereon, wherein the encoded
instructions cause the system to: collect and store data center
infrastructure system condition data, environmental condition data
and component condition data; analyze the collected infrastructure
system, environmental and component condition data; and based on
the collected and analyzed data, automatically make zero or more
adjustments to data center infrastructure system condition,
environmental condition and component condition; wherein the said
zero or more adjustments are based on a predictive analytics
functionality configured to continuously collect and analyze data,
and wherein the predictive analytics functionality is further
configured to implement predictive analytics of a single or
plurality of virtual machines, an instance or instances over a
cloud computing network, and to estimate demand for the said
virtual machines and cloud instances; and wherein the analytics for
demand comprises: estimating a baseline of virtual machine or cloud
demands based on collected real-time and historical demand data;
estimating a baseline of virtual machine or cloud status based on
collected real-time and historical demand data; predicting future
status and demand based on predictive modeling which further
comprises the collected real-time estimations; and based on the
predictive modeling and analytics, dynamically implementing an
action or actions.
[0012] In a system for data center infrastructure management
comprising a processing unit coupled to a memory element, and
having instructions encoded thereon, a method comprising:
collecting and storing data center infrastructure system condition
data, environmental condition data and component condition data;
analyzing the collected infrastructure system, environmental and
component condition data; and based on the collected and analyzed
data, automatically making zero or more adjustments to data center
infrastructure system condition, environmental condition and
component condition; wherein the said zero or more adjustments are
based on a predictive analytics functionality configured for
continuously collecting and analyzing data, and wherein the
predictive analytics functionality is further configured to
implement predictive analytics of a single or plurality of virtual
machines, an instance or instances over a cloud computing network,
and to estimate demand for the said virtual machines and cloud
instances; and wherein the analytics for demand comprises:
estimating a baseline of virtual machine or cloud demands based on
collected real-time and historical demand data; estimating a
baseline of virtual machine or cloud status based on collected
real-time and historical demand data; predicting future status and
demand based on predictive modeling which further comprises the
collected real-time estimations; and based on the predictive
modeling and analytics, dynamically implementing an action or
actions.
BRIEF DESCRIPTION OF THE DRAWINGS
[0013] FIG. 1 illustrates an embodiment of the Data Center
Infrastructure Management (DCIM) element controller logical
view.
[0014] FIG. 2 depicts the process flow for managing infrastructure
via the sample illustrated flowchart.
[0015] FIG. 3 depicts a logical view of the DCIM system according
to an embodiment.
DETAILED DESCRIPTION OF THE INVENTION
[0016] As stated above, Traditional data centers face challenges
with technical innovation, operational efficiency and modern design
principles. With increasingly complex environments such challenges
with energy efficiency and resource utilization management have
become vital to long term sustainment of data center facilities.
Current data center providers struggle to monitor infrastructure
systems, collect data from infrastructure systems and manage
infrastructure systems to allow optimal efficiency of the data
center facility. Embodiments of the present invention solve this
problem.
[0017] The Data Center Infrastructure Management (DCIM) system
described may be employed to provide continuous monitoring and
analysis of data to enable automated management of data center
mechanical, electrical and cooling infrastructure to maintain
optimal infrastructure efficiency.
[0018] Embodiments disclosed are different from, and superior to
what currently exists. Embodiments disclosed include a new and
improved method and system for infrastructure management and
control, and more particularly for data center infrastructure
management and control. According to an embodiment, the Data Center
Infrastructure Management System (DCIM) system comprises predictive
analytics described in this document, which is beyond the scope of
existing systems. The ability to automate infrastructure management
through collected data and predictive analytics provides a clear
advantage to what currently exists.
[0019] Data center infrastructure is constrained and static in
nature. The inefficiencies of such constrained static design are
quickly exposed when placed under a dynamic load. Without
continuous collection and analysis of infrastructure and
environmental data, management of data center infrastructure
systems and components is a hit and miss proposition. These
limitations cause inefficient power consumption and prohibit
automated management of data center infrastructure.
[0020] The described DCIM system comprising predictive analytics
may be employed to continuously collect and analyze infrastructure
system, component, and environmental data. The DCIM system
comprising predictive analytics may identify inefficiencies or
previously unknown interdependencies. The continuous collection and
analysis of infrastructure and environmental data enables automated
management of infrastructure systems and components to sustain
optimal infrastructure efficiencies. Alternatively and
additionally, embodiments of this invention can continuously
monitor, collect and analyze data to automate management of virtual
machine resources across a data center or data centers, wherein the
monitoring, collecting, analyzing and control can be performed
onsite, or remotely in a centralized fashion.
[0021] FIG. 1 illustrates an embodiment of the Data Center
Infrastructure Management (DCIM) element controller logical view.
The illustrated embodiment includes DCIM element controller 100,
wireless temperature sensors 102, wireless humidity sensors 104,
electrical systems elements 106, mechanical systems elements, and
power elements 112.
[0022] FIG. 2 depicts the process flow for managing infrastructure
via the sample illustrated flowchart. Step 202 includes measuring
air temperature. In step 204, a check is performed to evaluate
whether the measured air temperature is within an acceptable range.
If in step 204, the air temperature is not within the acceptable
range, step 206 is implemented wherein the CRAC (Computer Room Air
Conditioner), CDU (Coolant Distribution Unit) or/and RDHX (Rear
Door Heat Exchanger) is/are adjusted to increase or lower the air
temperature, as the case may be. If the air temperature is within
the acceptable range, or after the air temperature is brought
within the acceptable range, the next step 208, is performed
wherein the air flow is measured and in step 210, the measured air
flow is evaluated to check whether it is within an acceptable
pre-defined range. Step 212 includes adjusting the VFD (Variable
Frequency Drive) fans to bring the air flow within the acceptable
pre-defined range. Note that the above checks may be performed
sequentially (as described) or alternatively, they may be performed
simultaneously. Step 208 may include measuring water flow and in
step 210 the measured water flow is evaluated to check if it is
within a predefined range. Furthermore step 212 may include
adjusting the VFD water pumps or automated, adjustable flow control
valves to bring the water flow within an acceptable predefined
range. Variations in prioritization of checks are possible, and in
some instances, desirable, as would be apparent to a person having
ordinary skill in the art.
[0023] A system for data center infrastructure management
comprising a processing unit coupled to a memory element, and
having instructions encoded thereon, wherein the encoded
instructions cause the system to collect and store data center
infrastructure system condition data, environmental condition data
and component condition data; analyze the collected infrastructure
system, environmental and component condition data; and based on
the collected and analyzed data, automatically make zero or more
adjustments to data center infrastructure system condition,
environmental condition and component condition. The said analyzing
further comprises predictive analytics configured for continuously
collecting and analyzing data from the infrastructure system, the
environment, and the said component or components. The said
collecting further comprises collecting environmental data from a
plurality of wireless sensors and collecting infrastructure system
and component data from infrastructure elements wherein said
infrastructure system and component data comprise collecting air
temperature data and air flow data. The system is further caused to
employ the analyzed data via a DCIM element controller, wherein the
DCIM element controller comprises a means for configuring the
infrastructure system and components' operational states for
optimal efficiency, and wherein the configuring further comprises
configuring based on analyzing if ambient air temperature is within
a defined range. The configuring includes making zero (if ambient
air temperature is within the defined range) or more (if ambient
air temperature is not within the defined range) adjustments to the
CRAC, CDU or/and RDHX to bring the ambient air temperature to
within the defined range. Additionally, the configuring further
comprises measuring ambient air flow data, and analyzing if the
measured air flow is within a defined range, and making zero (if
ambient air flow is within the defined range) or more (if ambient
air flow is not within the defined range) adjustments to a single
or plurality of VFD fans to bring the said air flow within the
defined range. Additionally the configuring further comprises
measuring water flow data and analyzing if the measured water flow
is within acceptable predefined range and making zero or more
adjustments to a single or plurality of VFD water pumps or
automated, adjustable flow control valves to bring the said water
flow within the defined range. According to an embodiment, the
system is further caused to, via a presentation software module,
allow display of the collected and analyzed data to a single or
plurality of users. According to an additional embodiment the
system is caused to allow access to the system over a secure
network, and can access other systems via the said secure
network.
[0024] According to an embodiment, the predictive analytics
configured for continuously collecting and analyzing data, is
further configured to implement predictive analytics of a single or
plurality of virtual machines, an instance or instances over a
cloud computing network, and demand for the said virtual machines
and cloud instances, wherein the analytics for demand comprises:
estimating a baseline of virtual machine or cloud demands based on
collected real-time and historical demand data; estimating a
baseline of virtual machine or cloud status based on collected
real-time and historical demand data; predicting future status and
demand based on predictive modeling which further comprises the
collected real-time estimations; and based on the predictive
modeling and analytics, dynamically implementing an action or
actions. Thus, in an example embodiment, the disclosed predictive
analytics is a key feature that not only enables monitoring
infrastructure (electrical/cooling/mechanical) but also enables
monitoring systems comprising virtual machines and entire cloud
computing instances over a network. Predictive analytics for
virtual machines and clouds allow the system to further leverage
actionable analytics. For example based on real-time and historical
data, a predictive analytics engine comprised in the system can
predict when a cloud will be overrun with demand and dynamically
add capacity.
[0025] FIG. 3 depicts a logical view of the DCIM system according
to an embodiment. The illustrated embodiment includes wireless
sensors and infrastructure elements 300, DCIM element controller
302, data collection software 304, predictive analytics engine or
software 306, presentation software 308, database 310, presentation
client 312, and DCIM appliance or server 314.
[0026] The DCIM system comprising predictive analytics may comprise
a plurality of DCIM appliances, or servers 314, which may be
employed for hosting presentation software 308, predictive
analytics engine or software 306, data collection software 304 and
DCIM element controller software 302. The data collection software
304 is configured to continuously collect environmental data from a
plurality of wireless sensors 300 and infrastructure system and
component data from infrastructure elements 300. All of the
collected data is stored in the database hardware 310. The
predictive analytics engine or software 306 may be employed to
analyze the stored data. The DCIM element controller 302 may be
employed to issue operational state changes to infrastructure
systems or components based on data that has been collected and
analyzed. In one example, a wireless sensor measures air
temperature 202, the data is analyzed to determine if the air
temperature is within a defined range 204, if it is not within the
defined range, the DCIM element controller may issue instructions
to adjust the CRAC (Computer Room Air Conditioner), CDU or/and RDHX
to bring the air temperature within the defined range. Then a
wireless sensor 300 may measure air flow/pressure 204, the data is
analyzed to find if the airflow/pressure is within the defined
range, if it is not then the DCIM element controller 302 may issue
instructions to adjust the VFD (Variable Frequency Drive) fans to
bring the airflow/pressure within the defined range. Then a sensor
may measure water flow with the data analyzed to find if the water
flow is within the predefined range if it is not then the DCIM
element controller may issue instructions to adjust the VFD water
pumps or automated, adjustable flow control valves to bring the
water flow within the defined range. Note that the above checks may
be performed sequentially (as described) or alternatively, they may
be performed simultaneously. Variations in prioritization of checks
are possible, and in some instances, desirable, as would be
apparent to a person having ordinary skill in the art.
[0027] The described DCIM system comprising predictive analytics
may continuously collect and analyze data from a plurality of
infrastructure systems, components and wireless sensors. A
plurality of wireless sensors may be employed to continuously
collect environmental data.
[0028] The data collected by the DCIM system may be stored in a
database. The stored data may then be analyzed by the predictive
analytics engine. The analyzed data may be employed by the DCIM
element controller to manage infrastructure systems and components
operational states to sustain optimal infrastructure
efficiency.
[0029] In preferred embodiments, the predictive analytics
configured for continuously collecting and analyzing data, and
comprised in the DCIM, is further configured to collect and analyze
data from a single or plurality of virtual machines, and an
instance or instances over a cloud computing network. Additionally,
the predictive analytics includes, estimating a demand for the said
virtual machines and cloud instances, wherein the said estimating
comprises: estimating a baseline of virtual machine or cloud
demands based on collected real-time and historical demand data;
estimating a baseline of virtual machine or cloud status based on
collected real-time and historical demand data; predicting future
status and demand based on predictive modeling which further
comprises the collected real-time estimations; and based on the
predictive modeling and analytics, dynamically implementing an
action or actions. The DCIM element controller 302 may then be
employed to issue operational state changes to infrastructure
systems or components based on data that has been collected and
analyzed.
[0030] The presentation software permits viewing of all the
collected and analyzed data by an end user with the presentation
client software. The DCIM system may be accessible over a secure IP
network (not pictured). Additionally and alternatively, the DCIM
system can control infrastructure elements, systems, components,
virtual machines and cloud based instances, remotely, over a
network.
[0031] In a system for data center infrastructure management
comprising a processing unit coupled to a memory element, and
having instructions encoded thereon, a method comprising,
collecting and storing data center infrastructure system condition
data, environmental condition data and component condition data,
analyzing the collected infrastructure system, environmental and
component condition data, and based on the collected and analyzed
data, automatically making zero or more adjustments to data center
infrastructure system condition, environmental condition and
component condition.
[0032] According to an embodiment the analyzing is comprised in
predictive analytics configured for continuously collecting and
analyzing data from the infrastructure system, the environment, and
the said component or components. The collecting further comprises
collecting environmental data from a plurality of wireless sensors
and collecting infrastructure system and component data from
infrastructure elements wherein the said infrastructure system and
component data comprise collecting air temperature data and air
flow data.
[0033] An embodiment includes employing the analyzed data via a
DCIM element controller, wherein the DCIM element controller
comprises means for configuring the infrastructure system and
components' operational states for optimal efficiency.
Additionally, the said configuring further comprises configuring
based on analyzing if ambient air temperature is within a defined
range, and making zero (if the ambient air temperature is within
the defined range) or more (if the ambient air temperature is not
within the defined range) adjustments to the CRAC, CDU or/and RDHX
to bring the ambient air temperature to within the defined range.
According to additional embodiments the configuring further
comprises measuring ambient air flow data, and analyzing if the
measured air flow is within a defined range, and making zero (if
the ambient air flow is within the defined range) or more (if the
ambient air flow is not within the defined range) adjustments to a
single or plurality of VFD fans to bring the said air flow within
the defined range. According to additional embodiments the
configuring further comprises measuring water flow data, and
analyzing if the measured water flow is within a defined range, and
making zero (if the water flow is within the defined range) or more
(if the water flow is not within the defined range) adjustments to
a single or plurality of VFD water pumps or automated, adjustable
flow control valves to bring the said water flow within the defined
range.
[0034] Embodiments disclosed further include in the method, via a
presentation software module, allowing display of the collected and
analyzed data to a single or plurality of users, and allowing
access to the system over a secure network.
[0035] Embodiments disclosed comprise a DCIM system software suite,
a DCIM appliance or server used to install and run the DCIM system
software suite, system elements and wireless sensors for collecting
data from electrical, mechanical and cooling infrastructure systems
or/and components. Preferred embodiments further include an
intelligent predictive analytics engine to permit dynamic
management of infrastructure systems or components.
[0036] Having described at least one embodiment of the present
disclosure, various alterations, modifications and improvements
will readily occur to those skilled in the art. Such alterations,
modifications and improvements are intended to be within the scope
and spirit of the disclosure. Accordingly, the foregoing
description is by way of example only and is not intended to be
limiting.
[0037] Preferred embodiments include a DCIM system including all
hardware, software, system elements and wireless sensors described
above. Ideally the system is highly configurable, wherein the
database and predictive analytics engine can be configured for use
in a multitude of scenarios that require analysis of collected
data. Additionally, a presentation client and presentation
interface that will be used to present data to end users is
configurable according to various situations.
[0038] Embodiments of the system and method described may be
employed by any field where it would be beneficial for systems or
components to be dynamically managed based on defined data ranges
and with a defined set of control commands/instructions that can be
executed to change the operational state of the systems or
components.
[0039] Further variations of embodiments of this invention are
capable of continuously monitoring, collecting and analyzing data
to automate management of virtual machine resources across a data
center or data centers, on site or remotely, as would be apparent
to a person having ordinary skill in the art.
[0040] Additionally, partial or complete embodiments of the
disclosed invention can be utilized in alternate applications
without departing from the scope and spirit of the disclosure. For
example, DCIM systems and predictive analytics can be utilized to
manage electrical, mechanical, cooling, and other crucial
components, in commercial or residential buildings, factories,
supermarkets, stores, and other resource consuming space including
but not limited to buildings or dwellings, in an energy-efficient
and cost-effective manner.
[0041] Embodiments disclosed provide systems and methods for
efficient onsite and remote monitoring of infrastructure systems,
efficient and accurate collection of data from the infrastructure
systems and optionally automated management of these infrastructure
systems to allow optimal efficiency of data center facilities and
other such spaces.
[0042] Embodiments disclosed include dynamic real time management
and control of infrastructure resources in data centers and other
such facilities, resulting in increased efficiencies and lowered
costs. Systems and methods disclosed provide for continuous data
collection, real time data analysis and accurate forecasting for
resource allocation through embodiments of the predictive analysis
engine, module, and software.
[0043] Embodiments of the DCIM system comprising predictive
analytics may be employed to continuously collect and analyze
infrastructure system, component, and environmental data, identify
inefficiencies or previously unknown interdependencies, and enable
automated management of infrastructure systems and components to
sustain optimal infrastructure efficiencies.
[0044] Since various possible embodiments might be made of the
above invention, and since various changes might be made in the
embodiments above set forth, it is to be understood that all matter
herein described or shown in the accompanying drawings is to be
interpreted as illustrative and not to be considered in a limiting
sense. Thus it will be understood by those skilled in the art of
infrastructure management, and more specifically automated
infrastructure management especially pertaining to data centers,
that although the preferred and alternate embodiments have been
shown and described in accordance with the Patent Statutes, the
invention is not limited thereto or thereby.
[0045] The figures illustrate the architecture, functionality, and
operation of possible implementations of systems, methods and
computer program products according to various embodiments of the
present invention. It should also be noted that, in some
alternative implementations, the functions noted/illustrated may
occur out of the order noted in the figures. For example, two
blocks shown in succession may, in fact, be executed substantially
concurrently, or the blocks may sometimes be executed in the
reverse order, depending upon the functionality involved.
[0046] The terminology used herein is for the purpose of describing
particular embodiments only and is not intended to be limiting of
the invention. As used herein, the singular forms "a", "an" and
"the" are intended to include the plural forms as well, unless the
context clearly indicates otherwise. It will be further understood
that the terms "comprises" and/or "comprising," when used in this
specification, specify the presence of stated features, integers,
steps, operations, elements, and/or components, but do not preclude
the presence or addition of one or more other features, integers,
steps, operations, elements, components, and/or groups thereof.
[0047] Some portions of embodiments disclosed are implemented as a
program product for use with an embedded processor. The program(s)
of the program product defines functions of the embodiments
(including the methods described herein) and can be contained on a
variety of signal-bearing media. Illustrative signal-bearing media
include, but are not limited to: (i) information permanently stored
on non-writable storage media (e.g., read-only memory devices
within a computer such as CD-ROM disks readable by a CD-ROM drive);
(ii) alterable information stored on writable storage media (e.g.,
hard-disk drive, solid state disk drive, etc.); and (iii)
information conveyed to a computer by a communications medium, such
as through a computer or telephone network, including wireless
communications. The latter embodiment specifically includes
information downloaded from the Internet and via other networks.
Such signal-bearing media, when carrying computer-readable
instructions that direct the functions of the present invention,
represent embodiments of the present invention.
[0048] In general, the routines executed to implement the
embodiments of the invention, may be part of an operating system or
a specific application, component, program, module, object, or
sequence of instructions. The computer program of the present
invention typically is comprised of a multitude of instructions
that will be translated by the native computer into a
machine-accessible format and hence executable instructions. Also,
programs are comprised of variables and data structures that either
reside locally to the program or are found in memory or on storage
devices. In addition, various programs described hereinafter may be
identified based upon the application for which they are
implemented in a specific embodiment of the invention. However, it
should be appreciated that any particular program nomenclature that
follows is used merely for convenience, and thus the invention
should not be limited to use solely in any specific application
identified and/or implied by such nomenclature.
[0049] The present invention and some of its advantages have been
described in detail for some embodiments. It should be understood
that although the system and process is described with reference to
automated infrastructure management in water borne data centers,
the system and process is highly reconfigurable, and may be used in
other contexts as well. It should also be understood that various
changes, substitutions and alterations can be made herein without
departing from the spirit and scope of the invention as defined by
the appended claims. An embodiment of the invention may achieve
multiple objectives, but not every embodiment falling within the
scope of the attached claims will achieve every objective.
Moreover, the scope of the present application is not intended to
be limited to the particular embodiments of the process, machine,
manufacture, composition of matter, means, methods and steps
described in the specification. A person having ordinary skill in
the art will readily appreciate from the disclosure of the present
invention that processes, machines, manufacture, compositions of
matter, means, methods, or steps, presently existing or later to be
developed are equivalent to, and fall within the scope of, what is
claimed. Accordingly, the appended claims are intended to include
within their scope such processes, machines, manufacture,
compositions of matter, means, methods, or steps.
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