US20090132097A1

US20090132097A1 - Virtual cooling infrastructure

Info

Publication number: US20090132097A1
Application number: US12/260,704
Authority: US
Inventors: Ratnesh Kumar Sharma; Amip J. Shah; Cullen E. Bash; Chandrakant Patel; Chih C. Shih
Original assignee: Individual
Current assignee: Hewlett Packard Development Co LP
Priority date: 2007-11-20
Filing date: 2008-10-29
Publication date: 2009-05-21
Also published as: US20090132699A1; US8131515B2

Abstract

A virtual cooling infrastructure includes a demand manager having logical descriptions of a plurality of heat loads and the demand manager is configured to determine cooling load demands of the heat loads. The infrastructure also includes a capacity manager having logical descriptions of a plurality of cooling system components configured to supply cooling resources to cool the heat loads. The infrastructure further includes a service operator configured to map the cooling resources of the cooling system components to the cooling load demands of the heat loads.

Description

CROSS-REFERENCES

The present application shares some common subject matter with co-pending Provisional Patent Application Ser. No. 60/989,335 (Attorney Docket No. 200702605-1), entitled “Data Center Synthesis”, filed on Nov. 20, 2007, the disclosure of which is hereby incorporated by reference in its entirety.

BACKGROUND

There has been a substantial increase in the number of data centers, which may be defined as locations, for instance, rooms that house computer systems arranged in a number of racks. The computer systems are typically designed to perform jobs such as, providing Internet services or performing various calculations. In addition, data centers typically include cooling systems to substantially maintain the computer systems within desired thermodynamic conditions.
In addition to the number of data centers being increased, there has also been a large increase in the sizes and densities of the data centers. One result of this increase in size and density is that the data centers are becoming ever more complex and thus more difficult for human operators to manage efficiently. Virtualization at the hardware and software levels of the computer systems housed in the data centers have provided some benefits by allowing consolidation and driving higher levels of resource utilization. Typically, however, virtualization of the computer systems has also contributed to the growth in complexity and human operator intervention. Moreover, conventional virtualization of the computer systems typically does not factor the thermodynamic conditions in the data centers.
It would therefore be beneficial to have a virtualization infrastructure that enables efficient operation and cooling of the computer systems, while substantially minimizing human operator involvement and meeting performance goals.

BRIEF DESCRIPTION OF THE DRAWINGS

Features of the present invention will become apparent to those skilled in the art from the following description with reference to the figures, in which:

FIG. 1 shows a simplified block diagram of a system for provisioning cooling resources in a structure, according to an embodiment of the invention;

FIG. 2A illustrates a process diagram of a demand manager depicted in FIG. 1, according to an embodiment of the invention;

FIG. 2B illustrates a process diagram of a service operator and a capacity manager depicted in FIG. 1, according to an embodiment of the invention;

FIG. 3 shows a facility architecture employing the virtual cooling infrastructure depicted in FIG. 1, according to an embodiment of the invention;

FIG. 4 shows a flow diagram of a method of managing a virtual cooling infrastructure, according to an embodiment of the invention; and

FIG. 5 shows a block diagram of a computing apparatus configured to implement or execute the virtual cooling infrastructure depicted in FIG. 1, according to an embodiment of the invention.

DETAILED DESCRIPTION

For simplicity and illustrative purposes, the present invention is described by referring mainly to an exemplary embodiment thereof. In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present invention. It will be apparent however, to one of ordinary skill in the art, that the present invention may be practiced without limitation to these specific details. In other instances, well known methods and structures have not been described in detail so as not to unnecessarily obscure the present invention.
Disclosed herein is a virtual cooling infrastructure and a method of managing the virtual cooling infrastructure to efficiently allocate cooling resources, for instance, in a data center, manufacturing facility, or other structure containing heat loads. The virtual cooling infrastructure includes a demand manager, a capacity manager, and a service operator. The demand manager is configured to create logical descriptions of the heat loads and to determine cooling load demands of the heat loads. The capacity manager is configured to create logical descriptions of a plurality of cooling system components configured to supply cooling resources directly or indirectly to the heat loads. In addition, the service operator is configured to map the cooling resources to the cooling load demands of the heat loads or vice versa.
Through implementation of the virtual cooling infrastructure and method disclosed herein, cooling resources and heat loads are virtualized to provide improved utilization of a given environmental control infrastructure. In addition, the virtual cooling infrastructure and method enable thermal management targets to be achieved within the infrastructural and thermodynamic constraints existing at each of various stages and aggregation levels in a structure containing heat loads. In one regard, the virtual cooling infrastructure and method disclosed herein provide a scalable framework in which various algorithms for distribution, control, negotiation, etc., of cooling resource provisioning may be applied. In another regard, the virtual cooling infrastructure and method disclosed herein seamlessly automates the management of diverse individual cooling resources with the overall service delivery infrastructure of structures containing heat loads, such as, data centers, manufacturing facilities, housing structures, motorized vehicles, etc.
With reference first to FIG. 1, there is shown a simplified block diagram of a system 100 for provisioning cooling resources in a structure, according to an example. It should be understood that the system 100 may include additional elements and that some of the elements described herein may be removed and/or modified without departing from a scope of the system 100.
As shown, the system 100 includes a virtual cooling infrastructure 102, which may comprise software, firmware, and/or hardware and is configured to virtualize capacity outputs of cooling system components 120 based upon virtualized heat load demand inputs or vice versa. Generally speaking, the virtualization of the cooling system components 120, as well as virtualization of heat loads 125 enables improved utilization of a given environmental control infrastructure. The virtualization of the cooling system components 120 and the heat loads 125 may generally be defined as the creation of logical descriptions of the cooling system components 120 and the heat loads 125. In addition, the virtualization may also be defined as including the creation of logical descriptions of cooling resources available from the cooling system components 120 and the heat loads 125.
The heat loads 125 generally comprise heat generated by computer equipment, such as servers, networking equipment, storage devices, etc., components contained in the computer equipment, such as processors, power supplies, disk drives, etc., manufacturing equipment, such as drills, presses, robots, forming machines, etc., as well as any other heat generating elements, including, humans or other animals. The heat loads 125 may also comprise heat loads 125 generated by combinations of elements, such as, all of the servers housed in a single rack, all of the fabrication machines located in a particular area, etc. The heat loads 125 may be generated by any of the elements during performance of workloads, or when the elements are in an operational state. Thus, by way of particular example to heat loads 125 generated by computer equipment, the heat loads 125 may be generated when the computer equipment perform, for instance, computational jobs, graphics rendering operations, various server applications, data storage operations, switching operations, etc.
The cooling system components 120 generally include any reasonably suitable apparatus or combination of apparatuses, for instance, air conditioning units, heat exchangers, chilled water supplies, fans, blowers, etc., for supplying cooling fluid directly or indirectly to dissipate at least some of the heat loads 125. By way of example, the cooling system components 120 may thus be defined to include some or all of components forming a refrigeration cycle to cool the cooling fluid. The cooling system components 120 may also be defined to include particular elements within other cooling elements, such as, a heat exchanger, a fan, etc., contained in within an air conditioning unit. The cooling system components 120 may also include secondary cooling components, such as, a cooling tower, that may not directly supply cooling resources to the heat loads, but may nonetheless be an integral part of the overall cooling infrastructure.
The virtual cooling infrastructure 102 is depicted as including a demand manager 104, a service operator 106, and a capacity manager 108. The virtual cooling infrastructure 102 generally comprises logical representations of the heat loads 125 and the cooling system components 120, configured to perform various functions described herein below. In one example, the virtual cooling infrastructure 102 comprises software stored on a computer-readable storage medium, which may be implemented by a controller of a computing device. In another example, the virtual cooling infrastructure 102 comprises an overlay in an integrated cooling management system.
In instances where the virtual cooling infrastructure 102 comprises software, the virtual cooling infrastructure 102 may be stored on a computer readable storage medium in any reasonably suitable descriptive language and may be executed by the processor of a computing device (not shown). In these instances, the demand manager 104, the service operator 106, and the capacity manager 108 may comprise software modules or other programs or algorithms configured to perform the functions described herein below.
In addition, or alternatively, the virtual cooling infrastructure 102 may comprise firmware or hardware components. In these instances, the virtual cooling infrastructure 102 may comprise a circuit or other apparatus configured to perform the functions described herein. In addition, the demand manager 104, the service operator 106, and the capacity manager 108 may comprise one or more of software modules and hardware modules, such as one or more circuits.
As shown in FIG. 1, the virtual cooling infrastructure 102 is configured to receive input from an input source 130. The input source 130 may comprise a computing device, a storage device, a user-input device, etc., through or from which data may be inputted into the virtual cooling infrastructure 102. In addition, the virtual cooling infrastructure 102 and the input source 130 may form part of the same or different computing device.
The data inputted from or through the input source 130 may include, for instance, workload demand inputs (heat loads), cooling system component descriptions, workload constraints, cooling system component constraints, etc. The data may also include costs, which may be economic and/or environmental costs, associated with cooling the heat loads generated in performing the workloads. The virtual cooling infrastructure 102 may utilize the data as the data is received or may store the data in a data store 140, which may comprise a combination of volatile and non-volatile memory, such as DRAM, EEPROM, MRAM, flash memory, and the like. In addition, or alternatively, the data store 140 may comprise a device configured to read from and write to a removable media, such as, a floppy disk, a CD-ROM, a DVD-ROM, or other optical or magnetic media.
The input source 130 may also comprise one or more apparatuses configured to detect one or more conditions, such as, temperature, pressure, airflow characteristics, power consumption, etc. In addition, or alternatively, the input source 130 may comprise a database that stores historical data pertaining to the one or more conditions. In addition or alternatively, the input source 130 may comprise software and/or hardware configured to model or predict one or more environmental conditions. In any event, the virtual cooling infrastructure 102 may utilize the one or more detected conditions in creating logical representations of the heat loads 125 and the cooling system components 120.
The virtual cooling infrastructure 102 may output data pertaining to the determined capacity outputs. In addition, or alternatively, the virtual cooling infrastructure 102 may output instructions for implementing the determined capacity outputs to an output 150. The output 150 may comprise, for instance, a display configured to display the determined capacity outputs, a fixed or removable storage device on which the determined capacity outputs are stored, a connection to a network over which the identified set of components may be communicated, a connection to one or more of the cooling system components 120, a connection to one or more machines that generate the heat loads 125, etc.
Various operations that the demand manager 104, the service operator 106, and the capacity manager 108 are operable to perform will be described with respect to the following process diagrams 200 and 220 respectively depicted in FIGS. 2A and 2B. It should be understood that the process diagrams 200 and 220 may include additional elements and that some of the elements described herein may be removed and/or modified without departing from respective scopes of the process diagrams 200 and 220.
Turning first to FIG. 2A, there is shown a process diagram 200 of the demand manager 104, according to an example. As shown therein, the demand manager 104 receives heat load constraints 202 and demand inputs 204. In addition, the demand manager 104 outputs demand outputs/capacity inputs 206.
The heat load constraints 202 may include, for instance, criticalities of the workloads that generate the heat loads 125, provisions set forth in a service level agreement (SLA), infrastructure capacity, etc. The provisions set forth in an SLA may include security requirements, uptime requirements, delivery dates, etc., of one or more of the workloads.
The demand inputs 204 may include, for instance, characteristics of the machines that generate the heat loads 125, characteristics of the workloads that are performed to generate the heat loads 125, etc. The characteristics of the machines that generate the heat loads 125 may include cooling load requirements of the heat loads 125 generated during performance of current and/or future workloads, placements of the heat loads 125 in a structure, durations of the heat loads 125, the costs associated with the cooling load requirements, etc. The characteristics of the workloads that generate the heat loads 125 may include, for instance, the resource requirements for performing the workloads, the types of workloads to be performed, etc.
In one regard, the demand manager 104 is configured to forecast how the heat loads 125 are likely to change with time, for instance, based upon historical workload trends. In another regard, the demand manager 104 is configured to implement a recovery plan in the event that one or more of the cooling system components 120 and/or the machines that generate the heat loads 125 fail.
The demand manager 104 is configured to process the heat load constraints 202 and the demand inputs 204 to determine at least one demand output 206. The at least one demand output 206 may include, for instance, a cooling load estimate of the heat loads 125, locations of the heat loads 125, the estimated durations of the heat loads 125, costs, which may include either or both of economic and environmental costs, associated with deploying the machines, which generate the heat loads 125, zone designations of the heat loads 125, thermal management limits, etc. As discussed with respect to FIG. 2B, the demand outputs 206 are equivalent to the capacity inputs 206 that are inputted into the service operator 106.
According to an example, the demand manager 104 is configured to convert the demand inputs into cooling loads and the physical locations where the cooling loads are going to be needed. The demand manager 104 is thus configured to translate the heat load 125 demand into actual cooling load demand. In addition, the demand manager 104 is configured to determine costs, which may include either or both of economic and environmental costs, associated with the actual cooling load demand, while remaining within the thermal management limits of the cooling system components 120.
With respect now to FIG. 2B, there is shown a process diagram 220 of the service operator 106 and the capacity manager 108, according to an example. As shown therein, the capacity manager 108 receives cooling system inputs 222. The cooling system inputs 222 may include, for instance, descriptions of the cooling system components 120, descriptions of the resources that the cooling system components 120 require to operate, an operating cost function of the cooling system components 120, etc. The descriptions of the cooling system components 120 may comprise the physical descriptions of the cooling system components 120, such as, the available capacities, the maximum capacities, run times, reliabilities, etc. The descriptions of the resources may include, for instance, descriptions of power, heat, water, airflow, etc., that the cooling system components 120 require during their operations. The operating cost function may include, for instance, a determination of the economic impact of operating the cooling system components 120 overtime. In addition, the operating cost function may be in monetary terms or in terms of environmental impact, such as, exergy, carbon footprint, etc.
The capacity manager 108 is further configured to allocate cooling resources from the specific cooling system components 120 based upon the cooling loads determined by the demand manager 104 and as conveyed as the capacity inputs 206, or vice versa. In other words, the capacity manager 108 is configured to determine operating levels for the cooling system components 120 to adequately cool the heat loads 125 while staying within the heat load constraints 202 and other constraints, such as, capacity limitations, of the cooling system components 120. Alternatively, the capacity manager 108 is configured to determine the placement and/or magnitudes of the heat loads 125 while staying within operational limits of the cooling system components.
As also shown in FIG. 2B, the service operator 106 receives the demand outputs/capacity inputs 206 from the demand manager 104, which may have been determined as discussed above with respect to the workflow diagram 200. In addition, the service operator 106 receives the cooling resource allocation determined by the capacity manager 108. Generally speaking, the service operator 106 is configured to map out the demand outputs/capacity inputs 206 to the cooling resource allocation determined by the capacity manager 108, or to map out the cooling resource allocation to the demand outputs/capacity inputs 206. In other words, the service operator 106 works with the capacity manager 108 to provide the capacity allocation, zone identification, power estimate, COP estimate, TCO, utilization, etc., of the cooling resources supplied by the cooling system components 120.
The service operator 106 thus operates in a relatively more intelligent manner as compared with conventional localized cooling system controllers because the service operator 106 factors considerations that have relevance to a broader range of machines that generate the heat loads 125 and cooling system components 120. Moreover, the service operator 106 monitors the operations of the machines that generate the heat loads 125 and the cooling system components 120 to substantially ensure that one or more policies are being maintained. In one respect, this monitoring function performed by the service operator 106 enables the demand manager 104 and the capacity manager 108 to perform the functions described herein without having to also perform the monitoring function.
In addition, the service operator 106 is programmed to operate with an understanding that the cooling resources provided by the cooling system components 120 are limited and may thus prioritize the order in which the workloads are performed to also prioritize the order in which the heat loads 125 are generated. More particularly, the service operator 106 negotiates the prioritization of the workloads based upon a plurality of inputs and constraints and the capacities of the cooling system components 120. In one regard, the service operator 106 is able to perform these negotiations because it receives global information pertaining to the capacities of the cooling system components 120 and the heat load 125 demands.
The capacity outputs 224 may include, for instance, allocation of capacity utilization among the cooling system components 120, identification of zones associated with the cooling system components 120, estimation of power consumed by the cooling system components 120, calculation of the coefficient of performance (COP) of the cooling system components 120, calculation of the total cost of ownership (TCO) in implementing the cooling system components 120, calculation of the utilization of the cooling system components 120, etc.
Generally speaking, the service operator 106 is configured to determine placement of the heat loads 125, for instance, which of the machines are to receive which workloads, and to map resources supplied by the cooling system components 120 according to a prioritized arrangement. Alternatively, the service operator 106 is configured to determine resources supplied by the cooling system components 120 and to map placement of the heat loads 125 according to a prioritized arrangement. By way of example, if the service operator 106 requires a capacity of 50 kW to cool a number of heat loads 125, the service operator 106 queries the capacity manager 108 to determine whether 50 kW of capacity is available. The capacity manager 108 determines whether there is 50 kW of available capacity and responds to the service operator 106. If the capacity manager 108 responds that 50 kW of capacity is unavailable, the service operator 108 attempts to determine another allocation of workload and cooling resources in order to perform the workload while remaining within the available cooling resource capacity limitations.
In another example, when a fault occurs in one or more of the cooling system components 120, such that the capacity of the cooling system components 120 is reduced, the service operator 106 is configured to inform the demand manager 104 of the reduction in cooling resources. In this example, the demand manager 104 may determine which of the heat loads 125 are to be reduced to mitigate potential damages caused by the reduction in available cooling resources.
Turning now to FIG. 3, there is shown a facility architecture 300 employing the virtual cooling infrastructure 102 depicted in FIG. 1, according to an example. It should be understood that the facility architecture 300 may include additional elements and that some of the elements described herein may be removed and/or modified without departing from a scope of the facility architecture 300.
As shown in FIG. 3, the facility architecture 300 includes an integrated structure manager 302, a workload manager 304, a system manager 306, and a facility manager 308. The integrated structure manager 302 is configured to supply the virtual cooling infrastructure 102 with information pertaining to various policies that the virtual cooling infrastructure 102 is intended to follow. The policies may include, for instance, provisions set forth in a service level agreement (SLA), power usage goals, workload performance goals, etc.
The system manager 306 receives workload information on the heat loads 125 and forwards the heat load information to the demand manager 104 of the virtual cooling infrastructure 102. The system manager 306 also receives information pertaining to desired utilization of power levels for machines that generate the heat loads 125 from the integrated structure manager 302. The facility manager 308 receives cooling resource information from the cooling system components 120, such as, the level of capacity remaining in the cooling system components 120. The facility manager 308 also receives power usage information from power delivery devices 310 configured to supply power to the cooling system components 120. The facility manager 308 forwards this information to the capacity manager 108 of the virtual cooling infrastructure 102.
As discussed above, the demand manager 104 estimates the cooling load required by the heat loads 125 and the capacity manager 108 allocates cooling resources to the heat loads 125 based upon the available capacities of the cooling system components 120, while remaining within the capacity limitations of the cooling system components 120. In addition, or alternatively, the capacity manager 108 allocates cooling resources first and the demand manager 104 allocates heat loads 125 based upon the allocated cooling resources. In any regard, the service operator 106 is configured to monitor the heat loads 125 and the cooling resource provisioning to substantially ensure that various policies are being met.
As further shown in FIG. 3, the virtual cooling infrastructure 102 may communicate instructions to the facility manager 308 to vary operations of the cooling system components 120 based upon various factors, including, for instance, allocation of the cooling resources (capacity), utilization levels, coefficient of performance (COP), etc. In addition, the virtual cooling infrastructure 102 may also communicate information pertaining to service handling, for instance, passage of a service from one component of an infrastructure to another, to the facility manager 308.
The virtual cooling infrastructure 102 also communicates information pertaining to various metrics and cooling resource allocation zones to the integrated structure manager 302. The various metrics may include, for instance, cooling load estimates, workload locations, workload durations, zones of workload placement, thermal management limits, cost of deployment, etc. In addition, the integrated structure manager 302 may forward this information to the workload manager 304, which is configured to control placement of workloads that generates the heat loads 125.
In addition, or alternatively, although not shown, the virtual cooling infrastructure 102 may be implemented as a single overlay in an integrated cooling management system.
With reference now to FIG. 4, there is shown a flow diagram of a method 400 of managing a virtual cooling infrastructure 102 to efficiently allocate cooling resources, according to an example. It should be apparent to those of ordinary skill in the art that the method 400 represents a generalized illustration and that other steps may be added or existing steps may be removed, modified or rearranged without departing from a scope of the method 400.
The description of the method 400 is made with reference to the cooling provisioning system 100 illustrated in FIG. 1, and thus makes reference to the elements cited therein. It should, however, be understood that the method 400 is not limited to the elements set forth in the cooling provisioning system 100. Instead, it should be understood that the method 400 may be practiced by a system having a different configuration than that set forth in the system 100.
As shown in FIG. 4, at step 402, in the demand manager 104, logical descriptions of a plurality of heat loads 125 are created. In addition, at step 404, cooling load demands of the heat loads 125 are determined.
At step 406, in the capacity manager 108, logical descriptions of a plurality of cooling system components 120 configured to supply cooling resources to cool the heat loads 125 are created. In addition, at step 408, the capacity manager 108 is configured to identify capacity limitations of the cooling system components 120. Moreover, at step 410, the capacity manager 108 may allocate the cooling resources based upon the cooling load demands determined by the demand manager 104 within the capacity limitations of the cooling system components 120.
At step 412, in the service operator 106, the cooling resources of the cooling system components 120 are mapped to the cooling load demands of the heat loads 125. Alternatively, at step 412, in the service operator 106, the cooling load demands of the heat loads 125 are mapped to the cooling resources of the cooling system components 120. The step of mapping may include either of these mapping operations. In addition, at step 414, the service operator 106 may receive policy constraints and at step 416, may at least one of prioritize the placement of the heat loads 125 and modify the mapping of the cooling resources based upon the policy constraints. Prioritization of the placement of the heat loads 125 may comprise, for instance, determining which machines are to be operated and thus generate the heat loads 125 are and when the machines are to be operated and thus generate the heat loads 125.
At step 418 the virtual cooling infrastructure 102 may output data pertaining to the mapping of the cooling resources, data pertaining to the placement of the heat loads 125, data pertaining to the costs associated with the placement of the heat loads 125 and the cooling resource allocations, etc. In addition, or alternatively, at step 418, the virtual cooling infrastructure 102 may output instructions to one or more of the machines that generate the heat loads 125 and the cooling system components 120 to implement the mapping of the cooling resources, the heat load 125 placement determinations, etc.
Although not explicitly depicted in FIG. 4, the demand manager 104 may further determine costs associated with cooling the heat loads 125 and the service operator 106 may determine whether one or more policy constraints are maintainable based upon the costs determined by the demand manager 104.
Some or all of the operations set forth in the method 400 may be contained as a utility, program, or subprogram, in any desired computer accessible medium. In addition, the method 400 may be embodied by a computer program, which can exist in a variety of forms both active and inactive. For example, they may exist as software program(s) comprised of program instructions in source code, object code, executable code or other formats. Any of the above may be embodied on a computer readable medium.
Exemplary computer readable storage devices include conventional computer system RAM, ROM, EPROM, EEPROM, and magnetic or optical disks or tapes. Exemplary computer readable signals, whether modulated using a carrier or not, are signals that a computer system hosting or running the computer program can be configured to access, including signals downloaded through the Internet or other networks. Concrete examples of the foregoing include distribution of the programs on a CD ROM or via Internet download. In a sense, the Internet itself, as an abstract entity, is a computer readable medium. The same is true of computer networks in general. It is therefore to be understood that any electronic device capable of executing the above-described functions may perform those functions enumerated above.
FIG. 5 illustrates a block diagram of a computing apparatus 500 configured to implement or execute the virtual cooling infrastructure 102 depicted in FIG. 1, according to an example. In this respect, the computing apparatus 500 may be used as a platform for executing one or more of the functions described hereinabove with respect to the virtual cooling infrastructure 102.
The computing apparatus 500 includes a processor 502 that may implement or execute some or all of the steps described in the method 400. Commands and data from the processor 502 are communicated over a communication bus 504. The computing apparatus 500 also includes a main memory 506, such as a random access memory (RAM), where the program code for the processor 502, may be executed during runtime, and a secondary memory 508. The secondary memory 508 includes, for example, one or more hard disk drives 510 and/or a removable storage drive 512, representing a floppy diskette drive, a magnetic tape drive, a compact disk drive, etc., where a copy of the program code for the method 400 may be stored.
The removable storage drive 510 reads from and/or writes to a removable storage unit 514 in a well-known manner. User input and output devices may include a keyboard 516, a mouse 518, and a display 520. A display adaptor 522 may interface with the communication bus 504 and the display 520 and may receive display data from the processor 502 and convert the display data into display commands for the display 520. In addition, the processor(s) 502 may communicate over a network, for instance, the Internet, LAN, etc., through a network adaptor 524.
It will be apparent to one of ordinary skill in the art that other known electronic components may be added or substituted in the computing apparatus 500. It should also be apparent that one or more of the components depicted in FIG. 5 may be optional (for instance, user input devices, secondary memory, etc.).
What has been described and illustrated herein is a preferred embodiment of the invention along with some of its variations. The terms, descriptions and figures used herein are set forth by way of illustration only and are not meant as limitations. Those skilled in the art will recognize that many variations are possible within the scope of the invention, which is intended to be defined by the following claims—and their equivalents—in which all terms are meant in their broadest reasonable sense unless otherwise indicated.

Claims

1. A virtual cooling infrastructure comprising:

a demand manager having logical descriptions of a plurality of heat loads, wherein the demand manager is configured to determine cooling load demands of the heat loads;

a capacity manager having logical descriptions of a plurality of cooling system components configured to supply cooling resources to cool the heat loads; and

a service operator configured to map the cooling resources of the cooling system components to the cooling load demands of the heat loads.

2. The virtual cooling infrastructure according to claim 1, wherein the capacity manager is further configured to identify capacity limitations of the cooling system components and to allocate the cooling resources based upon the cooling load demands determined by the demand manager within the capacity limitations of the cooling system components.

3. The virtual cooling infrastructure according to claim 1, wherein the service operator is further configured to receive policy constraints and to at least one of prioritize placement of the heat loads in a structure and modify the mapping of the cooling resources to the cooling load demands, or vice versa, based upon the policy constraints.

4. The virtual cooling infrastructure according to claim 3, wherein the service operator is further configured to monitor operations of sources of the heat loads and the cooling system components to substantially ensure that the policy constraints are being maintained.

5. The virtual cooling infrastructure according to claim 1, wherein the demand manager is further configured to process a plurality of demand inputs to determine a plurality of demand outputs/capacity inputs, and wherein the demand manager is further configured to convey the demand outputs/capacity inputs to the capacity manager.

6. The virtual cooling infrastructure according to claim 5, wherein the demand manager is further configured to determine costs associated with the demand outputs/capacity inputs and to provide the service operator with the determined costs, and wherein the service operator is further configured to determine whether one or more policy constraints maintainable based upon the determined costs.

7. The virtual cooling infrastructure according to claim 1, wherein the logical descriptions of the cooling system components comprise logical descriptions of one or more of physical descriptions, respective capacities, cooling capabilities, actual run times, projected run times, and reliabilities of the plurality of cooling system components.

8. The virtual cooling infrastructure according to claim 1, wherein the logical descriptions of the cooling system components comprise at least one of resources associated with operating the cooling infrastructures and costs associated with operating the cooling infrastructures.

9. The virtual cooling infrastructure according to claim 1, wherein the demand manager, the capacity manager, and the service operator form part of a single overlay in an integrated cooling management system.

10. A method of managing a virtual cooling infrastructure to efficiently allocate cooling resources, said virtual cooling infrastructure comprising a demand manager, a service operator, and a capacity manager, said method comprising:

in the demand manager,

creating logical descriptions of a plurality of heat loads; and

determining cooling load demands of the heat loads;

in the capacity manager,

creating logical descriptions of a plurality of cooling system components configured to supply cooling resources to cool the heat loads; and

in the service operator,

mapping the cooling resources of the cooling system components to the cooling load demands of the heat loads or vice versa.

11. The method according to claim 10, said method further comprising:

in the capacity manager,

identifying capacity limitations of the cooling system components; and

allocating the cooling resources based upon the cooling load demands determined by the demand manager within the capacity limitations of the cooling system components.

12. The method according to claim 10, said method further comprising:

in the service operator,

receiving policy constraints;

at least one of prioritizing placement of the heat loads and modifying the mapping of the cooling resources based upon the policy constraints.

13. The method according to claim 10, said method further comprising:

in the demand manager,

determining costs associated with cooling the determined cooling load demands in cooling the heat loads; and

in the service operator;

determining whether one or more policy constraints are maintainable based upon the costs determined by the demand manager.

14. A computer readable storage medium on which is embedded one or more computer programs, said one or more computer programs implementing a method of managing a virtual cooling infrastructure to efficiently allocate cooling resources, said virtual cooling infrastructure comprising a demand manager, a service operator, and a capacity manager, said one or more computer programs comprising a set of instructions for:

in the demand manager,

creating logical descriptions of a plurality of heat loads; and

determining cooling load demands of the heat loads;

in the capacity manager,

in the service operator,

mapping the cooling resources of the cooling system components to the cooling load demands of the heat loads.

15. The computer readable storage medium according to claim 14, said one or more computer programs further including a set of instructions for:

in the capacity manager,

identifying capacity limitations of the cooling system components; and

allocating the cooling resources based upon the cooling load demands determined by the demand manager within the capacity limitations of the cooling system components; and

in the service operator,

receiving policy constraints; and

at least one of prioritizing the workloads placed on the heat loads and modifying the mapping of the cooling resources based upon the policy constraints.