Management of airflow provisioning to meet a cooling influence redundancy level

In an implementation, airflow provisioning in an area by a plurality of fluid moving devices is managed through assignment of the fluid moving devices to monitor and regulate conditions at respective subsets of a plurality of locations based upon determined influence levels of the fluid moving devices on the respective locations to meet a predefined cooling influence redundancy level. The predefined cooling influence redundancy level for a particular location identifies a number of the fluid moving devices that are to monitor and regulate a condition at the particular location.

BACKGROUND

Data centers typically include multiple cooling units, such as, computer room air conditioning (CRAG) units, arranged to supply cooling airflow to a plurality of servers arranged in rows of racks. The cooling airflow is often supplied through vent tiles distributed at multiple locations on a raised floor. More particularly, the cooling units supply cooling airflow into a plenum formed beneath the raised floor and the cooling airflow is supplied to the servers through the vent tiles.

Guaranteed uptime is typically an objective of mission critical data centers. As a result, most data center designs have built-in redundancy in their cooling systems. In typical N+k cooling redundancy designs, the cooling systems often over provision cooling to accommodate possible cooling system component failures. The over-provisioning of the cooling is performed by constantly running all of the cooling units at a capacity targeting the worst case failure scenario. As such, although the desired level of redundancy may be achieved, the cooling efficiency is greatly decreased. Conventional redundancy practices therefore lead to high operational costs and ultimately a high total cost of ownership.

DETAILED DESCRIPTION

Conventional techniques for categorizing cooling redundancy merely add additional cooling units into a data center without regard as to how the positioning of the additional cooling units affect different locations within the data center. As a result, the redundancy afforded by the additional cooling units is different for different locations within the data center. In addition, conventional techniques for categorizing cooling redundancy fail to consider the capacities of the cooling units and thus, there is no consideration as to how the cooling units are to be run. As such, conventional techniques of providing cooling redundancy merely run all of the cooling units all of the time or cycle all of the cooling units according to a predefined schedule. Conventional techniques for categorizing cooling redundancy therefore fail to accurately describe how the additional cooling units actually provide cooling redundancy in data centers and how the cooling redundancy may be achieved in a cost-efficient manner.

Disclosed herein is a cooling influence redundancy level, which may be defined as the number of cooling units, also referred herein as fluid moving devices, that are actively monitoring and regulating a condition, such as temperature, at a particular location. In other words, a location of interest, such as a rack inlet, is considered to have a “N+k” cooling influence redundancy level if the condition, such as temperature, at this location of interest is monitored and actively maintained by “k+1” cooling units. Thus, by way of example, if a thermal violation (e.g., temperature outside of a predetermined range) occurs at a location with a “N+k” cooling influence redundancy level, “k+1” cooling units will detect this thermal violation and respond simultaneously to mitigate the adverse thermal conditions. As such, a cooling influence redundancy level of “N+k” has a built-in action policy to respond to thermal violations at any location of interest when one or more cooling unit failures occur.

In one regard, by defining cooling influence redundancy levels for locations of interest in an area, such as rack inlets of a data center, the number of fluid moving devices that are able to provide redundant regulation of conditions at those locations may also be defined. As such, if one or more fluid moving devices that are to regulate a condition at a particular location of interest fails, other fluid moving devices that are also assigned to regulate the condition at that particular location of interest may vary their operations to compensate for the failure. In this regard, the cooling influence redundancy disclosed herein enables dynamic cooling redundancy to be performed in the area regardless of the locations in which the fluid moving devices are positioned in the area so long as there are at least two fluid moving devices that are able to supply cooling airflow to the different locations in the area.

Disclosed herein is a method for managing airflow provisioning in an area, such as a data center, by a plurality of fluid moving devices, in which the fluid moving devices are assigned to subsets of locations of interest in the area to meet predefined cooling influence redundancy levels for the locations of interest. Also disclosed herein are an apparatus for implementing the method and a non-transitory computer readable medium on which is stored machine readable instructions that implement the method.

As disclosed herein, the respective levels of influence each of the fluid moving devices has on the locations of interest are determined through use of a model that describes airflow transport and distribution to the locations of interest. In addition, the determined levels of influence are used to assign the fluid moving devices to the respective subsets of the locations of interest to meet the predefined cooling influence redundancy levels. As also disclosed herein, the fluid moving devices are managed to substantially minimize energy consumption in maintaining conditions at the locations of interest within predetermined ranges. More particularly, the fluid moving devices may be managed according to determined settings that minimize a cost function. In addition, according to an example, the fluid moving devices are managed by a set of controllers that are distributed with respect to each other.

Through implementation of aspects of the present disclosure, a cooling control technique is provided that results in cooling redundancy with relatively high cooling efficiency, e.g., through substantially minimizing the costs associated with airflow provisioning. In addition, the cooling control technique disclosed herein enables fluid moving devices to automatically respond to cooling failures in an area, to thereby avoid or mitigate damage caused by the failures. Moreover, aspects of the present disclosure also enable the controllers of the fluid moving devices to be distributed with respect to each other such that failure of a controller does not result in failures of all of the fluid moving devices.

With reference first toFIG. 1, there is shown a simplified perspective view of a section of an area100, in this instance, a data center, in which a method and apparatus for managing airflow provisioning may be implemented, according to an example. The data center100is depicted as having a plurality of racks102a-102n, a plurality of fluid moving devices (FMDs)114a. . .114l(the ellipses denoted between the FMDs114aand114lsignify that the data center100may include additional fluid moving devices), a plurality of vent tiles118a-118m, and a plurality of sensors120a-120n.

The racks102a-102nare depicted as being positioned on a raised floor110and as housing electronic devices116. The electronic devices116comprise, for instance, computers, sewers, bladed servers, disk drives, displays, etc. As shown inFIG. 1, airflow, such as cool airflow, is delivered through vent tiles118a-118min the floor110to the racks102a-102n. The FMDs114a-114lgenerally operate to supply airflow into a space112beneath the raised floor110, and in certain instances to cool heated airflow (indicated by the arrows124). The FMDs114a-114lmay comprise, for instance, air conditioning (AC) units that have actuators for controlling the temperature and the volume flow rate of the cooled airflow supplied by the fluid moving devices114a-114l. In other examples, the FMDs114a-114lcomprise heaters having actuators to control the temperature and volume flow rate of heated airflow supplied by the fluid moving devices114a-114l.

The vent tiles118a-118mcomprise manually and/or automatically adjustable vent tiles. In any regard, the vent tiles118a-118mmay be adjusted to thereby vary the volume flow rate of airflow supplied through the vent tiles118a-118m. When the vent tiles118a-118mcomprise automatically adjustable vent tiles, actuators (not shown) are provided to vary the operational settings of the vent tiles118a-118m. In addition, each of the vent tiles118a-118mmay also include an interface through which the vent tiles118a-118mmay receive instruction signals from a controller130. The operational settings of the vent tiles118a-118mmay include the opening levels of the vent tiles118that may be used to vary the volume flow rate of the airflow and, in some instances, a speed level of local fans used to vary the flow rates of the airflow through the vent tiles118a-118m. The vent tiles118a-118mmay have many different suitable configurations and are thus not to be limited to any particular type of vent tile.

In any regard, the airflow contained in the space112may include airflow supplied by more than one of the FMDs114a-114l. Thus, characteristics of the airflow, such as, temperature, pressure, humidity, flow rate, etc., delivered to various locations in the data center100may substantially be affected by the operations of multiples ones of the FMDs114a-114l. As such, conditions at various locations in the data center100may substantially be affected by the operations of more than one of the FMDs114a-114l. For instance, the temperature at an inlet of a particular rack may be affected by more than one of the FMDs114a-114land thus, if one of the FMDs114awere to fail, another one of the FMDs114bmay be able to deliver cooling airflow to that particular rack.

The sensors120a-120nmay be positioned in the data center100at various desired locations, such as at the inlets of various racks of interest, within the equipment116(which may comprise sensors integrated within the equipment116), the inlets and/or outlets of FMDs114a-114l, etc. The locations of interest at which the sensors120a-120nare located may comprise a subset of all of the racks contained in the data center100, a subset of all of the FMDs114a-114l, etc. In addition, multiple sensors120a-120nmay be positioned at various locations of interest. In any regard, the sensors120a-120nmay be networked, in a wired and/or wireless manner, with the controller130to convey detected condition information to the controller130. The detected conditions may include, for instance, temperatures at the inlets of the racks102a-102n, temperatures at the outlets of the vent tiles118, temperatures at the inlets and/or outlets of FMDs114a-114l, temperatures within some or all of the equipment116, etc. The detected conditions may, in addition or alternatively, include other environmental conditions, such as, pressure, humidity, airflow velocity, etc. In this regard, the sensors120a-120ncomprise any suitable types of sensors to detect the conditions.

As discussed in greater detail herein below, environmental condition information collected by the sensors120a-120nis used to determine various parameters of a model that describes airflow transport and distribution within the data center100. In one example, the model comprises a physics based state-space model. As also discussed in greater detail herein below, the model further describes effects of actuations on the fluid moving devices114a-114l, and in certain instances, the settings of the vent tiles118a-118m, on the airflow transport and distribution within the data center100. In this regard, the model disclosed herein may be a holistic model. Moreover, the model is implemented to manage airflow provisioning in the data center100, which includes minimization of the power required to cool the equipment116in the data center100. In addition, the management of airflow provisioning also includes compensation for failures by one or more of the fluid moving devices114a-114lor their respective controllers.

In one example, values obtained through implementation of the model are used to determine the levels of influence each of the fluid moving devices114a-114lhas at various locations of the data center100, such as at the inlets of the racks. The respective levels of influence that the fluid moving devices114a-114lhave on the various locations of the data center100are used to meet predefined cooling influence redundancy levels for the various locations. The cooling influence redundancy level generally identifies a number of the fluid moving devices114a-114lthat are to monitor and regulate a condition at a particular location, e.g., a particular rack inlet. The cooling influence redundancy level may therefore be considered as a level of redundancy to be provided to the particular location. In this regard, a predetermined number of fluid moving devices114a-114lhaving the highest level of influence over a particular location's condition may be assigned to monitor and regulate the condition at the particular location to thereby meet the predefined cooling influence redundancy level for that particular location. In addition, the predefined cooling influence redundancy level may vary between locations or may be uniform throughout the data center100.

In another example, the obtained values are used to control the fluid moving devices114a-114land the vent tiles118a-118m(when the vent tiles118a-118mcomprise adjustable vent tiles) to manage airflow provisioning in the data center100. In a further example, the obtained values are used in the minimization of a cost function to determine how the fluid moving devices114a-114lare to be operated to meet a predefined operational goal, such as minimization of energy consumption by the fluid moving devices114a-114lin maintaining conditions in the data center100within predetermined levels.

It should be understood that the data center100may include additional elements and that some of the elements described herein may be removed and/or modified without departing from a scope of the data center100. In addition, the data center100may comprise a data center that is in a fixed location, such as a building, and/or a data center that is in a movable structure, such as a shipping container or other relatively large movable structure. Moreover, although particular reference has been made in the description of the area100as comprising a data center, it should be understood that the area100may comprise other types of structures, such as, a room in a building, an entire building, etc.

Although the controller130is illustrated inFIG. 1as comprising an element separate from the electronic devices116, the controller130may comprise or be integrated with an electronic device116without departing from a scope of the data center100disclosed herein. In addition, or alternatively, the controller130may comprise a set of machine readable instructions to operate on a computing device, for instance, one of the electronic devices116or a different computing device. Moreover, although a single controller130has been depicted inFIG. 1, a plurality of controllers130may be implemented to respectively control individual ones or groups of fluid moving devices114a-114land, in further examples, individual ones or groups of vent tiles118a-118m.

Turning now toFIG. 2, there is shown a diagram200of a decentralized control system structure, according to an example. In the diagram200, only three fluid moving devices (FMDs)114a-114cand three controllers202a-202care shown for purposes of simplicity, but it should be understood that any suitable number of FMDs114a-114land controllers202a-2021may be provided without departing from a scope of the decentralized control system structure depicted therein.

InFIG. 2, the ovals around each of the FMDs114a-114crepresent locations in the data center100assigned to the FMDs114a-114c, which are also referred herein as zones of influence of the FMDs114a-114l. As depicted inFIG. 2, a first FMD114aand a second FMD114bshare an overlapping area210, the first FMD114aand a third FMD114cshare an overlapping area212, the second FMD114band the third FMD114cshare an overlapping area214, and all three FMDs114a-114cshare an overlapping area216. In addition, the first FMD114ais controlled by a first controller202a, the second FMD114bis controlled by a second controller202b, and the third FMD114cis controlled by a third controller202c. Each of the controllers202a-202cmay comprise or may be integrated with an electronic device116. In addition, or alternatively, each of the controllers202a-202cmay comprise a set of machine readable instructions to operate on a computing device, for instance, one of the electronic devices116or a different computing device.

According to an example, each of the controllers202a-202ccomprises a set of machine readable instructions that is stored in a separate machine with respect to the other sets of machine readable instructions, such that failure of a particular controller will not cause all of the fluid moving devices114a-114cto fail. The separate machines may comprise multiple ones of the electronic devices116, respective FMDs114a-114c, combinations thereof, etc.

In any regard, each of the controllers202a-202cis to control characteristics of airflow supplied by a respective FMD114a-114c. The characteristics of the airflow include the temperature and/or the volume flow rate of the airflow supplied by FMDs114a-114c. Although not shown, each of the controllers202a-202cis to access data pertaining to conditions detected by sensors120a-120ncontained in the respective zones of influence of the FMDs114a-114c.

Generally speaking, the diagram200inFIG. 2depicts a failure resistant decentralized cooling control system structure. That is, each of the overlapping areas210-216denote that if the first FMD114afails, the temperature vector (T1) will increase and the temperature increase in the overall regions210and212will be sensed by the second controller202band the third controller202c. The second controller202band the third controller202cmay each respond by provisioning greater cooling resources from the second FMD114band the third FMD114c, which will increase the supply of cooling airflow to the thermal zone originally regulated by the first FMD114ato thereby mitigate temperature increases due to the failure of the first FMD114a.

According to an example, each of the controllers202a-202cmay monitor and regulate conditions at various locations in the data center100to meet a predefined cooling influence redundancy level in the data center100. That is, for instance, if each of the locations of interest in the zone of interest of the first FMD114ais to have a predefined cooling influence redundancy level of n+1, then the conditions detected by the sensors120a-120nin that zone of influence are available to at least one of the second and third controllers202band202c, such that at least one of the second and third controllers202band202care also able to monitor and regulate conditions in the zone of influence of the first FMD114a. As such, the cooling influence redundancy level may be defined as an identification of a number of fluid moving devices114a-114l(or their controllers202a-202c) that are to monitor and regulate a condition at a particular location of interest, such as a rack inlet.

As also discussed in greater detail herein below, the controllers202a-202care to control operations of the FMDs114a-114l, such that the amount of energy consumed by the FMDs114a-114lin meeting cooling objectives is substantially minimized. That is, in contrast to conventional redundant systems, the FMDs114a-114lmay not be operated at relatively high energy consumptions to provide redundancy.

Turning now toFIG. 3, there is shown a block diagram of a machine300for managing airflow provisioning in an area100, such as the data center depicted inFIG. 1, according to an example. It should be understood that the machine300may include additional components and that some of the components described herein may be removed and/or modified without departing from the scope of the machine300.

As shown, the machine300includes a processor302, a data store304, an input/output interface306, and a controller310. The machine300comprises any of, for instance, a server, a computer, a laptop computer, a tablet computer, a personal digital assistant, a cellular telephone, or other electronic apparatus that is to perform a method for managing airflow provisioning in an area by a plurality of fluid moving devices114a-114l.

The controller310is further depicted as including an input/output module312, a data collecting module314, a model accessing module316, a parameter determining module318, a managing module320, and an actuation module322. The controller310may comprise the controller130depicted inFIG. 1, any of the controllers202a-202cdepicted inFIG. 2, or other controller of the FMDs114a-114l. In any regard, the processor302, which may comprise a microprocessor, a micro-controller, an application specific integrated circuit (ASIC), or the like, is to perform various processing functions in the machine300. One of the processing functions includes invoking or implementing the modules312-322contained in the controller310as discussed in greater detail herein below.

According to an example, the controller310comprises machine readable instructions stored, for instance, in a volatile or non-volatile memory, such as DRAM, EEPROM, MRAM, flash memory, floppy disk, a CD-ROM, a DVD-ROM, or other optical or magnetic media, and the like. In this example, the modules312-322comprise modules of machine readable instructions stored in the memory, which are executable by the processor302. According to another example, the controller310comprises a hardware device, such as a circuit or multiple circuits arranged on a board. In this example, the modules312-322comprise circuit components or individual circuits, which the processor302is to control. According to a further example, the controller310comprises a combination of modules with machine readable instructions and hardware modules.

The input/output interface306comprises a hardware and/or a software interface that may be connected to an internal bus and/or to a network330, over which the controller310may receive and communicate information. The network330generally represents a wired and/or wireless structure in the data center100for the transmission of data and/or signals between the various components in the data center100. As also shown inFIG. 3, and according to an example, the fluid moving devices114a-114l, the vent tiles118a-118m, and the sensors120a-120nare also connected to the network330and may thus communicate data with and/or receive instructions from the processor302. In examples in which the vent tiles118a-118mdo not comprise adaptive vent tiles, the vent tiles118a-118mmay be removed fromFIG. 3. In addition, in examples in which the controller310is to control a particular FMD114a, the remaining FMDs114b-114lmay be removed fromFIG. 3. Likewise,FIG. 3may depict the subset of sensors120a-120nfrom which the controller310is to receive data and the remaining sensors120a-120nmay be removed fromFIG. 3.

According to an example, the sensors120a-120nare each assigned an identifier that is unique to the sensor within the set of sensors120a-120nand the locations of the sensors120a-120nare tracked along with their respective identifiers. In this regard, when the sensors120a-120ncommunicate sensed data, such as a measured temperature at a particular rack inlet, the sensors120a-120nmay include their identifiers in the communications to enable their locations to be determined. In any regard, each of the controllers310of the FMDs114a-114lmay use sensed data from only those sensors120a-120nto which the controllers310are assigned to monitor and regulate, for instance, as determined by the predefined cooling influence redundancy levels of the FMDs114a-114lwith respect to the locations in which the sensors120a-120nare located.

According to an example, the sensors120a-120nbroadcast their sensed data to each of the controllers310of the FMDs114a-114l. In another example, the sensors120a-120ncommunicate their sensed data to a database and the controllers310of the FMDs114a-114laccess the database to retrieve sensed data stored in the database from the sensors120a-120nto which they are respectively assigned. In a further example, the controllers310of the FMDs114a-114lping the sensors120a-120nto which they are respectively assigned for current condition data at regular intervals of time.

In any regard, the processor302may receive the sensed data from the sensors120a-120nor selected subsets of the sensors120a-120nthrough the input/output interface306and may store the received data in the data store304. The processor302may use the sensed data, as well as other data stored in the data store304in implementing the modules312-322. The data store304comprises volatile and/or non-volatile memory, such as DRAM, EEPROM, MRAM, phase change RAM (PCRAM), Memristor, flash memory, and the like.

According to an example, the controller310outputs operational settings of the FMDs114a-114lto be implemented, for instance, during determination of the respective influence levels of the FMDs114a-114lon each of a plurality of locations. The operational settings may include volume flow rate set point(s), instructions pertaining to the determined volume flow rate set point(s), determined supply temperature set point(s), instructions pertaining to the determined supply temperature set point(s), determined operational settings and/or instructions pertaining to the determined operational settings through the input/output module306, etc.

According to an example, the operational settings are outputted to a display upon which the outputted information may be displayed, a printer upon which the outputted information may be printed, a network connection over which the outputted information may be conveyed to another computing device, a data storage device upon which the outputted information may be stored, etc. In this instance, a user may manually cause the FMDs114a-114lto be set to the operational settings, According to another example, the controller310communicates instruction signals over the network330to the FMDs114a-114l. In this example, the FMDs114a-114l, or their respective controllers, may vary the volume flow rates and/or supply air temperatures of the FMDs114a-114lto reach the determined set points as instructed by the controller310. According to another example, the operational settings of the vent tiles118a-118mare also varied during determination of the respective influence levels of the FMDs114a-114lon each of a plurality of locations.

As also discussed in greater detail herein below, the controller310may additionally or alternatively comprise a controller of a FMD114a. In addition, each of the remaining FMDs114b-114lmay be controlled by a respective controller having the configuration of the controller310. In this example, each of the controllers310of the FMDs114a-114lmay be stored or contained in separate machines300to thereby enhance redundancy in the control of the FMDs114a-114l. In addition, each of the controllers310of the FMDs114a-114lmay be assigned to monitor and regulate conditions of particular locations based upon conditions detected by the sensors120a-120n. Moreover, each of the controllers310is to control respective ones of the FMDs114a-114lin manners that substantially minimize the amount of energy consumed by the FMDs114a-114lin maintaining conditions in the locations within predetermined ranges. As used throughout the remainder of the present disclosure, references to various operations performed by the FMDs114a-114lare to be considered as equivalently being performed by the controllers310of the FMDs114a-114l.

Various manners in which the modules312-322of the controller310may operate are discussed with respect to the methods400-600depicted in FIGS.4-6. It should be readily apparent that the methods400-600respectively depicted inFIGS. 4-5represent generalized illustrations and that other elements may be added or existing elements may be removed, modified or rearranged without departing from the scopes of the methods400-600.

With reference first toFIG. 4, there is shown a flow diagram of a method400for managing airflow provisioning in an area, such as, a data center100, according to an example. At block402, a predefined cooling influence redundancy level for a plurality of locations in the area, e.g., data center100, is accessed, for instance, by the managing module320. As discussed above, the cooling influence redundancy level for a particular location identifies a number of the FMDs114a-114nthat are to monitor and regulate a condition at the particular location.

According to an example, the cooling influence redundancy level for the plurality of locations is predefined by a user, such as a data center administrator, a customer who is to receive the data center resources, etc., and may be stored in the data store304. In addition, a number of different cooling influence redundancy levels may be predefined for a number of different locations of interest in the data center100. Thus, for instance, locations, e.g., racks, housing equipment116that are to perform relatively more critical operations may have a relatively higher cooling influence redundancy level than other locations that house equipment116that are to perform relatively less critical operations. In this regard, a data center100operator may charge customers different rates depending upon the cooling influence redundancy levels the customers seek.

At block404, respective influence levels of the plurality of FMDs114a-114non each of the plurality of locations are determined, for instance, by the model accessing module316and the parameter determining module318. Various manners in which the respective influence levels of the plurality of FMDs114a-114non each of the plurality of locations may be determined are described in greater detail below with respect to the method400inFIG. 4.

At block406, the FMDs114a-114lare assigned to monitor and regulate the conditions of respective subsets of the plurality of locations to meet the predefined cooling influence redundancy level(s), for instance, by the managing module320. More particularly, the controllers310of the FMDs114a-114lare assigned to monitor and regulate those locations over which the FMDs114a-114lhave a determined influence level, in which the number of controllers310assigned to monitor and regulate those locations is determined by the predefined cooling influence redundancy level. Thus, by way of example, for a particular location whose condition is detected by a sensor120a, a first FMD114amay be determined to have the highest influence level on that particular location, a second FMD114bmay be determined to have the second highest influence level on that particular location, and a third FMD114cmay be determined to have the third highest influence level on that particular location. In this example, if the predefined cooling influence redundancy level is N+1, then the controllers310of the first FMD114aand the second FMD114bare assigned to monitor and regulate the particular location. Alternatively, if the predefined cooling influence redundancy level is N+2, then the controllers310of each of the first, second, and third FMDs114a-114care assigned to monitor and regulate the particular location.

Assignment of the plurality of FMDs114a-114lto monitor and regulate the conditions of respective subsets of the plurality of locations generally means that the FMDs114a-114lare to track the conditions detected by respective ones of the sensors120a-120nin the subsets of the plurality of locations, such as sensors120a-120nlocated at the inlets of the racks as depicted inFIG. 1. As such, in the example above, in which the predefined cooling redundancy level is N+1 for the particular location, the controllers310of the first and second FMDs114aand114bare to track and regulate conditions detected by the sensor120a. In addition, the controller310of the third FMD114cdoes not track the conditions detected by the sensor120a. As such, if the first. FMD114awere to fail, the second FMD114bwould still be able to monitor and regulate the conditions at the location of the sensor120a.

According to a particular example, at block402, a first predefined cooling influence redundancy level for a first location and a second predefined cooling influence redundancy level for a second location are accessed, in which the second predefined cooling influence redundancy level differs from the first predefined cooling influence redundancy level. In this example, assigning of the plurality of FMDs114a-114nat block406further comprises assigning the plurality of FMDs114a-114lto monitor and regulate the conditions of the first location and the second location based upon the determined influence levels of the plurality of FMDs114a-114lon the first location and the second location to meet the first predefined cooling influence redundancy level on the first location and the second predefined cooling influence redundancy level on the second location.

Turning now toFIG. 5, there is shown a flow diagram of a method500of determining the respective influence levels of the FMDs114a-114lon each of the plurality of locations, according to an example. In this regard, the method500depicts a relatively more detailed operation of block404inFIG. 4.

At block502, a model that describes airflow transport and distribution within the area is accessed, for instance, by the model accessing module316. The model may be stored in the data store304and the model accessing module316may access the model from the data store304. The model comprises a plurality of parameters and describes the effects of actuations on the plurality of FMDs114a-114lon the airflow transport and distribution within the area, such as the data center100. More particularly, the model describes the effects of actuations on the plurality of FMDs114a-114land the vent tiles118a-118min instances in which the vent tiles118a-114mare adjustable or are otherwise to be considered, on the transport and distribution of airflow supplied into the racks and thus the electronic devices116.

According to an example, the model is a state-space model based on energy and mass balance principles. In a non-limiting example, the model is a physics based state-space model. An example of the physics based state-space model is described by the following equation:

in which T represents a rack inlet temperature (location in the area), k and k+1 represent discrete time steps, SATiand VFDiare a supply air temperature and a blower speed of the ith FMD114a-114l, Ujis the opening of the jth vent tile118a-118m, NCRACand Ntileare the number of FMDs114a-114land vent tiles118a-118m, respectively, and wherein giand bjare parameters that capture influences of each FMD i and vent tile j, respectively, and C denotes a temperature change due to additional factors, such as recirculation and reversed flow. In instances in which the vent tiles118a-118mare not adjustable or if the effects of the vent tiles118a-118mon the airflow distribution are not to be factored, the term

{∑j=1Ntile⁢⁢bj·Uj⁡(k)]}
in Eqn (1) may be set to 1 or otherwise removed from the equation.

At block504, values for the parameters in the model are determined, for instance, by the parameter determining module318. Generally speaking, the parameter determining, module318determines the values for the parameters through an analysis of detected condition data received from the sensors120a-120n. More particularly, the parameter determining module318determines values for the parameters gi, bjand C in Eqn (1) through an optimization process, in which the parameter values that minimize the difference between the thermal status (rack inlet temperatures) predicted by the model using the parameters (gi, b1, and C) being evaluated and the detected conditions. The parameters (gi, bj, and C) that result in the least amount of difference between the thermal status (rack inlet temperatures) predicted by the model are selected as the values for the parameters (gi, bj, and C). This optimization process is repeated for each rack inlet temperature since each rack inlet temperature is characterized by a different set of parameters. Alternatively, the parameter determining module318may implement the parameter optimization process for a plurality of different rack inlet temperatures in parallel.

The parameter (gi) denotes the influence level of a particular FMD (i)114a-114lon a particular location (7), such as on the temperature at an inlet of a particular rack. By way of example, in a data center100having 8 FMDs114a-114l, each detected rack inlet temperature will have 8 influence levels (gi), each representing the influence level of one FMD114a-114l.

Turning now toFIG. 6, there is shown a flow diagram of a method600for managing airflow provisioning, and more particularly, for controlling, by a controller310of an FMD114a, the FMD114ato regulate the conditions at a plurality of locations that are assigned to the controller310, according to an example. The method600may be implemented by each of the controllers310of the remaining FMDs114b-114lin the data center100.

In implementing the method600, the controller310may have access to information to an associated FMD114a, such as the supply air temperature and the blower speed of the FMD114a. The controller310may also have access to the sensors120a-120nlocated in the zone of influence of the FMD114a.

At block602, a cost function is accessed, for instance, by the managing module320from the data store304. According to an example, the cost function comprises the total airflow provisioning power consumption and is defined with respect to the airflow provisioning actuations available on the FMD114a. The available airflow provisioning actuations in the FMD114acomprise temperature and volume flow rate of airflow supplied by the FMD114a.

At block604, airflow provisioning actuation of the FMD114ais determined through use of a model to minimize the cost function, for instance, by the managing module320. According to an example, and assuming that the jth zone is assigned to FMD114aand that the vent tiles118a-118mare not adaptive vent tiles and/or that the vent tiles118a-118mare not considered, the model for a rack inlet temperature (7) in the jth zone may be defined as:
T(k+1)=T(k)+gj·[SATj(k)−T(k)]·VFDj(k)+C(k),  Eqn (2)
in which the influence of recirculation and FMDs114b-114loutside the jth zone is included in the value C(k). Using this model, a model predictive controller (MPG) may be designed for each thermal zone to minimize the cooling cost incurred by each of the FMDs114a-114l. An example of the MPG is shown inFIG. 7, which the controller310of the FMD114amay use to minimize the cost function.

According to an example, given the current thermal status (rack inlet temperatures) as detected by the sensors120a-120nto which the controller310of the FMD114ais assigned, the MPG may implement the model to predict future rack inlet temperature trajectories when the trajectories of the airflow actuations (VFD and SAT of the fluid moving devices114a-114l) are given. The prediction of the future rack inlet temperature trajectories may be used to evaluate all of the possible actuations implemented at discrete time steps with the updated current thermal status, and thus, thermal anomalies may be handled, and operating cost may constantly be minimized in response to varying conditions within the data center100.

Additionally at block604, the model is implemented to minimize the cost function while substantially maintaining temperature levels at the rack inlets within predetermined ranges. The following equation describes an example in which the cost function represents the total cooling power:
VFDi3(k)RVFD+(−SATi(k))RSAT,  Eqn (3)

in which the RVFDand RSATare appropriate positive weights on the blower power of the FMD114aand the thermodynamic work of the chiller plant.

At block606, the supply air temperature and/or the volume flow rate of airflow supplied by the FMD114aare actuated, for instance, through output of instruction signals by the controller310to the actuators of the FMD114athrough the input/output module312, by the actuation module322.

An example of a control diagram700that includes the MPC702that implements the model disclosed herein is depicted inFIG. 7. As shown therein, the MPC702, which comprises the model and an optimization module (not shown), receives as inputs, a cost function that the optimization module runs to minimize by selecting the most appropriate airflow actuations, a threshold temperature (Tref) as the constraint of the optimization that future rack inlet temperatures must stay below, and rack inlet temperatures (T), for future rack inlet temperature prediction using the model. In other words, the MPC702seeks to determine the optimal settings of the FMD704, and in various instances, vent tiles118a-118m, represented by the SAT, VFD, and AVT depicted inFIG. 7, in response to dynamic IT workload in a particular rack. The airflow resources provisioning, transport, and distribution are coordinated because they are considered simultaneously in the same framework to minimize the airflow provisioning power.

Some or all of the operations set forth in the methods400-600may be contained as utilities, programs, or subprograms, in any desired computer accessible medium. In addition, the methods400-600may be embodied by computer programs, 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 storage medium.

Example computer readable storage media include conventional computer system RAM, ROM, EPROM, EEPROM, and magnetic or optical disks or tapes. Concrete examples of the foregoing include distribution of the programs on a CD ROM or via Internet download. It is therefore to be understood that any electronic device capable of executing the above-described functions may perform those functions enumerated above.

Turning now toFIG. 8, there is shown a block diagram of a computing device800to implement the methods depicted inFIGS. 4-6, in accordance with examples of the present disclosure. The device800includes a processor802, such as a central processing unit; a display device804, such as a monitor; a network interface808, such as a Local Area Network LAN, a wireless 802.11x LAN, a 3G mobile WAN or a WiMax WAN; and a computer-readable medium810. Each of these components is operatively coupled to a bus812. For example, the bus812may be an EISA, a PCI, a USB, a FireWire, a NuBus, or a PDS.

The computer readable medium810may be any suitable non-transitory medium that participates in providing instructions to the processor802for execution. For example, the computer readable medium810may be non-volatile media, such as an optical or a magnetic disk; volatile media, such as memory; and transmission media, such as coaxial cables, copper wire, and fiber optics.

The computer-readable medium810may also store an operating system814, such as Mac OS, MS Windows, Unix, or Linux; network applications816; and an airflow provisioning management application818. The network applications816include various components for establishing and maintaining network connections, such as machine readable instructions for implementing communication protocols including TCP/IP, HTTP, Ethernet, USB, and FireWire.

The airflow provisioning management application818provides various components for managing airflow provisioning in a data center100, as described above. The management application818may thus comprise any of the controllers130,310discussed above. In this regard, the management application818may include the modules312-322, which are also discussed above. In certain examples, some or all of the processes performed by the application818may be integrated into the operating system814. In certain examples, the processes may be at least partially implemented in digital electronic circuitry, or in computer hardware, machine readable instructions (including firmware and/or software), or in any combination thereof.