WO2019213466A1 - Gestion de puissance à variation dans le temps à l'intérieur de centres informatiques - Google Patents

Gestion de puissance à variation dans le temps à l'intérieur de centres informatiques Download PDF

Info

Publication number
WO2019213466A1
WO2019213466A1 PCT/US2019/030520 US2019030520W WO2019213466A1 WO 2019213466 A1 WO2019213466 A1 WO 2019213466A1 US 2019030520 W US2019030520 W US 2019030520W WO 2019213466 A1 WO2019213466 A1 WO 2019213466A1
Authority
WO
WIPO (PCT)
Prior art keywords
power
datacenter
policy
policies
time
Prior art date
Application number
PCT/US2019/030520
Other languages
English (en)
Inventor
Karimulla Raja Shaikh
Clark A. Jeria Frias
Martin P. LESLIE
Original Assignee
Virtual Power Systems, Inc.
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Virtual Power Systems, Inc. filed Critical Virtual Power Systems, Inc.
Publication of WO2019213466A1 publication Critical patent/WO2019213466A1/fr

Links

Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F1/00—Details not covered by groups G06F3/00 - G06F13/00 and G06F21/00
    • G06F1/26—Power supply means, e.g. regulation thereof
    • G06F1/263—Arrangements for using multiple switchable power supplies, e.g. battery and AC
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F1/00—Details not covered by groups G06F3/00 - G06F13/00 and G06F21/00
    • G06F1/26—Power supply means, e.g. regulation thereof
    • G06F1/28—Supervision thereof, e.g. detecting power-supply failure by out of limits supervision
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F1/00—Details not covered by groups G06F3/00 - G06F13/00 and G06F21/00
    • G06F1/26—Power supply means, e.g. regulation thereof
    • G06F1/30—Means for acting in the event of power-supply failure or interruption, e.g. power-supply fluctuations
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F1/00—Details not covered by groups G06F3/00 - G06F13/00 and G06F21/00
    • G06F1/26—Power supply means, e.g. regulation thereof
    • G06F1/32—Means for saving power
    • G06F1/3203—Power management, i.e. event-based initiation of a power-saving mode
    • G06F1/3206—Monitoring of events, devices or parameters that trigger a change in power modality
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F1/00—Details not covered by groups G06F3/00 - G06F13/00 and G06F21/00
    • G06F1/26—Power supply means, e.g. regulation thereof
    • G06F1/32—Means for saving power
    • G06F1/3203—Power management, i.e. event-based initiation of a power-saving mode
    • G06F1/3234—Power saving characterised by the action undertaken
    • G06F1/3287—Power saving characterised by the action undertaken by switching off individual functional units in the computer system
    • H—ELECTRICITY
    • H05—ELECTRIC TECHNIQUES NOT OTHERWISE PROVIDED FOR
    • H05K—PRINTED CIRCUITS; CASINGS OR CONSTRUCTIONAL DETAILS OF ELECTRIC APPARATUS; MANUFACTURE OF ASSEMBLAGES OF ELECTRICAL COMPONENTS
    • H05K7/00—Constructional details common to different types of electric apparatus
    • H05K7/14—Mounting supporting structure in casing or on frame or rack
    • H05K7/1485—Servers; Data center rooms, e.g. 19-inch computer racks
    • H05K7/1488—Cabinets therefor, e.g. chassis or racks or mechanical interfaces between blades and support structures
    • H05K7/1492—Cabinets therefor, e.g. chassis or racks or mechanical interfaces between blades and support structures having electrical distribution arrangements, e.g. power supply or data communications
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
    • Y02D10/00—Energy efficient computing, e.g. low power processors, power management or thermal management

Definitions

  • power can be provided by more than one power grid to provide redundancy, while for other data centers, power can be provided by a combination of a power grid, a power micro-grid, locally generated power, renewable power, and backup power. Regardless of how the power is supplied to the data center, providing reliable and efficient power to the large number of computers and associated equipment in modem datacenters is the critical design criterion to successful operation of such facilities.
  • Datacenters provide vital functions for businesses, governments, educational institutions, and other enterprises. Managing a scalable datacenter power infrastructure is essential to maintain consistent reliability of the datacenters.
  • Fig. 6 shows example rack and power configurations.
  • Fig. 7 shows a datacenter rack configuration.
  • This disclosure provides techniques for time-varying power management within datacenters.
  • Managing information technology (IT) tasks including the efficiency and reliability of power distribution, space allocation, and cooling capacity, is highly challenging.
  • the management of these resources is particularly difficult for datacenters, where the supply of and demand for power must be carefully balanced, analyzed, and anticipated.
  • Some datacenters are dedicated to a single organization, while other datacenters are contracted for use by multiple organizations.
  • the changing the topology can include selecting a power source, or selecting backup power such as UPSs or battery caches.
  • the modifying can include switching an intelligent power switch within the datacenter.
  • the modifying can include powering down a portion of the datacenter.
  • the powering down a portion of the datacenter can include powering down electrical equipment, powering down one or more IT racks, powering down a row of IT racks, powering down a cage, etc.
  • the powering down can occur after a time duration specified in the policy. The time duration can be long enough for electrical equipment such as a blade server to store data, operating system state, process state, and other information, before the blade server is shut down.
  • Fig. 2 is a flow diagram for modifying power arrangements.
  • One or more power arrangements can be modified to support time-varying power management within a datacenter.
  • a set of power policies is obtained and a priority for a policy is determined.
  • the policy within the set of power policies for managing power within a datacenter is determined.
  • a situation within the datacenter is identified, where the situation matches that described in the policy.
  • a situation can include power loads, anticipated power loads, power outage, etc.
  • a power arrangement is modified based on the policy.
  • the flow 200 includes modifying a power arrangement 210 within the datacenter based on the policy within the set of policies.
  • the power arrangement can include choosing power sources and distributing power from those sources to electrical equipment within the datacenter.
  • the power arrangement can include selecting a power source such as grid power, renewable micro-grid power, diesel- generator power, etc.; configuring power switches for distribution of power to data racks within the datacenter; determining whether buffer power such as battery buffer power may be needed to supplement grid power; power distribution unit settings; and so on.
  • a power source such as grid power, renewable micro-grid power, diesel- generator power, etc.
  • configuring power switches for distribution of power to data racks within the datacenter determining whether buffer power such as battery buffer power may be needed to supplement grid power; power distribution unit settings; and so on.
  • Software defined power can be used to match power sources such as grid power or renewable micro-grid power, uninterruptable power supplies (UPSs), backup power such as diesel-generator (DG) sets or batteries, and so on, to power requirements of equipment such as electrical equipment and cooling equipment in datacenters.
  • the software defined power can adapt power configurations and power allocations dynamically as equipment, processing, service level agreements, and other needs change. Power configurations can be adapted to capture underutilized power from some portions of a datacenter, and to provide that captured power to other portions of the datacenter.
  • Software defined power can support time-varying power management within datacenters.
  • a set of power policies is obtained and a priority for a policy within the set of policies for managing the power within the datacenter is determined.
  • a situation within the datacenter is identified, where the situation matches that described in the policy.
  • a power arrangement within the datacenter is modified based on the policy.
  • the management block can communicate with workload management 320.
  • Workload management can include orchestrating the workload of processing tasks by scheduling the processing tasks and by placing the tasks on processors within the datacenter.
  • Communication between power management and workload management can include power management sending power availability information to workload management, and receiving power policies and power configurations.
  • Power management can be in communication with agent provisioning and placement 322.
  • a virtual machine can include an instance of an operating system, an instance of an application, an agent based on a data flow graph, and so on.
  • the agent provisioning and placement can be based on using a hypervisor or virtual machine monitor (VMM).
  • Power availability information can be sent from power management to agent provisioning and placement, while power policies and power configurations in support of the agent provisioning and placement can be returned.
  • VMM virtual machine monitor
  • Other equipment or components within the datacenter cannot be controlled locally using intelligent control, but rather can be controlled centrally by power management.
  • This latter type of equipment can support direct control 344.
  • These other components 346 can include other PDUs, other UPSs, other switch gear, and so on.
  • Further equipment within the datacenter can be controlled by power management.
  • This further equipment can comprise infrastructure management 348, where infrastructure management can include HVAC management, facilities management, IT server management, and so on.
  • a policy can define a set of conditions within a datacenter.
  • the conditions can be based on a local state 410 of various pieces of electrical equipment, where the electrical equipment can include servers; communications equipment; backup and storage equipment; data racks; information technology racks; heating, cooling, air conditioning (HVAC) equipment; and so on.
  • the various pieces of electrical equipment can include power equipment such as power feeds, power loads, switches, etc.
  • the conditions of devices within the datacenter are checked periodically.
  • the states of the local devices can be compared to a situation, where the comparison can match the datacenter situation to that described in a policy.
  • the local state can include a disconnect time during which a policy can remain valid; status available (1) or unavailable (0) of a feed line feed A, feed B, or feed C; and a state of charge (SoC) of local storage (LS) as a percentage of maximum charge.
  • Delay 412 can be introduced into a policy.
  • a delay can be used to prevent policy“thrashing”, where policy thrashing could result from a changing state variable causing changes in policy application.
  • a policy can be assigned and a delay can be loaded into a countdown timer. The countdown can be based on a threshold. Once the threshold is reached, the countdown timer may not be reset based on a change in state.
  • a policy can include actions that can be taken.
  • policies that can support 2N redundancy are shown.
  • the policies can include policy 1 420, policy 2 422, policy 3 424, policy 4 426, policy 5 428, and so on.
  • policies can be ranked. In embodiments, the policies are ranked based on priority, where a priority can be determined for a policy within a set of policies for managing power within the datacenter. When a situation within the datacenter is identified that can match the situation described in two or more policies, then the first policy can be selected for execution.
  • Fig. 4B illustrates example power policies for 1N redundancy.
  • Power policies including power policies that support 1N redundancy, support time-varying power management within datacenters.
  • a policy can be used to define parameters for states of electrical equipment within a datacenter. The policy can also describe actions to be taken based on the state of the electrical equipment.
  • Example policies for 1N redundancy 402 are shown. Each policy can include fields for local state 430, delay 432, actions 434, and so on.
  • the local state can include disconnect time which can include a number of seconds since a previous policy was updated. A policy with a non-zero disconnect time can only be considered for use if a new policy has not been received in the specified duration of time such as a number of seconds.
  • the local state can include a status available/unavailable (1 / 0 respectively) for feed A, available/unavailable for feed B or feed C, a state of charge (SoC) for local storage as a percentage, and the like.
  • SoC state of charge
  • a certain action can be performed if a local state persists for an amount of time.
  • a technique that can be used to support state persistence can include defining a delay 432 that can apply to a policy rule. The delay can be used to initiate a countdown timer. A reset threshold can be applied to the countdown timer. A countdown towards a particular action may continue when a local state changes, instead of being interrupted by the local state change, based on the reset threshold. The countdown time can be reset if a local state changes and the reset threshold has not been reached. The countdown timer continues to count down interrupted once the reset threshold is met.
  • various actions 434 can be taken for a given policy.
  • the actions can include closing (1) or opening (0) an output relay for an output A’, closing or opening an output relay for an output B’, limiting an output A based on power capacity of output A, limiting output B based on power capacity of output B, or defining an amount of power that can be pulled from (a negative value) or pushed to (a positive value) feed C.
  • a plurality of policies can be included.
  • the plurality of policies can include policy 1 440, policy 2 442, policy 3 444, policy 4 446, policy 5 448, policy 6 450, and so on. While six policies are shown, other numbers of policies can be used to support 1N redundancy.
  • the order of policies can be significant, where the order of policies can indicate ranked priorities for the policies.
  • the rankings of the policies can be based on cost, availability, service level agreement, priority, and so on.
  • a datacenter 540 can be managed using time-varying techniques by a power policy engine 510.
  • the power policy engine can include one or more processors, servers, blade servers, cloud servers, and so on.
  • the one or more processors or one or more servers can be located within the datacenter, remotely from the datacenter, in the“cloud”, and the like.
  • the power policy engine 510 can access power policies 520.
  • the power polices can include one or more of power arrangements, power configurations, service level agreements, dynamic service level agreements, and so on.
  • the allocation policies can be stored in a networked database, where the networked database can include a structured query language (SQL) database.
  • SQL structured query language
  • the allocation policies can include power source limits, such as grid power limits, renewable micro-grid power limits, power source availability, and so on.
  • the power policies, including allocation or arrangement policies can include criteria such as power consumption limits, switch configurations, datacenter condition criteria, etc.
  • the power policies can identify datacenter switches and configurations for those switches to allow replenishing of the power caches or other backup power.
  • the identifying of datacenter situations, the determining of policy priorities, and the modifying of power arrangements, etc., can be performed by the power policy engine based on several techniques.
  • the techniques can be time-varying.
  • the power policy engine can use data collection and monitoring 530.
  • Data collection and monitoring can include power source availability, power load needs, power component operating health, and so on.
  • the data collection and monitoring can occur at the electrical equipment level where the electrical equipment can include servers, switches, uninterruptable power supplies (UPSs), batteries, etc.
  • the data collection and monitoring can occur at the data rack (IT rack) level, for a cluster of racks, for a cage, etc.
  • the power policy engine can use predictive analytics 532.
  • the predictive analytics can use data obtained from the datacenter as the datacenter is in operation, as well as historical data, to determine power usage trends.
  • the predictive analytics can be used to generate a value related to each power source, power load, switch, etc., where the value can be a score, a percentage, and so on.
  • the predictive analytics can be used to determine trends in power usage.
  • the power policy engine can use power usage prediction 534.
  • the power usage prediction can be based on historical power usage or present power usage, and can include other usage information such as anticipated client usage, processing job mix, seasonal factors such as lighting and cooling, and so on.
  • the power policy engine can use policy enforcement 536. Policy enforcement can be based on a service level agreement, a variable SLA, a dynamic SLA, etc. The policy enforcement can be used to provide power required by the SLA to throttle down power to datacenter equipment such as datacenter racks when higher priority jobs or SLAs are encountered, and the like.
  • the power policy engine can use cloud services 538. Cloud services can include storage services for storing power policies, as described elsewhere.
  • the cloud services can include determining or identifying services, where the determining a priority or identifying a situation can be performed in the cloud using cloud-based servers, and so on.
  • Fig. 6 shows example rack and power configurations.
  • Data racks or information technology (IT) racks can contain computing equipment, communication equipment, storage and backup equipment, and other electrical equipment.
  • the electrical equipment can include power supplies, batteries, uninterruptable power supplies, and so on.
  • the electrical equipment within the data racks can be powered and controlled based on time- varying power management within datacenters.
  • a set of power policies is obtained and a priority for a policy is determined.
  • the set of policies is used for managing the power within the datacenter.
  • a situation within the datacenter is identified where the situation matches that described in the policy.
  • a power arrangement within the datacenter is modified based on the policy.
  • the figure shows two example rack and power configurations, a first configuration 600, and a second configuration 602.
  • One or more batteries, one or more power supplies, a plurality of connectors, a plurality of power sensors, a plurality of load sensors, and controllers can comprise a consolidated rack mount power system.
  • An example system is shown in the first configuration 600 which includes rack 610, in turn composed of consolidated rack mount power systems 612, 614, 616, and 618.
  • the one or more batteries, the plurality of power supplies, the plurality of connectors, the plurality of power sensors, the plurality of load sensors, the plurality of converters, and the controllers can comprise a consolidated side mount power system.
  • An example setup is shown in the second configuration 602 which includes a first rack 620 and a second rack 622, together composing a consolidated side mount power system 624 placed between the first rack 620 and the second rack 622.
  • the consolidated rack mount power system and the consolidated side mount power system can be stackable.
  • consolidated rack mount power systems 612 and 614 are stacked one on top of the other in adjacent rack spaces.
  • the rack mount power systems can be evaluated and connected to the various electrical components contained with the racks 610, 620, and 622.
  • the evaluating and connecting the AC and DC power sources, and the controlling the power sources, can be accomplished using a software- defined power infrastructure.
  • the software-defined power infrastructure can control the evaluating and the connecting in a dynamic manner.
  • the stacking can provide for N+ parallelization.
  • N+ parallelization refers to a number of additional power supplies beyond the required number which are kept as standby or reserve power supplies. For example, if a particular cluster of racks requires six power supplies, an N+l configuration would provide seven power supplies, an N+2 configuration would provide eight power supplies, and so on.
  • the stacking can also provide for 2N parallelization. Again, using the example of six required power supplies, a 2N parallelization scheme would provide twelve power supplies. In the 2N redundancy configuration, any critical path in the power system is replicated to remove single points of failure and to increase robustness.
  • the consolidated side mount power system can also provide power across multiple racks. For example, a single consolidated side mount power system 624 can provide power across a first rack 620 and a second rack 622.
  • Fig. 7 shows a datacenter rack configuration.
  • Data racks also called information technology (IT) racks, contain a variety of electrical equipment for which power is controlled.
  • a datacenter can include multiple IT racks which can be powered and controlled based on time-varying power management within the datacenter.
  • a set of power policies for managing power within a datacenter is obtained, and a priority for a policy within the set of policies for managing the power is determined.
  • a situation within the datacenter is identified where the situation matches that described in the policy within the set of policies.
  • the set of policies varies over time, and the policy within the set of policies varies over time.
  • a power arrangement within the datacenter is modified based on the policy within the set of policies.
  • a datacenter can include multiple data racks.
  • Example 700 includes three data racks, indicated as rack 710, rack 720, and rack 730. While three data racks are shown in example 700, in practice, there can be more or fewer data racks.
  • the data rack 710 includes a power cache 712, a first server 714, a second server 716, and a power supply 718.
  • the power supply 718 can be used for AC-DC conversion and/or filtering of power to be used by the servers 714 and 716, as well as replenishment of the power cache 712.
  • the power cache 712 includes an array of rechargeable batteries.
  • the batteries include, but are not limited to, lead-acid, nickel metal hydride, lithium ion, nickel cadmium, and/or lithium ion polymer batteries.
  • the data rack 720 includes a power cache 722, a first server 724, a second server 726, and a power supply 728.
  • the data rack 730 includes a power cache 732, a first server 734, a second server 736, and a power supply 738.
  • the data racks are interconnected by communication links 740 and 742.
  • the communication links can be part of a local area network (LAN).
  • the communication links include a wired Ethernet, Gigabit Ethernet, or another suitable communication link.
  • the communication links enable each data rack to send and/or broadcast current power usage, operating conditions, and/or estimated power requirements to other data racks and/or upstream controllers such as a cluster controller.
  • a power cache can be located on each of the multiple data racks within the data center.
  • the power cache includes multiple batteries spread across the multiple data racks.
  • Each rack may be connected to a communication network 750.
  • Rack 710 is connected to network 750 via communication link 752.
  • Rack 720 is connected to network 750 via communication link 754.
  • Rack 730 is connected to network 750 via communication link 756.
  • the optimization engine 758 can retrieve operating parameters from each rack. In embodiments, the operating parameters are retrieved via SNMP (Simple Network
  • MIB Management Information Base
  • OIDs Object Identifiers
  • parameters such as instantaneous power consumption, average power consumption, number of cores in use, number of applications currently executing on a server, the mode of each application (suspended, running, etc.), internal temperature of each server and/or hard disk, and fan speed.
  • Other parameters may also be represented within the MIB.
  • the optimization engine 758 may derive a new dispatch strategy in order to achieve a power management goal.
  • embodiments include performing the optimizing with an optimization engine.
  • the topology representation 800 includes a first main power source 810, referred to as the“A feed.”
  • the topology representation 800 further includes a second main power source 814, referred to as the“B feed.”
  • Each feed is capable of powering each device in the datacenter simultaneously. This configuration is referred to as 2N redundancy for power.
  • the A feed 810 includes a grid source 871, and a secondary, local source of a diesel generator (DG) 873.
  • the grid source 871 is input to a power regulator 812 and then into one input of a switch block 820.
  • the diesel generator 873 is connected to a second input of the switch block 820.
  • the switch block 820 can be configured, by arrangement of a power policy, to select the diesel generator source or the grid source.
  • the switch block 820 feeds into an uninterruptable power supply (UPS) 830.
  • the UPS 830 includes an AC-DC converter 851 configured to charge a power cache 853.
  • the power cache 853 is a battery.
  • the UPS 830 further includes a DC-AC converter 855 that feeds into an input of a switch block 857.
  • the output of the switch block 820 feeds into a second input of the switch block 857.
  • the output of the UPS 830 is input to a power regulator 832, and then to an input of a switch block 840.
  • the switch block 857 can be configured, based on a power policy, to provide power from the power cache, or to bypass the power cache and provide power directly from the local or grid power source.
  • the second input of the switch block 840 is not connected, such that if the second input is selected, the A feed 810 is disconnected from the PDU 850.
  • the PDU Power Distribution Unit
  • a second set of power loads 862 may be added as part of a simulation of a dynamic power scenario.
  • a controller (not shown) can control the PDU 850.
  • the controller can be an intelligent power controller.
  • the controller can receive a power policy for use in the datacenter.
  • the controller can use a key.
  • the key can be used to support secure communications to and from the controller.
  • the key can be uploaded by a user, downloaded from the internet, embedded in the controller, and so on.
  • the B feed 814 includes a grid source 875, and a secondary, local source of a diesel generator (DG) 877.
  • the grid source 875 is input to a power regulator 816 and then into one input of a switch block 822.
  • the diesel generator 877 is input to a second input of the switch block 822.
  • the switch block 822 can be configured, based on a power policy, to select the diesel generator source or the grid source.
  • the switch block 822 feeds into a UPS 834.
  • the UPS 834 includes an AC-DC converter 861 configured to a charge power cache 863. In embodiments, power cache 863 may be a battery.
  • the UPS 834 further includes a DC-AC converter 865 that feeds into an input of a switch block 867.
  • the output of the switch block 822 feeds into a second input of a switch block 867.
  • the switch block 867 can be configured, based on a power policy, to provide power from the power cache, or to bypass the power cache and provide power directly from the local or grid power source.
  • the output of the UPS 834 is input to a power regulator 836, and then to an input of a switch block 842.
  • the second input of the switch block 842 is not connected, such that if the second input is selected, the B feed 814 is disconnected from the PDU 852 which in turn feeds the first set of power loads 860 and/or the second set of power loads 862 within the datacenter.
  • a controller (not shown) can control the PDU 852.
  • the controller can receive a power policy for use in the datacenter.
  • the controller can use a key.
  • the key can be used to support secure communications to and from the controller.
  • the key can be uploaded by a user, downloaded from the internet, embedded in the controller, and so on.
  • the A feed 810 and the B feed 814 comprise a first main power source and a second main power source.
  • the power source and the second power source can provide 2N redundancy to the power load.
  • the power source and a second power source share power to the multiple data racks, wherein the power is shared on a fractional basis.
  • a variety of dynamic power scenarios can be simulated based on the topology shown in Fig. 8.
  • Fig. 9 shows a system diagram for time-varying power management within datacenters.
  • a set of power policies for managing power within a datacenter is obtained.
  • a priority for a policy within the set of policies for managing the power within the datacenter is determined.
  • a situation within the datacenter is identified where the situation matches that described in the policy within the set of policies.
  • a power arrangement within the datacenter is modified based on the policy within the set of policies.
  • the set of policies varies over time, and the policy with the set of policies varies over time.
  • the priority is based on an order within the set of policies.
  • the system 900 can include one or more processors 910 and a memory 912 which stores instructions.
  • the memory 912 is coupled to the one or more processors 910, wherein the one or more processors 910 can execute instructions stored in the memory 912.
  • the memory 912 can be used for storing the following: instructions; databases of power sources, power caches and power loads; information pertaining to load requirements or redundancy requirements; power policies; and/or service level agreements (SLAs).
  • SLAs service level agreements
  • the memory can also be used for system support.
  • Information regarding time-varying power management within datacenters can be shown on a display 914 connected to the one or more processors 910.
  • the display can comprise a television monitor, a projector, a computer monitor (including a laptop screen, a tablet screen, a netbook screen, and the like), a smartphone display, a mobile device, or another electronic display.
  • the system 900 includes allocation policies 920.
  • the allocation polices can include service level agreements, dynamic service level agreements, and so on.
  • the allocation policies 920 are stored in a networked database, such as a structured query language (SQL) database.
  • the allocation policies 920 can include limits, such as power consumption limits, as well as switch configurations when certain conditions are met. For example, when conditions allow peak shaving to take place, and surplus power exists, the power policies can identify switches and their configurations to allow replenishing of the power caches.
  • the system 900 further includes a repository of power descriptions 930.
  • the power descriptions 930 can include, but are not limited to, power descriptions of power loads, power caches, power supplies, rack power profiles, batteries, buses, circuit breakers, fuses, and the like.
  • the power descriptions can include physical space needs, electrical equipment cooling requirements, etc.
  • the system 900 includes an obtaining component 940.
  • the obtaining component 940 can be used for obtaining a set of power policies for managing power within a datacenter.
  • the power policies can be based on available power sources such as grid power, diesel-generator power, alternative energy sources, or renewable energy sources; batery backup capabilities; and so on.
  • the system 900 includes a determining component 950.
  • the determining component 950 is configured to determine a priority for a policy within the set of policies for managing the power within the datacenter.
  • the priority can be determined based on various criteria. In embodiments, the priority is based on an order within the set of policies.
  • the priority can be used for selecting. In embodiments, the priority selects between a first policy and a second policy within the set of policies.
  • the determining can be performed on computing equipment such as a local server, a remote server, a cloud-based server, a mesh server, and the like.
  • the system 900 includes an identifying component 960.
  • the identifying component 960 can identify a situation within the datacenter where the situation matches that described in the policy within the set of policies.
  • the situation can match a portion of the datacenter, such as one or more information technology (IT) racks, a cage, and so on.
  • the situation can include power loads, power source configurations, backup power, and the like.
  • the situation can include job mix, scheduling factors such as running payroll, seasonal factors, etc.
  • the situation can include datacenter events such as a power outage, equipment failure, etc.
  • the system 900 includes a modifying component 970.
  • the modifying component 970 can modify a power arrangement within the datacenter based on the policy within the set of policies.
  • the power arrangement can include a power configuration, a power topology, etc.
  • the power arrangement can be based on a service level agreement.
  • the power arrangement, which can be based on a policy can be based on cost, availability factors, or reliability factors.
  • the power arrangement can be time dependent.
  • Disclosed embodiments can include a computer program product embodied in a non-transitory computer readable medium for power management, the computer program product comprising code which causes one or more processors to perform operations of: obtaining a set of power policies for managing power within a datacenter; determining a priority for a policy within the set of policies for managing the power within the datacenter; identifying a situation within the datacenter where the situation matches that described in the policy within the set of policies; and modifying a power arrangement within the datacenter based on the policy within the set of policies.
  • Each of the above methods may be executed on one or more processors on one or more computer systems.
  • Embodiments may include various forms of distributed computing, client/server computing, and cloud-based computing.
  • the depicted steps or boxes contained in this disclosure’s flow charts are solely illustrative and explanatory. The steps may be modified, omitted, repeated, or re ordered without departing from the scope of this disclosure. Further, each step may contain one or more sub-steps. While the foregoing drawings and description set forth functional aspects of the disclosed systems, no particular implementation or arrangement of software and/or hardware should be inferred from these descriptions unless explicitly stated or otherwise clear from the context. All such arrangements of software and/or hardware are intended to fall within the scope of this disclosure.
  • FIG. 1 The block diagrams and flowchart illustrations depict methods, apparatus, systems, and computer program products.
  • the elements and combinations of elements in the block diagrams and flow diagrams show functions, steps, or groups of steps of the methods, apparatus, systems, computer program products and/or computer-implemented methods. Any and all such functions— generally referred to herein as a“circuit,”“module,” or“system”— may be implemented by computer program instructions, by special-purpose hardware-based computer systems, by combinations of special purpose hardware and computer instructions, by combinations of general purpose hardware and computer instructions, and so on.
  • a programmable apparatus which executes any of the above-mentioned computer program products or computer-implemented methods may include one or more microprocessors, microcontrollers, embedded microcontrollers, programmable digital signal processors, programmable devices, programmable gate arrays, programmable array logic, memory devices, application specific integrated circuits, or the like. Each may be suitably employed or configured to process computer program instructions, execute computer logic, store computer data, and so on.
  • a computer may include a computer program product from a computer-readable storage medium and that this medium may be internal or external, removable and replaceable, or fixed.
  • a computer may include a Basic Input/Output System (BIOS), firmware, an operating system, a database, or the like that may include, interface with, or support the software and hardware described herein.
  • BIOS Basic Input/Output System
  • Embodiments of the present invention are neither limited to conventional computer applications nor the programmable apparatus that run them.
  • the embodiments of the presently claimed invention could include an optical computer, quantum computer, analog computer, or the like.
  • a computer program may be loaded onto a computer to produce a particular machine that may perform any and all of the depicted functions. This particular machine provides a means for carrying out any and all of the depicted functions.
  • any combination of one or more computer readable media may be utilized including but not limited to: a non-transitory computer readable medium for storage; an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor computer readable storage medium or any suitable combination of the foregoing; a portable computer diskete; a hard disk; a random access memory (RAM); a read-only memory (ROM), an erasable programmable read-only memory (EPROM, Flash, MRAM, FeRAM, or phase change memory); an optical fiber; a portable compact disc; an optical storage device; a magnetic storage device; or any suitable combination of the foregoing.
  • a computer readable storage medium may be any tangible medium that can contain or store a program for use by or in connection with an instruction execution system, apparatus, or device.
  • computer program instructions may include computer executable code.
  • languages for expressing computer program instructions may include without limitation C, C++, Java, JavaScriptTM, ActionScriptTM, assembly language, Lisp, Perl, Tel, Python, Ruby, hardware description languages, database programming languages, functional programming languages, imperative programming languages, and so on.
  • computer program instructions may be stored, compiled, or interpreted to run on a computer, a programmable data processing apparatus, a heterogeneous combination of processors or processor architectures, and so on.
  • embodiments of the present invention may take the form of web-based computer software, which includes client/server software, software-as-a-service, peer-to-peer software, or the like.
  • a computer may enable execution of computer program instructions including multiple programs or threads.
  • the multiple programs or threads may be processed approximately simultaneously to enhance utilization of the processor and to facilitate substantially simultaneous functions.
  • any and all methods, program codes, program instructions, and the like described herein may be implemented in one or more threads which may in turn spawn other threads, which may themselves have priorities associated with them.
  • a computer may process these threads based on priority or other order.
  • the verbs “execute” and“process” may be used interchangeably to indicate execute, process, interpret, compile, assemble, link, load, or a combination of the foregoing. Therefore, embodiments that execute or process computer program instructions, computer-executable code, or the like may act upon the instructions or code in any and all of the ways described.
  • the method steps shown are intended to include any suitable method of causing one or more parties or entities to perform the steps. The parties performing a step, or portion of a step, need not be located within a particular geographic location or country boundary. For instance, if an entity located within the United States causes a method step, or portion thereof, to be performed outside of the United States then the method is considered to be performed in the United States by virtue of the causal entity.

Landscapes

  • Engineering & Computer Science (AREA)
  • Theoretical Computer Science (AREA)
  • General Engineering & Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Computer Hardware Design (AREA)
  • Microelectronics & Electronic Packaging (AREA)
  • Computing Systems (AREA)
  • Power Engineering (AREA)
  • Power Sources (AREA)

Abstract

L'invention concerne la gestion de puissance à variation dans le temps à l'intérieur de centres informatiques. Un ensemble de politiques de puissance pour la gestion de la puissance dans un centre informatique est obtenu. L'ensemble de politiques varie dans le temps. Une priorité est déterminée pour une politique au sein de l'ensemble de politiques pour la gestion de la puissance dans le centre informatique. La politique au sein de l'ensemble varie dans le temps. Une situation à l'intérieur du centre informatique est identifiée, la situation concordant avec celle décrite dans la politique au sein de l'ensemble de politiques. Un arrangement de puissance à l'intérieur du centre informatique est modifié sur la base de la politique au sein de l'ensemble de politiques. L'arrangement de puissance à l'intérieur du centre informatique s'applique à une section du centre informatique comprenant une ou plusieurs baies informatiques. La modification comprend l'alimentation d'un ensemble de charges à l'intérieur du centre informatique par une source d'alimentation spécifique, la modification d'une topologie à l'intérieur du centre informatique, la mise hors tension d'une portion du centre informatique ou la modification d'un niveau de prise en charge d'accord de niveau de service.
PCT/US2019/030520 2018-05-04 2019-05-03 Gestion de puissance à variation dans le temps à l'intérieur de centres informatiques WO2019213466A1 (fr)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
US201862666773P 2018-05-04 2018-05-04
US62/666,773 2018-05-04

Publications (1)

Publication Number Publication Date
WO2019213466A1 true WO2019213466A1 (fr) 2019-11-07

Family

ID=68386173

Family Applications (1)

Application Number Title Priority Date Filing Date
PCT/US2019/030520 WO2019213466A1 (fr) 2018-05-04 2019-05-03 Gestion de puissance à variation dans le temps à l'intérieur de centres informatiques

Country Status (1)

Country Link
WO (1) WO2019213466A1 (fr)

Cited By (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2021211220A1 (fr) * 2020-04-14 2021-10-21 Microsoft Technology Licensing, Llc Gestion de ressources énergétiques pour des groupes de machines virtuelles
WO2022066697A1 (fr) * 2020-09-23 2022-03-31 Quantum Loophole, Inc. Orchestration de charges de travail de centre de données sur la base de prévisions énergétiques
US12007734B2 (en) 2022-09-23 2024-06-11 Oracle International Corporation Datacenter level power management with reactive power capping

Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20080178029A1 (en) * 2007-01-19 2008-07-24 Microsoft Corporation Using priorities to select power usage for multiple devices
US20090235097A1 (en) * 2008-03-14 2009-09-17 Microsoft Corporation Data Center Power Management
US8700929B1 (en) * 2007-06-08 2014-04-15 Exaflop Llc Load control in a data center
US8856576B2 (en) * 2010-11-09 2014-10-07 International Business Machines Corporation Energy capture of time-varying energy sources by varying computational workload
US9377837B2 (en) * 2009-07-21 2016-06-28 The Research Foundation For The State University Of New York Apparatus and method for efficient scheduling of tasks

Patent Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20080178029A1 (en) * 2007-01-19 2008-07-24 Microsoft Corporation Using priorities to select power usage for multiple devices
US8700929B1 (en) * 2007-06-08 2014-04-15 Exaflop Llc Load control in a data center
US20090235097A1 (en) * 2008-03-14 2009-09-17 Microsoft Corporation Data Center Power Management
US9377837B2 (en) * 2009-07-21 2016-06-28 The Research Foundation For The State University Of New York Apparatus and method for efficient scheduling of tasks
US8856576B2 (en) * 2010-11-09 2014-10-07 International Business Machines Corporation Energy capture of time-varying energy sources by varying computational workload

Cited By (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2021211220A1 (fr) * 2020-04-14 2021-10-21 Microsoft Technology Licensing, Llc Gestion de ressources énergétiques pour des groupes de machines virtuelles
US11650654B2 (en) 2020-04-14 2023-05-16 Microsoft Technology Licensing, Llc Managing power resources for pools of virtual machines
WO2022066697A1 (fr) * 2020-09-23 2022-03-31 Quantum Loophole, Inc. Orchestration de charges de travail de centre de données sur la base de prévisions énergétiques
US12007734B2 (en) 2022-09-23 2024-06-11 Oracle International Corporation Datacenter level power management with reactive power capping

Similar Documents

Publication Publication Date Title
US11126242B2 (en) Time varying power management within datacenters
US11455021B2 (en) Datacenter power management using AC and DC power sources
US11216059B2 (en) Dynamic tiering of datacenter power for workloads
US10128684B2 (en) Energy control via power requirement analysis and power source enablement
Pierson et al. Datazero: Datacenter with zero emission and robust management using renewable energy
US11107016B2 (en) Augmented power control within a datacenter using predictive modeling
US10429914B2 (en) Multi-level data center using consolidated power control
US11461513B2 (en) Data center power scenario simulation
Bates et al. Electrical grid and supercomputing centers: An investigative analysis of emerging opportunities and challenges
Zhang et al. Flex: High-availability datacenters with zero reserved power
EP3201717B1 (fr) Surveillance d'unités d'alimentation électrique d'ensemble de serveurs partagés
US20210344217A1 (en) Datacenter current injection for power management
US20210294406A1 (en) Datacenter power management using current injection
US9891685B1 (en) Reconfigurable backup battery unit
US10747289B2 (en) Data center power manipulation
US9910471B1 (en) Reconfigurable array of backup battery units
WO2019213466A1 (fr) Gestion de puissance à variation dans le temps à l'intérieur de centres informatiques
JPWO2017149618A1 (ja) 制御装置、発電制御装置、制御方法、システム、及び、プログラム
Li et al. Managing server clusters on renewable energy mix
US20210296900A1 (en) Datacenter power management through phase balancing
Malla et al. Coordinated priority-aware charging of distributed batteries in oversubscribed data centers
WO2017149617A1 (fr) Dispositif de commande, dispositif de commande d'ajustement d'offre/demande, dispositif de stockage d'énergie, dispositif de commande de sortie, système d'ajustement d'offre/demande, procédé de commande, procédé d'ajustement d'offre/demande, et programme
Liu et al. Towards an adaptive multi-power-source datacenter
US20200371574A1 (en) Datacenter power manipulation using power caches
US9448608B1 (en) Switchable backup battery for layered datacenter components

Legal Events

Date Code Title Description
121 Ep: the epo has been informed by wipo that ep was designated in this application

Ref document number: 19797024

Country of ref document: EP

Kind code of ref document: A1

NENP Non-entry into the national phase

Ref country code: DE

122 Ep: pct application non-entry in european phase

Ref document number: 19797024

Country of ref document: EP

Kind code of ref document: A1