System and method for intelligent data center power management and energy market disaster recovery

{
  "publication_number": "US11182201B1",
  "country": "US",
  "kind": "B1",
  "title": "System and method for intelligent data center power management and energy market disaster recovery",
  "abstract": "Systems and methods for intelligent data center power management and energy market disaster recovery comprised of data collection layer, infrastructure elements, application elements, power elements, virtual machine elements, analytics/automation/actions layer, analytics or predictive analytics engine, automation software, actions software, energy markets analysis layer and software and intelligent energy market analysis elements or software. Plurality of data centers employ systems and methods comprising a plurality of Tier 2 data centers that may be running applications, virtual machines and physical computer systems to enable data center and application disaster recovery from utility energy market outages. Systems and methods may be employed to enable application load balancing and data center power load balancing across a plurality of data centers by moving application and power loads from one data center location using power during peak energy hours to another data center location using power during off-peak hours.",
  "claims": [
    "1. A computer automated system for intelligent power management, comprising a processing unit coupled to a memory element, and having instructions encoded thereon, which instructions cause the system to: trigger a collection of infrastructure data, application data, power data, and machine element data; based on the collected data, trigger an operational state change, wherein the triggered operational state change further comprises an infrastructure load balancing, an application load balancing and a power load balancing by the processing unit, across a plurality of data centers by real-time migration of an infrastructure load, an application load and a power load from one data center to another; and wherein the system is configured to allow each data center to communicate with each other data center over a network and to connect to a plurality of energy providers over the network.",
    "2. The computer automated system of claim 1 wherein the system is further caused to: analyze the collected infrastructure data, application data, power data, and machine element data by an analytic engine comprised in the computer automated system; and wherein the triggered operational state change further comprises a machine element load balancing by the processing unit.",
    "3. The computer automated system of claim 1 wherein the system is further caused to: via an energy market analysis layer, automatically in real-time, manage data center and application disaster recovery from utility energy market outages based on data collected from the plurality of energy providers over the network.",
    "4. The computer automated system of claim 1 wherein the system is further caused to: based on the collected data, measure a plurality of parameters wherein if the measured plurality of parameters fall outside of a predefined range, execute a predefined action to bring the said measured plurality of parameters within the predefined range.",
    "5. The computer automated system of claim 1, wherein the system is further configured to: manage in real time, data center power distribution loads, application loads and virtual machine loads, across multiple data centers.",
    "6. The computer automated system of claim 1 wherein the system is further caused to: automatically initiate datacenter operation state changes to balance infrastructure loads, power loads and application loads across multiple datacenters.",
    "7. The computer automated system of claim 1 wherein the computer system is further configured to: analyze data collected from the plurality of energy providers over the network; and based on the analyzed data, enable automatic datacenter operation state changes.",
    "8. The computer automated system of claim 1 wherein the system is further caused to: enable scenario modeling for and of designated applications, virtual machines, and power loads; and predict outages caused by energy provider failures to pre-empt real-time back-up or migration of infrastructure loads, application loads, virtual machine loads or power loads in a data center.",
    "9. The computer automated system of claim 1 wherein the instructions further cause the system to: automatically manage virtual machine instances, which comprises killing of virtual servers or banks of physical computer systems during low application loads and turning up virtual machines or banks of physical computer systems prior to expected peak loads.",
    "10. In a computer automated system for intelligent power management and comprising a processing unit coupled to a memory element having instructions encoded thereon, a method comprising: triggering a collection of infrastructure data, application data, power data, and machine element data; based on the collected data, triggering an operational state change, wherein the triggered operational state change further comprises an infrastructure load balancing, an application load balancing and a power load balancing by the processing unit, across a plurality of data centers by real-time migration of an infrastructure load, an application load and a power load from one data center to another; and wherein the system is configured to allow each data center to communicate with each other data center over a network and to connect to a plurality of energy providers over the network.",
    "11. The method of claim 10 further comprising: analyzing the collected infrastructure data, application data, power data, and machine element data by an analytic engine comprised in the computer automated system; and wherein the triggered operational state change further comprises a machine element load balancing by the processing unit.",
    "12. The method of claim 10 further comprising: via an energy market analysis layer, automatically in real-time, managing data center and application disaster recovery from utility energy market outages based on data collected from the plurality of energy providers over the network.",
    "13. The method of claim 10 further comprising: based on the collected data, measuring a plurality of parameters wherein if the measured plurality of parameters fall outside of a predefined range, executing a predefined action to bring the said measured plurality of parameters within the predefined range.",
    "14. The method of claim 10, further comprising: managing in real time, data center power distribution loads, application loads and virtual machine loads, across multiple data centers.",
    "15. The method of claim 10 further comprising: automatically initiating datacenter operation state changes to balance infrastructure loads, power loads and application loads across multiple datacenters.",
    "16. The method of claim 10 further comprising: analyzing data collected from the plurality of energy providers over the network; and based on the analyzed data, enabling automatic datacenter operation state changes.",
    "17. The method of claim 10 further comprising: enabling scenario modeling for and of designated applications, virtual machines, and power loads; and predicting outages caused by energy provider failures to pre-empt real-time back-up or migration of infrastructure loads, application loads, virtual machine loads or power loads in a data center.",
    "18. The method of claim 10 further comprising: automatically managing virtual machine instances, which comprises killing of virtual servers or banks of physical computer systems during low application loads and turning up virtual machines or banks of physical computer systems prior to expected peak loads."
  ],
  "description_excerpt": "The present invention relates to intelligent power management and data recovery facilities.\n\nA data center is a facility designed to house, maintain, and power a plurality of computer systems. The computer systems within the data center are generally rack-mounted where a number of electronics units are stacked within a support frame.\n\nA conventional Tier 4 data center is designed with 2N+1 redundancy for all power distribution paths. This means that each power distribution component is redundant (2 of each component) plus there is another component added for another layer of redundancy. Essentially, if N is the number of components required for functionality, then 2N would mean you have twice the number of components required. The +1 means not only do you have full redundancy (2N) but you also have a spare, i.e. you can take any component offline and still have full redundancy. With this design you can lose one of the three components but still retain full redundancy in case of failover. Building a Tier 4 data center is cost prohibitive due to the additional power distribution components that must be purchased to provide 2N+1 redundancy for all power distribution paths.\n\nA conventional Tier 2 data center is designed with a single power distribution path with redundant power distribution components. Tier 2 data centers can be built with lower capital expenses but do not offer the same level of redundancy that many businesses running critical systems and applications require.",
  "cpc": [
    "G06F 9/4856",
    "A63C 17/01",
    "A63C 17/1418",
    "A63C 17/26",
    "A63C 2017/1463",
    "A63C 2203/14",
    "F16B 2/065",
    "F16B 9/02",
    "F16B 9/05",
    "F16M 11/04",
    "F16M 13/02",
    "G05B 15/02",
    "G05F 1/66",
    "G06F 9/505",
    "Y02D 10/00",
    "Y10T 24/44017"
  ],
  "ipc": [
    "A63C 17/01",
    "A63C 17/14",
    "A63C 17/26",
    "F16B 2/06",
    "F16B 9/02",
    "F16M 11/04",
    "F16M 13/02",
    "G05B 15/02",
    "G05D 17/00",
    "G05F 1/66",
    "G06F 9/48",
    "G06F 9/50"
  ],
  "assignees": [
    "Nautilus True LLC"
  ],
  "inventors": [
    "Arnold Castillo Magcale"
  ],
  "filing_date": "2019-10-08",
  "publication_date": "2021-11-23",
  "grant_date": "2021-11-23",
  "priority_date": "2014-01-09",
  "application_number": "US-201916596669-A",
  "family_id": "53494466",
  "cited_by_count": 3
}