Dynamic application placement based on cost and availability of energy in datacenters
First Claim
1. A computer-implemented method comprising:
- for hosting sites that run application instances to process workload;
tracking realtime energy parameters associated with the hosting sites and energy resources for the hosting sites, andtracking realtime availability of computing resources associated with the hosting sites;
constructing a framework including;
a hosting sites model that associates the realtime energy parameters and the realtime availability of the computing resources with operation of the hosting sites;
an application instances model that associates the application instances with the computing resources and the energy resources, wherein the application instances model includes power footprints and memory footprints for individual application instances;
solving the framework to output decisions based on the hosting sites model and the application instances model, wherein the solving considers the realtime energy parameters, the realtime availability of the computing resources, and the power footprints and the memory footprints for the individual application instances; and
automatically migrating at least some of the application instances between the hosting sites based on the decisions from the solving the framework.
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Accused Products
Abstract
An optimization framework for hosting sites that dynamically places application instances across multiple hosting sites based on the energy cost and availability of energy at these sites, application SLAs (service level agreements), and cost of network bandwidth between sites, just to name a few. The framework leverages a global network of hosting sites, possibly co-located with renewable and non-renewable energy sources, to dynamically determine the best datacenter (site) suited to place application instances to handle incoming workload at a given point in time. Application instances can be moved between datacenters subject to energy availability and dynamic power pricing, for example, which can vary hourly in day-ahead markets and in a time span of minutes in realtime markets.
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Citations
21 Claims
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1. A computer-implemented method comprising:
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for hosting sites that run application instances to process workload; tracking realtime energy parameters associated with the hosting sites and energy resources for the hosting sites, and tracking realtime availability of computing resources associated with the hosting sites; constructing a framework including; a hosting sites model that associates the realtime energy parameters and the realtime availability of the computing resources with operation of the hosting sites; an application instances model that associates the application instances with the computing resources and the energy resources, wherein the application instances model includes power footprints and memory footprints for individual application instances; solving the framework to output decisions based on the hosting sites model and the application instances model, wherein the solving considers the realtime energy parameters, the realtime availability of the computing resources, and the power footprints and the memory footprints for the individual application instances; and automatically migrating at least some of the application instances between the hosting sites based on the decisions from the solving the framework. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9)
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10. A power control system comprising:
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a processor and a storage device; a data collector stored on the storage device and executable by the processor, the data collector configured to collect computing parameters related to a plurality of datacenter servers, the computing parameters reflecting availability of computing elements; a simulator stored on the storage device and executable by the processor, the simulator configured to; collect historical parameters and realtime energy parameters of the datacenter servers reflecting availability of renewable and non-renewable energy sources and dynamic variations in energy prices, and calculate data points relating to the historical parameters and the realtime energy parameters for designated time intervals; a data processing engine stored on the storage device and executable by the processor, the data processing engine configured to correlate the computing parameters and the data points for the designated time intervals from the data collector and the simulator to produce correlated data related to the designated time intervals; a decision component stored on the storage device and executable by the processor, the decision component configured to receive the correlated data from the data processing engine and to make decisions based on a framework including a hosting site model, an application instance model, and a location energy model, the decisions related to power state changes of the hosting sites associated with the designated time intervals; and a power state actuator stored on the storage device and executable by the processor, the power state actuator configured to receive the decisions from the decision component and to manage power state changes associated with the received decisions within the designated time intervals. - View Dependent Claims (11, 12, 13, 14, 15, 16, 17, 18)
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19. A computer-implemented method, comprising:
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receiving data related to servers, the data reflecting historical parameters of computing elements and energy sources, realtime energy parameters for the energy sources, and availability of the computing elements, wherein the energy sources comprise both renewable and non-renewable energy sources; accessing a framework that includes; a hosting site model associated with operations of the servers, an application instances model of application instances that are run on the servers, and a location energy model that estimates power consumption at the servers; entering the received data into the framework to make server power state decisions based on the received data; and automatically relocating individual application instances between the servers based on the server power state decisions. - View Dependent Claims (20, 21)
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Specification