Abstract: A power capping system (10) and method (200) are provided. In one embodiment, a power capping system (10) includes a power controller (16) configured to calculate an error between a predefined maximum desired power and a power feedback signal associated with actual power consumption of a server (12) and to provide a power capping signal that substantially limits the power consumption of the server (12) based on a predetermined gain constant and the error. The system also includes a management interface (18) configured to generate a normalization factor based on the power feedback signal. The normalization factor can be implemented to normalize the error.

Abstract: A data center workload distribution management system includes a cooling cost engine to determine a cooling cost or cooling capacity for each of a plurality of zones of a data center and a workload distribution engine. The workload distribution engine is to identify the zone that has a lowest cooling cost and sufficient cooling capacity and also has sufficient processing capacity for a workload, determine a local cooling efficiency index for at least one location within the identified zone, and distribute the workload to the location having a local cooling efficiency index that indicates the highest cooling efficiency.

Abstract: Managing computer resources. Workload state information associated with one or more servers in a data center is accessed by a computer, the workload state information comprises workload placement on one or more servers, cooling conditions of the one or more servers, and performance requirements associated with a data center. Cooling state information of cooling resources associated with the one or more servers are accessed by the computer, the cooling state information comprises cooling conditions of the cooling resources. The workload state information and the cooling state information are compared by the computer. Based on the comparing, the computer generates workload repositioning instructions that instruct repositioning of workload on the one or more servers to meet the performance requirements.

Abstract: Methods, apparatus, systems and articles of manufacture to control fluid flow in a data center are disclosed herein. An example method disclosed herein comprises sensing a condition of a fluid in a first contained aisle on a first side of data center equipment, the fluid in the first contained aisle substantially isolated from a second contained aisle on a second side of the data center equipment, and controlling a vent to alter the fluid flow between the first contained aisle and the second contained aisle based on the sensed condition.

Abstract: In a method for managing a facility that is to receive resources from a first resource supply, a supply of resources available from the first resource supply is predicted for a predetermined period of time. In addition, a demand for resources in the facility during the predetermined period of time is predicted. A capacity schedule for the facility is planned to meet a predefined operational goal, in which the plan of the capacity schedule uses as inputs, the predicted supply of resources available from the first resource supply and the predicted demand for resources in the facility during the predetermined period of time. Moreover, a determination as to whether the planned capacity schedule meets the predefined operational goal is made.

Abstract: In an implementation, a method for managing airflow provisioning in an area comprising a plurality of racks, wherein a plurality of fluid moving devices are to supply airflow to the plurality of racks through a plurality of adjustable vent tiles, includes accessing a model that describes airflow transport and distribution within the area, said model comprising a plurality of parameters, determining values for the plurality of parameters, and implementing the model to partition the area into a plurality of fluid moving device zones of influence with a desired level of overlapping among the plurality of fluid moving device zones of influence.

Abstract: In a method for supplying a resource to an entity from a resource actuator, a plurality of physics-based models pertaining to the resource actuator and the entity are developed, a condition detected at the entity is received, feedback control on a resource demand of the entity employed based upon the detected condition, feed forward control on the resource demand of the entity is employed based upon the detected condition and the plurality of physics-based models, a constraint optimization problem having an objective function and at least one constraint using the plurality of physics-based models is formulated, a solution to the constraint optimization problem is determined, in which the solution provides the actuator setting, and the resource actuator is set to the actuator setting to supply the entity with the resource from the resource actuator.

Abstract: A plurality of data flows can be routed from a first node of the network to one or more other nodes of the network. A destination of a data packet for each data flow is determined. When the destination node of the data packet of that data flow is not adjacent to the first node, a probabilistic determination is made for a next hop of data packets of that data flow. When the destination node of the data packet of that data flow is adjacent to the first node, a priority designation is made for the next hop of data packets of that data flow as being the destination node. The next hop for data packets of the data flow is determined based on either the probabilistic determination or the priority designation.

Abstract: A set of virtual local area networks (VLANs) are defined from a set of nodes that comprise a data center network. A set of possible paths are determined for routing data packets from a root node to one or more other nodes of the set of nodes. A set of probabilistic values are identified for determining a path in the set of possible paths that individual data packets are to take as between the root node and a destination node specified by the individual data packet. The data packets are routed to the destination node specified by that data packet, along a path that is determined by use of the set of probabilistic values. The path may be provided by one or more VLANs.

Abstract: A method for controlling resource allocation is provided. The method includes determining a service metric associated with a first application, wherein the first application is associated with one or more virtual machines. The method further includes comparing the service metric to an application specific service level goal associated with the first application and modifying a resource allocation associated with the first application at one or more of the virtual machines.

Abstract: A system and method for manipulating environmental conditions in an infrastructure containing a fluid moving device are disclosed that include identifying correlations between operational settings of the fluid moving device and environmental conditions resulting from changes to the operational settings. In addition, an environmental condition detected at a location proximate to or within the plenum following supply of fluid into the plenum by the fluid moving device is received and errors between the received environmental condition and a reference environmental condition are identified. Operational settings for the fluid moving device to achieve the reference environmental condition are determined based upon the identified correlations and errors.

Abstract: A resource consumption of a resource compartment for a time interval is predicted. A resource entitlement for the resource compartment for the time interval is determined based on the predicted resource consumption.

Abstract: A data center workload distribution management system includes a cooling cost engine to determine a cooling cost or cooling capacity for each of a plurality of zones of a data center and a workload distribution engine. The workload distribution engine is to identify the zone that has a lowest cooling cost and sufficient cooling capacity and also has sufficient processing capacity for a workload, determine a local cooling efficiency index for at least one location within the identified zone, and distribute the workload to the location having a local cooling efficiency index that indicates the highest cooling efficiency.

Abstract: In a method for manipulating environmental conditions in an infrastructure containing one or more adaptive vent tiles, correlations between opening levels of the one or more adaptive vent tiles and an environmental condition at one or more heat dissipating devices are identified. In addition, one or more environmental conditions at locations proximate to or within the one or more heat dissipating devices are received and errors between the received one or more environmental conditions and one or more reference environmental conditions are identified. Moreover, opening levels for the one or more adaptive vent tiles are determined based upon the identified correlations and errors.

Abstract: A switch determines a path, not included in a first set of virtual networks associated with the switch. It is determined if the path can be added to an existing virtual network in the first set of virtual networks. If the path cannot be added, a new virtual network is created to include the path.

Abstract: A set of virtual local area networks (VLANs) are defined from a set of nodes that comprise a data center network. A set of possible paths are determined for routing data packets from a root node to one or more other nodes of the set of nodes. A set of probabilistic values are identified for determining a path in the set of possible paths that individual data packets are to take as between the root node and a destination node specified by the individual data packet. The data packets are routed to the destination node specified by that data packet, along a path that is determined by use of the set of probabilistic values. The path may be provided by one or more VLANs.

Abstract: A plurality of data flows can be routed from a first node of the network to one or more other nodes of the network. A destination of a data packet for each data flow is determined. When the destination node of the data packet of that data flow is not adjacent to the first node, a probabilistic determination is made for a next hop of data packets of that data flow. When the destination node of the data packet of that data flow is adjacent to the first node, a priority designation is made for the next hop of data packets of that data flow as being the destination node. The next hop for data packets of the data flow is determined based on either the probabilistic determination or the priority designation.

Abstract: Embodiments of the present invention pertain to dynamically resizing a virtual machine container. According to one embodiment, an optimal utilization is determined based on a desired performance for a multi-tiered application and transaction mix information that describes a mix of transactions that result from executing the multi-tiered application. Automatic modification of an amount of a physical resource a virtual machine container is entitled to for executing a particular application component associated with the multi-tiered application is enabled where the amount is automatically modified based on the optimal utilization.

Abstract: A method for real-time server management may include determining a server architecture model based on performance characteristics of a component of a server. The method may further include determining a real-time model of the server from the server architecture model based on real-time server operation data, and adapting a performance controller for the server to operational characteristics of the server based on the real-time model.

Abstract: The present disclosure includes a system and method for apportioning power consumption. In an example of apportioning power consumption according to the present disclosure, a transaction mix for a service is determined (104, 204, 330, 420), component resource usage for each of a number of components that are used while completing the service is determined (106, 206, 108, 208, 422), and component power consumption for each of the number of components is determined by use of the component resource usage (334, 424).