Patent application number | Description | Published |
20100070784 | Reducing Power Consumption in a Server Cluster - A method of reducing power consumption of a server cluster of host systems with virtual machines executing on the host systems is disclosed. The method includes recommending host system power-on when there is a host system whose utilization is above a target utilization, and recommending host system power-off when there is a host system whose utilization is below the target utilization. Recommending host system power-on includes calculating impact of powering on a standby host system with respect to reducing the number of highly-utilized host systems in the server cluster. The impact of powering on is calculated by simulating moving some virtual machines from highly utilized host systems to the standby host system being recommended to be powered on. Recommending host system power-off includes calculating impact of powering off a host system with respect to decreasing the number of less-utilized host systems in the server cluster. The impact of powering off is calculated by simulating moving all virtual machines from the host system, which is being recommended to be powered-off, to less-utilized host systems. | 03-18-2010 |
20110231696 | Method and System for Cluster Resource Management in a Virtualized Computing Environment - Methods and systems for cluster resource management in virtualized computing environments are described. VM spares are used to reserve (or help discover or otherwise obtain) a set of computing resources for a VM. While VM spares may be used for a variety of scenarios, particular uses of VM spares include using spares to ensure resource availability for requests to power on VMs as well as for discovering, obtaining, and defragmenting the resources and VMs on a cluster, e.g., in response to requests to reserve resources for a VM or to respond to a notification of a failure for a given VM. | 09-22-2011 |
20120042312 | PROCESS DEMAND PREDICTION FOR DISTRIBUTED POWER AND RESOURCE MANAGEMENT - Methods and systems for allocating resources in a virtual desktop resource environment are provided. A method includes making a prediction on the future demand for processes running on a distributed environment with several hosts. The prediction is based on the process demand history and includes the removal of historic process demand glitches. Further, the prediction is used to perform a cost and benefit analysis for moving a candidate process from one host to another, and the candidate process is moved to a different host when the cost and benefit analysis recommends such move. In another embodiment, the predictions on future process demand are used for distributed power management by putting hosts in stand-by mode when the overall demand decreases or by adding hosts to the distributed environment when the load increases. | 02-16-2012 |
20130097319 | SOFTWARE APPLICATION PLACEMENT USING COMPUTING RESOURCE CONTAINERS - Embodiments associate software applications with computing resource containers based on placement rules. A placement rule indicates that a first software application is to be co-located with a second software application during execution of the first and second software applications, or that the first software application is to be separated from the second software application during execution of the first and second software applications. A target computing resource container is selected based on the placement rule and a computing resource container that is associated with the first software application. The second software application is associated with the target computing resource container, and the placement rule may be provided to the target computing resource container. | 04-18-2013 |
20130097464 | SOFTWARE APPLICATION PLACEMENT BASED ON FAILURE CORRELATION - Embodiments associate software applications with computing resources based on failure correlation information and an anti-affinity rule. An anti-affinity rule indicates that a first software application is to be separated from a second software application during execution. A management device determines failure correlations between a first computing resource that is associated with the first software application and a plurality of computing resources other than the first computing resource. The management device selects the computing resource that corresponds to the lowest failure correlation and associates the second software application with the selected computing resource based on the anti-affinity rule. | 04-18-2013 |
20130160003 | MANAGING RESOURCE UTILIZATION WITHIN A CLUSTER OF COMPUTING DEVICES - Systems and methods described herein manage a computing device. A method includes receiving a threshold for an operating condition of a first computing device. An expected resource utilization of a computer program is determined. In addition, the method determines whether the computer program may be executed within the first computing device based on the operating condition threshold and the expected resource utilization of the computer program. | 06-20-2013 |
20130311824 | METHOD AND SYSTEM FOR CLUSTER RESOURCE MANAGEMENT IN A VIRTUALIZED COMPUTING ENVIRONMENT - Methods and systems for cluster resource management in virtualized computing environments are described. VM spares are used to reserve (or help discover or otherwise obtain) a set of computing resources for a VM. While VM spares may be used for a variety of scenarios, particular uses of VM spares include using spares to ensure resource availability for requests to power on VMs as well as for discovering, obtaining, and defragmenting the resources and VMs on a cluster, e.g., in response to requests to reserve resources for a VM or to respond to a notification of a failure for a given VM. | 11-21-2013 |
20130346969 | Opportunistically Proactive Resource Management Using Spare Capacity - Embodiments perform opportunistically proactive resource scheduling for a plurality of resource-consuming entities. The scheduling is based on both current entitlement (or demand) by the entities and predicted future entitlement (or demand) by the entities. Resources are allocated based on the current demands, while any remaining resource capacity is further allocated to entities based on predicted demands. In some embodiments, the scheduling is performed on a cluster of hosts executing a plurality of virtual machines (VMs) in a virtualized datacenter to implement load balancing. | 12-26-2013 |
20140331227 | SOFTWARE APPLICATION PLACEMENT USING COMPUTING RESOURCE CONTAINERS - Embodiments associate software applications with computing resource containers based on placement rules. A placement rule indicates that a first software application is to be co-located with a second software application during execution of the first and second software applications and second placement rule indicates that the first software application is to be separated from the second software application when the second placement rule is violated by enforcing the first placement rule. The placement rule also indicates that the first software application is to be separated from the second software application during execution of the first and second software applications and the second placement rule indicates the first software application is to be co-located with the second software application when the second placement rule is violated by enforcing the first placement rule. | 11-06-2014 |