Abstract: A method, system and computer program product for selecting a target hypervisor to run a migrated virtual machine. An “effective priority value,” representing the virtual machine's priority with respect to the other virtual machines running on the same hypervisor, is calculated for the virtual machine when it is running on the source hypervisor as well as if it were to run on a target hypervisor for each possible target hypervisor. The target hypervisor associated with the minimum difference in absolute value terms between the virtual machine's effective priority value calculated when it is running on the source hypervisor and its effective priority value calculated if it were to be migrated to run on a target hypervisor is selected to receive the migrating virtual machine. In this manner, the effective priority metric has enabled a target hypervisor to be chosen that most closely matches the priority environment of the source hypervisor.

Abstract: A method, a computer program product, and a computer system for cognitive validation of date/time information based on weather information. A computer trains a machine learning model to determine weather properties in images, by utilizing training images with verified metadata and historical weather data. The computer receives an image taken at a specific location and at an alleged time. The computer generates summarized weather hypotheses with a probability distribution, based on probabilities and confidence levels of the one or more weather hypotheses. The computer verifies the alleged time, by using the machine learning model. The machine learning model is used to determine weather properties in the image and to compare the weather properties in the image to known weather information at the specific location and at the alleged time.

Abstract: A method, a computer program product, and a computer system for cognitive validation of date/time information based on weather information. A computer trains a machine learning model to determine weather properties in images, by utilizing training images with verified metadata and historical weather data. The computer receives an image taken at a specific location and at an alleged time. The computer generates summarized weather hypotheses with a probability distribution, based on probabilities and confidence levels of the one or more weather hypotheses. The computer verifies the alleged time, by using the machine learning model. The machine learning model is used to determine weather properties in the image and to compare the weather properties in the image to known weather information at the specific location and at the alleged time.

Abstract: A method, system and computer program product for selecting a target hypervisor to run a migrated virtual machine. An “effective priority value,” representing the virtual machine's priority with respect to the other virtual machines running on the same hypervisor, is calculated for the virtual machine when it is running on the source hypervisor as well as if it were to run on a target hypervisor for each possible target hypervisor. The target hypervisor associated with the minimum difference in absolute value terms between the virtual machine's effective priority value calculated when it is running on the source hypervisor and its effective priority value calculated if it were to be migrated to run on a target hypervisor is selected to receive the migrating virtual machine. In this manner, the effective priority metric has enabled a target hypervisor to be chosen that most closely matches the priority environment of the source hypervisor.

Abstract: A computer implemented method and system for managing resources available to an application in a shared pool of configurable network computing resources is provided. The method includes receiving, by a metric collector, one or more service level metrics correlated with one or more time intervals. The service level metrics are converted to hypervisor weights and a hypervisor is configured to allocate computing resources to a virtual machine according to the hypervisor weights. In response to translating and implementing the hypervisor weights, a dynamic cost model is created. The cost model is correlated with chosen service level metrics as well as with the duration of time a chosen service level metric is implemented.

Abstract: A method, system and computer program product for selecting a target hypervisor to run a migrated virtual machine. An “effective priority value,” representing the virtual machine's priority with respect to the other virtual machines running on the same hypervisor, is calculated for the virtual machine when it is running on the source hypervisor as well as if it were to run on a target hypervisor for each possible target hypervisor. The target hypervisor associated with the minimum difference in absolute value terms between the virtual machine's effective priority value calculated when it is running on the source hypervisor and its effective priority value calculated if it were to be migrated to run on a target hypervisor is selected to receive the migrating virtual machine. In this manner, the effective priority metric has enabled a target hypervisor to be chosen that most closely matches the priority environment of the source hypervisor.

Abstract: A method, system and computer program product for selecting a target hypervisor to run a migrated virtual machine. An “effective priority value,” representing the virtual machine's priority with respect to the other virtual machines running on the same hypervisor, is calculated for the virtual machine when it is running on the source hypervisor as well as if it were to run on a target hypervisor for each possible target hypervisor. The target hypervisor associated with the minimum difference in absolute value terms between the virtual machine's effective priority value calculated when it is running on the source hypervisor and its effective priority value calculated if it were to be migrated to run on a target hypervisor is selected to receive the migrating virtual machine. In this manner, the effective priority metric has enabled a target hypervisor to be chosen that most closely matches the priority environment of the source hypervisor.

Abstract: A method, system and computer program product for selecting a target hypervisor to run a migrated virtual machine. An “effective priority value,” representing the virtual machine's priority with respect to the other virtual machines running on the same hypervisor, is calculated for the virtual machine when it is running on the source hypervisor as well as if it were to run on a target hypervisor for each possible target hypervisor. The target hypervisor associated with the minimum difference in absolute value terms between the virtual machine's effective priority value calculated when it is running on the source hypervisor and its effective priority value calculated if it were to be migrated to run on a target hypervisor is selected to receive the migrating virtual machine. In this manner, the effective priority metric has enabled a target hypervisor to be chosen that most closely matches the priority environment of the source hypervisor.

Abstract: A method, system and computer program product for selecting a target hypervisor to run a migrated virtual machine. An “effective priority value,” representing the virtual machine's priority with respect to the other virtual machines running on the same hypervisor, is calculated for the virtual machine when it is running on the source hypervisor as well as if it were to run on a target hypervisor for each possible target hypervisor. The target hypervisor associated with the minimum difference in absolute value terms between the virtual machine's effective priority value calculated when it is running on the source hypervisor and its effective priority value calculated if it were to be migrated to run on a target hypervisor is selected to receive the migrating virtual machine. In this manner, the effective priority metric has enabled a target hypervisor to be chosen that most closely matches the priority environment of the source hypervisor.

Abstract: A method, system and computer program product for selecting a target hypervisor to run a migrated virtual machine. An “effective priority value,” representing the virtual machine's priority with respect to the other virtual machines running on the same hypervisor, is calculated for the virtual machine when it is running on the source hypervisor as well as if it were to run on a target hypervisor for each possible target hypervisor. The target hypervisor associated with the minimum difference in absolute value terms between the virtual machine's effective priority value calculated when it is running on the source hypervisor with its effective priority value calculated if it were to be migrated to run on a target hypervisor is selected to receive the migrating virtual machine. In this manner, the effective priority metric has enabled a target hypervisor to be chosen that most closely matches the priority environment of the source hypervisor.

Abstract: A method, system and computer program product for selecting a target hypervisor to run a migrated virtual machine. An “effective priority value,” representing the virtual machine's priority with respect to the other virtual machines running on the same hypervisor, is calculated for the virtual machine when it is running on the source hypervisor as well as if it were to run on a target hypervisor for each possible target hypervisor. The target hypervisor associated with the minimum difference in absolute value terms between the virtual machine's effective priority value calculated when it is running on the source hypervisor and its effective priority value calculated if it were to be migrated to run on a target hypervisor is selected to receive the migrating virtual machine. In this manner, the effective priority metric has enabled a target hypervisor to be chosen that most closely matches the priority environment of the source hypervisor.

Abstract: A computer implemented method and system for managing resources available to an application in a shared pool of configurable network computing resources is provided. The method includes receiving, by a metric collector, one or more service level metrics correlated with one or more time intervals. The service level metrics are converted to hypervisor weights and a hypervisor is configured to allocate computing resources to a virtual machine according to the hypervisor weights. In response to translating and implementing the hypervisor weights, a dynamic cost model is created. The cost model is correlated with chosen service level metrics as well as with the duration of time a chosen service level metric is implemented.