Abstract: Processes, machines, and manufactures involving adaptable containers that can be built and torn down more efficiently than VMs, may support various processes, and may be maintained without the presence of an active process. These adaptable containers may also be configured to support a process type and may support various processes at the same time as well. Other features and aspects are provided and taught.

Abstract: Embodiments directed toward a method, and a system. A method can be directed toward deciding whether to accept a virtual machine migration on a host. The method can include receiving a request to host a migrated virtual machine. The method can include determining if the host is overcommitted. The method can include selecting a low priority virtual machine in response to the host being overcommitted. The method can include determining if a resource for the low priority virtual machine can be reduced to accommodate the migrated virtual machine. The method can include reducing the resources for the low priority virtual machine in response to the resources being able to be reduced. The method can include accepting the request to host the migrated virtual machine in response to the reduction of the resources.

Abstract: Processes, machines, and manufactures involving adaptable containers that can be built and torn down more efficiently than VMs, may support various processes, and may be maintained without the presence of an active process. These adaptable containers may also be configured to support a process type and may support various processes at the same time as well. Other features and aspects are provided and taught.

Abstract: Processes, machines, and manufactures involving adaptable containers that can be built and torn down more efficiently than VMs, may support various processes, and may be maintained without the presence of an active process. These adaptable containers may also be configured to support a process type and may support various processes at the same time as well. Other features and aspects are provided and taught.

Abstract: An approach for generating a deployment pattern for reuse after the deployment of a set of virtual machines and related application artifacts in a networked computing environment (e.g., a cloud computing environment) is provided. In a typical embodiment, information associated with one or more previously provisioned application environments is derived and, after analyzing the information, a deployment pattern is created in the form of tangible artifacts which may be reuse for further deployments without the need to trace back the original procedures used to deploy the previously previsioned application environment.

Abstract: Embodiments of the present invention provide an approach for optimizing a configuration of virtual machine (VM) instances. In a typical embodiment, such optimization comprises either the splitting of a single VM instance into multiple VM instances or the consolidation of multiple VM instances into fewer (e.g., a single) VM instance. Along these lines, it will first be determined which VM instances would be good candidates for reconfiguration. Under one approach, VM instances that are candidates for reconfiguration are identified based upon an analysis of applicable/associated service level agreement (SLA) terms versus the performance of the VM instances. For example, VM instances can be reconfigured if such reconfiguration will maximize a benefit provided by the applicable SLA terms (e.g., if the splitting of a single VM instance into multiple VM instances would cause a workload to be processed more efficiently, resulting in a more favorable cost/benefit ratio).

Abstract: Intelligent lighting is provided to motorists traveling down a stretch of road by sequentially turning on adjacent lighting devices in a lighting segment only when required, such as when vehicles are approaching the lighting devices, and turning off the lighting devices or decreasing a light intensity output of the lighting devices to a predefined minimum lighting intensity output level when no vehicles are present. In addition, which bulb to use in a multi-bulb lighting device is determined, as well as the optimal lighting intensity level of the selected bulb. Further, it is determined which lighting devices in a lighting segment may be turned off or dimmed while maintaining a predefined minimum safe light/brightness level along a pathway associated with the lighting segment.

Abstract: An approach is provided to provide a high availability (HA) cloud environment. In the approach, an active cloud environment is established in one cloud computing environment using a primary set of resources and a passive cloud environment is established in another cloud computing environment, with the passive cloud environment using fewer resources than are used by the active cloud environment. A workload is serviced by the active cloud environment. While servicing the workload, cloud commands are processed that alter the primary set of resources and the commands are stored in a queue. When a failure of the active cloud environment occurs, the workload is serviced by the passive cloud environment in the second cloud computing environment and the cloud commands stored in the queue are used to alter the resources used by the passive cloud environment.

Abstract: A computer-implemented method, a computer program product, and a system for selecting a host from a plurality of host for an application pattern component using a service level agreement (SLA) requirement are provided. The computer-implemented method for selecting a host from a plurality of hosts for an application pattern component using a service level agreement requirement can include receiving the service level agreement requirement for the application pattern component. The method can include receiving a first capability metric of the host from the plurality of hosts. The method can include determining whether the first capability metric of the host from the plurality of hosts is sufficient for the service level agreement requirement. The method can include selecting the host in response to the host being sufficient for the service level agreement requirement.

Abstract: Embodiments of the present invention provide approaches for allowing management of a virtual machine (VM) by multiple cloud providers in a networked computing environment (e.g., a cloud computing environment). Specifically, in a typical embodiment, a system identifies a set of provisioned resources of a VM managed by a first cloud provider, generates a set of artifacts containing information for a second cloud provider to allow co-management of the VM by the first cloud provider and the second cloud provider, and provides access to the set of provisioned resources of the VM to the second cloud provider. As such, a single virtual machine may be managed by multiple (e.g., geographically distinct) cloud providers to cooperatively and selectively execute VM operations because the end product (i.e., VM) from the first and second cloud providers is the same.

Abstract: A computer-implemented method, a computer program product, and a system for selecting a host from a plurality of host for an application pattern component using a service level agreement (SLA) requirement are provided. The computer-implemented method for selecting a host from a plurality of hosts for an application pattern component using a service level agreement requirement can include receiving the service level agreement requirement for the application pattern component. The method can include receiving a first capability metric of the host from the plurality of hosts. The method can include determining whether the first capability metric of the host from the plurality of hosts is sufficient for the service level agreement requirement. The method can include selecting the host in response to the host being sufficient for the service level agreement requirement.

Abstract: A system and computer-implemented method for managing a workload in an environment is disclosed. The method may include establishing a shadow workload on a shadow computer environment, wherein the shadow workload is a copy of an original workload. The method may include communicating a shadow input for the shadow workload, wherein the shadow input is a copy of an original input for the original workload. The method may also include collecting an original output from the original workload and a shadow output from the shadow workload. The method may also include determining, by comparing the original output from the original workload with the shadow output from the shadow workload, whether the shadow computer environment is configured to operate the original workload.

Abstract: Embodiments of the present invention relate to an approach for resolving and/or implementing policies based on layers of a network stack (e.g., cloud computing stack). Specifically, for a given policy that is being resolved, the system first evaluates the applicability of the policy to each layer in the network stack. For a given policy, the system then evaluates the relative effectiveness of applying the policy to achieve the overall goal of the policy. Based on the best fit evaluation of the relative comparison, the system then decides how and where the policy is enacted (e.g., determines a protocol for implementing the policy).

Abstract: Processes, machines, and manufactures involving adaptable containers that can be built and torn down more efficiently than VMs, may support various processes, and may be maintained without the presence of an active process. These adaptable containers may also be configured to support a process type and may support various processes at the same time as well. Other features and aspects are provided and taught.

Abstract: A method of determining preferred WIFI hotspots. The method includes the steps of: detecting, by a computer processor, an attempt to connect to a first WIFI hotspot by a wireless device in a first area; and in response to detecting the attempt to connect to the first WIFI hotspot: identifying, by the computer processor, at least one bandwidth requirement of the wireless device; determining, by the computer processor, preferences based on contextual information corresponding to the wireless device and its user; collecting, by the computer processor, a plurality of WIFI hotspots available in the first area and identify prices and network bandwidth offered by each of the plurality of WIFI hotspots; and recommending, by the computer processor, preferred WIFI hotspots in the first area based on the identified bandwidth requirements, the determined preferences, and the process and network bandwidth offered by each of the plurality of WIFI hotspots.

Abstract: A method ensures Quality of Bandwidth (QoB) in a Wi-Fi connection between one or more wireless devices and an access point to an Internet. A hardware access point controller receives a plurality of requests for data transmission bandwidth between multiple wireless devices and an access point. The access point provides access to the Internet, the requests are for overlapping time periods. The hardware access point controller dynamically allocates subsets of bandwidth capacity provided by the access point to each of the wireless devices. A position detector detects a movement of a specific wireless device relative to the access point. The hardware access point controller identifies a change in data transmission bandwidth between the specific wireless device and the access point caused by the movement of the specific wireless device, and adjusts the subsets of bandwidth capacity by adjusting available frequencies for the specific wireless device.

Abstract: Virtual machines are allocated among servers in a virtual environment, whereby each virtual machine has a current placement. A current fitness score is calculated for each virtual machine based on its current placement. Proposed placement plans are then generated, each plan including a proposed placement of each virtual machine. For each plan, a plan score is created. Each plan score is created by calculating a proposed fitness score for each virtual machine based on a proposed placement of that virtual machine in accordance with that plan, generating a virtual machine score for each virtual machine based on a comparison of that virtual machine's current fitness score and proposed fitness score, and then combining the virtual machine scores. The plan scores are then compared, and a target plan is selected from among the plans. The virtual machines are then reallocated among the servers in accordance with the target proposed placement plan.

Abstract: An approach is provided to provide a high availability (HA) cloud environment. In the approach, an active cloud environment is established in one cloud computing environment using a primary set of resources and a passive cloud environment is established in another cloud computing environment, with the passive cloud environment using fewer resources than are used by the active cloud environment. A workload is serviced by the active cloud environment. While servicing the workload, cloud commands are processed that alter the primary set of resources and the commands are stored in a queue. When a failure of the active cloud environment occurs, the workload is serviced by the passive cloud environment in the second cloud computing environment and the cloud commands stored in the queue are used to alter the resources used by the passive cloud environment.

Abstract: Virtual machines are allocated among servers in a virtual environment, whereby each virtual machine has a current placement. A current fitness score is calculated for each virtual machine based on its current placement. Proposed placement plans are then generated, each plan including a proposed placement of each virtual machine. For each plan, a plan score is created. Each plan score is created by calculating a proposed fitness score for each virtual machine based on a proposed placement of that virtual machine in accordance with that plan, generating a virtual machine score for each virtual machine based on a comparison of that virtual machine's current fitness score and proposed fitness score, and then combining the virtual machine scores. The plan scores are then compared, and a target plan is selected from among the plans. The virtual machines are then reallocated among the servers in accordance with the target proposed placement plan.

Abstract: Embodiments of the present invention provide a set of algorithmic methods that can be used to select which partially and/or pre-provisioned virtual machines (VMs) should be used as a base platform to satisfy a new workload (e.g., provisioning) request received in a networked computing environment (e.g., a cloud computing environment). Specifically, when a workload request is received, a set (e.g., at last one) of software programs needed to process the workload request is identified. Then, a set of VMs is selected from a pool of pre-provisioned VMs having the set of software programs. In general, multiple methods and/or factors can be followed to select the set of VMs. Examples include a length of time to install the set of VMs, a probability of the set of VMs being in demand, and/or or a quantity of the set of VMs having the set of software programs. Once the set of VMs has been selected, the set of VMs may be installed, and the workload request can be processed using the set of software programs.