Abstract: Energy efficiency is managed in a multi-cluster system. The system detects an event in which a current operating frequency of an active cluster enters or crosses any of one or more predetermined frequency spots of the active cluster, wherein the active cluster includes one or more first processor cores. When the event is detected, the system performs the following steps: (1) identifying a target cluster including one or more second processor cores, wherein the each first processor core in the first cluster and each second processor core in the second cluster have different energy efficiency characteristics; (2) activating at least one second processor core in the second cluster; (3) determining whether to migrate one or more interrupt requests from the first cluster to the second cluster; and (4) determining whether to deactivate at least one first processor core of the active cluster based on a performance and power requirement.

Abstract: The present disclosure provides modular electronic devices that are capable of managing task performance based on a particular context of computing resources currently available from the ad hoc combination of devices.

Abstract: For distributed processing using location-based IoT device clusters, using a processor and a memory at a central IoT device, a data source that is to be used for processing a workload is determined. A set of IoT devices that are operating within a threshold distance from the data source at a first time is selected. At the central IoT device, to form a cluster of IoT devices, a subset of the set of IoT devices is selected. Each IoT device in the subset satisfies a clustering condition. The processor at the central IoT device is instructed to configure a device application at a first IoT device in the subset of IoT devices, the device application enabling the first IoT device to participate in the cluster and process the workload.

Abstract: A computing environment includes a computing system, where the computing system includes a plurality of logical partitions, a hypervisor supporting the plurality of logical partitions, a plurality of SR-IOV adapters, where at least one of the logical partitions is mapped to a virtual function on a first SR-IOV adapter of the plurality of adapters, and where migrating an SR-IOV adapter configuration in the computing environment includes: cloning, on a second SR-IOV adapter, a configuration of the first SR-IOV adapter; placing the second SR-IOV adapter and the virtual function in an error state; remapping the virtual function from the first SR-IOV adapter to the second SR-IOV adapter; and placing the second SR-IOV adapter and the virtual function in an error recovery state.

Abstract: For distributed processing using clustering of interdependent Internet of Things (IoT) devices, at a central device, a data source to be used for processing a workload is determined. A set is selected of devices operating within a threshold distance from the data source at a first time. A first subset of the set of devices is selected. Each device in the first subset satisfies a clustering condition. A first device in the subset is instructed to configure a lightweight application to participate in the cluster and process the workload. The processing of the workload is halted on a second device, where the first device has a processing dependency on the second device in processing the workload. A preserved current state of processing the workload is transferred from the first device to a third device. The processing of the workload is continued using the second device and the third device.

Abstract: A method and system for suspending and resuming a virtual machine. The method and system include a hypervisor to provide a guest operating system of a virtual machine with an instruction for the virtual machine to enter a sleep mode. The hypervisor receives, from the guest operating system, a confirmation that the virtual machine is in the sleep mode. Following receipt of confirmation that the virtual machine is in sleep mode, the hypervisor suspends the virtual machine.

Abstract: An information processing apparatus calculates, for each of a plurality of job execution conditions indicating a registration destination queue and a designated degree of parallelism, an estimated start time indicating an estimated time at which execution of a new job starts. The information processing apparatus calculates an execution time of the new job for each of the plurality of degrees of parallelism. The information processing apparatus calculates, for each of the job execution conditions, an estimated end time indicating an estimated time at which execution of the new job ends. The information processing apparatus registers a new job execution request for execution of the new job with the designated degree of parallelism indicated in an earliest job execution condition that gives the earliest execution end time among the job execution conditions, in the registration destination queue indicated in the earliest job execution condition.

Abstract: Described systems and methods enable performing software audits remotely and automatically, on a relatively large number of client systems (e.g., a corporate network, a virtual desktop infrastructure system, etc.) An audit engine executes on each client system, in a hardware virtualization configuration wherein the audit engine executes outside an audited virtual machine. When receiving an audit request from an audit server, some embodiments of the audit engine drop an audit agent into the audited virtual machine, and remove the audit agent upon completion of the audit.

Abstract: A cluster system includes an interface and a processor. The interface is to receive a request from a user associated with one of a plurality of shells. The processor is to determine a plurality of tasks to respond to the request; determine a local set of data and a shared set of data for a task of the plurality of tasks, wherein the local set of data is associated with the one of the plurality of shells; and provide the task, a local set indication, and a shared set indication to a worker associated with the task, wherein the local set indication refers to the local set of data and the shared set indication refers to the shared set of data.

Abstract: Methods, systems, and computer-readable media for optimizing and enhancing delivery of application virtualization layers to client computing devices are described herein. In various embodiments, an application virtualization layer optimization service may identify a first and a second application virtualization layer to be delivered to one or more client computing devices. Each application virtualization layer may represent a package of one or more applications. A layer analysis service may analyze the first and second application virtualization layers to determine conflicts between the layers, using predetermined conflict analysis rules, and generate an actionable conflict resolution report based on the analysis.

Abstract: A method for operating a server farm with a plurality of servers operably connected with each other includes: receiving a job request of a computational task to be handled by the server farm; determining, from the plurality of servers, one or more servers operable to accept the job request; determining a respective effective energy efficiency value associated with at least the one or more servers; and assigning the computational task to a server with the highest effective energy efficiency value. The effective energy efficiency value is defined by a service rate of the respective server divided by a difference between an energy consumption rate value when the respective server is busy and an energy consumption rate value when the respective server is idle. The present invention also relates to a server farm operated by the method.

Abstract: For managing a pool of virtual computer systems, master status and a rebasing task are assigned to at least one virtual computer system of the pool. A non-reserved status is assigned to virtual computer systems of the pool that are not assigned tasks. A virtual computer system of the pool is selected to respond to a rebasing request. The selecting includes selecting one of the at least one virtual computer system that currently has a master status and that currently has a processing load less than a predetermined threshold and, when no virtual computer system of the pool currently has a master status and a processing load less than the predetermined threshold, selecting a non-reserved one of the virtual computer systems to perform rebasing for the request and changing the non-reserved status of the selected, non-reserved one of the virtual computer systems to master status.

Abstract: Embodiments are directed to implementing the protocol endpoint (PE) as a LUN object without significant modification to also support additional features. In particular, since many of the additional features are similar to those already implemented within storage group objects, it would be desirable to implement a PE using both a LUN object and a storage group object linked together. This result may be accomplished by implementing the PE as a LUN object is used when certain features are being accessed and as a storage group object that is used when other features are being accessed. This linkage may be achieved by indexing both the storage group object and the LUN object representing the PE using the same World Wide Name.

Abstract: Embodiments of the present invention include a computer program product for running a virtual manager scheduler for scheduling activities for virtual machines. The computer program product may include program instructions to: define a schedule for one or more activities to be executed for a virtual machine; apply an adjustment to the schedule in accordance with feedback information received via a virtual machine client aggregating the feedback information from a plurality of virtual machine clients, each being related to a virtual machine, per scheduled activity type; and determine of a group adjustment for a determined group of the virtual machine clients based on a function of the feedback information of the plurality of virtual machine clients.

Abstract: Embodiments of the present invention include a computer system for running a virtual manager scheduler for scheduling activities for virtual machines. The computer system may include program instructions to: define a schedule for one or more activities to be executed for a virtual machine; apply an adjustment to the schedule in accordance with feedback information received via a virtual machine client aggregating the feedback information from a plurality of virtual machine clients, each being related to a virtual machine, per scheduled activity type; and determine of a group adjustment for a determined group of the virtual machine clients based on a function of the feedback information of the plurality of virtual machine clients.

Abstract: Methods and systems for flow migration between virtual network appliances in a cloud computing network are described. A network appliances managing architecture for migrating flow between VNAs including a controller to receive performance data for a VNA and analyze the performance data to determine whether the VNA has a weak performance status, where the weak performance status corresponds to any one of an overloaded, an under-loaded, and a failed status. The network appliances managing architecture further includes a classifier to receive a flow migration request from the controller for migrating one or more flows of data packets from the VNA based on the analyzing. The classifier further identifies an active VNA for flow migration based on a mapping policy and migrates the one or more flows from the VNA to the at least one active VNA.

Abstract: A hypervisor can handle requests from applications in a processing environment, where the processing environment consists of shared computing resources. A system can receive a request from an application, and the hypervisor can determine that the request is one that may result in poor interoperability between the application and the processing environment. The hypervisor can identify a processing solution that is more compatible, and it can fulfill the request using the more compatible option. However, the hypervisor need not alert the application of the modified execution; rather, the hypervisor can communicate to the application that the request has been fulfilled.

Abstract: A virtual computer system service receives a request to migrate a virtual machine instance from a first physical host to another physical host. The virtual computer system service identifies a configuration of the first physical host and obtains a data structure that specifies compatibility values for pairings of physical host configurations. The virtual computer system uses the configuration of the first physical host and the data structure to select a compatible physical host configuration. Using this compatible physical host configuration, the virtual computer system service selects a set of physical hosts that have this compatible physical host configuration. The set of physical hosts is used to select a second physical host onto which the virtual machine instance is migrated.

Abstract: A hypervisor can handle requests from applications in a processing environment, where the processing environment consists of shared computing resources. A system can receive a request from an application, and the hypervisor can determine that the request is one that may result in poor interoperability between the application and the processing environment. The hypervisor can identify a processing solution that is more compatible, and it can fulfill the request using the more compatible option. However, the hypervisor need not alert the application of the modified execution; rather, the hypervisor can communicate to the application that the request has been fulfilled.

Abstract: A method, system, and computer program product includes a processor storing, in an order of invocation, a plurality of operations in an ordered list. The first entry is a primary operation and that is a synchronous operation and the subsequent entries include an asynchronous operation, and the secondary operations are required to complete before the primary operation can complete. The processor invokes, in the order of invocation, the plurality of operations. Based on invoking the primary operation and the secondary operations, the processor stores information about the operations as content in a stack. The processor determines that the primary operation can be completed by analyzing a portion of the content of the stack.