Abstract: Embodiments of network processing resource management in computing devices are disclosed therein. An example method includes receiving a request from a network interface controller to perform network processing operations at a first core of a main processor for packets assigned by the network interface controller to a queue of a virtual port of the network interface controller. The method also includes determining whether the first core has a utilization level higher than a threshold when performing the network processing operations to effect processing and transmission of the packets. If the first core has a utilization level higher than the threshold, the method includes issuing a command to the network interface to modify affinitization of the queue from the first core to a second core having a utilization level lower than the threshold.

Abstract: A storage system includes a management processor and main processors. Each of the main processors is configured to alternately switch between a period in which main function processing, including I/O processing in response to an I/O request from a host, is executed and a period in which a management instruction is executed. The management processor is configured to: manage information associating each of uncompleted management instructions, which are already transmitted to the main processors, with a transmission destination main processor to which the each of the uncompleted management instructions is transmitted; select, based on the uncompleted management instructions of the main processors, a transmission destination main processor to which a next management instruction is to be transmitted, from among the main processors; and transmit the next management instruction to the selected transmission destination main processor.

Abstract: Systems and methods for migrating a plurality of virtual machines (VMs) from a private cluster to a public cloud include identifying the plurality of VMs currently residing in the private cluster to be migrated to the public cloud. A communication graph indicative of communications involving the plurality of VMs is determined. A migration sequence for the plurality of VMs based on the communication graph is generated. The plurality of VMs is migrated from the private cluster to the public cloud according to the migration sequence.

Abstract: An example computing system for allocating Virtual Network Functions (VNF) in a datacenter includes a processing unit, a computation module and an allocation module. The computation module is configured to determine an extinction factor corresponding to a datacenter unit in the datacenter based on a state of the datacenter and a VNF catalogue including a plurality of VNFs; and to develop an allocation model based on the determined extinction factor. The allocation module is configured to allocate a first VNF from the plurality of VNFs in the datacenter based on the allocation model.

Abstract: A method of emulating nested page table (NPT) mode-based execute control in a virtualized computing system includes: providing NPT mode-based execute control from a hypervisor to a virtual machine (VM) executing in the virtualized computing system; generating a plurality of shadow NPT hierarchies at the hypervisor based on an NPT mode-based execute policy obtained from the VM; configuring a processor of the virtualized computing system to exit from the VM to the hypervisor in response to an escalation from a user privilege level to a supervisor privilege level caused by guest code of the VM; and exposing a first shadow NPT hierarchy of the plurality of shadow NPT hierarchies to the processor in response to an exit from the VM to the hypervisor due to the escalation from the user privilege level to the supervisor privilege level.

Abstract: The present disclosure provides a cloud platform and a construction method thereof. The cloud platform includes a plurality of compute nodes and at least two storage backends. The construction method includes: establishing an association relationship between the compute nodes and the at least two storage backends, such that each compute node is associated with one and only one storage backend. Different storage backends are associated with different compute nodes. When the compute node generates an image file, a type of the image file is determined. The type of the image file includes a base image file or an exported image file. The image file is stored according to the type of the image file and the storage backend associated with the compute node that generates the image file. The technical solutions of the present disclosure enhance the overall disaster tolerance and stability of the cloud platform.

Abstract: A control device includes at least a first task that has a first priority including processing execution performed by a program execution part and a command calculation part, a second task that has a second priority, lower than the first priority, including processing execution performed by a parsing part, and a third task that has a third priority including execution of a processing content different from the first task and the second task are set in a scheduler. The control device further includes a priority changing part monitoring a processing state of the parsing part, and when the processing state of the parsing part meets a predetermined condition, changing the second priority set to the second task corresponding to the condition.

Abstract: Embodiments of the present invention provide a method, system and computer program product for the dynamic association of components in a multi-tier application to different layers of a corresponding multi-tier application infrastructure. In an embodiment of the invention, a method for dynamically associating components in a multi-tier application to different layers of a corresponding multi-tier application infrastructure includes defining in memory of a host computing system a pattern that has an inventory of components of a multi-tier application. The method also includes associating each of the components with a corresponding tier label for an n-tier architecture. The method yet further includes loading the pattern into a pattern engine. Finally, the method includes deploying by the pattern engine each component of the pattern to a layer of the n-tier architecture corresponding to a tier label associated with the component.

Abstract: An apparatus and a method for managing computing resources are disclosed. The apparatus for managing computing resources includes a task input interface configured to receive a plurality of processing-target tasks; a task processor configured to sequentially process the plurality of received processing-target tasks; and a duplicate device manager configured to generate one or more duplicate devices by duplicating the apparatus for managing computing resources based on at least one among a ratio of a number of unprocessed tasks to a number of processing-target tasks and the number of unprocessed tasks, and assign unprocessed tasks to the one or more generated duplicate devices.

Abstract: Systems for achieving and maintaining a specified state of a computing resource in a distributed computing environment. A method embodiment commences upon receiving one or more specification parameters that describe a desired target state associated with a particular computing resource and/or of a particular computing environment. The specification parameters that characterize the desired target state of a resource are recorded in a target state data structure. Periodically, an agent issues a state progression query to determine if the computing resource has reached its desired target state. The query is then processed by collecting state parameters that describe the then-current state of the computing resource or environment. The target state data structure is accessed to identify one or more state differences between the desired target state and the then-current state of the particular computing resource and/or its particular computing environment.

Abstract: Provided is a task scheduling method. The method may include: assigning a task to one of first processing units functionally connected to an electronic device; and migrating, at least partially on the basis of a performance control condition related to the task, the task to one of second processing units for processing.

Abstract: Apparatus and methods are described herein for multiple single level security (MSLS) domains including, but not limited to, a secure kernel hypervisor (SKH). The SKH configures a single multi-tenant cloud to host the MSLS domains. A cloud orchestration system (COS) configures the single multi-tenant cloud to set up a plurality of separate virtual work packages (VWPs) for the MSLS domains. A key management system (KMS) is configured to manage security objects associated with the MSLS domains.

Abstract: A task allocating method for a reconfigurable processing system is provided by the present disclosure. The method includes determining a use status of a hardware processing resource of the reconfigurable processing system. The hardware processing resource includes m task channels and a reconfigurable computing array, and one task channel controls at least one operator in the reconfigurable computing array at a time to process one task. The number m is a positive integer and allocating a first task in n tasks to be processed according to the use status of the hardware processing resource, so that at least one task channel in the m task channels controls the reconfigurable computing array to process simultaneously at least one task which includes the first task, where the number n is a positive integer. A task allocating system for a reconfigurable processing system is also provided by the present disclosure.

Abstract: In one embodiment, a system includes a processing circuit and logic integrated with and/or executable by the processing circuit that causes the processing circuit to receive a congestion notification message from a first virtual switch of a first server indicating that a first virtual machine (VM) hosted by the first server is overloaded. The logic also causes the processing circuit to advertise a congestion status of the first VM in a congestion status message to one or more virtual switches in a network in response to receiving the congestion notification message. Moreover, the logic causes the processing circuit to cause all virtual switches in the network except for the first virtual switch to stop sending traffic destined for the first VM while the first VM is overloaded without restricting sending traffic that is destined for other VMs hosted by the first server.

Abstract: A method and system for automatically metering a distributed file system node is provided. The method includes receiving data associated with jobs for execution via a distributed file system. Characteristics of the jobs are uploaded and policy metrics data associated with hardware usage metering is retrieved. Resource requests associated with hardware resource usage are retrieved and attributes associated with the resource requests are uploaded. The policy metrics data is analyzed and a recommendation circuit is queried with respect to the resource requests. A set of metrics of the policy metrics data associated with the resource requests is determined and a machine learning circuit is updated. Utilized hardware resources are determined with respect to the hardware usage metering and said resource requests.

Abstract: A computer-implemented method, computer program product and computing system for batch processing computing elements on a computing system are provided. The computer-implemented method, computer program product and computing system determine a configuration of the computing system hosting the computing elements, identify a plurality of computing elements to batch process, and batch process the plurality of computing elements based on the determined configuration of the computing system.

Abstract: A system and method for providing quality of service (QoS) for clients running on host computers to access a common resource uses a resource pool module and a local scheduler in at least one of the host computers. The resource pool module operates to compute an entitlement of each client for the common resource based on a current capacity for the common resource and demands of the clients for the common resource. In addition, the resource pool module operates to assign a portion of the computed current capacity for the common resource to a particular host computer using the computed entitlement of each client running on the particular host computer. The local scheduler operates to allocate the portion of the computed current capacity among the clients running on the particular host computer.

Abstract: Systems and methods for live migration of VMs between different nodes are provided. The system and methods utilize a heat map and an access pattern to determine the fetching order of files and/or blocks from the cache of a host node for rebuilding the cache on a destination node. The systems and methods are able to persist the cache of a host node across a crash, allowing a destination node to fetch blocks and/or files from the cache on the host node after a crash instead of having to access the VM files and/or blocks from an original source. Accordingly, the systems and methods decrease migration latency of the VM and free up network bandwidth during the live migration when compared to prior systems and methods that utilize just the heat map to determine the fetching order and/or that are not able to persist the cache across a crash.

Abstract: A policy-driven method of migrating a virtual computing resource that is executing an application workload includes the steps of determining that at least one of multiple policies of the application has been violated by the virtual computing resource while executing the workload in a first virtual data center, and responsive to said determining, programmatically performing: (1) searching for a virtual data center to which the virtual computing resource can be migrated, (2) determining that the virtual computing resource will be able to comply with all of the policies of the application while executing the workload if the virtual computing resource is migrated to the second virtual data center, and (3) based on determining the ability to comply, migrating the virtual computing resource across clouds, namely from the first virtual data center to the second virtual data center.

Abstract: The present disclosure describes acquiring characteristic behavior data of a user in real time, and at a detection triggering moment, matching the characteristic behavior data with a behavior pattern baseline obtained through offline calculation, thus predicting a peak or a trough of resource use. In this way, a resource specification to be used by the user is dynamically adjusted in advance according to a behavior pattern of the user, to meet a resource use demand of the user, and avoid that the user is in shortage of resources in the peak time or wastes resources in the trough time, thus achieving better predictability.