Abstract: There is provided a method and apparatus to generate temporal congestion signals. The method is used by a device and includes receiving a packet which includes a request for network state information and generating one or more temporal congestion signals. The method also including adding the temporal congestion signals to the packet and transmitting the packet including the temporal congestion signals. The temporal congestion signals can include one or more of a line busyness signal, which measures the duration of a busy period of the device, and a line idleness signal, which measures the duration of an idle period of the device.

Abstract: There is provided a method and apparatus to generate temporal congestion signals. The method is used by a device and includes receiving a packet which includes a request for network state information and generating one or more temporal congestion signals. The method also including adding the temporal congestion signals to the packet and transmitting the packet including the temporal congestion signals. The temporal congestion signals can include one or more of a line busyness signal, which measures the duration of a busy period of the device, and a line idleness signal, which measures the duration of an idle period of the device.

Abstract: There is provided a method and apparatus to provide notification of change events for microburst mitigation. The method is used by a sending device and includes tracking changes in scheduled data to be sent in a traffic flow and identifying a positive change in an amount of scheduled data to be sent in the traffic flow. The sending device then marks one or more packets to be sent in the traffic flow with a notification field, and then transmits the one or more packets including the notification field. The notification field can then be used by a recipient device, for example a network element, to identify and mitigate microbursts in a proactive manner.

Abstract: The present disclosure describes methods and systems for proactively managing a distributed computer network based on learned relationships between state changes and network events. During an initial identification phase, information representing state changes occurring at host nodes, and network events occurring at network nodes, is collected and processed to generate a database of event probability signatures, each event probability signature indicating a respective probability that a specified event type will occur at a specified network node given a specified type of state change at one of the hosts. During a subsequent action phase, a smart network engine can interact with software drivers installed on each host node to actively monitor for state changes, and when a state change is detected, compare the type of state change with the types of state changes specified in the plurality of event probability signatures to select a matching event probability signature.

Abstract: In some examples, a system receives input information for an application, the input information comprising a specification of a performance parameter relating to the application, and information of an arrangement of components of the application. The system generates, based on the input specification of the parameter and the information of the arrangement of components of the application, a plurality of configuration options representing respective different sets of resources, where a first set of resources of the different sets of resources includes resources of a plurality of cloud environments from different cloud providers. The system selects, based on a target goal, a configuration option of the plurality of configuration options, and output deployment information to cause deployment of the selected configuration option.

Abstract: In some examples, a system receives input information for an application, the input information comprising a specification of a performance parameter relating to the application, and information of an arrangement of components of the application. The system generates, based on the input specification of the parameter and the information of the arrangement of components of the application, a plurality of configuration options representing respective different sets of resources, where a first set of resources of the different sets of resources includes resources of a plurality of cloud environments from different cloud providers. The system selects, based on a target goal, a configuration option of the plurality of configuration options, and output deployment information to cause deployment of the selected configuration option.

Abstract: Techniques for network state-aware and network scheduling policy-aware task scheduling are provided. In one aspect, a method for scheduling tasks in a distributed computing network includes the steps of: collecting a pool of candidate resources in the distributed computing network for performing a given one of the tasks; predicting a performance of each of the candidate resources in performing the given task based on both i) a state and ii) a scheduling policy of the distributed computing network; and selecting a best candidate resource for the given task based on the performance. A system for scheduling tasks in a distributed computing network is also provided which includes a task scheduler; and a network scheduler, wherein the task scheduler is configured to schedule the tasks in the distributed computing network based on both i) the state and ii) the scheduling policy of the distributed computing network.

Abstract: Techniques for network state-aware and network scheduling policy-aware task scheduling are provided. In one aspect, a method for scheduling tasks in a distributed computing network includes the steps of: collecting a pool of candidate resources in the distributed computing network for performing a given one of the tasks; predicting a performance of each of the candidate resources in performing the given task based on both i) a state and ii) a scheduling policy of the distributed computing network; and selecting a best candidate resource for the given task based on the performance. A system for scheduling tasks in a distributed computing network is also provided which includes a task scheduler; and a network scheduler, wherein the task scheduler is configured to schedule the tasks in the distributed computing network based on both i) the state and ii) the scheduling policy of the distributed computing network.