Abstract: The techniques and/or systems described herein are configured to determine a set of update operations to transition a network from an observed network state to a target network state and to generate an update dependency graph used to dynamically schedule the set of update operations based on constraint(s) defined to ensure reliability of the network during the transition. The techniques and/or systems dynamically schedule the set of update operations based on feedback. For example, the feedback may include an indication that a previously scheduled update operation has been delayed, has failed, or has been successfully completed.

Abstract: The techniques and/or systems described herein are configured to determine a set of update operations to transition a network from an observed network state to a target network state and to generate an update dependency graph used to dynamically schedule the set of update operations based on constraint(s) defined to ensure reliability of the network during the transition. The techniques and/or systems dynamically schedule the set of update operations based on feedback. For example, the feedback may include an indication that a previously scheduled update operation has been delayed, has failed, or has been successfully completed.

Abstract: One or more approximations of query output in a data analytics platform are controlled. The one or more approximations are controlled by generating values of error metrics associated with placements of samplers in one or more query execution plans associated with the query, and injecting a plurality of samplers into the query execution plans, using the determined values of the error metrics, in lieu of storing samples of input to the query prior to execution of the query.

Abstract: Latency in responding to queries directed to geographically distributed data can be reduced by allocating individual steps, of a multi-step compute operation requested by the query, among the geographically distributed computing devices so as to reduce the duration of shuffling of intermediate data among such devices, and, additionally, by pre-moving, prior to the receipt of the query, portions of the distributed data that are input to a first step of the multistep compute operation, to, again, reduce the duration of the exchange of intermediate data. The pre-moving of input data occurring, and the adaptive allocation of intermediate steps, are prioritized for high-value data sets. Additionally, a threshold increase in a quantity of data exchanged across network communications can be established to avoid incurring network communication usage without an attendant gain in latency reduction.

Abstract: The ensuring of predictable and quantifiable networking performance includes adaptively throttling the rate of VM-to-VM traffic flow. A receiving hypervisor can detect congestion and communicate messages for throttling traffic flow to reduce congestion at the receiving hypervisor.

Abstract: The techniques and/or systems described herein implement a fault handling service that is able to ensure that at least part of a network can avoid congestion (e.g., a link exceeding capacity) as long as a predetermined maximum number of faults is not exceeded. The fault handling service models different combinations of possible faults based on network topology and then computes an amount of traffic to be communicated via individual paths such that congestion is avoided as long as a number of actual faults that occur is less than or equal to the predetermined maximum number of faults.

Abstract: The ensuring of predictable and quantifiable networking performance. Embodiments of the invention combine a congestion free network core with a hypervisor based (i.e., edge-based) throttling design to help insure quantitative and invariable subscription bandwidth rates. A lightweight shim layer in a hypervisor can adaptively throttle the rate of VM-to-VM traffic flow. A receiving hypervisor can detect congestion and communicate back to sending hypervisors that rates are to be regulated. In response, sending hypervisors can reduce transmission rate to mitigate congestion at the receiving hypervisor. In some embodiments, the principles are extended to any message processors communicating over a congestion free network.

Abstract: The provisioning of a host computing system by a controller located over a wide area network. The host computing system has power-on code that automatically executes upon powering up, and causes the host to notify the controller of the host address. In a first level of bootstrapping, the controller instructs the host to download a maintenance operating system. The host responds by downloading and installing a maintenance operating system, enabling further bootstrapping. The persistent memory may further have security data, such as a public key, that allows the host computing system to securely identify the source of the download instructions (and subsequent instructions) as originating from the controller. A second level of bootstrapping may accomplish the configuring of the host with a hypervisor and a host agent. A third level of bootstrapping may accomplish the provisioning of virtual machines on the host.

Abstract: Traffic in a cloud is controlled by the nodes participating in the cloud. Tenants of the cloud each have a ratio. On any given node, a current transmission rate of the node is allocated among the tenants of the node, or more specifically, their execution units (e.g., virtual machines) on the node. Thus each tenant receives a predefined portion of the transmission capacity of the node. The transmission capacity can vary as conditions on the network change. For example, if congestion occurs, the transmission capacity may be decreased. Nonetheless, each tenant receives, according to its ratio, a same relative portion of the overall transmission capacity.

Abstract: The ensuring of predictable and quantifiable networking performance. Embodiments of the invention combine a congestion free network core with a hypervisor based (i.e., edge-based) throttling design to help insure quantitative and invariable subscription bandwidth rates. A lightweight shim layer in a hypervisor can adaptively throttle the rate of VM-to-VM traffic flow. A receiving hypervisor can detect congestion and communicate back to sending hypervisors that rates are to be regulated. In response, sending hypervisors can reduce transmission rate to mitigate congestion at the receiving hypervisor. In some embodiments, the principles are extended to any message processors communicating over a congestion free network.

Abstract: Examples are disclosed herein that relate to estimating and predicting vehicular fuel use. One example estimates fuel usage by a vehicle during a trip by obtaining sensor measurements from one or more sensors of a mobile computing device during the trip, determining a plurality of trip features from the sensor measurements, each trip feature representing an aspect of one or more of energy produced and energy consumed during the trip, obtaining vehicle-specific parameters of the vehicle, and determining an estimated fuel usage from the vehicle-specific parameters and the plurality of trip features for output by the computing device.

Abstract: The described implementations relate to distributed computing. One implementation provides a system that can include an outlier detection component that is configured to identify an outlier task from a plurality of tasks based on runtimes of the plurality of tasks. The system can also include a cause evaluation component that is configured to evaluate a cause of the outlier task. For example, the cause of the outlier task can be an amount of data processed by the outlier task, contention for resources used to execute the outlier task, or a communication link with congested bandwidth that is used by the outlier task to input or output data. The system can also include one or more processing devices configured to execute one or more of the components.

Abstract: A computing cluster operated according to a resource allocation policy based on a predictive model of completion time. The predictive model may be applied in a resource control loop that iteratively updates resources assigned to an executing job. At each iteration, the amount of resources allocated to the job may be updated based on of the predictive model so that the job will be scheduled to complete execution at a target completion time. The target completion time may be derived from a utility function determined for the job. The utility function, in turn, may be derived from a service level agreement with service guarantees and penalties for late completion of a job. Allocating resources in this way may maximize utility for an operator of the computing cluster while minimizing disruption to other jobs that may be concurrently executing.

Abstract: The use of statistics collected during the parallel distributed execution of the tasks of a job may be used to optimize the performance of the task or similar recurring tasks. An execution plan for a job is initially generated, in which the execution plan includes tasks. Statistics regarding operations performed in the tasks are collected while the tasks are executed via parallel distributed execution. Another execution plan is then generated for another recurring job, in which the additional execution plan has at least one task in common with the execution plan for the job. The additional execution plan is subsequently optimized based at least on the statistics to produce an optimized execution plan.

Abstract: The ensuring of predictable and quantifiable networking performance. Embodiments of the invention combine a congestion free network core with a hypervisor based (i.e., edge-based) throttling design to help insure quantitative and invariable subscription bandwidth rates. A lightweight shim layer in a hypervisor can adaptively throttle the rate of VM-to-VM traffic flow. A receiving hypervisor can detect congestion and communicate back to sending hypervisors that rates are to be regulated. In response, sending hypervisors can reduce transmission rate to mitigate congestion at the receiving hypervisor. In some embodiments, the principles are extended to any message processors communicating over a congestion free network.

Abstract: Described is a technology by which driver safety technology such as collision detection is implemented via mobile device (e.g., smartphone) sensors and a cloud service that processes data received from vehicles associated with the devices. Trajectory-related data is received at the cloud service and used to predict collisions between vehicles and/or lane departures of vehicles. To operate the service in real-time with low latency, also described is dividing driving areas into grids, e.g., based upon traffic density, having parallel grid servers each responsible for only vehicles in or approaching its own grid, and other parallel/distributed mechanisms of the cloud service.

Abstract: The techniques and/or systems described herein are configured to determine a set of update operations to transition a network from an observed network state to a target network state and to generate an update dependency graph used to dynamically schedule the set of update operations based on constraint(s) defined to ensure reliability of the network during the transition. The techniques and/or systems dynamically schedule the set of update operations based on feedback. For example, the feedback may include an indication that a previously scheduled update operation has been delayed, has failed, or has been successfully completed.

Abstract: The techniques and/or systems described herein implement a fault handling service that is able to ensure that at least part of a network can avoid congestion (e.g., a link exceeding capacity) as long as a predetermined maximum number of faults is not exceeded. The fault handling service models different combinations of possible faults based on network topology and then computes an amount of traffic to be communicated via individual paths such that congestion is avoided as long as a number of actual faults that occur is less than or equal to the predetermined maximum number of faults.

Abstract: Described is a technology by which driver safety technology such as collision detection is implemented via mobile device (e.g., smartphone) sensors and a cloud service that processes data received from vehicles associated with the devices. Trajectory-related data is received at the cloud service and used to predict collisions between vehicles and/or lane departures of vehicles. To operate the service in real-time with low latency, also described is dividing driving areas into grids, e.g., based upon traffic density, having parallel grid servers each responsible for only vehicles in or approaching its own grid, and other parallel/distributed mechanisms of the cloud service.

Abstract: Various technologies pertaining to scheduling network traffic in a network are described. A request to transfer data from a first computing device to a second computing device includes data that identifies a volume of the data to be transferred and a deadline, where the data is to be transferred prior to the deadline. A long-term schedule is computed based upon the request, wherein the long-term schedule defines flow of traffic through the network over a relatively long time horizon. A short-term schedule is computed based upon the long-term schedule, where devices in the network are configured based upon the short-term schedule.