The present invention provide the data processing method: predicting traffic of a to-be-processed data stream of the first executor in a first time period according to historical information about processing data by the first executor, so as to obtain prediction information of the traffic of the data stream in the first time period, where the historical information includes traffic information of data processed by the first executor in a historical time period, and the traffic prediction information includes predictors of traffic at multiple moments in the first time period; if the traffic prediction information includes a predictor that exceeds a threshold, reducing a data obtaining velocity of the first executor from a first velocity to a second velocity; and obtaining a first data set of the to-be-processed data stream at the second velocity.

Some embodiments of the invention provide a network forwarding element that can be dynamically reconfigured to adjust its data message processing to stay within a desired operating temperature or power consumption range. In some embodiments, the network forwarding element includes (1) a data-plane forwarding circuit (data plane) to process data tuples associated with data messages received by the IC, and (2) a control-plane circuit (control plane) for configuring the data plane forwarding circuit. The data plane includes several data processing stages to process the data tuples. The data plane also includes an idle-signal injecting circuit that receives from the control plane configuration data that the control plane generates based on the IC's temperature. Based on the received configuration data, the idle-signal injecting circuit generates idle control signals for the data processing stages. Each stage that receives an idle control signal enters an idle state during which the majority of the components of that stage do not perform any operations, which reduces the power consumed and temperature generated by that stage during its idle state.

Disclosed is technology for improving the quality of an IoT service by avoiding using a frequency band in which signal disturbance occurs and using a BS in an overload state.

A traffic distribution method and apparatus in a hybrid access network, where the method includes transmitting, by a hybrid access aggregation point (HAAP), probe traffic using a second tunnel after determining that a first tunnel is congested when user traffic is transmitted over the first tunnel, obtaining, by the HAAP, a status of the first tunnel and a status of the second tunnel, determining, by the HAAP according to the status of the first tunnel and the status of the second tunnel, whether the status of the first tunnel and the status of the second tunnel meet an offloading condition, and transmitting, by the HAAP, the user traffic using the first tunnel and the second tunnel after determining that the status of the first tunnel and the status of the second tunnel meet the offloading condition.

A system for admission and flow control is disclosed. In some embodiments, the system includes a switch for routing network traffic, having multiple classes of service (CoSs), from multiple ingress ports to one or more of multiple egress ports. The system also includes multiple ingress-level class of service queues (InCoS-Qs) and one or more egress-level class of service queues (EgCoS-Qs), each InCoS-Q and EgCoS-Q corresponding to one of CoSs. The switch is configured to detect congestion in a particular EgCoS-Q, corresponding to a particular CoS, the particular EgCoS-Q being associated with a particular host; identify an InCoS-Q corresponding to that particular CoS, and associated with that particular host; and block that InCoS-Q, while allowing routing of the network traffic from one or more InCoS-Qs corresponding to that particular CoS, the one or more InCoS-Qs corresponding to one or more other hosts.

Some embodiments of the invention provide a network forwarding element that can be dynamically reconfigured to adjust its data message processing to stay within a desired operating temperature or power consumption range. In some embodiments, the network forwarding element includes (1) a data-plane forwarding circuit (data plane) to process data tuples associated with data messages received by the IC, and (2) a control-plane circuit (control plane) for configuring the data plane forwarding circuit. The data plane includes several data processing stages to process the data tuples. The data plane also includes an idle-signal injecting circuit that receives from the control plane configuration data that the control plane generates based on the IC's temperature. Based on the received configuration data, the idle-signal injecting circuit generates idle control signals for the data processing stages. Each stage that receives an idle control signal enters an idle state during which the majority of the components of that stage do not perform any operations, which reduces the power consumed and temperature generated by that stage during its idle state.

Technologies for load-aware traffic steering include a compute device that includes a multi-homed network interface controller (NIC) with a plurality of NICs. The compute device determines a target virtual network function (VNF) of a plurality of VNFs to perform a processing operation on a network packet. The compute device further identifies a first steering point of a first NIC to steer the received network packet to virtual machines (VMs) associated with the target VNF and retrieves a resource utilization metric that corresponds to a usage level of a component of the compute device used by the VMs to process the network packet. Additionally, the compute device determines whether the resource utilization metric indicates a potential overload condition and provides a steering instruction to a second steering point of a second NIC that is usable to redirect the network traffic to the other VMs via the identified second steering point.

A method begins by one or more processing modules of a computing device in a dispersed storage network (DSN) detecting an overload condition associated with one or more storage units (SUs) of a SU set associated with the DSN and continues with the one or more processing modules receiving congestion information from at least some of the one or more SUs of the SU set. The method continues with the one or more processing modules selecting a congestion reduction scheme based on the congestion information and executing congestion reduction operations in accordance with the congestion reduction scheme. The method continues with the one or more processing modules determining whether the overload condition has ended and based on a determination that the overload condition has ended, suspending the execution of the one or more congestion reduction operations.

A system for admission and flow control is disclosed. In some embodiments, the system includes a switch for routing network traffic, having multiple classes of service (CoSs), from multiple ingress ports to one or more of multiple egress ports. The system also includes multiple ingress-level class of service queues (InCoS-Qs) and one or more egress-level class of service queues (EgCoS-Qs), each InCoS-Q and EgCoS-Q corresponding to one of CoSs. The switch is configured to detect congestion in a particular EgCoS-Q, corresponding to a particular CoS, the particular EgCoS-Q being associated with a particular host; identify an InCoS-Q corresponding to that particular CoS, and associated with that particular host; and block that InCoS-Q, while allowing routing of the network traffic from one or more InCoS-Qs corresponding to that particular CoS, the one or more InCoS-Qs corresponding to one or more other hosts.

One aspect of the disclosure relates to, among other things, a method for optimizing and provisioning a software-as-a-service (SaaS). The method includes determining a graph comprising interconnected stages for the SaaS, wherein each stage has a replication factor and one or more metrics that are associated with one or more service level objectives of the SaaS, determining a first replication factor associated with a first one of the stages which meets a first service level objective of the SaaS, adjusting the first replication factor associated with the first one of the stage based on the determined first replication factor, and provisioning the SaaS onto networked computing resources based on the graph and replication factors associated with each stage.