Disclosed are a traffic control method, a traffic control apparatus and a server. In some embodiments, the method includes: determining, by a device on a network side, a first queue delay based on transceiving time of a communication data packet currently received from a user terminal and transceiving time of a communication data packet received from the user terminal last time; adjusting a first quality of service parameter based on the first queue delay, a second queue delay stored by the device on the network side and a reception data volume of the device on the network side, to obtain a second quality of service parameter; and transmitting the second quality of service parameter to the user terminal, and the user terminal transmits subsequent communication data packets based on the second quality of service parameter.

Various embodiments for elastic resource provisioning in a disaggregated cloud computing environment, by a processor device, are provided. Respective members of pools of hardware resources within the disaggregated cloud computing environment are provisioned to a tenant according to an application-level service level agreement (SLA). Upon detecting a potential violation of the application-level SLA, additional respective members of the pools of hardware resources are provisioned on a component level to the tenant to avoid a violation of the SLA by one of a scale-up process and a scale-out process.

A virtual resource automatic selection system includes a setting unit that sets, for a plurality of pieces of training data composed of two or more parameters, a classification boundary between virtual resource clusters that are ranked in accordance with a capacity of a virtual resource in terms of a relationship between the two or more parameters. When a construction request for a new virtual network is received, a receiving unit receives information composed of the parameters. A determining unit determines to which of the virtual resource clusters the parameters belong. An allocating unit allocates a capacity of a virtual resource to the virtual network. An acquiring unit acquires network performance information from the virtual network. A second determining unit determines whether the network performance information satisfies a desired quality of service. The setting unit updates the classification boundary in accordance with a determination result of the second determining unit.

An information processing apparatus comprises a controller. The controller is configured to execute: acquiring a plurality of datasets, each of the datasets being configured with a combination of training data and a correct answer label; and implementing machine learning of an estimation model using the acquired plurality of datasets, wherein the training data includes workload information about an application constructed based on a microservice architecture and resource use information about resources used for each of components included in the application, in a learning target environment, the correct answer label is configured to show a true value of quality of service of the application, and the machine learning comprises training the estimation model such that, for each of the datasets, an estimated value of the quality of service calculated with the estimation model based on the training data corresponds to the true value shown by the correct answer label.

Various embodiments of apparatus, systems (e.g., a gateway device) and/or methods are described for internet managing bandwidth and data usage. A category is assigned for each respective connected device in a stored list of the connected devices based on a function of each respective connected device. A priority list of the connected devices is created with regard to bandwidth use based on the category of the respective connected device. Bandwidth is provided to the connected devices based on the priority list. Also, a data reserve being less than a total recurring data cap is created. In response to determining a predefined data threshold has been met during a recurring period, non-critical functions of the connected devices are disabled for a remainder of the recurring period based on the priority list while allowing data communications with critical functions for the remainder of the recurring period.

An information processing system capable of controlling bursting more appropriately is provided. The information processing system includes: a credit management unit that manages a credit amount for controlling allocation of a resource amount of resources via the bursting with respect to each of a plurality of operation targets; and a bursting management unit that calculates the resource amount to be added via the bursting with respect to each of the plurality of operation targets according to the credit amount managed by the credit management unit and issues an instruction to a storage apparatus to allocate each calculated resource amount to each of the plurality of operation targets.

A method in which an enterprise switches its devices to various federated network slices across operators based on cost, time, quality, and/or availability parameters defined in flexible rules managed by the enterprise. The method includes obtaining, by a controller of an enterprise, one or more parameters of a device served by a network slice of a core network. The method further includes, based on the one or more parameters of the device and one or more rules, determining, by the controller, whether a triggering event associated with a slice reselection occurred and based on the triggering event and the one or more rules, selecting, by the controller, a federated network slice from among a plurality of network slices provided by a plurality of core networks. The method further includes the controller causing the device to switch from the network slice to the federated network slice.

Embodiments relate to xMR sensors, in particular AMR and/or TMR angle sensors with an angle range of 360 degrees. In embodiments, AMR angle sensors with a range of 360 degrees combine conventional, highly accurate AMR angle structures with structures in which an AMR layer is continuously magnetically biased by an exchange bias coupling effect. The equivalent bias field is lower than the external rotating magnetic field and is applied continuously to separate sensor structures. Thus, in contrast with conventional solutions, no temporary, auxiliary magnetic field need be generated, and embodiments are suitable for magnetic fields up to about 100 mT or more. Additional embodiments relate to combined TMR and AMR structures. In such embodiments, a TMR stack with a free layer functioning as an AMR structure is used. With a single such stack, contacted in different modes, a high-precision angle sensor with 360 degrees of uniqueness can be realized.

An apparatus comprises: a processor configured to: select a first channel from among a plurality of channels in a network, and generate a first message assigning a first grant corresponding to the first channel; a transmitter coupled to the processor and configured to transmit the first message; and a receiver coupled to the processor and configured to receive a second message on the first channel and in response to the first message. A method comprises: selecting a first channel from among a plurality of channels in a network; generating a first message assigning a first grant corresponding to the first channel; transmitting the first message; and receiving a second message on the first channel in response to the first message

The present invention relates to a method and a device for allocating resources, where the method includes: providing, by an infrastructure management node, options to a service application; determining, according to a selection result of the options fed back by the service application, physical resources of a level corresponding to the selection result; and creating virtual resources on the physical resources of the level corresponding to the selection result, and provides the virtual resources to the service application. Correspondingly, the present invention provides an infrastructure management node, thereby satisfying a deployment requirement of the service application and guaranteeing QoS of the service application.