Abstract:
Localizing a location of a mobile device may be performed by obtaining times of flights between the mobile device and an access point at a first and second location. A heading of the mobile device and a distance between the first and second location may be further obtained. The times of flight, heading, and distance may be used to localize the second location.
Abstract:
A set of antennas is selected from a plurality of antennas for transmitting data streams on a plurality of subcarriers based on channel state information of a communications channel between the plurality of antennas and a plurality of receive antennas at a client device, a number of the data streams to be transmitted, and a channel coherence time of the communications channel. A size of the set is equal to or greater than the number of data streams.
Abstract:
Described herein are techniques for performing a channel scan based on a mobility state of a device. The mobility state of a device relative to an access point may be determined using time-of-flight information. A channel scan may be performed based on the mobility state determination.
Abstract:
Localizing a location of a mobile device may be performed by obtaining times of flights between the mobile device and an access point at a first and second location. A heading of the mobile device and a distance between the first and second location may be further obtained. The times of flight, heading, and distance may be used to localize the second location.
Abstract:
Identifying a component within an application executed in a network includes obtaining a traffic matrix, the traffic matrix defining a rate for which packets of data are exchanged between VMs corresponding to an application, analyzing the traffic matrix to identify VMs within a component, modifying the traffic matrix to create a modified traffic matrix, and defining, for the application, a tenant application graph (TAG) model based on the modified traffic matrix.
Abstract:
Network flow classification can include clustering a network flow database into a number of at least one of applications and network flows. Network flow classification can include classifying the number of the at least one of applications and network flows.
Abstract:
According to an example, signal transmissions by a first antenna apparatus and a second antenna apparatus connected to a central processing apparatus through an Ethernet switch may be synchronized with respect to each other. An Ethernet packet containing first data and second data may be generated, in which the first antenna apparatus is to wirelessly transmit the first data and the second antenna apparatus is to wirelessly transmit the second data. In addition, the Ethernet packet may be communicated to the Ethernet switch, in which the Ethernet switch includes a first port that is in communication with the first antenna apparatus and a second port that is in communication with the second antenna apparatus, and the Ethernet switch is to communicate the Ethernet packet through the first port and a copy of the Ethernet packet through the second port substantially simultaneously with respect to each other.
Abstract:
Example implementations disclosed herein can be used to generate composite network policy graphs based on multiple network policy graphs input by network users that may have different goals for the network. The resulting composite network policy graph can be used to program a network so that it meets the requirements necessary to achieve the goals of at least some of the network users. In one example implementation, a method can include receiving multiple network policy graphs, generating composite endpoint groups based on relationships between endpoint groups and policy graph sources, generating composite paths based on the relationships between the endpoints and the network policy graphs, generating a composite network policy graph based on the composite endpoint groups and the composite paths, and analyzing the composite network policy graph to determine conflicts or errors.
Abstract:
Identifying a component within an application executed in a network includes obtaining a traffic matrix, the traffic matrix defining a rate for which packets of data are exchanged between VMs corresponding to an application, analyzing the traffic matrix to identify VMs within a component, modifying the traffic matrix to create a modified traffic matrix, and defining, for the application, a tenant application graph (TAG) model based on the modified traffic matrix.
Abstract:
An example method for allocating resources in accordance with aspects of the present disclosure includes collecting proposals from a plurality of modules, the proposals assigning the resources to the plurality of modules and resulting in topology changes in a computer network environment, identifying a set of proposals in the proposals, the set of proposals complying with policies associated with the plurality of modules, instructing the plurality of modules to evaluate the set of proposals, selecting a proposal from the set of proposals, and instructing at least one module associated with the selected proposal to instantiate the selected proposal.